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Corresponding author: Mirko Hennig, Department of Biochemistry and Molecular Biology, Medical
University of South Carolina, 173 Ashley Ave, PO Box 250509, Charleston, SC 29425; Email:
hennig@musc.edu
RNA Structure Determination by NMR:
Combining Labeling and Pulse Techniques
Braden M. Roth and Mirko Hennig1
Department of Biochemistry and Molecular Biology, Medical University of South
Carolina, Charleston, SC 29425
Abstract. RNA exhibits considerable structural and functional diversity beyond
well established roles of ribosomal, transfer and messenger RNAs, as illustrated by
the discovery of ever increasing numbers of diverse RNA structures involved in
gene processing and regulation. RNA molecules are often quite flexible; they can
function in a genuinely unfolded form and adapt for recognition of both the shape
and the charge distribution on a potential ligand with exquisite specificity. Liquid
state NMR spectroscopy is uniquely suited to answer important questions
concerning biophysical properties of RNA molecules including their three-
dimensional shape, secondary structure distribution, and flexibility by looking at
dynamic ensembles of structures. Here we review the fields of RNA sample
preparation and NMR methodology that facilitate the determination of RNA
structure in solution.
Keywords. RNA synthesis, Isotope labeling, RNA purification, NMR, resonance
assignment, structure determination.
Introduction
The increasing awareness of the essential role of RNA in biological processes,
including its involvement in translation, gene regulation, and viral infections, make
RNA an interesting target for structural studies. Structure is the link between sequence
and function and thus knowledge of the three dimensional structure of RNA is central
to understanding its biology. It is indispensable for describing the underlying
determinants of catalytic mechanisms, ligand binding, and molecular recognition in
macromolecular assemblies.
In this review, after a brief survey of the current status, we will provide the
workflow employed by our laboratory emphasizing the factors essential for the
determination of RNA structures in solution using high-resolution Nuclear Magnetic
Resonance (NMR) methodology and the progress that has been made so far in these
areas. The key issues to determine the structure of RNA at the atomic level are: how to
produce sufficient amounts of isotopically labeled RNA, and once produced, how to
purify the RNA; then, how to obtain unambiguous NMR resonance assignments of the
RNA; and finally, how to utilize collected restraints in NMR structure determination.
The review will conclude with a brief look at the future of high-resolution NMR in the
study of the structural biology of RNA in solution.
1. Current Status of RNA Structures Solved by NMR
Despite the biological importance of RNA, knowledge of their structures lags
considerably behind that of proteins. Nearly 98% of the transcriptional output of the
human genome is non-(protein)-coding RNA (ncRNA) [1; 2]. This estimate is based
upon the fact that intronic RNA constitutes 95% of primary protein-coding transcripts
[3; 4]. Yet less than 2% of Protein Data Bank (PDB) structures represent RNA. This
deficit lies largely in the difficulties in applying the most productive techniques in
protein structure determination to RNA. Rugged energy landscapes and multistate
RNA folding kinetics pose serious obstacles to crystallization for structure
determination by X-ray crystallography. Coinciding with methodological developments
in the early 1990s that allowed for stable isotope labeling, the rate of deposition into
the PDB of RNA structures solved using NMR methodology increased more than
threefold after 1995 to an average of 23 per year. Indeed, nearly half of the RNA-only
structures in the PDB have been determined by NMR. Among the 337 unique NMR
structures that have been deposited between 1992 and 2009, the average length is 23
nucleotides (nt). Only three RNA NMR structures contain more than 50 nt, of which
one is a homodimeric, GAAA tetraloop-receptor RNA complex totaling 86 nt (see 4.5).
However, recent years have seen fewer RNA solution structures deposited in the PDB
(14 in 2008 and 15 in 2009, respectively), and the two largest NMR structures were
solved several years ago, in 2003 and 2004 (PDB accession codes 1P5P and 1S9S,
respectively). The pace of RNA structural biology in solution remains modest because
severe spectral overlap and rapid relaxation in larger RNA continue to complicate
structural studies by NMR. Nevertheless, NMR offers great potential not only with
respect to structural characterization of RNA but also provides the unique ability to
study the details of dynamics which appear integral to understanding RNA function.
The use of deuteration and of TROSY (Transverse Relaxation-Optimized
Spectroscopy)-based experiments have already played an important role in extending
the size of RNA molecules amenable to solution NMR studies.
2. Sample Preparation
Given the inherent insensitivity of NMR, the preparation of RNA molecules for
structure determination by NMR can be quite challenging. Commercially available
oligonucleotides on the millimolar scale required by NMR are often cost-prohibitive,
so investigators will generally employ large-scale in vitro transcription strategies to
produce the molecules in-house. In addition to scale, several custom-labeled transcripts
are often required to generate a single structure, making the process expensive and
labor-intensive. Therefore, careful consideration must be taken to develop a research
plan that maximizes the production of multiple large-scale transcripts while minimizing
effort and expense. In the following sections, strategies for nucleotide preparation, in
vitro transcription, and transcript purification are presented.
2.1. Nucleotide Synthesis
The enrichment of 13
C and 15
N-labeled nucleotides represents a critical step in the
development of multidimensional heteronuclear NMR experiments for structure
determination of RNAs (reviewed in [5; 6]). Assignment of larger RNAs; however,
requires alternative labeling strategies to combat spectral crowding [7; 8]. Site-specific
and random deuteration in conjunction with 13
C and 15
N labeling has proven essential
for the solution of RNAs larger than 30 kDa [9; 10]. At considerable expense, a variety
of uniformly, isotopically labeled rNTPs are commercially available (e.g. Cassia
LLC/Cambridge Isotope Labs and Isotec/Sigma-Aldrich). Most recently, site-
specifically deuterated rNTPs became commercially available (Cassia LLC/Cambridge
Isotope Labs). The ability to produce labeled rNTPs in-house is essential for the
productivity of research groups with limited financial resources and/or an interest in
developing new NMR methodologies. In the case of uniform 13
C, 15
N, and 2
H labeling,
the preparation of rNTPs follows protocols pioneered by the Pardi and Williamson
laboratories [11-13]. Briefly, total RNA is extracted from high-density E. coli cultures
grown in media with strictly defined carbon and nitrogen sources. The RNA is
hydrolyzed with Nuclease P1 and applied to a boronate resin column to separate
rNMPs from dNMPs. Enzymatic phosphorylation of purified rNMPs follows a two-
step process in which rNMPs are converted to rNDPs via nucleotide-specific kinases.
The reaction is coupled to an ATP-regeneration step that powers the production of
triphosphates. Fully-charged rNTPs are re-purified by a boronate affinity column,
removing salts and high molecular weight impurities that could interfere with efficient
in vitro transcription.
Myokinase, guanylate kinase and nucleoside monophosphate kinase enzymes
responsible for NMP-NDP conversion are purified commercially from varying sources,
but can be expensive and unstable. Alternatively, nucleotide-specific monophosphate-
charging enzymes can be cloned directly from bacteria. E. coli adk, cmk, gmk and
pyrH genes fused to a His6-tagged, solubility-enhancing GB1 partner [14] are easily
expressed in large quantities using standard expression and purification methods. In
addition, the bacterial monophosphate kinases are more efficient than their commercial
counterparts and are stably stored at −80 °C (Roth and Hennig, unpublished). Finally,
costs can be further reduced by modifying the ATP regeneration/triphosphate charging
reaction to instead utilize phosphocreatine and creatine kinase [15].
More exotic nucleotide labeling strategies (e.g. site-specific deuteration or 19
F
incorporation) require additional steps including the chemical synthesis of custom-
labeled ribose [7; 16; 17] and/or coupling of an isotopically-labeled base to the sugar
moiety [18-20], possibly requiring an additional UTP→CTP conversion as the final step.
While some specifically-deuterated NTPs are commercially available, fluorinated
rNTPs are not. The details of alternative rNTP labeling are discussed in section 3.
2.2. DNA-Template Directed Synthesis of RNA Using T7 RNA Polymerase
The production of millimolar quantities of RNA required for structural analysis by
NMR is generally accomplished by large-scale in vitro transcription reactions. The
preferred enzyme for this reaction is bacteriophage T7 RNA polymerase because it is
better characterized than other common DNA-directed RNA polymerases (T3 and SP6)
[21; 22]. There are two basic strategies for oligonucleotide synthesis using T7. Short
RNA (<50 nt) transcriptions can be carried out using synthetic DNA templates. The
template can be comprised of complementary DNA oligonucleotides or a top strand
consisting of the 17-nt T7 promoter and a complementary strand that contains the T7
promoter and the transcript of interest [23]. The second strategy utilizes a double-
stranded plasmid that consists of the T7 promoter, the desired RNA product, and a
suitable restriction enzyme sequence to linearize the plasmid and terminate
transcription. This strategy is preferred because it is more efficient, produces fewer
abortive transcripts, and facilitates subsequent purification of the relatively small
transcript from the much larger DNA template [23].
Optimization of the transcription reaction prior to large-scale production is
essential since the yield of in vitro transcribed RNA is dependent on many factors
which are not fully understood. The most critical factors for efficient T7 transcription;
however, are the MgCl2/rNTP ratio and T7 polymerase and DNA template
concentrations. Duplicate small-scale (10−50 μl) transcriptions can be designed in a
rational sparse matrix [24] to find optimal conditions chosen to promote total RNA
yield (e.g. when using unlabeled NTPs) or to maximize transcript yield per mole of
labeled nucleotides. After optimization, a 1 mL pilot transcription is recommended to
verify predicted yields and to estimate the volume required for full-scale (millimolar)
transcript production.
DNA template design must take into account two disadvantages of T7-directed
RNA synthesis. First, an efficient reaction requires that T7 is primed by at least two
guanosines as the initiating nucleotides of the transcript [21]. Second, T7 RNA
polymerase can produce “add-on” (n+1, n+2) transcripts that are suboptimal for
structure determination [21]. This 3'-end heterogeneity can be resolved through
purification techniques or template design that incorporates a cis-acting ribozyme.
The hammerhead ribozyme is a small (<50 nt) catalytic RNA consisting of three
stems and a conserved core that efficiently cleaves substrates containing an XUN motif,
where X can be any base and N must be an unpaired A, C, or U. The most efficiently
cleaved sequence is the GUC triplet [25]. The hammerhead can be used to hydrolyze
RNA substrates in trans [26], or engineered as part of a cis-acting, self-cleaving RNA
transcript [27]. Hydrolysis of the phosphodiester bond occurs after the GUC, resulting
in a population of RNA transcripts with homogeneous 3'-ends. Critical to the activity of
the ribozyme is the conserved three-way junction that forms the required base pairing
around the GUC triplet (Figure 1A). Proper folding of the RNA-hammerhead transcript
may require modifications of nucleotides at its 3'-end in order to base pair with the
desired RNA sequence and promote the formation of a third stem. Therefore, it is
imperative that the potential RNA-hammerhead constructs are subjected to an RNA
folding algorithm such as Quikfold [28; 29] to confirm the proper formation of the
cleavage junction (Figure 1A). Additionally, purification of the desired RNA from the
hammerhead requires extra steps since superior resolution is necessary to separate
similarly-sized transcripts. Finally, hammerhead transcriptions introduce extra cost
because a sizeable portion of the synthesized transcript is discarded following
purification of the target RNA. This consideration is important when preparing NMR-
scale transcripts using expensive isotope-labeled nucleotides.
Figure 1. Overview and purification of a cis-hammerhead transcript. (A) Secondary structure prediction of a
3’ hammerhead construct. Base pairing between the target transcript (black) and hammerhead (grey) forms
the third stem and positions the GUC triplet in the proper context for self-cleavage, releasing a target RNA
with homogeneous 3’ ends. (B) Purification of a 22mer/hammerhead RNA analyzed by 8 M urea-PAGE.
(Top) FPLC anion-exchange is insufficient to resolve the hammerhead (HH) and hairpin (HP) cleavage
products. Subsequent HPLC anion-exchange results in purified 22 mer RNA for NMR analysis (bottom).
2.3. RNA Purification
Traditionally, milligram quantities of in vitro-transcribed RNA were purified by
denaturing (8 M urea) PAGE followed by electroelution from the gel matrix, desalting,
buffer exchange, and refolding [21; 30]. The distinct advantage of this method is the
ability to separate preparative quantities of RNA with single-nucleotide resolution. On
the other hand, gel-purification is a labor-intensive, RNA-denaturing process that
yields transcripts contaminated with water-soluble acrylamide oligomers [23].
Although the impurities can be removed through extensive washing or dialysis, the
process is time-consuming and incomplete. For these reasons, new methods of
purifying large-scale transcription reactions have been developed, including anion-
exchange [31; 32], size-exclusion [23; 33] and DNA affinity chromatography [34]. The
RNA purification protocols adapted by our laboratory utilize components of these
methods to produce NMR-quality transcripts with varying size and complexity under
native conditions. Briefly, large-scale (5−15 mL) T7 run-off transcriptions are
centrifuged to remove pyrophosphate precipitates, then buffer-exchanged with an
appropriate centrifugal filter device. Unincorporated nucleotides and short abortive
transcripts are also largely removed by this step. Removal of T7 polymerase, plasmid
DNA template and the remaining abortive transcripts is achieved by FPLC anion
exchange chromatography (GE HiTrapQ HP). Following high-salt elution, fractions
corresponding to the expected transcript are analyzed for purity by denaturing PAGE
and pooled (Figure 1B). Finally, the sample is exchanged back into the low-salt buffer
for NMR analysis. This protocol yields high-quality RNA samples in <2 days with
minimal sample loss, but it is dependent on first-rate optimization prior to full-scale
transcription. While FPLC anion exchange is well-suited to purify discrete transcripts,
its resolution is limited. Where more stringent purification is required, the sample is
exchanged into a buffer suitable for HPLC anion-exchange chromatography. The
Dionex DNAPac provides nucleotide resolution of pre-purified RNAs and is ideal for
the separation of contaminant transcripts and hammerhead cleavage products. Again,
the resolved transcripts are verified by denaturing PAGE, pooled, buffer exchanged and
quantified for NMR (Figure 1B). Unlike reversed-phase chromatography, pre-
purification by FPLC is a simple, robust method of “cleaning” large-scale transcripts
prior to DNAPac separation in a non-denaturing environment free of potentially
problematic organic solvents.
3. Labeling Approaches
NMR structure determinations of RNA are simplified by the application of multi-
dimensional, heteronuclear NMR experiments. However, these experiments require
milligram quantities of isotopically labeled RNA, so the production of isotopically
labeled RNA remains critical to the success of these NMR-based structure studies [5;
35]. In contrast to the abundant 1
H and 31
P isotopes, the naturally occurring nuclei 12
C
and 14
N cannot be readily studied with high-resolution NMR techniques. Nucleotide-
specific labeling schemes are compatible with RNA synthesis using T7 RNA
polymerase and relatively straightforward because the four individual rNMPs can
conveniently be separated by ion exchange HPLC chromatography. Thus, all labeling
schemes described can be tailored to address specific assignment problems.
3.1. Conventional Labeling of RNA with 13
C and 15
N
Uniformly labeled rNTPs (GCN
, CCN
, ACN
, UCN
) for in vitro transcription reactions
can be readily produced by phosphorylation of nucleotides isolated from bacteria
grown on 13
C- and/or 15
N enriched media [11-13; 36]. Through the use of 13
C and 15
N
isotopic labeling and multidimensional heteronuclear NMR experiments, studies of 15-
kDa RNAs are commonplace and methodological developments have been reviewed
[37-43].
3.2. Deuteration Strategies
The specific substitution of protons with deuterium represents the most promising way
to increase sensitivity while simplifying spectra. Labeling schemes involving
deuteration afford two benefits: first, the spectra will be less crowded and second, the
relaxation properties of carbon and the remaining proton nuclei will be favorably
altered. The reduced proton spin density decreases relaxation times of protons in RNAs.
In addition, any 13
C atoms attached to deuterium have slower relaxation properties
relative to 13
C−1
H moieties. Therefore, deuterium labeling has particularly aided in the
study of large RNA molecules. Adopting the enzymatic synthesis strategy of the
Williamson laboratory, the following differentially deuterated ribonucleotides can be
prepared for transcription reactions:
Beginning with 2
H,13
C-uniformly labeled glucose, the ribose portion of the
nucleotides are deuterated at the H3', H4', H5', H5'' positions to give [1',2',3',4',5'-
13
C5,3',4',5',5''-2
H4]-rNTPs which greatly simplify the NMR spectra for large RNAs
[17; 44]. In addition, pyrimidine bases with deuteration at the H5 position, 5-
2
H(pyrimidine)-rNTPs, can be included, removing the spectral crowding from strong
H5/H6 crosspeaks. This labeling pattern conserves important NOEs between base and
ribose while affording all the previously described benefits of deuteration. The H2'
protons, which normally reside in the most crowded region of the proton spectrum, can
be identified based on their chemical shift. If faster 1
H T2-relaxation caused by 13
C−1
H
dipole-dipole interactions presents a problem, uniformly 2
H labeled glucose can be
used to generate [12
C5,3',4',5',5''-2
H4(5-2
H(pyrimidine))]-NTPs for transcription
reactions.
Random fractionally deuterated nucleotides, 15
N,13
C-(50% 2
H) rNTPs or GCN50%D
,
CCN50%D
, ACN50%D
, UCN50%D
), are prepared by growth of M. methylotrophus on 15
N-
ammonium sulfate and 13
C-methanol as sole carbon and nitrogen sources [36].
Alternatively, E. coli can be grown on minimal salt media containing 15
N-ammonium
sulfate and 13
C-glucose. The growth is carried out in 50% D2O. Perdeuterated,
15
N,13
C,2
H rNTPs (GCND
, CCND
, ACND
, UCND
) can be synthesized by growing bacteria in
100% D2O in minimal media, optionally supplemented with 15
N-ammonium sulfate
and/or 13
C-acetate/methanol/glucose as sole nitrogen and carbon sources [45; 46].
Random fractional deuteration as well as perdeuteration is useful for NMR of large
systems due to improved relaxation properties. Apart from C5' methylene ribose
carbons, random fractional deuteration of RNA does not suffer from the production of
isotopomers with chemical shift heterogeneity and decreased signal intensities. A
general disadvantage of deuterium labeling is the reduced 1
H-1
H NOE based
information content essential for structure determination.
3.3. Labeling of RNA with 19
F
Fluorinated ribosomal 5S-rRNA [47] and tRNA [48] isolated from E. coli grown in the
presence of 5F-U revealed high levels (>80%) of incorporation of 5F-UTP in place of
UTP as early as 1977. Since this pioneering work, substantial effort has been made on
the study of nucleic acids using both liquid- [15; 19; 49-51] and solid-state 19
F NMR
[52; 53]. Advantages of using spin 19
F as an NMR probe are its high sensitivity (83%
of 1
H) combined with 100% natural abundance and a wide chemical shift distribution
(ca. 50-fold larger than that of 1
H) which typically leads to well-resolved signals in
one-dimensional NMR spectra. The 19
F chemical shift of a covalently bound fluorine
atom is extraordinarily sensitive towards changes in the local microenvironment which
is primarily attributable to the anisotropic distribution of the electrons in the 2-p
orbitals. The van der Waals radius of a fluorine atom, 1.35Å, is only slightly larger than
that of a hydrogen (1.2Å) and smaller than a methyl group (2.0Å) providing a
promising candidate to substitute for either of those without structural or functional
alteration. The introduction of 19
F substitutions into the heterocyclic bases is non-
perturbing and provides researchers with uniquely positioned, sensitive NMR reporter
groups to monitor 1) conformation, 2) molecular interactions and 3) dynamics of RNA.
As a result of drastically simplified spectra, 19
F-NMR spectroscopy can provide very
useful information on specific aspects of the structure, interactions, and mobility of
RNAs that could not otherwise be obtained.
