This document discusses using 3D-RISM and protein electrostatic fields to analyze protein-ligand interactions. 3D-RISM is an analytical method that can determine solvent densities around proteins. The document compares using the XED force field versus GAFF to model electrostatics, finding better results with XED. It also describes using protein electrostatic "field points" to identify potential ligand binding sites and compare protein similarity. Several challenges are noted, including preparing proteins and defining active sites, but initial results look promising.

1. Comparing the electrostatic properties of protein active sites
and other Cresset research

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Agenda
> Looking at 3D RISM
> Work by Mark Mackey and Paolo Tosco
> Approaches to Protein Fields
> Work by Andy Smith, Susana Tomasio
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New use for the XED force field?
3D-RISM

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3D-RISM
> Analytical method for working out where water
goes (Ornstein-Zernike equation)
> Conceptually equivalent to running an infinite-
time MD simulation on the solvent and extracting
the solvent particle densities
ℎ 𝑟𝑟12, 𝜔𝜔1, 𝜔𝜔2
= 𝑐𝑐 𝑟𝑟12, 𝜔𝜔1, 𝜔𝜔2
+ 𝜌𝜌 � 𝑑𝑑𝑑𝑑3 𝑑𝑑𝑑𝑑3 𝑐𝑐 𝑟𝑟13, 𝜔𝜔1, 𝜔𝜔3 ℎ(𝑟𝑟32, 𝜔𝜔3, 𝜔𝜔2)

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3D-RISM
> Analytical method for working out where water
goes (Ornstein-Zernike equation)
> Conceptually equivalent to running an infinite-
time MD simulation on the solvent and extracting
the solvent particle densities
> Horribly complicated maths
> GPL implementation in Amber Tools
> Output is grid containing particle densities
> Thermodynamic analysis to assign “happiness”
to each water

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> Results depend on the potential function from
solvent to solute u(r12, Ω1, Ω2)
> In practise, this means vdW + electrostatics
> Results only as good as your potential functions
> Does the XED description of electrostatics
improve the results?
Problems

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Electrostatics from Molecular Mechanics
> XED force field – eXtended Electron Distribution
> Multipoles via additional monopoles
> Huckel
> separation of π and σ charges – substituent effects
> find bond orders and assign hybridization – analogue N atoms
> Full MM Force Field with excellent coverage of organic
chemistry and proteins
> Minimization, Conformations etc.
> Additional atoms cost more than ACC
> Cheaper than other multipole methods
> Local polarization
H
0
.
5
-
0
.
5
+0
.
9
+0
.
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Comparing XED with GAFF – Hydrogen Density
XED GAFF
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Comparing XED with GAFF – Hydrogen Density
XED GAFF
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Comparing XED with GAFF – Hydrogen Density
XED GAFF
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Comparing XED with GAFF – Oxygen Density
XED GAFF
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RISM with XED Conclusions
> Initial results look promising
> Water patterns around small molecules look
better with XED
> Does this extend to protein environments?
> Does it change the ‘happiness’ factor?
> We’ll keep you posted
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A quick refresher
Field points
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Field Points & Scoring
Calculate interaction energy
potential with charged oxygen
probe. Contour this potential
Field points indicate potential
sites where protein atoms want
to sit
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Field Points & Scoring
Minimize Oxygen probe from
many starting points onto
surface of ligand
Charge on probe determines
which field we are calculating.
-
-
+
Field points indicate potential
sites where protein atoms want
to sit
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Similarity Metric Relies on Field Values
A B
2
ABBA
AB
EE
E →→ +
=
BBAA
AB
AB
EE
E
S
+
=
2
∑ ×=→
Afp
ABABA fppositionFfpsizeE ))(()(
EA→B = “Energy”, SAB = Similiarity
A B
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Example Ligand field – 1FVT
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Fields and More
Proteins
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Protein Field Problem
> Can’t use the ligand field points to sample the
protein field
> Most should be inside the protein surface
> Same problem will exist for protein field points
> Protein field points will show where ligand atoms want
to be
> Most should be inside the ligand surface
> But we can still compare proteins to proteins
> Predict protein similarity
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Validation
> Find all dissimilar proteins that bind the same
ligand
> Show that the field for these is similar
> What ligands?
> ATP ?
> Yuk!
> NADP ?
> Yuk!
> Estradiol ?
> Yuk!
 Lots of similar proteins with similar ligands, few
diverse proteins with synthetic ligands
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Problems
> Protein preparation a key step
> Time consuming
> Required automated process
> How to handle highly charged proteins
> Scaling?
> How to handle water?
> Remove?
> How to handle metals?
> Point charge?
> How to define the active site?
>Where is it, and where does it stop?
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Charged Proteins
> Traditional ligand approach – uniformly scaled formal
charges (Native)
> All formal charges are divided by 8
> Uniformly scaled formal charges with a distance
dependant dielectric (Native-DDD)
> Remove or scale formal charges further for solvated
charged residues (Varichg)
> Fully solvated formal charges: charge scaler=80
> Buried in the protein: charge scaler=2
> Varichg with a distance dependent dielectric
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Some Good Results – 1FVT Native
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Some Good Results – 4MBS DDD
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Some Good Results – 1OIT DDD+Scaling
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Still Work in Progress
> New thinking for protein preparation
> Checking of Asn/Gln, Ser/Thr/Tyr orientations
> Possible integration with RISM work
> Validate through protein similarity rather than ligand
binding ?
> Still need to understand when each field generation
method works and why
> DDD looks good, but is not best for all proteins
> Need ideas on how to close the ligand-protein field
gap
> Would be nice to compare ligand and protein fields directly,
but you can’t
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Some Good Results
Ligand field =
Protein field =
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28. © Cressetsmarter chemistry | smarter decisions
mark@cresset-group.com
susana@cresset-group.com
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