Fluorinated RNA can routinely be prepared by either phosphoramidite-based
chemical synthesis [51] or in vitro transcription reactions using RNA polymerase. We
recently established the efficient and economical enzymatic synthesis of the fluorinated
nucleotide analogues 5F-UTP, 5F-CTP [18; 19], and 2F-ATP [15]. The base analog
5F-uracil is readily used as a substrate for uracil phosphoribosyl transferase, which
provides a novel and efficient route to produce 5F-UMP, and ultimately 5F-UTP. The
fluorinated nucleotide analogues 2F-AMP and 5F-CMP can be synthesized by
enzymatic conversions of 2F-adenine using adenine phosphoribosyltransferase and by
conversion of the nucleoside analog 5F-cytidine catalyzed by uridine kinase. Our
laboratory subsequently demonstrated that these fluorinated rNTP analogues can be
specifically incorporated into RNA and that the modified nucleotide analogue 5F-Cyt
selectively base-pairs with guanine [18; 19], 5F-Ura selectively base-pairs with adenine
[18; 19], and 2F-Ade selectively base-pairs with uridine in a non-perturbing way [15]
in individual samples containing one of these labeling schemes. Alternative, specific
labeling of RNA with 19
F at the 2'-position in the ribose can be problematic especially
for regions adopting non-canonical conformations because of the conformational bias
imposed by the fluorine substitution. 2'-Deoxy-2'-fluorinated nucleosides are
effectively locked in the C3'-endo sugar pucker normally associated with A-form RNA
geometry [54-56].
4. NMR Resonance Assignments
It is the limited chemical diversity in comparison to proteins that complicate NMR (and
other) studies of RNA and its complexes. RNA secondary structure is trivial by
comparison with proteins, being essentially the code of Watson-Crick base pairing:
Guanine (Gua) pairs with Cytosine (Cyt); Adenine (Ade) pairs with Uracyl (Ura)
(Figure 2). RNA mainly adopts A-form helical geometries, which contributes to
chemical shift degeneracy and makes unambiguous assignments challenging for larger
RNAs. A second problem in studies of RNA with molecular weights above 25 kDa is
the fast decay of the NMR signal due to relaxation. Line widths in NMR spectra are
inversely proportional to the relaxation rates. Therefore the signal-to-noise in NMR
spectra of larger molecules is poor. The line width problem can be overcome by (1) the
use of deuteration to eliminate proton mediated relaxation pathways and (2) the NMR
method called TROSY [57].
4.1. Initial Characterization of Target RNA Constructs
Characterizing the conformation of an RNA under investigation is a crucial first step
before conducting a detailed and time-consuming NMR analysis. At the outset, the
suitability of the system for a high-resolution structure elucidation and optimal sample
conditions for acquisition of the required NMR experiments should be determined. The
imino proton region of the proton NMR spectrum of an unlabeled RNA sample in H2O
provides a sensitive diagnostic for this purpose. One peak should be observed for each
Watson-Crick and two for each G·U wobble base pair in the molecule. Since the imino
protons exchange rapidly with the bulk H2O, we typically record jump-return echo
experiments that avoid presaturation, while providing the most efficient water
suppression [58]. The pyrimidine base protons can provide a valuable alternative,
circumventing problems related to solvent exchange or conformational heterogeneity.
H5-H6 cross peaks can be conveniently monitored in WATERGATE-2D TOCSY
(total correla
every pyrimi
Figure 2. Watso
5'-phosphodiest
uracil are show
indicated. Defin
while endocycl
RNA is commo
Overhauser effe
bond correlatio
phosphorous re
and HCCH-TO
resonances. Ma
H3'/H5'/H5''-rib
transfer steps. N
Exchangeable i
experiment, wh
H5(C5C4N4)H
HCCH-COSY [
H5/H6 and A s
shared quaterna
spin system (red
in A-form RNA
independent 1
J(
and HCCH-TO
HCNCH transfe
73]. Optimized
chemical shift
involved in hyd
is accomplished
ation spectrosc
idine.
on-Crick base pair
ter bond. Hydroge
n as dashed lines.
nition of backbone
ic torsion angles
only achieved thr
ect (NOE) pattern
ons is shown usin
sonances Pi and P
OCSY experiments
agnetization can
bose protons for
Nucleobase spin s
mino protons in G
hile crucial ami
and (H)N6(CC)H
[64] and HCCH-T
spin systems. A T
ary carbons in larg
d circles) of unlab
A. Uniform labeli
(C,C) couplings an
OCSY experiment
ers magnetization
d HCN-type pulse
and show signific
drogen bonds (dark
d using a HNN-CO
opy) experime
red fragment of RN
en bonding intera
Standard atom nu
e α, β, γ, δ, ε, and
ν0 through ν4 are
rough identificatio
ns (gray ovals). Th
ng black circles.
Pi+1. HCP-CCH-T
s and thus resolv
also be transferr
detection using e
systems (orange c
G and U are corre
no proton linkag
H experiments for
TOCSY [65; 66] e
TROSY-relayed HC
ger RNA molecul
eled RNA is hamp
ing with 13
C allow
nd chemical shift
ts are used to un
from the anomeri
e schemes facilita
cant sensitivity g
k blue circles) and
OSY experiment o
ents where one
NA with sequence
ctions between cy
umbering of ribos
ζ and glycosidic χ
e given for adenin
on of sequential b
he spin system for
HCP experiment
TOCSY [59] and P
ve relevant correl
red from 31
P reso
either COSY- [6
circles) can be ass
elated with non-ex
ges with non-ex
C and A spin syst
experiments are us
CCH-COSY can i
es [64]. Magnetiz
pered due to the sm
ws magnetization
evolution on the C
nambiguously ass
ic H1' proton to th
ate assignments t
ains [74; 75]. Th
d quantification of
or one of its varian
expects a H5-
e cytosine (i), aden
ytosine and guano
se and the four com
χ torsion angles is
ne. Sequential assi
base H8 and H6
r sequential assign
ts correlate H4'-C
P(CC)H-TOCSY [
lations on the bet
onances to the 3
J
1] or heteronucle
signed using throu
xchangeable proton
xchangeable proto
tems, respectively
sed to unambiguou
identify A H2-H8
zation transfer thro
mall 3
J(H1',H2') vi
transfer using lar
C1' to C5' carbons
sign ribose spin
he base H6/8 proto
through joint glyc
he simultaneous id
corresponding h2
J
nts. Independent as
H6 correlation
nine (i+1), linked b
osine and adenine
mmon nucleobase
s indicated for cyto
ignments of unlab
to ribose H1' nu
nments using thro
C4' spin systems
[60] combine the
tter dispersed C1
J(H,P) scalar cou
ear TOCSY-type
ugh-bond experim
ns using an H(CC
ons are obtained
y [63]. Complemen
usly assign pyrimi
8 spin systems thro
ough the ribose pr
icinal coupling pre
rger, conformation
s. Thus, HCCH-CO
systems [67-71].
ons (green circles)
cosidic N1/9 nitr
dentification of n
J(N,N) scalar coup
ssignments of pote
n for
by 3',
e and
s are
osine
beled
clear
ough-
with
HCP
'-H1'
upled
[62]
ments.
CN)H
d by
ntary
idine
ough
roton
esent
nally
OSY
The
[72;
rogen
uclei
lings
ential
nitrogen hydrogen bond acceptor sites can be obtained from a two-bond 2
J(H,N) 1
H,15
N-HSQC experiment
using the intraresidue 2
J(H2,N1), 2
J(H2,N3), and 2
J(H8,N7) correlations for the purine residues in the RNA
molecule [76].
4.2. Assignment Strategy for Unlabeled RNA (< 25 nt)
Imino proton resonances are assigned sequence-specifically at the earliest stage from
water flip-back, WATERGATE-2D NOESY (nuclear Overhauser effect spectroscopy)
[77] spectra to verify the construct integrity and secondary structure predictions. The
subsequent assignment of non-exchangeable RNA resonances is commonly achieved
through identification of sequential base H8 and H6 to ribose H1' nuclear Overhauser
effect (NOE) patterns seen in helical regions of nucleic acid structure, in analogy to the
procedure originally utilized for DNA studies in the 1980s [78] (Figure 2). Complete
ribose H2', H3', H4', H5', and H5" spin system identifications are hampered by limited
dispersion (ca. 1ppm) and inefficient through-bond magnetization transfer from the
better resolved H1' resonances in TOCSY and COSY (correlation spectroscopy)
experiments. The 3
J(H1',H2') vicinal coupling is ca. 1 Hz for the C3'-endo puckers,
typically found in A-form helices [79-81]. However, a number of 1
H,31
P-
multidimensional HETCOR (heteronuclear correlation) schemes are available for
sequential assignment of 31
P and to extended ribose 1
H resonance assignments [61; 62].
The resulting two dimensional H3'/H5'/H5'',31
P-correlations can be concatenated with
homonuclear 1
H,1
H-NOESY or TOCSY experiments to transfer magnetization to
potentially better resolved resonances like H1' or aromatic H8/H6 resonances [82; 83].
Gradient-selected, sensitivity-enhanced heteronuclear single-quantum correlation
experiments (HSQC) [84; 85] recorded at natural 13
C abundance greatly facilitate site-
specific assignments owing to distinct ribose C1', C4', C5', Ade C2, Cyt C5, and Ura
C5 carbon chemical shifts. Ribose C2' and C3' as well as base Cyt/Ura C6 and
Gua/Ade C8 chemical shift ranges overlap yet can be distinguished from other carbon
sites in RNA (Table 2).
The 2'-hydroxyl group plays fundamental roles in both the structure and the
function of RNA and is the major determinant of the conformational and
thermodynamic differences between RNA and DNA. In aqueous solution the rapid
exchange of the hydroxyl proton with the solvent typically prevents its observation in
RNA at room temperature by NMR. Recently, our laboratory reported assignments and
a conformational analysis of 2'-OH groups of a medium sized RNA by means of
TOCSY and NOESY experiments at low temperature [86; 87].
4.3. Assignment Strategy for 19
F-labeled RNA
Using available chemical shifts from unmodified RNA samples, we have successfully
assigned the 19
F resonances for each 2F-Ade, 5F-Ura and 5F-Cyt in modified, medium-
sized RNA samples. The unambiguous fluorine chemical shift assignments in
substituted RNA can be accomplished using an approach that combines homo- and
heteronuclear through-space 19
F,1
H-HOESY, 1
H,1
H-NOESY, and 19
F,19
F-NOESY with
through-bond 1
H,19
F-HMBC (heteronuclear multiple bond correlation) experiments.
4.4. Assignment Strategy for Uniformly 13
C,15
N-labeled RNA (< 40 nt)
The NOE-based approach described in section 4.2 relies on assumptions about
structure and assignments, rendering it susceptible to errors from structural bias. A
methodology that achieves sequential assignment via unambiguous through-bond
correlation experiments, as is the case for proteins, would be more ideal. Such through-
bond NMR experiments are usually given a name that indicates the magnetization
transfer route. A possible approach for 13
C labeled RNAs is HCP correlation via
sequential INEPT (Insensitive Nuclei Enhancement by Polarization Transfer) transfers
[88; 89] (Figure 2, Table 2). Unfortunately, complete sequential assignments of even
medium-sized RNA molecules using through-bond experiments such as HCP, HCP-
TOCSY and HP-HETCOR are hampered by notoriously overlapped resonances and
modest sensitivity. Thus, unambiguous through-bond assignment using HCP-like
experiments is always difficult and impractical for larger RNA target molecules (> 40
nt).
Out of necessity, sequential assignments are therefore achieved using through-
space 1
H,1
H contacts derived from 3D and 4D-isotope edited NOESY experiments.
Fortunately, 13
C and 15
N enrichment permits a suite of through-bond experiments that
help to alleviate the inherent ambiguity problem of through-space contacts (Figure 2).
HCCH-COSY and HCCH-TOCSY experiments are used to unambiguously assign
ribose spin systems [67-71] (Figure 2). We commonly employ a hybrid version, the
HCCH-COSY-TOCSY [90; 91] to unambiguously assign crowded ribose spin systems.
The HCN and HCNCH experiments can elucidate intranucleotide H6/H8-H1'
correlations within and between the base and ribose resonances, significantly reducing
the ambiguity present in the NOESY-based assignment procedure.
Canonical base-pair hydrogen bonding of the Watson-Crick type is fundamental in
all biological processes where nucleic acids are involved. NMR experiments have been
introduced that allow the direct identification of donor and acceptor nitrogen atoms
involved in hydrogen bonds [92; 93]. The partially covalent character of hydrogen
bonds gives rise to measurable scalar spin-spin couplings of the type h2
J(N,N) and
h1
J(H,N) that represent important additional NMR parameters for the structure
determination of nucleic acids in solution [92; 93]. In addition to the unambiguous
determination of donor (D) and acceptor (A) nuclei involved in hydrogen bond
formation, the magnitude of the h
J(D,A) couplings reports on the hydrogen bond
geometry.
4.5. Assignment Strategy for Type-Specifically Labeled RNA (> 40 nt)
Despite the use of isotope labeling with 13
C and 15
N, resonance assignments of larger
RNAs (> 40 nt) continue to be challenging. Above 50 nucleotides, through-bond
experiments start to fail because of rapid transverse relaxation. In particular, the
sensitivity of through-bond experiments correlating exchangeable and non-
exchangeable base protons rapidly deteriorates due to long transfer times associated
with small heteronuclear 1
J(C,N) and multi-bond 2,3
J(C,C) couplings. The following
three case studies (Table 1) were chosen based on the important state-of-the-art
technologies that were applied in conjunction with the molecular weight of the targeted
RNAs.
Table 1. Large RNA (greater than 50 nucleotides) NMR structures in the PDB.
PDB accession Code No # of nucleotides (nt) Description Reference
1P5P 77 HCV IRES domain II [94]
1S9S 101 MMLV Encapsidation signal [10]
2ADT 86 GAAA tetraloop-receptor [9]
Figure 3. Large RNA structures determined by NMR. A) HCV IRES Domain II (26 kDa, PDB accession
code 1P5P). B) GAAA Tetraloop Receptor Complex (30 kDa, PDB accession code 2ADT). C) Moloney
Murine Leukemia Virus Encapsidation Signal (34 kDa, PDB accession code 1S9S).
4.5.1. Structure of HCV IRES Domain II (26 kDa)
Larger RNAs often necessitate a “divide and conquer” strategy. This approach assumes
a modular architecture of the target RNA sequence without tertiary contacts between
the smaller sub-domains (e.g. distant ends of an elongated stem-loop). Accordingly, the
NMR solution structure of the 77-nt domain II of the hepatitis C virus (HCV) IRES
(internal ribosome entry site) RNA was determined by Puglisi and coworkers (Figure
3A). The excision of two stably folded 34- and 55-nucleotide segments representing the
entire domain II allowed for high-resolution structure determinations using
conventional, uniformly 13
C,15
N-labeled RNA samples. Subsequently, the global
conformation of domain II, a distorted L-shape, could be determined using a joint
refinement procedure against residual dipolar coupling (RDC) restraints from both the
two smaller segments as well as 60 RDCs determined for the large domain II construct.
The inclusion of RDC restraints obtained from partially oriented RNA samples enabled
precise definition of the relative orientation of the distant ends of the domain II RNA.
Weakly aligned RNA samples were obtained by adding Pf1-phage as a cosolute. A
full-length, intact 100 kDa HCV IRES was constructed by joining a 15
N-labeled
domain II segment and an unlabeled segment comprising domains III and IV using T4
RNA ligase [95]. A comparison of the imino 1
H and 15
N chemical shift data from the
64-nucleotide domain II with the segmentally labeled, intact 314-nucleotide IRES RNA
supports the notion of an independently folded subdomain and suggests an
indistinguishable structure in the larger context.
4.5.2. Structure of a GAAA Tetraloop Receptor Complex (30 kDa)
In an effort to address the striking lack of RNA tertiary structures in solution, Butcher
and coworkers solved the NMR structure of a homodimeric, 30 kDa GAAA tetraloop-
receptor RNA complex (Figure 3B). The twofold symmetry of this homodimeric
arrangement considerably reduces the complexity of the NMR spectra. A total of seven
nucleotide-type-specific RNA samples, GCN
CCN
, ACN
UCN
, GCN
UCN
, GCN
, ACN
, CCN
, and
UCN
, were prepared in addition to a uniformly labeled RNA sample, GACUCN
.
Adiabatic frequency-swept inversion pulses optimized to an empirically observed
relationship between 1
J(C,H) and carbon chemical shift are commonly used in purge-
filter elements to ensure the uniform inversion of all ribose and base carbon sites.
Elegant 12
C-filtered/13
C-edited (100% D2O) and simultaneous 12
C,14
N-filtered/13
C,15
N-
edited (90% H2O/10% D2O) 3D NOESY spectra have been proposed [96] where
monitored 1
H magnetization that starts at either 12
C- or 14
N-bound protons is transferred
via isotropic mixing and is subsequently detected at 13
C- or 15
N-bound protons. The 86-
nucleotide RNA-RNA homodimer exhibits unfavorable, faster T2-relaxation of both
protons and carbons when compared to the 101-nucleotide core encapsidation signal
described above. Due to these limitations, the authors relied on more sensitive 2D
(rather than 3D or 4D) isotope-filtered/edited NOESY experiments for unambiguously
identifying NOEs between labeled and unlabeled nucleotides [97; 98]. Remarkably, the
13
C-filtered experiments suffered from 1
H line broadening stemming from 13
C−1
H
dipole-dipole interactions, necessitating a selective deuteration scheme for the ribose
ring to complete resonance and NOE assignments. Here, specifically deuterated
[3',4',5',5''-2
H4(H5-2
H(pyrimidine))]-NTPs were used which offer narrower H1'- and
H2'-line width with the added benefit of reduced overlap originating from H5-base
proton (pyrimidine) and H3', H4', H5', and H5''-ribose resonances [7]. RDC data was
essential for accurate structure determination of the distant helical ends, but the authors
also had to overcome sample precipitation issues in the presence of Pf1-phage by
lowering the sample concentration, permitting measurement of only 24 1
H−15
N RDCs.
4.5.3. Structure of the Encapsidation Signal of the Moloney Murine Leukemia Virus
(34 kDa)
An alternative strategy is to resort to nucleotide-specific labeling to facilitate the NMR
data accumulation and accomplish complete assignment. Summers and coworkers were
able to determine the solution structure of the 101 nucleotide Moloney Murine
Leukemia Virus (MMLV), both free [10] (Figure 3C) and bound to the nucleocapsid
(NC) domain of Gag [99]. This represents the largest nucleic acid NMR structure to
date using a total of nine differently labeled RNA samples. Resonance assignments
were obtained using a new strategy that relies heavily on isotope-filtered/edited
NOESY experiments in combination with nucleotide specific isotopic labeling which
allows for unambiguous, nucleotide-specific identification of spin systems. Four
samples were generated using nucleotide-type-specific 13
C,15
N-labeled RNA samples,
GCN
, ACN
, CCN
, and UCN
, respectively, to help distinguish intra- from internucleotide
NOE connectivities in 3D and 4D 13
C-edited NOESY experiments. In addition, four
nucleotide-type-specific 1
H-labeled RNA samples were generated using, GH
, AH
, CH
,
and UH
, respectively, with remaining nucleotides being 90% perdeuterated, XD
. Finally,
the exchangeable imino proton assignments were confirmed using a 15
N-labeled G and
U sample, GN
UN
. The overall structure of the RNA consists of three stem-loops, two of
which coaxially stack, while a short flexible linker connects the third stem-loop. A 15
N-
relaxation analysis using the GN
UN
-sample revealed that one stem-loop segment
tumbled independently from the other two in solution, mitigating to some extent the
sensitivity issues associated with slowly tumbling, large RNA molecules. RDC data
could be used only for refinement of the individual, isolated stem-loop segments
because the intact RNA precipitated in the presence of Pf1-phage cosolute.
Table 2. NMR experiments for RNA resonance assignment.
Approximate RNA size Isotope labeling scheme NMR experimentsa
Reference
< 25 nt
unlabeled:
(GACU)U
1
H, 1
H-COSY
1
H, 1
H-TOCSY
1
H, 1
H-NOESY
31
P, 1
H-COSY
31
P, 1
H-TOCSY
31
P, 1
H-TOCSYNOESY
1
H, 13
C-HSQC
[100]
[101]
[77]
[61; 102]
[62]
[82; 83]
[84; 85]
< 40 nt
uniformly 13
C,15
N:
(GACU)CN
1
H, 13
C-Constant time HSQC
1
H, 13
C-Constant time TROSY
1
H, 15
N-HSQC
1
H, 15
N-2
J-HSQC
HCCH-COSY
HCCH-TOCSY
HCCH-COSYTOCSY
HCP
PCH
HCN
HCNCH
HNN-COSY
HN(C)CH-TOCSY
HC(C)NH-TOCSY
3D 13
C-edited NOESY
4D 13
C-edited NOESY
2D 15
N-edited NOESY
[103]
[104]
[105]
[76]
[64]
[65; 66]
[90; 91]
[59; 88]
[102; 106]
[75; 107-109]
[73; 110]
[92; 93]
[111-113]
[114-116]
[117]
[118]
[119]
< 50 nt
- type-specific labeling,
e.g.: (GC)CN
(AU)U
and
(GC)U
(AU)CN
- site-specific
deuteration:
(GCAU)D
1
H, 13
C-HMQC
1
H, 15
N-HMQC
1
H, 15
N-TROSY
12
C,14
N-filtered/13
C,15
N-edited
3D NOESY
[74]
[74; 120]
[121]
[96; 122; 123]
> 50 nt
type-specific deuteration,
e.g. (G)U
(CAU)D
12
C,13
C-filtered/edited 12
C,13
C-
edited/filtered 2D NOESY
[97; 98]
a
Underlined experiments are preferably carried out in D2O.
5. Restraint Collection for Structure Determination
After sequence specific assignments of RNAs are obtained, the structure determination
is traditionally based on collecting sufficient numbers of proton-proton distance
restraints utilizing NOESY experiments. Potentially, the short distance restraints
between pairs of protons can be complemented with torsion angle information
accessible through J-coupling constants. Vicinal 3
J scalar coupling constants can
provide useful structural information about the sugar pucker, the β and ε backbone
torsion angle conformations, as well as the glycosidic torsion χ which defines the
orientation of nucleobases with respect to the sugar moiety (Figure 2).
In general, there is a practical difficulty in defining RNA structures precisely by
NMR because traditional NOE and J-coupling based structure calculation relies on
either short-range distance (< 6 Å) or local torsion angle information. The structural
analysis of the RNA backbone conformation is complicated by the lack of useful
1
H−1
H NOE distance restraints available that define the backbone torsions. RNAs often
are elongated structures which are better approximated as cylindrical rather than
globular shapes. Thus there is a lack of NOE information between distant ends of the
molecule, and as a result, the relative orientations of helical segments at opposite ends
of the molecule are poorly defined. Recent advances in methodology have aimed to
alleviate or overcome this shortcoming [124; 125]. Experiments to measure
orientational, rather than distance dependent dipolar couplings, and cross-correlated
relaxation rates have been developed providing additional structural information. RDC
data not only provide additional information for a better definition of the global
orientation of the segments with respect to each other but also carries valuable
information on the dynamical properties of the RNA studied.
5.1. Proton-Proton Distance Restraints
NOEs provide distance restraints for pairs of hydrogen atoms. Only short proton-proton
distances in the range < 6 Å are accessible through NOESY-type experiments. The
intensity of NOESY cross peaks is approximately proportional to the inverse of the
averaged distance to the power of six, <1/rij
6
>, assuming an isolated pair of proton
spins i and j.
For RNA NMR studies, NOE derived distance restraints are often determined
semi-quantitatively and placed into four categories: Strong, medium, weak and very
weak NOEs. A conservative approach sets all the lower bounds to 1.8 Å (van der
Waals radius) with upper bounds ranging from 3.0 Å for the most intense NOEs to 7.0
Å for the weakest NOEs found in H2O experiments. Potential problems with
interpretation of obtained NOESY cross peak intensities in terms of 1
H−1
H distances in
structure calculations arise mainly from the phenomenon of spin diffusion. Spin
diffusion causes a breakdown of the isolated spin pair approximation because nearby
protons provide competing indirect pathways for observing the direct NOE between the
two protons. Spin diffusion effects are significant at longer NOESY mixing times (>
100 ms) leading to damped direct-pathway cross peak intensities and resulting in
underestimated interproton distances. Furthermore, multistep transfer pathways can
result in false NOE assignments. However, in an early stage of the assignment
procedure based on NOESY correlations, spin diffusion pathways can aid the
identification of spin systems. Thus, for assignments it is recommended to analyze
NOESY spectra acquired with a range of mixing times (ca. 50−200 ms).
5.2. Torsion Angle Restraints
J-coupling restraints can be implemented in two different ways during structure
determination. They can be introduced qualitatively by restricting a torsion angle in a
loose manner (± 30°) to one of the three staggered rotamers along the phosphodiester
backbone or defining the preferred ribose sugar pucker such as C2'-endo or C3'-endo.
Alternatively, vicinal J-couplings can be quantitatively related to a certain torsion angle
using semi-empirical Karplus relations of the form: 3
J = A cos2
θ + B cosθ + C, where θ
is the intervening torsion angle [63; 126].
The quantitative analysis of scalar J-couplings, especially in the case of
homonuclear 3
J(H,H) couplings related to the ribose sugar pucker, becomes more and
more difficult with increasing molecular weight and largely fails for RNAs larger than
40 nt. In contrast, the efficiency of cross-correlated relaxation pathways scales linearly
with the overall correlation time of the molecule, which is related to its size. Cross-
correlated relaxation rates have been introduced to high resolution NMR as a novel
parameter for structure determination [127; 128] and allow the characterization of
conformations for larger RNA molecules for which J-coupling analysis is not feasible
anymore.
5.2.1. Sugar Pucker
The ribose sugar geometry is defined by five alternating torsion angles (ν0 through ν4,
Figure 2). Usually, the ribose sugar adopts one of the energetically preferred C2'-endo
(South) or C3'-endo (North) conformations. A number of 1
H,1
H and 1
H,13
C scalar
couplings are available to determine the sugar pucker qualitatively with the
combination of H1'-H2' and H3'-H4' coupling constants being the most useful for
smaller RNAs. The 3
J(H1',H2') vicinal coupling is > 8 Hz for C2'-endo puckers and ca.
1 Hz for the C3'-endo puckers, typically found in A-form helices [79; 80; 89]. The
opposite behavior is expected for the 3
J(H3',H4') coupling constant with C2'-endo
puckers associated with small and the C3'-endo puckers associated with relatively large
coupling constant values. An alternative is the measurement of cross-correlated
relaxation rates between neighboring 13
C−1
H dipoles within the ribose ring to define
the sugar pucker. For RNAs, cross-correlated relaxation rates can be measured using an
experiment that belongs to the HCCH class, and precisely determine the ribose sugar
pucker without the need of any empirical Karplus parameterization [129]. The
resolution of this experiment can be further enhanced by adding a CC-TOCSY transfer
[130].
5.2.2. γ Torsion Angle
Measurement of the γ torsion is difficult due to the need for stereospecific assignments
of the H5' and H5'' proton resonances. In principle, the two-bond C4',H5'/H5''
couplings can be used in conjunction with the vicinal H4',H5'/H5'' couplings to define γ
[81; 131].
5.2.3. Glycosidic Torsion Angle χ
The preferred orientation around χ in A-form helix is anti, which makes the base
accessible for commonly found hydrogen bonding interaction. Two heteronuclear
vicinal 1
H,13
C couplings contain useful information about the glycosidic torsion angle χ.
The 3
J(H1',C) couplings involving the C4,C8 carbons in purines and the C2,C6 carbons
in pyrimidines, all depend on the χ torsion [81; 132]. We have shown that the
magnitude of a five bond scalar 5
J(H1',F)-coupling observed upon 5F-Ura and 5F-Cyt
substitutions also depends on the glycosidic torsion angle χ [18]. Alternative
applications have been published where the cross-correlated relaxation between two
13
C−1
H dipoles or a dipole and the glycosidic 15
N CSA is utilized to collect information
about the glycosidic torsion angle χ [133-135].
5.2.4. ε and β Torsion Angles
The ε and β torsions can be determined by measuring a variety of 13
C,31
P and 1
H,31
P
scalar couplings. Some of these torsions may be measured directly in 2D 1
H,31
P
heteronuclear HETCOR experiments [61; 102] and non-refocused 1
H,31
P HSQCs if the
phosphorous and proton resonances are sufficiently resolved. However, both the ribose
proton and phosphorus resonances involved are generally overlapped for even
moderate size RNAs. Accurate measurements for 13
C,31
P and 1
H,31
P couplings can be
obtained from both phosphorous-fitting of doublets from singlets [136] or spin echo
difference experiments [137-141]. J-HMBC techniques can be applied to determine
3
J(H,P) couplings [142]. A quantitative version of the HCP experiment allows for
quantitation of 3
J(C4',P) [143].
5.2.5. α and ζ Torsion Angles
The α and ζ torsions are not accessible by J-coupling measurements because the
involved 16
O nuclei have no magnetic moment. Some groups have used 31
P chemical
shifts as a guide for loose constraints on these torsions [144]; however, the correlation
between 31
P chemical shifts and the phosphodiester backbone conformation is not well
understood in RNA. Cross-correlated relaxation rates have been employed to gain
information on the α and ζ torsions. The cross-correlated relaxation between a ribose
13
C−1
H dipole and the 31
P chemical shift anisotropy (CSA) carries valuable structural
information about the phosphodiester conformation [145].
5.3. RDC Restraints
Several methods have been developed to create a slightly anisotropic environment for
molecules tumbling in solution. This results in a small degree of alignment of the
molecule, such that the dipolar couplings no longer average to zero, while retaining the
quality of high-resolution NMR spectra. The most promising systems for NMR studies
of partially aligned systems are dilute liquid crystalline bicelles [146] or Pf1
bacteriophage solutions [147; 148]. RDCs depend on the average value of an
orientational function and the inverse cube of the distance, 1/r3
, between the coupled
nuclei. Two polar angles θ and φ characterize the orientation of the internuclear vector
that connects coupled nuclei with respect to the principal axis system of the molecular
alignment tensor A. Thus, for a directly bonded pair of nuclei with known distance,
such as 1
H−13
C or 1
H−15
N in labeled RNA, angular restraints can be extracted from
dipolar coupling data and incorporated during the structure calculation. Three
experiments form the basis of our strategy in regard to RNA structure determination.
To measure nucleobase 1
DHC residual dipolar couplings, constant-time (CT)-TROSY
and CT-anti-TROSY spectra [149; 150] are acquired in the absence (isotropic) and the
presence (anisotropic) of Pf1 phage. 1
DHC values are obtained by subtracting the
isotropic values from the anisotropic J-couplings. To measure one-bond ribose 1'
through 4' 1
DHC, a J-modulated CT-HSQC experiment is acquired and analyzed as
described [151]. Either a J-modulated 1
H-15
N-HSQC or a gradient-enhanced,
interleaved inphase-antiphase (IPAP)-HSQC experiment provides additional 1
DHN
RDC restraints [152; 153]. Field-induced alignment studies are also feasible for RNA
and the obtained RDC data can complement data measured in the presence of external
aligning media to resolve redundancies [154]. The measurement of independent sets of
RDCs can provide a detailed view of both RNA structure and dynamics. A minimum
of five RDCs must be measured per base or rigid sub-segment to establish segment
specific order tensors, although in practice more are desirable to improve the precision
to which individual As can be determined. A comparison of principal values of
ordering can provide valuable information about relative motional amplitudes between
segments. Measurements that allow one to obtain dipolar generalized order parameters
SRDC (that are identical to order parameters derived from heteronuclear spin relaxation
measurements) are sensitive to a much broader motional time scale (ps-ms, thus
potentially covering biologically relevant μs-ms time scales) [155-158].
6. Structure Calculation
In the early stages of a project, we typically employ qualitative NOESY NMR data
reporting on RNA secondary structure in combination with thermodynamic-based
folding algorithms as implemented in the NMR-assisted prediction of secondary
structure (NAPSS) to obtain accurate low-resolution structures [159]. Together with the
initial characterization, this is most helpful in assessing the folding state of the target
RNA.
Input data for RNA structure calculations include the previously introduced
experimental restraints: NOE-based 1
H−1
H distance, torsion angle, cross-correlated
relaxation rate, and RDC restraints. Direct experimental evidence for base paring
interactions can be obtained through measurement of h
J(D,A) couplings and hydrogen
bond restraints in form of donor-acceptor distances can be introduced. Non-
experimental constraints include planarity restraints and conformational database
potentials of mean force [160] that have been introduced to reproduce planar base pairs,
torsion angle correlations, and sequential and nonsequential base-base interactions
observed in RNA crystal structures. Such constraints must be applied with great care
since they have no experimental basis; their inclusion introduces bias and apparent
improvements in precision at the cost of imposing conformations that may not be
present. Small angle X-ray scattering (SAXS) data can provide useful low resolution
information on the global structural features of RNA-protein complexes facilitating the
determination of overall dimensions, radius of gyration and shape of biomolecules
[161-163]. The mutually complementary NMR and SAXS data serve to reduce angular
degrees of freedom and to confine the translational degrees of freedom, respectively.
Solution X-ray scattering data was successfully employed to refine the 30 kDa
RNA−RNA complex described in section 4.5.3 [164].
Once a restraint set is assembled, we typically generate an initial NOE-derived
structure for refinement with the RDC data by subjecting 100 random extended
structures to a simulated annealing protocol using XPLOR-NIH [165] as described
[166; 167]. Starting structures are calculated from randomized RNA coordinates using
solely energy terms from holonomic constraints such as geometric and non-bonded
terms. Torsion angle dynamics (TAD) as implemented in XPLOR and CNS prove to be
robust and have a higher convergence rate with respect to molecular dynamics in
Cartesian coordinate space [168]. The ca. 25 lowest energy structures without NOE
violations ≥0.5 Å are refined via a three step RDC-based protocol designed first to
refine the local structure and then the global structure [169]. A new module has been
developed for fitting SAXS data via XPLOR-NIH [162]. The lowest energy structures
after simulated annealing and subsequent refinement against sets of RDCs and SAXS
data are minimized using the AMBER module Sander [170]. Due to more adapted
force fields, AMBER yields better and more consistent results for nucleic acids [171].
A number of statistics are commonly evaluated to judge the convergence and
quality of the family of calculated RNA NMR structures: Root Mean Square Deviation
(RMSD), number of NOE, RDC, and torsion restraints; residual distance, dipolar
coupling, and torsion violations; and the largest distance, dipolar coupling, and torsion
violations. Typically, the distance restraints are further dissected into the number of
interresidue, intraresidue, and intermolecular NOEs. The NMR input data have to be
satisfactorily reproduced in high quality structures. Thus, the process of NMR
assignment and restraint collection and subsequent structure calculation is iterative; in
the process, wrong assignments will be corrected and additional restraints may be
identified. Useful RMSDs to consider include only regions of interest and are usually a
more accurate descriptor of the quality of the structure than the overall global RMSD.
Local RMSDs are given because the overall global value can easily be in the 2.0−3.0 Å
range, which might otherwise be indicative of poor convergence. Most RNA structures
studied include poorly defined regions such as a disordered loop, terminal base pairs, or
a nucleotide lacking internucleotide NOEs.
Finally, the obtained structures are validated by carrying out structure calculations
omitting a randomly chosen subset of the RDC data while refining against the
remaining RDCs [172]. The accuracy of a family of RNA NMR structures is cross-
validated by the agreement between the back-calculated RDCs derived from the
structures and the omitted RDC subset. Alternatively, a comparison between calculated
and observed 1
H chemical shifts represents another possibility for cross-validation of
structures derived from NMR restraints [173].
7. Future Perspectives
7.1. Segmental Labeling of RNA.
Resonance overlap caused by the limited chemical and structural diversity presents an
inherent barrier to investigate larger RNA in solution by NMR. As the number of
resonances increases, even uniform or nucleotide-type specific labels are not sufficient
to provide the necessary spectral dispersion. The isotopic labeling of RNA segments,
facilitated by T4 RNA ligase, simplifies the spectral complexity by reducing the
number of NMR-active atoms. T4 RNA ligase catalyzes the ligation of single-stranded
RNA or DNA to either oligoribo- or oligodeoxyribonucleotides through the formation
of a standard 3'→5' phosphodiester bond with hydrolysis of ATP to AMP and PPi [174;
175]. An elegant and economic approach using in vitro transcription and hammerhead
ribozyme cleavage for generating complementary labeling schemes has recently been
described [95; 176]. The incorporation of isotopically labeled RNA fragments into the
middle of the full-length target RNA molecule necessitates a three-way ligation; such a
multiple segmental labeling of RNA with three segments has recently been
demonstrated [177].
RNA structure determination remains a key challenge and represents the next
frontier to modern structural biology. The dominance of ncRNAs in the genomic
output of higher organisms suggests that they are not simply occasional transcripts with
peculiar structure and function, but rather that they may constitute an extensive but
hitherto incompletely characterized regulatory network within higher organisms. A
decade of structural genomics dramatically increased the database of known protein
structures by developing and applying methodologies to determine them as rapidly and
cost-effectively as possible. To date, though conceptually conceived a decade ago [178],
the primary mission of high-throughput determination of RNA structures has not been
seriously undertaken. Nevertheless, a tremendous amount of exciting research is
currently underway. Improvements in the fields of RNA NMR methodology and
biochemistry, paired with technical advances in NMR instrumentation have paved the
way for more streamlined structural efforts targeting RNA in the future.
Acknowledgments
The authors gratefully acknowledge past and present members of the Hennig laboratory
for helpful discussions, Drs Christina Mozes and Brendan Duggan for critical reading
of the manuscript, and Dr Brendan Duggan for PDB data base mining. This work was
supported by funding from the National Institutes of Health (AI064307, AI081640 and
RR024442) and by the National Science Foundation (NSF 0845512).
References
[1] J.S. Mattick, EMBO Rep 2 (2001), 986-991.
[2] C.P. Ponting, P.L. Oliver, and W. Reik, Cell 136 (2009), 629-641.
[3] E.S. Lander, et al., Nature 409 (2001), 860-921.
[4] J.C. Venter, et al., Science 291 (2001), 1304-1351.
[5] K.T. Dayie, Int J Mol Sci 9 (2008), 1214-1240.
[6] K. Lu, Y. Miyazaki, and M.F. Summers, J Biomol Nmr 46 (2010), 113-125.
[7] L.G. Scott, T.J. Tolbert, and J.R. Williamson, Methods Enzymol 317 (2000), 18-38.
[8] P. Vallurupalli, L. Scott, M. Hennig, J.R. Williamson, and L.E. Kay, J Am Chem Soc 128 (2006),
9346-9347.
[9] J.H. Davis, M. Tonelli, L.G. Scott, L. Jaeger, J.R. Williamson, and S.E. Butcher, J Mol Biol 351
(2005), 371-382.
[10] V. D'Souza, A. Dey, D. Habib, and M.F. Summers, J Mol Biol 337 (2004), 427-442.
[11] E.P. Nikonowicz, A. Sirr, P. Legault, F.M. Jucker, L.M. Baer, and A. Pardi, Nucleic Acids Res 20
(1992), 4507-4513.
[12] R.T. Batey, M. Inada, E. Kujawinski, J.D. Puglisi, and J.R. Williamson, Nucleic Acids Res 20
(1992), 4515-4523.
[13] R.T. Batey, J.L. Battiste, and J.R. Williamson, Methods Enzymol 261 (1995), 300-322.
[14] P. Zhou, A.A. Lugovskoy, and G. Wagner, J Biomol Nmr 20 (2001), 11-14.
[15] L.G. Scott, B.H. Geierstanger, J.R. Williamson, and M. Hennig, J Am Chem Soc 126 (2004),
11776-11777.
[16] J. Cromsigt, J. Schleucher, T. Gustafsson, J. Kihlberg, and S. Wijmenga, Nucleic Acids Res 30
(2002), 1639-1645.
[17] T.J. Tolbert and J.R. Williamson, J Am Chem Soc 118 (1996), 7929-7940.
[18] M. Hennig, M.L. Munzarova, W. Bermel, L.G. Scott, V. Sklenar, and J.R. Williamson, J Am
Chem Soc 128 (2006), 5851-5858.
[19] M. Hennig, L.G. Scott, E. Sperling, W. Bermel, and J.R. Williamson, J Am Chem Soc 129 (2007),
14911-14921.
[20] H.L. Schultheisz, B.R. Szymczyna, L.G. Scott, and J.R. Williamson, ACS Chem Biol 3 (2008),
499-511.
[21] J.F. Milligan, D.R. Groebe, G.W. Witherell, and O.C. Uhlenbeck, Nucleic Acids Res 15 (1987),
8783-8798.
[22] J.F. Milligan and O.C. Uhlenbeck, Methods Enzymol 180 (1989), 51-62.
[23] P.J. Lukavsky and J.D. Puglisi, RNA 10 (2004), 889-893.
[24] Y. Yin and C.W. Carter, Jr., Nucleic Acids Res 24 (1996), 1279-1286.
[25] E. Wyszko, J.P. Fuerste, M. Barciszewska, M. Szymanski, R. Adamiak, V.A. Erdmann, and J.
Barciszewski, J Biochem 126 (1999), 326-332.
[26] T.P. Shields, E. Mollova, L. Ste Marie, M.R. Hansen, and A. Pardi, RNA 5 (1999), 1259-1267.
[27] S.R. Price, N. Ito, C. Oubridge, J.M. Avis, and K. Nagai, J Mol Biol 249 (1995), 398-408.
[28] N.R. Markham and M. Zuker, Nucleic Acids Res 33 (2005), W577-581.
[29] N.R. Markham and M. Zuker, UNAFold, in, 2008, pp. 3-31.
[30] J.R. Wyatt, M. Chastain, and J.D. Puglisi, Biotechniques 11 (1991), 764-769.
[31] A.C. Anderson, S.A. Scaringe, B.E. Earp, and C.A. Frederick, RNA 2 (1996), 110-117.
[32] F. Wincott, A. DiRenzo, C. Shaffer, S. Grimm, D. Tracz, C. Workman, D. Sweedler, C. Gonzalez,
S. Scaringe, and N. Usman, Nucleic Acids Res 23 (1995), 2677-2684.
[33] I. Kim, S.A. McKenna, E. Viani Puglisi, and J.D. Puglisi, RNA 13 (2007), 289-294.
[34] H.K. Cheong, E. Hwang, C. Lee, B.S. Choi, and C. Cheong, Nucleic Acids Res 32 (2004), e84.
[35] K. Lu, Y. Miyazaki, and M.F. Summers, J Biomol Nmr 46 (2009), 113-125.
[36] R.T. Batey, N. Cloutier, H. Mao, and J.R. Williamson, Nucleic Acids Res 24 (1996), 4836-4837.
[37] L. Zidek, R. Stefl, and V. Sklenar, Curr Opin Struct Biol 11 (2001), 275-281.
[38] J. Cromsigt, B. van Buuren, J. Schleucher, and S. Wijmenga, Methods Enzymol 338 (2001), 371-
399.
[39] B. Furtig, C. Richter, J. Wohnert, and H. Schwalbe, Chembiochem 4 (2003), 936-962.
[40] M.P. Latham, D.J. Brown, S.A. McCallum, and A. Pardi, Chembiochem 6 (2005), 1492-1505.
[41] H. Wu, L.D. Finger, and J. Feigon, Methods Enzymol 394 (2005), 525-545.
[42] L.G. Scott and M. Hennig, Methods Mol Biol 452 (2008), 29-61.
[43] J. Flinders and T. Dieckmann, Prog Nucl Magn Reson Spectrosc 48 (2006), 137-159.
[44] T.J. Tolbert and J.R. Williamson, J Am Chem Soc 119 (1997), 12100-12108.
[45] E.P. Nikonowicz, K. Kalurachchi, and E. DeJong, FEBS Lett 415 (1997), 109-113.
[46] E.P. Nikonowicz, M. Michnicka, K. Kalurachchi, and E. DeJong, Nucleic Acids Res 25 (1997),
1390-1396.
[47] A.G. Marshall and J.L. Smith, J Am Chem Soc 99 (1977), 635-636.
[48] J. Horowitz, J. Ofengand, W.E. Daniel, Jr., and M. Cohn, J Biol Chem 252 (1977), 4418-4420.
[49] P.V. Cornish, D.P. Giedroc, and M. Hennig, J Biomol Nmr 35 (2006), 209-223.
[50] C. Kreutz, H. Kahlig, R. Konrat, and R. Micura, Angew Chem Int Ed Engl 45 (2006), 3450-3453.
[51] B. Puffer, C. Kreutz, U. Rieder, M.O. Ebert, R. Konrat, and R. Micura, Nucleic Acids Res 37
(2009), 7728-7740.
[52] E.A. Louie, P. Chirakul, V. Raghunathan, S.T. Sigurdsson, and G.P. Drobny, J Magn Reson 178
(2006), 11-24.
[53] G.L. Olsen, T.E. Edwards, P. Deka, G. Varani, S.T. Sigurdsson, and G.P. Drobny, Nucleic Acids
Res 33 (2005), 3447-3454.
[54] J.J. Barchi, Jr., L.S. Jeong, M.A. Siddiqui, and V.E. Marquez, Journal of Biochemical &
Biophysical Methods 34 (1997), 11-29.
[55] B. Reif, V. Wittmann, H. Schwalbe, C. Griesinger, K. Worner, K. JahnHofmann, J.W. Engels,
and W. Bermel, Helvetica Chimica Acta 80 (1997), 1952-1971.
[56] C. Thibaudeau, J. Plavec, and J. Chattopadhyaya, Journal of Organic Chemistry 63 (1998), 4967-
4984.
[57] K. Pervushin, R. Riek, G. Wider, and K. Wuthrich, Proc Natl Acad Sci U S A 94 (1997), 12366-
12371.
[58] V. Sklenar, B.R. Brooks, G. Zon, and A. Bax, FEBS Lett 216 (1987), 249-252.
[59] J.P. Marino, H. Schwalbe, C. Anklin, W. Bermel, D.M. Crothers, and C. Griesinger, J Biomol
Nmr 5 (1995), 87-92.
[60] S.S. Wijmenga, H.A. Heus, H.A. Leeuw, H. Hoppe, M. van der Graaf, and C.W. Hilbers, J
Biomol Nmr 5 (1995), 82-86.
[61] V. Sklenar, H. Miyashiro, G. Zon, H.T. Miles, and A. Bax, FEBS Lett 208 (1986), 94-98.
[62] G.W. Kellogg, J Magn Reson 98 (1992), 176-182.
[63] S.S. Wijmenga and B.N.M. van Buuren, Prog Nucl Magn Reson Spectrosc 32 (1998), 287-387.
[64] B. Simon, K. Zanier, and M. Sattler, J Biomol Nmr 20 (2001), 173-176.
[65] P. Legault, B.T. Farmer, L. Mueller, and A. Pardi, J Am Chem Soc 116 (1994), 2203-2204.
[66] J.P. Marino, J.H. Prestegard, and D.M. Crothers, J Am Chem Soc 116 (1994), 2205-2206.
[67] S.W. Fesik, H.L. Eaton, E.T. Olejniczak, E.R.P. Zuiderweg, L.P. McIntosh, and F.W. Dahlquist, J
Am Chem Soc 112 (1990), 886-888.
[68] L.E. Kay, M. Ikura, and A. Bax, J Am Chem Soc 112 (1990), 888-889.
[69] E.P. Nikonowicz and A. Pardi, J Mol Biol 232 (1993), 1141-1156.
[70] A. Pardi, Methods Enzymol 261 (1995), 350-380.
[71] A. Pardi and E.P. Nikonowicz, J Am Chem Soc 114 (1992), 9202-9203.
[72] B.T. Farmer, L. Muller, E.P. Nikonowicz, and A. Pardi, J Am Chem Soc 115 (1993), 11040-11041.
[73] V. Sklenar, M.R. Rejante, R.D. Peterson, E. Wang, and J. Feigon, J. Am. Chem. Soc. 115 (1993),
12181-12182.
[74] J.P. Marino, J.L. Diener, P.B. Moore, and C. Griesinger, J Am Chem Soc 119 (1997), 7361-7366.
[75] V. Sklenar, T. Dieckmann, S.E. Butcher, and J. Feigon, J Magn Reson 130 (1998), 119-124.
[76] V. Sklenar, R.D. Peterson, M.R. Rejante, and J. Feigon, J Biomol Nmr 4 (1994), 117-122.
[77] G. Lippens, C. Dhalluin, and J.M. Wieruszeski, J Biomol Nmr 5 (1995), 327-331.
[78] K. Wuthrich, NMR of proteins and nucleic acids, Wiley, New York, 1986.
[79] E. Duchardt, C. Richter, B. Reif, S.J. Glaser, J.W. Engels, C. Griesinger, and H. Schwalbe, J
Biomol Nmr 21 (2001), 117-126.
[80] H. Schwalbe, J.P. Marino, S.J. Glaser, and C. Griesinger, J Am Chem Soc 117 (1995), 7251-7252.
[81] H. Schwalbe, J.P. Marino, G.C. King, R. Wechselberger, W. Bermel, and C. Griesinger, J Biomol
Nmr 4 (1994), 631-644.
[82] G.W. Kellogg, A.A. Szewczak, and P.B. Moore, J Am Chem Soc 114 (1992), 2727-2728.
[83] G.W. Kellogg and B.I. Schweitzer, J Biomol Nmr 3 (1993), 577-595.
[84] L. Kay, P. Keifer, and T. Saarinen, J Am Chem Soc 114 (1992), 10663-10665.
[85] J. Schleucher, M. Schwendinger, M. Sattler, P. Schmidt, O. Schedletzky, S.J. Glaser, O.W.
Sørensen, and C. Griesinger, J Biomol Nmr 4 (1994), 301-306.
[86] J. Fohrer, M. Hennig, and T. Carlomagno, J Mol Biol 356 (2006), 280-287.
[87] M. Hennig, J. Fohrer, and T. Carlomagno, J Am Chem Soc 127 (2005), 2028-2029.
[88] H.A. Heus, S.S. Wijmenga, F.J.M. Vandeven, and C.W. Hilbers, J Am Chem Soc 116 (1994),
4983-4984.
[89] J.P. Marino, H. Schwalbe, C. Anklin, W. Bermel, D.M. Crothers, and C. Griesinger, J Am Chem
Soc 116 (1994), 6472-6473.
[90] W. Hu, L.T. Kakalis, L. Jiang, F. Jiang, X. Ye, and A. Majumdar, J Biomol Nmr 12 (1998), 559-
564.
[91] S.J. Glaser, H. Schwalbe, J.P. Marino, and C. Griesinger, J Magn Reson B 112 (1996), 160-180.
[92] A.J. Dingley and S. Grzesiek, J Am Chem Soc 120 (1998), 8293-8297.
[93] K. Pervushin, A. Ono, C. Fernandez, T. Szyperski, M. Kainosho, and K. Wuthrich, Proc Natl
Acad Sci USA 95 (1998), 14147-14151.
[94] P.J. Lukavsky, I. Kim, G.A. Otto, and J.D. Puglisi, Nat Struct Biol 10 (2003), 1033-1038.
[95] I. Kim, P.J. Lukavsky, and J.D. Puglisi, J Am Chem Soc 124 (2002), 9338-9339.
[96] C. Zwahlen, P. Legault, S.J.F. Vincent, J. Greenblatt, R. Konrat, and L.E. Kay, J Am Chem Soc
119 (1997), 6711-6721.
[97] J. Iwahara, J.M. Wojciak, and R.T. Clubb, J Biomol Nmr 19 (2001), 231-241.
[98] R.D. Peterson, C.A. Theimer, H. Wu, and J. Feigon, J Biomol Nmr 28 (2004), 59-67.
[99] V. D'Souza and M.F. Summers, Nature 431 (2004), 586-590.
[100] A.A. Shaw, C. Salaun, J.-F. Dauphin, and B. Ancian, J Magn Reson Ser A 120 (1996), 110-115.
[101] J. Cavanagh and M. Rance, J Magn Reson 96 (1992), 670-678.
[102] T. Carlomagno, M. Hennig, and J.R. Williamson, J Biomol Nmr 22 (2002), 65-81.
[103] G.W. Vuister and A. Bax, J Magn Reson 98 (1992), 428-435.
[104] A. Meissner and O.W. Sorensen, J Magn Reson 139 (1999), 439-442.
[105] S. Mori, C. Abeygunawardana, M.O. Johnson, and P.C. van Zijl, J Magn Reson B 108 (1995), 94-
98.
[106] G. Varani, F. Aboul-ela, F. Allain, and C.C. Gubser, J Biomol Nmr 5 (1995), 315-320.
[107] R. Riek, K. Pervushin, C. Fernandez, M. Kainosho, and K. Wuthrich, J Am Chem Soc 123 (2001),
658-664.
[108] V. Sklenar, R.D. Peterson, M.R. Rejante, and J. Feigon, J Biomol Nmr 3 (1993), 721-727.
[109] H. Van Melckebeke, A. Pardi, J. Boisbouvier, J.P. Simorre, and B. Brutscher, J Biomol Nmr 32
(2005), 263-271.
[110] R. Fiala, J. Czernek, and V. Sklenar, J Biomol Nmr 16 (2000), 291-302.
[111] J.P. Simorre, G.R. Zimmermann, L. Mueller, and A. Pardi, J Biomol Nmr 7 (1996), 153-156.
[112] J.P. Simorre, G.R. Zimmermann, L. Mueller, and A. Pardi, J Am Chem Soc 118 (1996), 5316-
5317.
[113] J.P. Simorre, G.R. Zimmermann, A. Pardi, B.T. Farmer, 2nd, and L. Mueller, J Biomol Nmr 6
(1995), 427-432.
[114] R. Fiala, F. Jiang, and D.J. Patel, J Am Chem Soc 118 (1996), 689-690.
[115] J. Wohnert, M. Gorlach, and H. Schwalbe, J Biomol Nmr 26 (2003), 79-83.
[116] J. Wohnert, R. Ramachandran, M. Gorlach, and L.R. Brown, J Magn Reson 139 (1999), 430-433.
[117] B. Brutscher, J. Boisbouvier, E. Kupce, C. Tisne, F. Dardel, D. Marion, and J.P. Simorre, J
Biomol Nmr 19 (2001), 141-151.
[118] R.C. Morshauser and E.R. Zuiderweg, J Magn Reson 139 (1999), 232-239.
[119] L. Mueller, P. Legault, and A. Pardi, J Am Chem Soc 117 (1995), 11043-11048.
[120] A. Bax, R.H. Griffey, and B.L. Hawkins, J Magn Reson 55 (1983), 301-315.
[121] A.A. Szewczak, G.W. Kellogg, and P.B. Moore, FEBS Lett 327 (1993), 261-264.
[122] J. Farjon, J. Boisbouvier, P. Schanda, A. Pardi, J.P. Simorre, and B. Brutscher, J Am Chem Soc
131 (2009), 8571-8577.
[123] D. Nietlispach, J Biomol Nmr 31 (2005), 161-166.
[124] A. Bax, G. Kontaxis, and N. Tjandra, Methods Enzymol 339 (2001), 127-174.
[125] H. Zhou, A. Vermeulen, F.M. Jucker, and A. Pardi, Biopolymers 52 (1999), 168-180.
[126] J.P. Marino, H. Schwalbe, and C. Griesinger, Acc. Chem. Res. 32 (1999), 614-623.
[127] B. Reif, M. Hennig, and C. Griesinger, Science 276 (1997), 1230-1233.
[128] H. Schwalbe, T. Carlomagno, M. Hennig, J. Junker, B. Reif, C. Richter, and C. Griesinger,
Methods Enzymol 338 (2001), 35-81.
[129] I.C. Felli, C. Richter, C. Griesinger, and H. Schwalbe, J Am Chem Soc 121 (1999), 1956-1957.
[130] C. Richter, C. Griesinger, I. Felli, P.T. Cole, G. Varani, and H. Schwalbe, J Biomol Nmr 15
(1999), 241-250.
[131] J.V. Hines, G. Varani, S.M. Landry, and I. Tinoco Jr., J Am Chem Soc 115 (1993), 11002-11003.
[132] L. Trantirek, R. Stefl, J.E. Masse, J. Feigon, and V. Sklenar, J Biomol Nmr 23 (2002), 1-12.
[133] E. Duchardt, C. Richter, O. Ohlenschlager, M. Gorlach, J. Wohnert, and H. Schwalbe, J Am Chem
Soc 126 (2004), 1962-1970.
[134] S. Ravindranathan, C.H. Kim, and G. Bodenhausen, J Biomol Nmr 27 (2003), 365-375.
[135] J. Rinnenthal, C. Richter, J. Ferner, E. Duchardt, and H. Schwalbe, J Biomol Nmr 39 (2007), 17-
29.
[136] H. Schwalbe, W. Samstag, J.W. Engels, W. Bermel, and C. Griesinger, J Biomol Nmr 3 (1993),
479-486.
[137] C.G. Hoogstraten and A. Pardi, J Magn Reson 133 (1998), 236-240.
[138] P. Legault, F.M. Jucker, and A. Pardi, FEBS Lett 362 (1995), 156-160.
[139] T. Szyperski, C. Fernandez, A. Ono, K. Wuthrich, and M. Kainosho, J Magn Reson 140 (1999),
491-494.
[140] W. Hu, S. Bouaziz, E. Skripkin, and A. Kettani, J Magn Reson 139 (1999), 181-185.
[141] G.M. Clore, E.C. Murphy, A.M. Gronenborn, and A. Bax, J Magn Reson 134 (1998), 164-167.
[142] C.H. Gotfredsen, A. Meissner, J.O. Duus, and O.W. Sorensen, Magn Reson Chem 38 (2000), 692-
695.
[143] C. Richter, B. Reif, K. Worner, S. Quant, J.P. Marino, J.W. Engels, C. Griesinger, and H.
Schwalbe, J Biomol Nmr 12 (1998), 223-230.
[144] P. Legault and A. Pardi, J Magn Reson B 103 (1994), 82-86.
[145] C. Richter, B. Reif, C. Griesinger, and H. Schwalbe, J Am Chem Soc 122 (2000), 12728-12731.
[146] N. Tjandra and A. Bax, Science 278 (1997), 1111-1114.
[147] M.R. Hansen, P. Hanson, and A. Pardi, Methods Enzymol 317 (2000), 220-240.
[148] M.R. Hansen, L. Mueller, and A. Pardi, Nat Struct Biol 5 (1998), 1065-1074.
[149] J. Boisbouvier, B. Brutscher, A. Pardi, D. Marion, and J.-P. Simorre, J Am Chem Soc 122 (2000),
6779-6780.
[150] P. Andersson, J. Weigelt, and G. Otting, J Biomol Nmr 12 (1998), 435-441.
[151] N. Tjandra and A. Bax, J Magn Reson 124 (1997), 512-515.
[152] L. Yao, J. Ying, and A. Bax, J Biomol Nmr 43 (2009), 161-170.
[153] N. Tjandra, S. Grzesiek, and A. Bax, J Am Chem Soc 118 (1996), 6264-6272.
[154] Q. Zhang, R. Throolin, S.W. Pitt, A. Serganov, and H.M. Al-Hashimi, J Am Chem Soc 125 (2003),
10530-10531.
[155] J. Meiler, J.J. Prompers, W. Peti, C. Griesinger, and R. Bruschweiler, J Am Chem Soc 123 (2001),
6098-6107.
[156] J.R. Tolman, J Am Chem Soc 124 (2002), 12020-12030.
[157] J.R. Tolman, H.M. Al-Hashimi, L.E. Kay, and J.H. Prestegard, J Am Chem Soc 123 (2001), 1416-
1424.
[158] J.R. Tolman and K. Ruan, Chem Rev 106 (2006), 1720-1736.
[159] J.M. Hart, S.D. Kennedy, D.H. Mathews, and D.H. Turner, J Am Chem Soc 130 (2008), 10233-
10239.
[160] G.M. Clore and J. Kuszewski, J Am Chem Soc 125 (2003), 1518-1525.
[161] A. Grishaev, J. Wu, J. Trewhella, and A. Bax, J Am Chem Soc 127 (2005), 16621-16628.
[162] A. Grishaev, J. Ying, M.D. Canny, A. Pardi, and A. Bax, J Biomol Nmr 42 (2008), 99-109.
[163] F. Gabel, B. Simon, M. Nilges, M. Petoukhov, D. Svergun, and M. Sattler, J Biomol Nmr 41
(2008), 199-208.
[164] X. Zuo, J. Wang, T.R. Foster, C.D. Schwieters, D.M. Tiede, S.E. Butcher, and Y.X. Wang, J Am
Chem Soc 130 (2008), 3292-3293.
[165] C.D. Schwieters, J.J. Kuszewski, N. Tjandra, and G. Marius Clore, J Magn Reson 160 (2003), 65-
73.
[166] P.V. Cornish, M. Hennig, and D.P. Giedroc, Proc Natl Acad Sci U S A 102 (2005), 12694-12699.
[167] P.L. Nixon, A. Rangan, Y.G. Kim, A. Rich, D.W. Hoffman, M. Hennig, and D.P. Giedroc, J Mol
Biol 322 (2002), 621-633.
[168] E.G. Stein, L.M. Rice, and A.T. Brunger, J Magn Reson 124 (1997), 154-164.
[169] S.A. McCallum and A. Pardi, J Mol Biol 326 (2003), 1037-1050.
[170] D.A. Pearlman, D.A. Case, J.W. Caldwell, W.R. Ross, T.E. Cheatham, S. DeBolt, D.G.S.
Ferguson, and P. Kollman, Computer Physics Communications 91 (1995), 1-41.
[171] V. Tsui and D.A. Case, J Am Chem Soc 122 (2000), 2489-2498.
[172] G.M. Clore and D.S. Garrett, J Am Chem Soc 121 (1999), 9008-9012.
[173] J.A. Cromsigt, C.W. Hilbers, and S.S. Wijmenga, J Biomol Nmr 21 (2001), 11-29.
[174] T.E. England and O.C. Uhlenbeck, Biochemistry 17 (1978), 2069-2076.
[175] M.J. Moore and C.C. Query, Methods Enzymol 317 (2000), 109-123.
[176] A.G. Tzakos, L.E. Easton, and P.J. Lukavsky, J Am Chem Soc 128 (2006), 13344-13345.
[177] F.H. Nelissen, A.J. van Gammeren, M. Tessari, F.C. Girard, H.A. Heus, and S.S. Wijmenga,
Nucleic Acids Res 36 (2008), e89.
[178] J.A. Doudna, Nat Struct Biol 7 Suppl (2000), 954-956.

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Roth and Hennig 2010

  • 1. 1 Corresponding author: Mirko Hennig, Department of Biochemistry and Molecular Biology, Medical University of South Carolina, 173 Ashley Ave, PO Box 250509, Charleston, SC 29425; Email: hennig@musc.edu RNA Structure Determination by NMR: Combining Labeling and Pulse Techniques Braden M. Roth and Mirko Hennig1 Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC 29425 Abstract. RNA exhibits considerable structural and functional diversity beyond well established roles of ribosomal, transfer and messenger RNAs, as illustrated by the discovery of ever increasing numbers of diverse RNA structures involved in gene processing and regulation. RNA molecules are often quite flexible; they can function in a genuinely unfolded form and adapt for recognition of both the shape and the charge distribution on a potential ligand with exquisite specificity. Liquid state NMR spectroscopy is uniquely suited to answer important questions concerning biophysical properties of RNA molecules including their three- dimensional shape, secondary structure distribution, and flexibility by looking at dynamic ensembles of structures. Here we review the fields of RNA sample preparation and NMR methodology that facilitate the determination of RNA structure in solution. Keywords. RNA synthesis, Isotope labeling, RNA purification, NMR, resonance assignment, structure determination. Introduction The increasing awareness of the essential role of RNA in biological processes, including its involvement in translation, gene regulation, and viral infections, make RNA an interesting target for structural studies. Structure is the link between sequence and function and thus knowledge of the three dimensional structure of RNA is central to understanding its biology. It is indispensable for describing the underlying determinants of catalytic mechanisms, ligand binding, and molecular recognition in macromolecular assemblies. In this review, after a brief survey of the current status, we will provide the workflow employed by our laboratory emphasizing the factors essential for the determination of RNA structures in solution using high-resolution Nuclear Magnetic Resonance (NMR) methodology and the progress that has been made so far in these areas. The key issues to determine the structure of RNA at the atomic level are: how to produce sufficient amounts of isotopically labeled RNA, and once produced, how to purify the RNA; then, how to obtain unambiguous NMR resonance assignments of the RNA; and finally, how to utilize collected restraints in NMR structure determination. The review will conclude with a brief look at the future of high-resolution NMR in the study of the structural biology of RNA in solution.
  • 2. 1. Current Status of RNA Structures Solved by NMR Despite the biological importance of RNA, knowledge of their structures lags considerably behind that of proteins. Nearly 98% of the transcriptional output of the human genome is non-(protein)-coding RNA (ncRNA) [1; 2]. This estimate is based upon the fact that intronic RNA constitutes 95% of primary protein-coding transcripts [3; 4]. Yet less than 2% of Protein Data Bank (PDB) structures represent RNA. This deficit lies largely in the difficulties in applying the most productive techniques in protein structure determination to RNA. Rugged energy landscapes and multistate RNA folding kinetics pose serious obstacles to crystallization for structure determination by X-ray crystallography. Coinciding with methodological developments in the early 1990s that allowed for stable isotope labeling, the rate of deposition into the PDB of RNA structures solved using NMR methodology increased more than threefold after 1995 to an average of 23 per year. Indeed, nearly half of the RNA-only structures in the PDB have been determined by NMR. Among the 337 unique NMR structures that have been deposited between 1992 and 2009, the average length is 23 nucleotides (nt). Only three RNA NMR structures contain more than 50 nt, of which one is a homodimeric, GAAA tetraloop-receptor RNA complex totaling 86 nt (see 4.5). However, recent years have seen fewer RNA solution structures deposited in the PDB (14 in 2008 and 15 in 2009, respectively), and the two largest NMR structures were solved several years ago, in 2003 and 2004 (PDB accession codes 1P5P and 1S9S, respectively). The pace of RNA structural biology in solution remains modest because severe spectral overlap and rapid relaxation in larger RNA continue to complicate structural studies by NMR. Nevertheless, NMR offers great potential not only with respect to structural characterization of RNA but also provides the unique ability to study the details of dynamics which appear integral to understanding RNA function. The use of deuteration and of TROSY (Transverse Relaxation-Optimized Spectroscopy)-based experiments have already played an important role in extending the size of RNA molecules amenable to solution NMR studies. 2. Sample Preparation Given the inherent insensitivity of NMR, the preparation of RNA molecules for structure determination by NMR can be quite challenging. Commercially available oligonucleotides on the millimolar scale required by NMR are often cost-prohibitive, so investigators will generally employ large-scale in vitro transcription strategies to produce the molecules in-house. In addition to scale, several custom-labeled transcripts are often required to generate a single structure, making the process expensive and labor-intensive. Therefore, careful consideration must be taken to develop a research plan that maximizes the production of multiple large-scale transcripts while minimizing effort and expense. In the following sections, strategies for nucleotide preparation, in vitro transcription, and transcript purification are presented. 2.1. Nucleotide Synthesis The enrichment of 13 C and 15 N-labeled nucleotides represents a critical step in the development of multidimensional heteronuclear NMR experiments for structure determination of RNAs (reviewed in [5; 6]). Assignment of larger RNAs; however,
  • 3. requires alternative labeling strategies to combat spectral crowding [7; 8]. Site-specific and random deuteration in conjunction with 13 C and 15 N labeling has proven essential for the solution of RNAs larger than 30 kDa [9; 10]. At considerable expense, a variety of uniformly, isotopically labeled rNTPs are commercially available (e.g. Cassia LLC/Cambridge Isotope Labs and Isotec/Sigma-Aldrich). Most recently, site- specifically deuterated rNTPs became commercially available (Cassia LLC/Cambridge Isotope Labs). The ability to produce labeled rNTPs in-house is essential for the productivity of research groups with limited financial resources and/or an interest in developing new NMR methodologies. In the case of uniform 13 C, 15 N, and 2 H labeling, the preparation of rNTPs follows protocols pioneered by the Pardi and Williamson laboratories [11-13]. Briefly, total RNA is extracted from high-density E. coli cultures grown in media with strictly defined carbon and nitrogen sources. The RNA is hydrolyzed with Nuclease P1 and applied to a boronate resin column to separate rNMPs from dNMPs. Enzymatic phosphorylation of purified rNMPs follows a two- step process in which rNMPs are converted to rNDPs via nucleotide-specific kinases. The reaction is coupled to an ATP-regeneration step that powers the production of triphosphates. Fully-charged rNTPs are re-purified by a boronate affinity column, removing salts and high molecular weight impurities that could interfere with efficient in vitro transcription. Myokinase, guanylate kinase and nucleoside monophosphate kinase enzymes responsible for NMP-NDP conversion are purified commercially from varying sources, but can be expensive and unstable. Alternatively, nucleotide-specific monophosphate- charging enzymes can be cloned directly from bacteria. E. coli adk, cmk, gmk and pyrH genes fused to a His6-tagged, solubility-enhancing GB1 partner [14] are easily expressed in large quantities using standard expression and purification methods. In addition, the bacterial monophosphate kinases are more efficient than their commercial counterparts and are stably stored at −80 °C (Roth and Hennig, unpublished). Finally, costs can be further reduced by modifying the ATP regeneration/triphosphate charging reaction to instead utilize phosphocreatine and creatine kinase [15]. More exotic nucleotide labeling strategies (e.g. site-specific deuteration or 19 F incorporation) require additional steps including the chemical synthesis of custom- labeled ribose [7; 16; 17] and/or coupling of an isotopically-labeled base to the sugar moiety [18-20], possibly requiring an additional UTP→CTP conversion as the final step. While some specifically-deuterated NTPs are commercially available, fluorinated rNTPs are not. The details of alternative rNTP labeling are discussed in section 3. 2.2. DNA-Template Directed Synthesis of RNA Using T7 RNA Polymerase The production of millimolar quantities of RNA required for structural analysis by NMR is generally accomplished by large-scale in vitro transcription reactions. The preferred enzyme for this reaction is bacteriophage T7 RNA polymerase because it is better characterized than other common DNA-directed RNA polymerases (T3 and SP6) [21; 22]. There are two basic strategies for oligonucleotide synthesis using T7. Short RNA (<50 nt) transcriptions can be carried out using synthetic DNA templates. The template can be comprised of complementary DNA oligonucleotides or a top strand consisting of the 17-nt T7 promoter and a complementary strand that contains the T7 promoter and the transcript of interest [23]. The second strategy utilizes a double- stranded plasmid that consists of the T7 promoter, the desired RNA product, and a
  • 4. suitable restriction enzyme sequence to linearize the plasmid and terminate transcription. This strategy is preferred because it is more efficient, produces fewer abortive transcripts, and facilitates subsequent purification of the relatively small transcript from the much larger DNA template [23]. Optimization of the transcription reaction prior to large-scale production is essential since the yield of in vitro transcribed RNA is dependent on many factors which are not fully understood. The most critical factors for efficient T7 transcription; however, are the MgCl2/rNTP ratio and T7 polymerase and DNA template concentrations. Duplicate small-scale (10−50 μl) transcriptions can be designed in a rational sparse matrix [24] to find optimal conditions chosen to promote total RNA yield (e.g. when using unlabeled NTPs) or to maximize transcript yield per mole of labeled nucleotides. After optimization, a 1 mL pilot transcription is recommended to verify predicted yields and to estimate the volume required for full-scale (millimolar) transcript production. DNA template design must take into account two disadvantages of T7-directed RNA synthesis. First, an efficient reaction requires that T7 is primed by at least two guanosines as the initiating nucleotides of the transcript [21]. Second, T7 RNA polymerase can produce “add-on” (n+1, n+2) transcripts that are suboptimal for structure determination [21]. This 3'-end heterogeneity can be resolved through purification techniques or template design that incorporates a cis-acting ribozyme. The hammerhead ribozyme is a small (<50 nt) catalytic RNA consisting of three stems and a conserved core that efficiently cleaves substrates containing an XUN motif, where X can be any base and N must be an unpaired A, C, or U. The most efficiently cleaved sequence is the GUC triplet [25]. The hammerhead can be used to hydrolyze RNA substrates in trans [26], or engineered as part of a cis-acting, self-cleaving RNA transcript [27]. Hydrolysis of the phosphodiester bond occurs after the GUC, resulting in a population of RNA transcripts with homogeneous 3'-ends. Critical to the activity of the ribozyme is the conserved three-way junction that forms the required base pairing around the GUC triplet (Figure 1A). Proper folding of the RNA-hammerhead transcript may require modifications of nucleotides at its 3'-end in order to base pair with the desired RNA sequence and promote the formation of a third stem. Therefore, it is imperative that the potential RNA-hammerhead constructs are subjected to an RNA folding algorithm such as Quikfold [28; 29] to confirm the proper formation of the cleavage junction (Figure 1A). Additionally, purification of the desired RNA from the hammerhead requires extra steps since superior resolution is necessary to separate similarly-sized transcripts. Finally, hammerhead transcriptions introduce extra cost because a sizeable portion of the synthesized transcript is discarded following purification of the target RNA. This consideration is important when preparing NMR- scale transcripts using expensive isotope-labeled nucleotides.
  • 5. Figure 1. Overview and purification of a cis-hammerhead transcript. (A) Secondary structure prediction of a 3’ hammerhead construct. Base pairing between the target transcript (black) and hammerhead (grey) forms the third stem and positions the GUC triplet in the proper context for self-cleavage, releasing a target RNA with homogeneous 3’ ends. (B) Purification of a 22mer/hammerhead RNA analyzed by 8 M urea-PAGE. (Top) FPLC anion-exchange is insufficient to resolve the hammerhead (HH) and hairpin (HP) cleavage products. Subsequent HPLC anion-exchange results in purified 22 mer RNA for NMR analysis (bottom). 2.3. RNA Purification Traditionally, milligram quantities of in vitro-transcribed RNA were purified by denaturing (8 M urea) PAGE followed by electroelution from the gel matrix, desalting, buffer exchange, and refolding [21; 30]. The distinct advantage of this method is the ability to separate preparative quantities of RNA with single-nucleotide resolution. On the other hand, gel-purification is a labor-intensive, RNA-denaturing process that yields transcripts contaminated with water-soluble acrylamide oligomers [23]. Although the impurities can be removed through extensive washing or dialysis, the process is time-consuming and incomplete. For these reasons, new methods of purifying large-scale transcription reactions have been developed, including anion- exchange [31; 32], size-exclusion [23; 33] and DNA affinity chromatography [34]. The RNA purification protocols adapted by our laboratory utilize components of these methods to produce NMR-quality transcripts with varying size and complexity under native conditions. Briefly, large-scale (5−15 mL) T7 run-off transcriptions are centrifuged to remove pyrophosphate precipitates, then buffer-exchanged with an appropriate centrifugal filter device. Unincorporated nucleotides and short abortive transcripts are also largely removed by this step. Removal of T7 polymerase, plasmid DNA template and the remaining abortive transcripts is achieved by FPLC anion exchange chromatography (GE HiTrapQ HP). Following high-salt elution, fractions corresponding to the expected transcript are analyzed for purity by denaturing PAGE and pooled (Figure 1B). Finally, the sample is exchanged back into the low-salt buffer for NMR analysis. This protocol yields high-quality RNA samples in <2 days with minimal sample loss, but it is dependent on first-rate optimization prior to full-scale transcription. While FPLC anion exchange is well-suited to purify discrete transcripts,
  • 6. its resolution is limited. Where more stringent purification is required, the sample is exchanged into a buffer suitable for HPLC anion-exchange chromatography. The Dionex DNAPac provides nucleotide resolution of pre-purified RNAs and is ideal for the separation of contaminant transcripts and hammerhead cleavage products. Again, the resolved transcripts are verified by denaturing PAGE, pooled, buffer exchanged and quantified for NMR (Figure 1B). Unlike reversed-phase chromatography, pre- purification by FPLC is a simple, robust method of “cleaning” large-scale transcripts prior to DNAPac separation in a non-denaturing environment free of potentially problematic organic solvents. 3. Labeling Approaches NMR structure determinations of RNA are simplified by the application of multi- dimensional, heteronuclear NMR experiments. However, these experiments require milligram quantities of isotopically labeled RNA, so the production of isotopically labeled RNA remains critical to the success of these NMR-based structure studies [5; 35]. In contrast to the abundant 1 H and 31 P isotopes, the naturally occurring nuclei 12 C and 14 N cannot be readily studied with high-resolution NMR techniques. Nucleotide- specific labeling schemes are compatible with RNA synthesis using T7 RNA polymerase and relatively straightforward because the four individual rNMPs can conveniently be separated by ion exchange HPLC chromatography. Thus, all labeling schemes described can be tailored to address specific assignment problems. 3.1. Conventional Labeling of RNA with 13 C and 15 N Uniformly labeled rNTPs (GCN , CCN , ACN , UCN ) for in vitro transcription reactions can be readily produced by phosphorylation of nucleotides isolated from bacteria grown on 13 C- and/or 15 N enriched media [11-13; 36]. Through the use of 13 C and 15 N isotopic labeling and multidimensional heteronuclear NMR experiments, studies of 15- kDa RNAs are commonplace and methodological developments have been reviewed [37-43]. 3.2. Deuteration Strategies The specific substitution of protons with deuterium represents the most promising way to increase sensitivity while simplifying spectra. Labeling schemes involving deuteration afford two benefits: first, the spectra will be less crowded and second, the relaxation properties of carbon and the remaining proton nuclei will be favorably altered. The reduced proton spin density decreases relaxation times of protons in RNAs. In addition, any 13 C atoms attached to deuterium have slower relaxation properties relative to 13 C−1 H moieties. Therefore, deuterium labeling has particularly aided in the study of large RNA molecules. Adopting the enzymatic synthesis strategy of the Williamson laboratory, the following differentially deuterated ribonucleotides can be prepared for transcription reactions: Beginning with 2 H,13 C-uniformly labeled glucose, the ribose portion of the nucleotides are deuterated at the H3', H4', H5', H5'' positions to give [1',2',3',4',5'- 13 C5,3',4',5',5''-2 H4]-rNTPs which greatly simplify the NMR spectra for large RNAs
  • 7. [17; 44]. In addition, pyrimidine bases with deuteration at the H5 position, 5- 2 H(pyrimidine)-rNTPs, can be included, removing the spectral crowding from strong H5/H6 crosspeaks. This labeling pattern conserves important NOEs between base and ribose while affording all the previously described benefits of deuteration. The H2' protons, which normally reside in the most crowded region of the proton spectrum, can be identified based on their chemical shift. If faster 1 H T2-relaxation caused by 13 C−1 H dipole-dipole interactions presents a problem, uniformly 2 H labeled glucose can be used to generate [12 C5,3',4',5',5''-2 H4(5-2 H(pyrimidine))]-NTPs for transcription reactions. Random fractionally deuterated nucleotides, 15 N,13 C-(50% 2 H) rNTPs or GCN50%D , CCN50%D , ACN50%D , UCN50%D ), are prepared by growth of M. methylotrophus on 15 N- ammonium sulfate and 13 C-methanol as sole carbon and nitrogen sources [36]. Alternatively, E. coli can be grown on minimal salt media containing 15 N-ammonium sulfate and 13 C-glucose. The growth is carried out in 50% D2O. Perdeuterated, 15 N,13 C,2 H rNTPs (GCND , CCND , ACND , UCND ) can be synthesized by growing bacteria in 100% D2O in minimal media, optionally supplemented with 15 N-ammonium sulfate and/or 13 C-acetate/methanol/glucose as sole nitrogen and carbon sources [45; 46]. Random fractional deuteration as well as perdeuteration is useful for NMR of large systems due to improved relaxation properties. Apart from C5' methylene ribose carbons, random fractional deuteration of RNA does not suffer from the production of isotopomers with chemical shift heterogeneity and decreased signal intensities. A general disadvantage of deuterium labeling is the reduced 1 H-1 H NOE based information content essential for structure determination. 3.3. Labeling of RNA with 19 F Fluorinated ribosomal 5S-rRNA [47] and tRNA [48] isolated from E. coli grown in the presence of 5F-U revealed high levels (>80%) of incorporation of 5F-UTP in place of UTP as early as 1977. Since this pioneering work, substantial effort has been made on the study of nucleic acids using both liquid- [15; 19; 49-51] and solid-state 19 F NMR [52; 53]. Advantages of using spin 19 F as an NMR probe are its high sensitivity (83% of 1 H) combined with 100% natural abundance and a wide chemical shift distribution (ca. 50-fold larger than that of 1 H) which typically leads to well-resolved signals in one-dimensional NMR spectra. The 19 F chemical shift of a covalently bound fluorine atom is extraordinarily sensitive towards changes in the local microenvironment which is primarily attributable to the anisotropic distribution of the electrons in the 2-p orbitals. The van der Waals radius of a fluorine atom, 1.35Å, is only slightly larger than that of a hydrogen (1.2Å) and smaller than a methyl group (2.0Å) providing a promising candidate to substitute for either of those without structural or functional alteration. The introduction of 19 F substitutions into the heterocyclic bases is non- perturbing and provides researchers with uniquely positioned, sensitive NMR reporter groups to monitor 1) conformation, 2) molecular interactions and 3) dynamics of RNA. As a result of drastically simplified spectra, 19 F-NMR spectroscopy can provide very useful information on specific aspects of the structure, interactions, and mobility of RNAs that could not otherwise be obtained. Fluorinated RNA can routinely be prepared by either phosphoramidite-based chemical synthesis [51] or in vitro transcription reactions using RNA polymerase. We
  • 8. recently established the efficient and economical enzymatic synthesis of the fluorinated nucleotide analogues 5F-UTP, 5F-CTP [18; 19], and 2F-ATP [15]. The base analog 5F-uracil is readily used as a substrate for uracil phosphoribosyl transferase, which provides a novel and efficient route to produce 5F-UMP, and ultimately 5F-UTP. The fluorinated nucleotide analogues 2F-AMP and 5F-CMP can be synthesized by enzymatic conversions of 2F-adenine using adenine phosphoribosyltransferase and by conversion of the nucleoside analog 5F-cytidine catalyzed by uridine kinase. Our laboratory subsequently demonstrated that these fluorinated rNTP analogues can be specifically incorporated into RNA and that the modified nucleotide analogue 5F-Cyt selectively base-pairs with guanine [18; 19], 5F-Ura selectively base-pairs with adenine [18; 19], and 2F-Ade selectively base-pairs with uridine in a non-perturbing way [15] in individual samples containing one of these labeling schemes. Alternative, specific labeling of RNA with 19 F at the 2'-position in the ribose can be problematic especially for regions adopting non-canonical conformations because of the conformational bias imposed by the fluorine substitution. 2'-Deoxy-2'-fluorinated nucleosides are effectively locked in the C3'-endo sugar pucker normally associated with A-form RNA geometry [54-56]. 4. NMR Resonance Assignments It is the limited chemical diversity in comparison to proteins that complicate NMR (and other) studies of RNA and its complexes. RNA secondary structure is trivial by comparison with proteins, being essentially the code of Watson-Crick base pairing: Guanine (Gua) pairs with Cytosine (Cyt); Adenine (Ade) pairs with Uracyl (Ura) (Figure 2). RNA mainly adopts A-form helical geometries, which contributes to chemical shift degeneracy and makes unambiguous assignments challenging for larger RNAs. A second problem in studies of RNA with molecular weights above 25 kDa is the fast decay of the NMR signal due to relaxation. Line widths in NMR spectra are inversely proportional to the relaxation rates. Therefore the signal-to-noise in NMR spectra of larger molecules is poor. The line width problem can be overcome by (1) the use of deuteration to eliminate proton mediated relaxation pathways and (2) the NMR method called TROSY [57]. 4.1. Initial Characterization of Target RNA Constructs Characterizing the conformation of an RNA under investigation is a crucial first step before conducting a detailed and time-consuming NMR analysis. At the outset, the suitability of the system for a high-resolution structure elucidation and optimal sample conditions for acquisition of the required NMR experiments should be determined. The imino proton region of the proton NMR spectrum of an unlabeled RNA sample in H2O provides a sensitive diagnostic for this purpose. One peak should be observed for each Watson-Crick and two for each G·U wobble base pair in the molecule. Since the imino protons exchange rapidly with the bulk H2O, we typically record jump-return echo experiments that avoid presaturation, while providing the most efficient water suppression [58]. The pyrimidine base protons can provide a valuable alternative, circumventing problems related to solvent exchange or conformational heterogeneity. H5-H6 cross peaks can be conveniently monitored in WATERGATE-2D TOCSY
  • 9. (total correla every pyrimi Figure 2. Watso 5'-phosphodiest uracil are show indicated. Defin while endocycl RNA is commo Overhauser effe bond correlatio phosphorous re and HCCH-TO resonances. Ma H3'/H5'/H5''-rib transfer steps. N Exchangeable i experiment, wh H5(C5C4N4)H HCCH-COSY [ H5/H6 and A s shared quaterna spin system (red in A-form RNA independent 1 J( and HCCH-TO HCNCH transfe 73]. Optimized chemical shift involved in hyd is accomplished ation spectrosc idine. on-Crick base pair ter bond. Hydroge n as dashed lines. nition of backbone ic torsion angles only achieved thr ect (NOE) pattern ons is shown usin sonances Pi and P OCSY experiments agnetization can bose protons for Nucleobase spin s mino protons in G hile crucial ami and (H)N6(CC)H [64] and HCCH-T spin systems. A T ary carbons in larg d circles) of unlab A. Uniform labeli (C,C) couplings an OCSY experiment ers magnetization d HCN-type pulse and show signific drogen bonds (dark d using a HNN-CO opy) experime red fragment of RN en bonding intera Standard atom nu e α, β, γ, δ, ε, and ν0 through ν4 are rough identificatio ns (gray ovals). Th ng black circles. Pi+1. HCP-CCH-T s and thus resolv also be transferr detection using e systems (orange c G and U are corre no proton linkag H experiments for TOCSY [65; 66] e TROSY-relayed HC ger RNA molecul eled RNA is hamp ing with 13 C allow nd chemical shift ts are used to un from the anomeri e schemes facilita cant sensitivity g k blue circles) and OSY experiment o ents where one NA with sequence ctions between cy umbering of ribos ζ and glycosidic χ e given for adenin on of sequential b he spin system for HCP experiment TOCSY [59] and P ve relevant correl red from 31 P reso either COSY- [6 circles) can be ass elated with non-ex ges with non-ex C and A spin syst experiments are us CCH-COSY can i es [64]. Magnetiz pered due to the sm ws magnetization evolution on the C nambiguously ass ic H1' proton to th ate assignments t ains [74; 75]. Th d quantification of or one of its varian expects a H5- e cytosine (i), aden ytosine and guano se and the four com χ torsion angles is ne. Sequential assi base H8 and H6 r sequential assign ts correlate H4'-C P(CC)H-TOCSY [ lations on the bet onances to the 3 J 1] or heteronucle signed using throu xchangeable proton xchangeable proto tems, respectively sed to unambiguou identify A H2-H8 zation transfer thro mall 3 J(H1',H2') vi transfer using lar C1' to C5' carbons sign ribose spin he base H6/8 proto through joint glyc he simultaneous id corresponding h2 J nts. Independent as H6 correlation nine (i+1), linked b osine and adenine mmon nucleobase s indicated for cyto ignments of unlab to ribose H1' nu nments using thro C4' spin systems [60] combine the tter dispersed C1 J(H,P) scalar cou ear TOCSY-type ugh-bond experim ns using an H(CC ons are obtained y [63]. Complemen usly assign pyrimi 8 spin systems thro ough the ribose pr icinal coupling pre rger, conformation s. Thus, HCCH-CO systems [67-71]. ons (green circles) cosidic N1/9 nitr dentification of n J(N,N) scalar coup ssignments of pote n for by 3', e and s are osine beled clear ough- with HCP '-H1' upled [62] ments. CN)H d by ntary idine ough roton esent nally OSY The [72; rogen uclei lings ential
  • 10. nitrogen hydrogen bond acceptor sites can be obtained from a two-bond 2 J(H,N) 1 H,15 N-HSQC experiment using the intraresidue 2 J(H2,N1), 2 J(H2,N3), and 2 J(H8,N7) correlations for the purine residues in the RNA molecule [76]. 4.2. Assignment Strategy for Unlabeled RNA (< 25 nt) Imino proton resonances are assigned sequence-specifically at the earliest stage from water flip-back, WATERGATE-2D NOESY (nuclear Overhauser effect spectroscopy) [77] spectra to verify the construct integrity and secondary structure predictions. The subsequent assignment of non-exchangeable RNA resonances is commonly achieved through identification of sequential base H8 and H6 to ribose H1' nuclear Overhauser effect (NOE) patterns seen in helical regions of nucleic acid structure, in analogy to the procedure originally utilized for DNA studies in the 1980s [78] (Figure 2). Complete ribose H2', H3', H4', H5', and H5" spin system identifications are hampered by limited dispersion (ca. 1ppm) and inefficient through-bond magnetization transfer from the better resolved H1' resonances in TOCSY and COSY (correlation spectroscopy) experiments. The 3 J(H1',H2') vicinal coupling is ca. 1 Hz for the C3'-endo puckers, typically found in A-form helices [79-81]. However, a number of 1 H,31 P- multidimensional HETCOR (heteronuclear correlation) schemes are available for sequential assignment of 31 P and to extended ribose 1 H resonance assignments [61; 62]. The resulting two dimensional H3'/H5'/H5'',31 P-correlations can be concatenated with homonuclear 1 H,1 H-NOESY or TOCSY experiments to transfer magnetization to potentially better resolved resonances like H1' or aromatic H8/H6 resonances [82; 83]. Gradient-selected, sensitivity-enhanced heteronuclear single-quantum correlation experiments (HSQC) [84; 85] recorded at natural 13 C abundance greatly facilitate site- specific assignments owing to distinct ribose C1', C4', C5', Ade C2, Cyt C5, and Ura C5 carbon chemical shifts. Ribose C2' and C3' as well as base Cyt/Ura C6 and Gua/Ade C8 chemical shift ranges overlap yet can be distinguished from other carbon sites in RNA (Table 2). The 2'-hydroxyl group plays fundamental roles in both the structure and the function of RNA and is the major determinant of the conformational and thermodynamic differences between RNA and DNA. In aqueous solution the rapid exchange of the hydroxyl proton with the solvent typically prevents its observation in RNA at room temperature by NMR. Recently, our laboratory reported assignments and a conformational analysis of 2'-OH groups of a medium sized RNA by means of TOCSY and NOESY experiments at low temperature [86; 87]. 4.3. Assignment Strategy for 19 F-labeled RNA Using available chemical shifts from unmodified RNA samples, we have successfully assigned the 19 F resonances for each 2F-Ade, 5F-Ura and 5F-Cyt in modified, medium- sized RNA samples. The unambiguous fluorine chemical shift assignments in substituted RNA can be accomplished using an approach that combines homo- and heteronuclear through-space 19 F,1 H-HOESY, 1 H,1 H-NOESY, and 19 F,19 F-NOESY with through-bond 1 H,19 F-HMBC (heteronuclear multiple bond correlation) experiments.
  • 11. 4.4. Assignment Strategy for Uniformly 13 C,15 N-labeled RNA (< 40 nt) The NOE-based approach described in section 4.2 relies on assumptions about structure and assignments, rendering it susceptible to errors from structural bias. A methodology that achieves sequential assignment via unambiguous through-bond correlation experiments, as is the case for proteins, would be more ideal. Such through- bond NMR experiments are usually given a name that indicates the magnetization transfer route. A possible approach for 13 C labeled RNAs is HCP correlation via sequential INEPT (Insensitive Nuclei Enhancement by Polarization Transfer) transfers [88; 89] (Figure 2, Table 2). Unfortunately, complete sequential assignments of even medium-sized RNA molecules using through-bond experiments such as HCP, HCP- TOCSY and HP-HETCOR are hampered by notoriously overlapped resonances and modest sensitivity. Thus, unambiguous through-bond assignment using HCP-like experiments is always difficult and impractical for larger RNA target molecules (> 40 nt). Out of necessity, sequential assignments are therefore achieved using through- space 1 H,1 H contacts derived from 3D and 4D-isotope edited NOESY experiments. Fortunately, 13 C and 15 N enrichment permits a suite of through-bond experiments that help to alleviate the inherent ambiguity problem of through-space contacts (Figure 2). HCCH-COSY and HCCH-TOCSY experiments are used to unambiguously assign ribose spin systems [67-71] (Figure 2). We commonly employ a hybrid version, the HCCH-COSY-TOCSY [90; 91] to unambiguously assign crowded ribose spin systems. The HCN and HCNCH experiments can elucidate intranucleotide H6/H8-H1' correlations within and between the base and ribose resonances, significantly reducing the ambiguity present in the NOESY-based assignment procedure. Canonical base-pair hydrogen bonding of the Watson-Crick type is fundamental in all biological processes where nucleic acids are involved. NMR experiments have been introduced that allow the direct identification of donor and acceptor nitrogen atoms involved in hydrogen bonds [92; 93]. The partially covalent character of hydrogen bonds gives rise to measurable scalar spin-spin couplings of the type h2 J(N,N) and h1 J(H,N) that represent important additional NMR parameters for the structure determination of nucleic acids in solution [92; 93]. In addition to the unambiguous determination of donor (D) and acceptor (A) nuclei involved in hydrogen bond formation, the magnitude of the h J(D,A) couplings reports on the hydrogen bond geometry. 4.5. Assignment Strategy for Type-Specifically Labeled RNA (> 40 nt) Despite the use of isotope labeling with 13 C and 15 N, resonance assignments of larger RNAs (> 40 nt) continue to be challenging. Above 50 nucleotides, through-bond experiments start to fail because of rapid transverse relaxation. In particular, the sensitivity of through-bond experiments correlating exchangeable and non- exchangeable base protons rapidly deteriorates due to long transfer times associated with small heteronuclear 1 J(C,N) and multi-bond 2,3 J(C,C) couplings. The following three case studies (Table 1) were chosen based on the important state-of-the-art technologies that were applied in conjunction with the molecular weight of the targeted RNAs.
  • 12. Table 1. Large RNA (greater than 50 nucleotides) NMR structures in the PDB. PDB accession Code No # of nucleotides (nt) Description Reference 1P5P 77 HCV IRES domain II [94] 1S9S 101 MMLV Encapsidation signal [10] 2ADT 86 GAAA tetraloop-receptor [9] Figure 3. Large RNA structures determined by NMR. A) HCV IRES Domain II (26 kDa, PDB accession code 1P5P). B) GAAA Tetraloop Receptor Complex (30 kDa, PDB accession code 2ADT). C) Moloney Murine Leukemia Virus Encapsidation Signal (34 kDa, PDB accession code 1S9S). 4.5.1. Structure of HCV IRES Domain II (26 kDa) Larger RNAs often necessitate a “divide and conquer” strategy. This approach assumes a modular architecture of the target RNA sequence without tertiary contacts between the smaller sub-domains (e.g. distant ends of an elongated stem-loop). Accordingly, the NMR solution structure of the 77-nt domain II of the hepatitis C virus (HCV) IRES (internal ribosome entry site) RNA was determined by Puglisi and coworkers (Figure 3A). The excision of two stably folded 34- and 55-nucleotide segments representing the entire domain II allowed for high-resolution structure determinations using conventional, uniformly 13 C,15 N-labeled RNA samples. Subsequently, the global conformation of domain II, a distorted L-shape, could be determined using a joint refinement procedure against residual dipolar coupling (RDC) restraints from both the two smaller segments as well as 60 RDCs determined for the large domain II construct. The inclusion of RDC restraints obtained from partially oriented RNA samples enabled precise definition of the relative orientation of the distant ends of the domain II RNA. Weakly aligned RNA samples were obtained by adding Pf1-phage as a cosolute. A full-length, intact 100 kDa HCV IRES was constructed by joining a 15 N-labeled domain II segment and an unlabeled segment comprising domains III and IV using T4 RNA ligase [95]. A comparison of the imino 1 H and 15 N chemical shift data from the 64-nucleotide domain II with the segmentally labeled, intact 314-nucleotide IRES RNA supports the notion of an independently folded subdomain and suggests an indistinguishable structure in the larger context.
  • 13. 4.5.2. Structure of a GAAA Tetraloop Receptor Complex (30 kDa) In an effort to address the striking lack of RNA tertiary structures in solution, Butcher and coworkers solved the NMR structure of a homodimeric, 30 kDa GAAA tetraloop- receptor RNA complex (Figure 3B). The twofold symmetry of this homodimeric arrangement considerably reduces the complexity of the NMR spectra. A total of seven nucleotide-type-specific RNA samples, GCN CCN , ACN UCN , GCN UCN , GCN , ACN , CCN , and UCN , were prepared in addition to a uniformly labeled RNA sample, GACUCN . Adiabatic frequency-swept inversion pulses optimized to an empirically observed relationship between 1 J(C,H) and carbon chemical shift are commonly used in purge- filter elements to ensure the uniform inversion of all ribose and base carbon sites. Elegant 12 C-filtered/13 C-edited (100% D2O) and simultaneous 12 C,14 N-filtered/13 C,15 N- edited (90% H2O/10% D2O) 3D NOESY spectra have been proposed [96] where monitored 1 H magnetization that starts at either 12 C- or 14 N-bound protons is transferred via isotropic mixing and is subsequently detected at 13 C- or 15 N-bound protons. The 86- nucleotide RNA-RNA homodimer exhibits unfavorable, faster T2-relaxation of both protons and carbons when compared to the 101-nucleotide core encapsidation signal described above. Due to these limitations, the authors relied on more sensitive 2D (rather than 3D or 4D) isotope-filtered/edited NOESY experiments for unambiguously identifying NOEs between labeled and unlabeled nucleotides [97; 98]. Remarkably, the 13 C-filtered experiments suffered from 1 H line broadening stemming from 13 C−1 H dipole-dipole interactions, necessitating a selective deuteration scheme for the ribose ring to complete resonance and NOE assignments. Here, specifically deuterated [3',4',5',5''-2 H4(H5-2 H(pyrimidine))]-NTPs were used which offer narrower H1'- and H2'-line width with the added benefit of reduced overlap originating from H5-base proton (pyrimidine) and H3', H4', H5', and H5''-ribose resonances [7]. RDC data was essential for accurate structure determination of the distant helical ends, but the authors also had to overcome sample precipitation issues in the presence of Pf1-phage by lowering the sample concentration, permitting measurement of only 24 1 H−15 N RDCs. 4.5.3. Structure of the Encapsidation Signal of the Moloney Murine Leukemia Virus (34 kDa) An alternative strategy is to resort to nucleotide-specific labeling to facilitate the NMR data accumulation and accomplish complete assignment. Summers and coworkers were able to determine the solution structure of the 101 nucleotide Moloney Murine Leukemia Virus (MMLV), both free [10] (Figure 3C) and bound to the nucleocapsid (NC) domain of Gag [99]. This represents the largest nucleic acid NMR structure to date using a total of nine differently labeled RNA samples. Resonance assignments were obtained using a new strategy that relies heavily on isotope-filtered/edited NOESY experiments in combination with nucleotide specific isotopic labeling which allows for unambiguous, nucleotide-specific identification of spin systems. Four samples were generated using nucleotide-type-specific 13 C,15 N-labeled RNA samples, GCN , ACN , CCN , and UCN , respectively, to help distinguish intra- from internucleotide NOE connectivities in 3D and 4D 13 C-edited NOESY experiments. In addition, four nucleotide-type-specific 1 H-labeled RNA samples were generated using, GH , AH , CH , and UH , respectively, with remaining nucleotides being 90% perdeuterated, XD . Finally, the exchangeable imino proton assignments were confirmed using a 15 N-labeled G and U sample, GN UN . The overall structure of the RNA consists of three stem-loops, two of which coaxially stack, while a short flexible linker connects the third stem-loop. A 15 N-
  • 14. relaxation analysis using the GN UN -sample revealed that one stem-loop segment tumbled independently from the other two in solution, mitigating to some extent the sensitivity issues associated with slowly tumbling, large RNA molecules. RDC data could be used only for refinement of the individual, isolated stem-loop segments because the intact RNA precipitated in the presence of Pf1-phage cosolute. Table 2. NMR experiments for RNA resonance assignment. Approximate RNA size Isotope labeling scheme NMR experimentsa Reference < 25 nt unlabeled: (GACU)U 1 H, 1 H-COSY 1 H, 1 H-TOCSY 1 H, 1 H-NOESY 31 P, 1 H-COSY 31 P, 1 H-TOCSY 31 P, 1 H-TOCSYNOESY 1 H, 13 C-HSQC [100] [101] [77] [61; 102] [62] [82; 83] [84; 85] < 40 nt uniformly 13 C,15 N: (GACU)CN 1 H, 13 C-Constant time HSQC 1 H, 13 C-Constant time TROSY 1 H, 15 N-HSQC 1 H, 15 N-2 J-HSQC HCCH-COSY HCCH-TOCSY HCCH-COSYTOCSY HCP PCH HCN HCNCH HNN-COSY HN(C)CH-TOCSY HC(C)NH-TOCSY 3D 13 C-edited NOESY 4D 13 C-edited NOESY 2D 15 N-edited NOESY [103] [104] [105] [76] [64] [65; 66] [90; 91] [59; 88] [102; 106] [75; 107-109] [73; 110] [92; 93] [111-113] [114-116] [117] [118] [119] < 50 nt - type-specific labeling, e.g.: (GC)CN (AU)U and (GC)U (AU)CN - site-specific deuteration: (GCAU)D 1 H, 13 C-HMQC 1 H, 15 N-HMQC 1 H, 15 N-TROSY 12 C,14 N-filtered/13 C,15 N-edited 3D NOESY [74] [74; 120] [121] [96; 122; 123] > 50 nt type-specific deuteration, e.g. (G)U (CAU)D 12 C,13 C-filtered/edited 12 C,13 C- edited/filtered 2D NOESY [97; 98] a Underlined experiments are preferably carried out in D2O. 5. Restraint Collection for Structure Determination After sequence specific assignments of RNAs are obtained, the structure determination is traditionally based on collecting sufficient numbers of proton-proton distance restraints utilizing NOESY experiments. Potentially, the short distance restraints between pairs of protons can be complemented with torsion angle information accessible through J-coupling constants. Vicinal 3 J scalar coupling constants can provide useful structural information about the sugar pucker, the β and ε backbone torsion angle conformations, as well as the glycosidic torsion χ which defines the orientation of nucleobases with respect to the sugar moiety (Figure 2).
  • 15. In general, there is a practical difficulty in defining RNA structures precisely by NMR because traditional NOE and J-coupling based structure calculation relies on either short-range distance (< 6 Å) or local torsion angle information. The structural analysis of the RNA backbone conformation is complicated by the lack of useful 1 H−1 H NOE distance restraints available that define the backbone torsions. RNAs often are elongated structures which are better approximated as cylindrical rather than globular shapes. Thus there is a lack of NOE information between distant ends of the molecule, and as a result, the relative orientations of helical segments at opposite ends of the molecule are poorly defined. Recent advances in methodology have aimed to alleviate or overcome this shortcoming [124; 125]. Experiments to measure orientational, rather than distance dependent dipolar couplings, and cross-correlated relaxation rates have been developed providing additional structural information. RDC data not only provide additional information for a better definition of the global orientation of the segments with respect to each other but also carries valuable information on the dynamical properties of the RNA studied. 5.1. Proton-Proton Distance Restraints NOEs provide distance restraints for pairs of hydrogen atoms. Only short proton-proton distances in the range < 6 Å are accessible through NOESY-type experiments. The intensity of NOESY cross peaks is approximately proportional to the inverse of the averaged distance to the power of six, <1/rij 6 >, assuming an isolated pair of proton spins i and j. For RNA NMR studies, NOE derived distance restraints are often determined semi-quantitatively and placed into four categories: Strong, medium, weak and very weak NOEs. A conservative approach sets all the lower bounds to 1.8 Å (van der Waals radius) with upper bounds ranging from 3.0 Å for the most intense NOEs to 7.0 Å for the weakest NOEs found in H2O experiments. Potential problems with interpretation of obtained NOESY cross peak intensities in terms of 1 H−1 H distances in structure calculations arise mainly from the phenomenon of spin diffusion. Spin diffusion causes a breakdown of the isolated spin pair approximation because nearby protons provide competing indirect pathways for observing the direct NOE between the two protons. Spin diffusion effects are significant at longer NOESY mixing times (> 100 ms) leading to damped direct-pathway cross peak intensities and resulting in underestimated interproton distances. Furthermore, multistep transfer pathways can result in false NOE assignments. However, in an early stage of the assignment procedure based on NOESY correlations, spin diffusion pathways can aid the identification of spin systems. Thus, for assignments it is recommended to analyze NOESY spectra acquired with a range of mixing times (ca. 50−200 ms). 5.2. Torsion Angle Restraints J-coupling restraints can be implemented in two different ways during structure determination. They can be introduced qualitatively by restricting a torsion angle in a loose manner (± 30°) to one of the three staggered rotamers along the phosphodiester backbone or defining the preferred ribose sugar pucker such as C2'-endo or C3'-endo. Alternatively, vicinal J-couplings can be quantitatively related to a certain torsion angle
  • 16. using semi-empirical Karplus relations of the form: 3 J = A cos2 θ + B cosθ + C, where θ is the intervening torsion angle [63; 126]. The quantitative analysis of scalar J-couplings, especially in the case of homonuclear 3 J(H,H) couplings related to the ribose sugar pucker, becomes more and more difficult with increasing molecular weight and largely fails for RNAs larger than 40 nt. In contrast, the efficiency of cross-correlated relaxation pathways scales linearly with the overall correlation time of the molecule, which is related to its size. Cross- correlated relaxation rates have been introduced to high resolution NMR as a novel parameter for structure determination [127; 128] and allow the characterization of conformations for larger RNA molecules for which J-coupling analysis is not feasible anymore. 5.2.1. Sugar Pucker The ribose sugar geometry is defined by five alternating torsion angles (ν0 through ν4, Figure 2). Usually, the ribose sugar adopts one of the energetically preferred C2'-endo (South) or C3'-endo (North) conformations. A number of 1 H,1 H and 1 H,13 C scalar couplings are available to determine the sugar pucker qualitatively with the combination of H1'-H2' and H3'-H4' coupling constants being the most useful for smaller RNAs. The 3 J(H1',H2') vicinal coupling is > 8 Hz for C2'-endo puckers and ca. 1 Hz for the C3'-endo puckers, typically found in A-form helices [79; 80; 89]. The opposite behavior is expected for the 3 J(H3',H4') coupling constant with C2'-endo puckers associated with small and the C3'-endo puckers associated with relatively large coupling constant values. An alternative is the measurement of cross-correlated relaxation rates between neighboring 13 C−1 H dipoles within the ribose ring to define the sugar pucker. For RNAs, cross-correlated relaxation rates can be measured using an experiment that belongs to the HCCH class, and precisely determine the ribose sugar pucker without the need of any empirical Karplus parameterization [129]. The resolution of this experiment can be further enhanced by adding a CC-TOCSY transfer [130]. 5.2.2. γ Torsion Angle Measurement of the γ torsion is difficult due to the need for stereospecific assignments of the H5' and H5'' proton resonances. In principle, the two-bond C4',H5'/H5'' couplings can be used in conjunction with the vicinal H4',H5'/H5'' couplings to define γ [81; 131]. 5.2.3. Glycosidic Torsion Angle χ The preferred orientation around χ in A-form helix is anti, which makes the base accessible for commonly found hydrogen bonding interaction. Two heteronuclear vicinal 1 H,13 C couplings contain useful information about the glycosidic torsion angle χ. The 3 J(H1',C) couplings involving the C4,C8 carbons in purines and the C2,C6 carbons in pyrimidines, all depend on the χ torsion [81; 132]. We have shown that the magnitude of a five bond scalar 5 J(H1',F)-coupling observed upon 5F-Ura and 5F-Cyt substitutions also depends on the glycosidic torsion angle χ [18]. Alternative applications have been published where the cross-correlated relaxation between two
  • 17. 13 C−1 H dipoles or a dipole and the glycosidic 15 N CSA is utilized to collect information about the glycosidic torsion angle χ [133-135]. 5.2.4. ε and β Torsion Angles The ε and β torsions can be determined by measuring a variety of 13 C,31 P and 1 H,31 P scalar couplings. Some of these torsions may be measured directly in 2D 1 H,31 P heteronuclear HETCOR experiments [61; 102] and non-refocused 1 H,31 P HSQCs if the phosphorous and proton resonances are sufficiently resolved. However, both the ribose proton and phosphorus resonances involved are generally overlapped for even moderate size RNAs. Accurate measurements for 13 C,31 P and 1 H,31 P couplings can be obtained from both phosphorous-fitting of doublets from singlets [136] or spin echo difference experiments [137-141]. J-HMBC techniques can be applied to determine 3 J(H,P) couplings [142]. A quantitative version of the HCP experiment allows for quantitation of 3 J(C4',P) [143]. 5.2.5. α and ζ Torsion Angles The α and ζ torsions are not accessible by J-coupling measurements because the involved 16 O nuclei have no magnetic moment. Some groups have used 31 P chemical shifts as a guide for loose constraints on these torsions [144]; however, the correlation between 31 P chemical shifts and the phosphodiester backbone conformation is not well understood in RNA. Cross-correlated relaxation rates have been employed to gain information on the α and ζ torsions. The cross-correlated relaxation between a ribose 13 C−1 H dipole and the 31 P chemical shift anisotropy (CSA) carries valuable structural information about the phosphodiester conformation [145]. 5.3. RDC Restraints Several methods have been developed to create a slightly anisotropic environment for molecules tumbling in solution. This results in a small degree of alignment of the molecule, such that the dipolar couplings no longer average to zero, while retaining the quality of high-resolution NMR spectra. The most promising systems for NMR studies of partially aligned systems are dilute liquid crystalline bicelles [146] or Pf1 bacteriophage solutions [147; 148]. RDCs depend on the average value of an orientational function and the inverse cube of the distance, 1/r3 , between the coupled nuclei. Two polar angles θ and φ characterize the orientation of the internuclear vector that connects coupled nuclei with respect to the principal axis system of the molecular alignment tensor A. Thus, for a directly bonded pair of nuclei with known distance, such as 1 H−13 C or 1 H−15 N in labeled RNA, angular restraints can be extracted from dipolar coupling data and incorporated during the structure calculation. Three experiments form the basis of our strategy in regard to RNA structure determination. To measure nucleobase 1 DHC residual dipolar couplings, constant-time (CT)-TROSY and CT-anti-TROSY spectra [149; 150] are acquired in the absence (isotropic) and the presence (anisotropic) of Pf1 phage. 1 DHC values are obtained by subtracting the isotropic values from the anisotropic J-couplings. To measure one-bond ribose 1' through 4' 1 DHC, a J-modulated CT-HSQC experiment is acquired and analyzed as described [151]. Either a J-modulated 1 H-15 N-HSQC or a gradient-enhanced, interleaved inphase-antiphase (IPAP)-HSQC experiment provides additional 1 DHN
  • 18. RDC restraints [152; 153]. Field-induced alignment studies are also feasible for RNA and the obtained RDC data can complement data measured in the presence of external aligning media to resolve redundancies [154]. The measurement of independent sets of RDCs can provide a detailed view of both RNA structure and dynamics. A minimum of five RDCs must be measured per base or rigid sub-segment to establish segment specific order tensors, although in practice more are desirable to improve the precision to which individual As can be determined. A comparison of principal values of ordering can provide valuable information about relative motional amplitudes between segments. Measurements that allow one to obtain dipolar generalized order parameters SRDC (that are identical to order parameters derived from heteronuclear spin relaxation measurements) are sensitive to a much broader motional time scale (ps-ms, thus potentially covering biologically relevant μs-ms time scales) [155-158]. 6. Structure Calculation In the early stages of a project, we typically employ qualitative NOESY NMR data reporting on RNA secondary structure in combination with thermodynamic-based folding algorithms as implemented in the NMR-assisted prediction of secondary structure (NAPSS) to obtain accurate low-resolution structures [159]. Together with the initial characterization, this is most helpful in assessing the folding state of the target RNA. Input data for RNA structure calculations include the previously introduced experimental restraints: NOE-based 1 H−1 H distance, torsion angle, cross-correlated relaxation rate, and RDC restraints. Direct experimental evidence for base paring interactions can be obtained through measurement of h J(D,A) couplings and hydrogen bond restraints in form of donor-acceptor distances can be introduced. Non- experimental constraints include planarity restraints and conformational database potentials of mean force [160] that have been introduced to reproduce planar base pairs, torsion angle correlations, and sequential and nonsequential base-base interactions observed in RNA crystal structures. Such constraints must be applied with great care since they have no experimental basis; their inclusion introduces bias and apparent improvements in precision at the cost of imposing conformations that may not be present. Small angle X-ray scattering (SAXS) data can provide useful low resolution information on the global structural features of RNA-protein complexes facilitating the determination of overall dimensions, radius of gyration and shape of biomolecules [161-163]. The mutually complementary NMR and SAXS data serve to reduce angular degrees of freedom and to confine the translational degrees of freedom, respectively. Solution X-ray scattering data was successfully employed to refine the 30 kDa RNA−RNA complex described in section 4.5.3 [164]. Once a restraint set is assembled, we typically generate an initial NOE-derived structure for refinement with the RDC data by subjecting 100 random extended structures to a simulated annealing protocol using XPLOR-NIH [165] as described [166; 167]. Starting structures are calculated from randomized RNA coordinates using solely energy terms from holonomic constraints such as geometric and non-bonded terms. Torsion angle dynamics (TAD) as implemented in XPLOR and CNS prove to be robust and have a higher convergence rate with respect to molecular dynamics in
  • 19. Cartesian coordinate space [168]. The ca. 25 lowest energy structures without NOE violations ≥0.5 Å are refined via a three step RDC-based protocol designed first to refine the local structure and then the global structure [169]. A new module has been developed for fitting SAXS data via XPLOR-NIH [162]. The lowest energy structures after simulated annealing and subsequent refinement against sets of RDCs and SAXS data are minimized using the AMBER module Sander [170]. Due to more adapted force fields, AMBER yields better and more consistent results for nucleic acids [171]. A number of statistics are commonly evaluated to judge the convergence and quality of the family of calculated RNA NMR structures: Root Mean Square Deviation (RMSD), number of NOE, RDC, and torsion restraints; residual distance, dipolar coupling, and torsion violations; and the largest distance, dipolar coupling, and torsion violations. Typically, the distance restraints are further dissected into the number of interresidue, intraresidue, and intermolecular NOEs. The NMR input data have to be satisfactorily reproduced in high quality structures. Thus, the process of NMR assignment and restraint collection and subsequent structure calculation is iterative; in the process, wrong assignments will be corrected and additional restraints may be identified. Useful RMSDs to consider include only regions of interest and are usually a more accurate descriptor of the quality of the structure than the overall global RMSD. Local RMSDs are given because the overall global value can easily be in the 2.0−3.0 Å range, which might otherwise be indicative of poor convergence. Most RNA structures studied include poorly defined regions such as a disordered loop, terminal base pairs, or a nucleotide lacking internucleotide NOEs. Finally, the obtained structures are validated by carrying out structure calculations omitting a randomly chosen subset of the RDC data while refining against the remaining RDCs [172]. The accuracy of a family of RNA NMR structures is cross- validated by the agreement between the back-calculated RDCs derived from the structures and the omitted RDC subset. Alternatively, a comparison between calculated and observed 1 H chemical shifts represents another possibility for cross-validation of structures derived from NMR restraints [173]. 7. Future Perspectives 7.1. Segmental Labeling of RNA. Resonance overlap caused by the limited chemical and structural diversity presents an inherent barrier to investigate larger RNA in solution by NMR. As the number of resonances increases, even uniform or nucleotide-type specific labels are not sufficient to provide the necessary spectral dispersion. The isotopic labeling of RNA segments, facilitated by T4 RNA ligase, simplifies the spectral complexity by reducing the number of NMR-active atoms. T4 RNA ligase catalyzes the ligation of single-stranded RNA or DNA to either oligoribo- or oligodeoxyribonucleotides through the formation of a standard 3'→5' phosphodiester bond with hydrolysis of ATP to AMP and PPi [174; 175]. An elegant and economic approach using in vitro transcription and hammerhead ribozyme cleavage for generating complementary labeling schemes has recently been described [95; 176]. The incorporation of isotopically labeled RNA fragments into the middle of the full-length target RNA molecule necessitates a three-way ligation; such a
  • 20. multiple segmental labeling of RNA with three segments has recently been demonstrated [177]. RNA structure determination remains a key challenge and represents the next frontier to modern structural biology. The dominance of ncRNAs in the genomic output of higher organisms suggests that they are not simply occasional transcripts with peculiar structure and function, but rather that they may constitute an extensive but hitherto incompletely characterized regulatory network within higher organisms. A decade of structural genomics dramatically increased the database of known protein structures by developing and applying methodologies to determine them as rapidly and cost-effectively as possible. To date, though conceptually conceived a decade ago [178], the primary mission of high-throughput determination of RNA structures has not been seriously undertaken. Nevertheless, a tremendous amount of exciting research is currently underway. Improvements in the fields of RNA NMR methodology and biochemistry, paired with technical advances in NMR instrumentation have paved the way for more streamlined structural efforts targeting RNA in the future. Acknowledgments The authors gratefully acknowledge past and present members of the Hennig laboratory for helpful discussions, Drs Christina Mozes and Brendan Duggan for critical reading of the manuscript, and Dr Brendan Duggan for PDB data base mining. This work was supported by funding from the National Institutes of Health (AI064307, AI081640 and RR024442) and by the National Science Foundation (NSF 0845512). References [1] J.S. Mattick, EMBO Rep 2 (2001), 986-991. [2] C.P. Ponting, P.L. Oliver, and W. Reik, Cell 136 (2009), 629-641. [3] E.S. Lander, et al., Nature 409 (2001), 860-921. [4] J.C. Venter, et al., Science 291 (2001), 1304-1351. [5] K.T. Dayie, Int J Mol Sci 9 (2008), 1214-1240. [6] K. Lu, Y. Miyazaki, and M.F. Summers, J Biomol Nmr 46 (2010), 113-125. [7] L.G. Scott, T.J. Tolbert, and J.R. Williamson, Methods Enzymol 317 (2000), 18-38. [8] P. Vallurupalli, L. Scott, M. Hennig, J.R. Williamson, and L.E. Kay, J Am Chem Soc 128 (2006), 9346-9347. [9] J.H. Davis, M. Tonelli, L.G. Scott, L. Jaeger, J.R. Williamson, and S.E. Butcher, J Mol Biol 351 (2005), 371-382. [10] V. D'Souza, A. Dey, D. Habib, and M.F. Summers, J Mol Biol 337 (2004), 427-442. [11] E.P. Nikonowicz, A. Sirr, P. Legault, F.M. Jucker, L.M. Baer, and A. Pardi, Nucleic Acids Res 20 (1992), 4507-4513. [12] R.T. Batey, M. Inada, E. Kujawinski, J.D. Puglisi, and J.R. Williamson, Nucleic Acids Res 20 (1992), 4515-4523. [13] R.T. Batey, J.L. Battiste, and J.R. Williamson, Methods Enzymol 261 (1995), 300-322. [14] P. Zhou, A.A. Lugovskoy, and G. Wagner, J Biomol Nmr 20 (2001), 11-14. [15] L.G. Scott, B.H. Geierstanger, J.R. Williamson, and M. Hennig, J Am Chem Soc 126 (2004), 11776-11777. [16] J. Cromsigt, J. Schleucher, T. Gustafsson, J. Kihlberg, and S. Wijmenga, Nucleic Acids Res 30 (2002), 1639-1645. [17] T.J. Tolbert and J.R. Williamson, J Am Chem Soc 118 (1996), 7929-7940. [18] M. Hennig, M.L. Munzarova, W. Bermel, L.G. Scott, V. Sklenar, and J.R. Williamson, J Am Chem Soc 128 (2006), 5851-5858.
  • 21. [19] M. Hennig, L.G. Scott, E. Sperling, W. Bermel, and J.R. Williamson, J Am Chem Soc 129 (2007), 14911-14921. [20] H.L. Schultheisz, B.R. Szymczyna, L.G. Scott, and J.R. Williamson, ACS Chem Biol 3 (2008), 499-511. [21] J.F. Milligan, D.R. Groebe, G.W. Witherell, and O.C. Uhlenbeck, Nucleic Acids Res 15 (1987), 8783-8798. [22] J.F. Milligan and O.C. Uhlenbeck, Methods Enzymol 180 (1989), 51-62. [23] P.J. Lukavsky and J.D. Puglisi, RNA 10 (2004), 889-893. [24] Y. Yin and C.W. Carter, Jr., Nucleic Acids Res 24 (1996), 1279-1286. [25] E. Wyszko, J.P. Fuerste, M. Barciszewska, M. Szymanski, R. Adamiak, V.A. Erdmann, and J. Barciszewski, J Biochem 126 (1999), 326-332. [26] T.P. Shields, E. Mollova, L. Ste Marie, M.R. Hansen, and A. Pardi, RNA 5 (1999), 1259-1267. [27] S.R. Price, N. Ito, C. Oubridge, J.M. Avis, and K. Nagai, J Mol Biol 249 (1995), 398-408. [28] N.R. Markham and M. Zuker, Nucleic Acids Res 33 (2005), W577-581. [29] N.R. Markham and M. Zuker, UNAFold, in, 2008, pp. 3-31. [30] J.R. Wyatt, M. Chastain, and J.D. Puglisi, Biotechniques 11 (1991), 764-769. [31] A.C. Anderson, S.A. Scaringe, B.E. Earp, and C.A. Frederick, RNA 2 (1996), 110-117. [32] F. Wincott, A. DiRenzo, C. Shaffer, S. Grimm, D. Tracz, C. Workman, D. Sweedler, C. Gonzalez, S. Scaringe, and N. Usman, Nucleic Acids Res 23 (1995), 2677-2684. [33] I. Kim, S.A. McKenna, E. Viani Puglisi, and J.D. Puglisi, RNA 13 (2007), 289-294. [34] H.K. Cheong, E. Hwang, C. Lee, B.S. Choi, and C. Cheong, Nucleic Acids Res 32 (2004), e84. [35] K. Lu, Y. Miyazaki, and M.F. Summers, J Biomol Nmr 46 (2009), 113-125. [36] R.T. Batey, N. Cloutier, H. Mao, and J.R. Williamson, Nucleic Acids Res 24 (1996), 4836-4837. [37] L. Zidek, R. Stefl, and V. Sklenar, Curr Opin Struct Biol 11 (2001), 275-281. [38] J. Cromsigt, B. van Buuren, J. Schleucher, and S. Wijmenga, Methods Enzymol 338 (2001), 371- 399. [39] B. Furtig, C. Richter, J. Wohnert, and H. Schwalbe, Chembiochem 4 (2003), 936-962. [40] M.P. Latham, D.J. Brown, S.A. McCallum, and A. Pardi, Chembiochem 6 (2005), 1492-1505. [41] H. Wu, L.D. Finger, and J. Feigon, Methods Enzymol 394 (2005), 525-545. [42] L.G. Scott and M. Hennig, Methods Mol Biol 452 (2008), 29-61. [43] J. Flinders and T. Dieckmann, Prog Nucl Magn Reson Spectrosc 48 (2006), 137-159. [44] T.J. Tolbert and J.R. Williamson, J Am Chem Soc 119 (1997), 12100-12108. [45] E.P. Nikonowicz, K. Kalurachchi, and E. DeJong, FEBS Lett 415 (1997), 109-113. [46] E.P. Nikonowicz, M. Michnicka, K. Kalurachchi, and E. DeJong, Nucleic Acids Res 25 (1997), 1390-1396. [47] A.G. Marshall and J.L. Smith, J Am Chem Soc 99 (1977), 635-636. [48] J. Horowitz, J. Ofengand, W.E. Daniel, Jr., and M. Cohn, J Biol Chem 252 (1977), 4418-4420. [49] P.V. Cornish, D.P. Giedroc, and M. Hennig, J Biomol Nmr 35 (2006), 209-223. [50] C. Kreutz, H. Kahlig, R. Konrat, and R. Micura, Angew Chem Int Ed Engl 45 (2006), 3450-3453. [51] B. Puffer, C. Kreutz, U. Rieder, M.O. Ebert, R. Konrat, and R. Micura, Nucleic Acids Res 37 (2009), 7728-7740. [52] E.A. Louie, P. Chirakul, V. Raghunathan, S.T. Sigurdsson, and G.P. Drobny, J Magn Reson 178 (2006), 11-24. [53] G.L. Olsen, T.E. Edwards, P. Deka, G. Varani, S.T. Sigurdsson, and G.P. Drobny, Nucleic Acids Res 33 (2005), 3447-3454. [54] J.J. Barchi, Jr., L.S. Jeong, M.A. Siddiqui, and V.E. Marquez, Journal of Biochemical & Biophysical Methods 34 (1997), 11-29. [55] B. Reif, V. Wittmann, H. Schwalbe, C. Griesinger, K. Worner, K. JahnHofmann, J.W. Engels, and W. Bermel, Helvetica Chimica Acta 80 (1997), 1952-1971. [56] C. Thibaudeau, J. Plavec, and J. Chattopadhyaya, Journal of Organic Chemistry 63 (1998), 4967- 4984. [57] K. Pervushin, R. Riek, G. Wider, and K. Wuthrich, Proc Natl Acad Sci U S A 94 (1997), 12366- 12371. [58] V. Sklenar, B.R. Brooks, G. Zon, and A. Bax, FEBS Lett 216 (1987), 249-252. [59] J.P. Marino, H. Schwalbe, C. Anklin, W. Bermel, D.M. Crothers, and C. Griesinger, J Biomol Nmr 5 (1995), 87-92. [60] S.S. Wijmenga, H.A. Heus, H.A. Leeuw, H. Hoppe, M. van der Graaf, and C.W. Hilbers, J Biomol Nmr 5 (1995), 82-86. [61] V. Sklenar, H. Miyashiro, G. Zon, H.T. Miles, and A. Bax, FEBS Lett 208 (1986), 94-98. [62] G.W. Kellogg, J Magn Reson 98 (1992), 176-182. [63] S.S. Wijmenga and B.N.M. van Buuren, Prog Nucl Magn Reson Spectrosc 32 (1998), 287-387.
  • 22. [64] B. Simon, K. Zanier, and M. Sattler, J Biomol Nmr 20 (2001), 173-176. [65] P. Legault, B.T. Farmer, L. Mueller, and A. Pardi, J Am Chem Soc 116 (1994), 2203-2204. [66] J.P. Marino, J.H. Prestegard, and D.M. Crothers, J Am Chem Soc 116 (1994), 2205-2206. [67] S.W. Fesik, H.L. Eaton, E.T. Olejniczak, E.R.P. Zuiderweg, L.P. McIntosh, and F.W. Dahlquist, J Am Chem Soc 112 (1990), 886-888. [68] L.E. Kay, M. Ikura, and A. Bax, J Am Chem Soc 112 (1990), 888-889. [69] E.P. Nikonowicz and A. Pardi, J Mol Biol 232 (1993), 1141-1156. [70] A. Pardi, Methods Enzymol 261 (1995), 350-380. [71] A. Pardi and E.P. Nikonowicz, J Am Chem Soc 114 (1992), 9202-9203. [72] B.T. Farmer, L. Muller, E.P. Nikonowicz, and A. Pardi, J Am Chem Soc 115 (1993), 11040-11041. [73] V. Sklenar, M.R. Rejante, R.D. Peterson, E. Wang, and J. Feigon, J. Am. Chem. Soc. 115 (1993), 12181-12182. [74] J.P. Marino, J.L. Diener, P.B. Moore, and C. Griesinger, J Am Chem Soc 119 (1997), 7361-7366. [75] V. Sklenar, T. Dieckmann, S.E. Butcher, and J. Feigon, J Magn Reson 130 (1998), 119-124. [76] V. Sklenar, R.D. Peterson, M.R. Rejante, and J. Feigon, J Biomol Nmr 4 (1994), 117-122. [77] G. Lippens, C. Dhalluin, and J.M. Wieruszeski, J Biomol Nmr 5 (1995), 327-331. [78] K. Wuthrich, NMR of proteins and nucleic acids, Wiley, New York, 1986. [79] E. Duchardt, C. Richter, B. Reif, S.J. Glaser, J.W. Engels, C. Griesinger, and H. Schwalbe, J Biomol Nmr 21 (2001), 117-126. [80] H. Schwalbe, J.P. Marino, S.J. Glaser, and C. Griesinger, J Am Chem Soc 117 (1995), 7251-7252. [81] H. Schwalbe, J.P. Marino, G.C. King, R. Wechselberger, W. Bermel, and C. Griesinger, J Biomol Nmr 4 (1994), 631-644. [82] G.W. Kellogg, A.A. Szewczak, and P.B. Moore, J Am Chem Soc 114 (1992), 2727-2728. [83] G.W. Kellogg and B.I. Schweitzer, J Biomol Nmr 3 (1993), 577-595. [84] L. Kay, P. Keifer, and T. Saarinen, J Am Chem Soc 114 (1992), 10663-10665. [85] J. Schleucher, M. Schwendinger, M. Sattler, P. Schmidt, O. Schedletzky, S.J. Glaser, O.W. Sørensen, and C. Griesinger, J Biomol Nmr 4 (1994), 301-306. [86] J. Fohrer, M. Hennig, and T. Carlomagno, J Mol Biol 356 (2006), 280-287. [87] M. Hennig, J. Fohrer, and T. Carlomagno, J Am Chem Soc 127 (2005), 2028-2029. [88] H.A. Heus, S.S. Wijmenga, F.J.M. Vandeven, and C.W. Hilbers, J Am Chem Soc 116 (1994), 4983-4984. [89] J.P. Marino, H. Schwalbe, C. Anklin, W. Bermel, D.M. Crothers, and C. Griesinger, J Am Chem Soc 116 (1994), 6472-6473. [90] W. Hu, L.T. Kakalis, L. Jiang, F. Jiang, X. Ye, and A. Majumdar, J Biomol Nmr 12 (1998), 559- 564. [91] S.J. Glaser, H. Schwalbe, J.P. Marino, and C. Griesinger, J Magn Reson B 112 (1996), 160-180. [92] A.J. Dingley and S. Grzesiek, J Am Chem Soc 120 (1998), 8293-8297. [93] K. Pervushin, A. Ono, C. Fernandez, T. Szyperski, M. Kainosho, and K. Wuthrich, Proc Natl Acad Sci USA 95 (1998), 14147-14151. [94] P.J. Lukavsky, I. Kim, G.A. Otto, and J.D. Puglisi, Nat Struct Biol 10 (2003), 1033-1038. [95] I. Kim, P.J. Lukavsky, and J.D. Puglisi, J Am Chem Soc 124 (2002), 9338-9339. [96] C. Zwahlen, P. Legault, S.J.F. Vincent, J. Greenblatt, R. Konrat, and L.E. Kay, J Am Chem Soc 119 (1997), 6711-6721. [97] J. Iwahara, J.M. Wojciak, and R.T. Clubb, J Biomol Nmr 19 (2001), 231-241. [98] R.D. Peterson, C.A. Theimer, H. Wu, and J. Feigon, J Biomol Nmr 28 (2004), 59-67. [99] V. D'Souza and M.F. Summers, Nature 431 (2004), 586-590. [100] A.A. Shaw, C. Salaun, J.-F. Dauphin, and B. Ancian, J Magn Reson Ser A 120 (1996), 110-115. [101] J. Cavanagh and M. Rance, J Magn Reson 96 (1992), 670-678. [102] T. Carlomagno, M. Hennig, and J.R. Williamson, J Biomol Nmr 22 (2002), 65-81. [103] G.W. Vuister and A. Bax, J Magn Reson 98 (1992), 428-435. [104] A. Meissner and O.W. Sorensen, J Magn Reson 139 (1999), 439-442. [105] S. Mori, C. Abeygunawardana, M.O. Johnson, and P.C. van Zijl, J Magn Reson B 108 (1995), 94- 98. [106] G. Varani, F. Aboul-ela, F. Allain, and C.C. Gubser, J Biomol Nmr 5 (1995), 315-320. [107] R. Riek, K. Pervushin, C. Fernandez, M. Kainosho, and K. Wuthrich, J Am Chem Soc 123 (2001), 658-664. [108] V. Sklenar, R.D. Peterson, M.R. Rejante, and J. Feigon, J Biomol Nmr 3 (1993), 721-727. [109] H. Van Melckebeke, A. Pardi, J. Boisbouvier, J.P. Simorre, and B. Brutscher, J Biomol Nmr 32 (2005), 263-271. [110] R. Fiala, J. Czernek, and V. Sklenar, J Biomol Nmr 16 (2000), 291-302. [111] J.P. Simorre, G.R. Zimmermann, L. Mueller, and A. Pardi, J Biomol Nmr 7 (1996), 153-156.
  • 23. [112] J.P. Simorre, G.R. Zimmermann, L. Mueller, and A. Pardi, J Am Chem Soc 118 (1996), 5316- 5317. [113] J.P. Simorre, G.R. Zimmermann, A. Pardi, B.T. Farmer, 2nd, and L. Mueller, J Biomol Nmr 6 (1995), 427-432. [114] R. Fiala, F. Jiang, and D.J. Patel, J Am Chem Soc 118 (1996), 689-690. [115] J. Wohnert, M. Gorlach, and H. Schwalbe, J Biomol Nmr 26 (2003), 79-83. [116] J. Wohnert, R. Ramachandran, M. Gorlach, and L.R. Brown, J Magn Reson 139 (1999), 430-433. [117] B. Brutscher, J. Boisbouvier, E. Kupce, C. Tisne, F. Dardel, D. Marion, and J.P. Simorre, J Biomol Nmr 19 (2001), 141-151. [118] R.C. Morshauser and E.R. Zuiderweg, J Magn Reson 139 (1999), 232-239. [119] L. Mueller, P. Legault, and A. Pardi, J Am Chem Soc 117 (1995), 11043-11048. [120] A. Bax, R.H. Griffey, and B.L. Hawkins, J Magn Reson 55 (1983), 301-315. [121] A.A. Szewczak, G.W. Kellogg, and P.B. Moore, FEBS Lett 327 (1993), 261-264. [122] J. Farjon, J. Boisbouvier, P. Schanda, A. Pardi, J.P. Simorre, and B. Brutscher, J Am Chem Soc 131 (2009), 8571-8577. [123] D. Nietlispach, J Biomol Nmr 31 (2005), 161-166. [124] A. Bax, G. Kontaxis, and N. Tjandra, Methods Enzymol 339 (2001), 127-174. [125] H. Zhou, A. Vermeulen, F.M. Jucker, and A. Pardi, Biopolymers 52 (1999), 168-180. [126] J.P. Marino, H. Schwalbe, and C. Griesinger, Acc. Chem. Res. 32 (1999), 614-623. [127] B. Reif, M. Hennig, and C. Griesinger, Science 276 (1997), 1230-1233. [128] H. Schwalbe, T. Carlomagno, M. Hennig, J. Junker, B. Reif, C. Richter, and C. Griesinger, Methods Enzymol 338 (2001), 35-81. [129] I.C. Felli, C. Richter, C. Griesinger, and H. Schwalbe, J Am Chem Soc 121 (1999), 1956-1957. [130] C. Richter, C. Griesinger, I. Felli, P.T. Cole, G. Varani, and H. Schwalbe, J Biomol Nmr 15 (1999), 241-250. [131] J.V. Hines, G. Varani, S.M. Landry, and I. Tinoco Jr., J Am Chem Soc 115 (1993), 11002-11003. [132] L. Trantirek, R. Stefl, J.E. Masse, J. Feigon, and V. Sklenar, J Biomol Nmr 23 (2002), 1-12. [133] E. Duchardt, C. Richter, O. Ohlenschlager, M. Gorlach, J. Wohnert, and H. Schwalbe, J Am Chem Soc 126 (2004), 1962-1970. [134] S. Ravindranathan, C.H. Kim, and G. Bodenhausen, J Biomol Nmr 27 (2003), 365-375. [135] J. Rinnenthal, C. Richter, J. Ferner, E. Duchardt, and H. Schwalbe, J Biomol Nmr 39 (2007), 17- 29. [136] H. Schwalbe, W. Samstag, J.W. Engels, W. Bermel, and C. Griesinger, J Biomol Nmr 3 (1993), 479-486. [137] C.G. Hoogstraten and A. Pardi, J Magn Reson 133 (1998), 236-240. [138] P. Legault, F.M. Jucker, and A. Pardi, FEBS Lett 362 (1995), 156-160. [139] T. Szyperski, C. Fernandez, A. Ono, K. Wuthrich, and M. Kainosho, J Magn Reson 140 (1999), 491-494. [140] W. Hu, S. Bouaziz, E. Skripkin, and A. Kettani, J Magn Reson 139 (1999), 181-185. [141] G.M. Clore, E.C. Murphy, A.M. Gronenborn, and A. Bax, J Magn Reson 134 (1998), 164-167. [142] C.H. Gotfredsen, A. Meissner, J.O. Duus, and O.W. Sorensen, Magn Reson Chem 38 (2000), 692- 695. [143] C. Richter, B. Reif, K. Worner, S. Quant, J.P. Marino, J.W. Engels, C. Griesinger, and H. Schwalbe, J Biomol Nmr 12 (1998), 223-230. [144] P. Legault and A. Pardi, J Magn Reson B 103 (1994), 82-86. [145] C. Richter, B. Reif, C. Griesinger, and H. Schwalbe, J Am Chem Soc 122 (2000), 12728-12731. [146] N. Tjandra and A. Bax, Science 278 (1997), 1111-1114. [147] M.R. Hansen, P. Hanson, and A. Pardi, Methods Enzymol 317 (2000), 220-240. [148] M.R. Hansen, L. Mueller, and A. Pardi, Nat Struct Biol 5 (1998), 1065-1074. [149] J. Boisbouvier, B. Brutscher, A. Pardi, D. Marion, and J.-P. Simorre, J Am Chem Soc 122 (2000), 6779-6780. [150] P. Andersson, J. Weigelt, and G. Otting, J Biomol Nmr 12 (1998), 435-441. [151] N. Tjandra and A. Bax, J Magn Reson 124 (1997), 512-515. [152] L. Yao, J. Ying, and A. Bax, J Biomol Nmr 43 (2009), 161-170. [153] N. Tjandra, S. Grzesiek, and A. Bax, J Am Chem Soc 118 (1996), 6264-6272. [154] Q. Zhang, R. Throolin, S.W. Pitt, A. Serganov, and H.M. Al-Hashimi, J Am Chem Soc 125 (2003), 10530-10531. [155] J. Meiler, J.J. Prompers, W. Peti, C. Griesinger, and R. Bruschweiler, J Am Chem Soc 123 (2001), 6098-6107. [156] J.R. Tolman, J Am Chem Soc 124 (2002), 12020-12030.
  • 24. [157] J.R. Tolman, H.M. Al-Hashimi, L.E. Kay, and J.H. Prestegard, J Am Chem Soc 123 (2001), 1416- 1424. [158] J.R. Tolman and K. Ruan, Chem Rev 106 (2006), 1720-1736. [159] J.M. Hart, S.D. Kennedy, D.H. Mathews, and D.H. Turner, J Am Chem Soc 130 (2008), 10233- 10239. [160] G.M. Clore and J. Kuszewski, J Am Chem Soc 125 (2003), 1518-1525. [161] A. Grishaev, J. Wu, J. Trewhella, and A. Bax, J Am Chem Soc 127 (2005), 16621-16628. [162] A. Grishaev, J. Ying, M.D. Canny, A. Pardi, and A. Bax, J Biomol Nmr 42 (2008), 99-109. [163] F. Gabel, B. Simon, M. Nilges, M. Petoukhov, D. Svergun, and M. Sattler, J Biomol Nmr 41 (2008), 199-208. [164] X. Zuo, J. Wang, T.R. Foster, C.D. Schwieters, D.M. Tiede, S.E. Butcher, and Y.X. Wang, J Am Chem Soc 130 (2008), 3292-3293. [165] C.D. Schwieters, J.J. Kuszewski, N. Tjandra, and G. Marius Clore, J Magn Reson 160 (2003), 65- 73. [166] P.V. Cornish, M. Hennig, and D.P. Giedroc, Proc Natl Acad Sci U S A 102 (2005), 12694-12699. [167] P.L. Nixon, A. Rangan, Y.G. Kim, A. Rich, D.W. Hoffman, M. Hennig, and D.P. Giedroc, J Mol Biol 322 (2002), 621-633. [168] E.G. Stein, L.M. Rice, and A.T. Brunger, J Magn Reson 124 (1997), 154-164. [169] S.A. McCallum and A. Pardi, J Mol Biol 326 (2003), 1037-1050. [170] D.A. Pearlman, D.A. Case, J.W. Caldwell, W.R. Ross, T.E. Cheatham, S. DeBolt, D.G.S. Ferguson, and P. Kollman, Computer Physics Communications 91 (1995), 1-41. [171] V. Tsui and D.A. Case, J Am Chem Soc 122 (2000), 2489-2498. [172] G.M. Clore and D.S. Garrett, J Am Chem Soc 121 (1999), 9008-9012. [173] J.A. Cromsigt, C.W. Hilbers, and S.S. Wijmenga, J Biomol Nmr 21 (2001), 11-29. [174] T.E. England and O.C. Uhlenbeck, Biochemistry 17 (1978), 2069-2076. [175] M.J. Moore and C.C. Query, Methods Enzymol 317 (2000), 109-123. [176] A.G. Tzakos, L.E. Easton, and P.J. Lukavsky, J Am Chem Soc 128 (2006), 13344-13345. [177] F.H. Nelissen, A.J. van Gammeren, M. Tessari, F.C. Girard, H.A. Heus, and S.S. Wijmenga, Nucleic Acids Res 36 (2008), e89. [178] J.A. Doudna, Nat Struct Biol 7 Suppl (2000), 954-956.