This document discusses computational techniques for studying biological systems containing transition metals. It provides examples of using quantum mechanics (QM) to study cisplatin binding to DNA and molecular mechanics (MM) and docking to study ruthenium complexes binding to kinases. For cisplatin-DNA, normal mode analysis found the lowest energy collective movements and QM minimization determined preferred geometries. For ruthenium-kinase, docking predicted binding energies that correlated with experimental values. Computational chemistry methods are versatile and useful for designing metal-based drugs by integrating different techniques to overcome individual limitations.

1. Exploration of large conformational spaces
- Protein-Ligand Docking: binds a ligand in a specific
region of a protein (GOLD 5.0).
- Normal Mode Analysis: gets the lowest energy
collective movements of a system (UCSF Chimera 1.7).
What is inside the Theoretical Chemist toolbox?
Application of computational techniques on biological systems containing transition metals
Molecular Modelling of Transition Metals
E. Ortega-Carrasco,A. Lledós, J.D. Maréchal
Unitat de Química Física, Departament de Química, UniversitatAutònoma de Barcelona, Edifici C.n.,
08193 Cerdanyola delVallès, Catalunya, Espanya
eortega@qf.uab.cat
IntroductionComputational Chemistry is a discipline using mathematical methods for the
calculation of molecular properties or for the simulation of molecular behaviour.1
There is a broad range of methodologies although they are mostly based in two
different fields: Quantum Mechanics (QM) or Molecular Mechanics (MM), being
more accurate the first one and quicker the latter. Which methods are more
adequate to study a given system depends on the ratio between electronic and
conformational accuracy needed.
We are intensively focusing on the study of bioinorganic systems by computational
means and more particularly the problem of the binding of metalodrugs to their
targets. This represents one of the most challenging systems to study because the
exploration of a relatively large conformational space (MM) is required and fine
electronic representations of the metal could be needed (QM). However, the quality
of the methods to use are dependent on how the first coordination sphere of the
metal participates to the binding. In inert bindings like Ruthenium Arene complexes
interacting with kinase, MM based methods could be sufficient while for active
bindings like those of cisplatin to the double strand structure of the DNA QM
calculations are needed at some point.
Here we present two studies on those systems to illustrate how computational
chemistry could be relevant in the field of design of metalodrugs.
(1) IUPAC. Compendium of ChemicalTerminology, 2nd ed. (the "Gold Book"). Compiled by A. D. McNaught and A.Wilkinson. Blackwell Scientific Publications, Oxford (1997).
(2) E.Ortega-Carrasco,A. Lledós, J.-D. Maréchal Submitted.
QM based:
MM based:
- QM minimizations: founds the lowest energy geometry.
Precise and useful for small and model systems (Gaussian 09).
QM/MM Methods:calculate with precision a
small part of the system taking into account the rest
of the molecule at a lower computational level
(ONIOM, implemented in Gaussian 09)
* In parenthesis: the name of the program used at this point.
Cisplatin-DNA adducts Ruthenium-Kinase systemsThe activity of cisplatin implies the coordination of the platinum to N7 atoms
of two guanines and the deformation of the DNA strand.
(I) Energetic exploration of the principal movements of the cisplatin-GG model
(1st coordination sphere)
(II) Normal Mode Analysis of the effect of cisplatin docked to DNA.
ConclusionsTo ascertain the impact of the DNA strand on geometry of the
first coordination of the metal, Normal Mode Analysis was
carried out. This technique allows us to determine the impact
of the coordination of the cisplatin drug in the whole strand
They show how the coordination sphere is more restricted for
the geometry of the 1,3-intrastrand.
Several questions remain to be addressed:
- What is the real weight of the first coordination sphere of the metal in defining the
geometry of the adducts experimentally observed?
-What is the contribution of the DNA partner ?
Prediction of bio-inorganic interactions by Protein-Ligand Docking protocol.2
The experimental value of IC50 of some Ruthenium complexes has been compared to
the value of binding energy resulting from the Protein-Ligand Docking approach.
Calculations have been repeated a total of 16 times changing the geometry of the
ligand (x-ray structure or an optimized one), the flexibility of the protein (totally fixed or
allowing flexibility in the cavity) and the different scoring functions available in the
GOLD suite (GoldScore, ChemScore, ChemPLP and ASP).
The versatility of Computational Chemistry methodologies for design purposes is
constantly increasing. One of the reason of this expansion is the possibility to
integrate several methodologies together in order to overcome individual
limitations, the choice of the correct technique can save us time and effort. At this
point, the ability of the theoretician can be determinant to successfully achieve
this interconnection.
Images From:
http://x3dna.org/highlights/schematic-diagrams-of-base-pair-parameters
Tilt (t) and twist (W) angles correspond to the structural variables that most change in
X-ray structures of the principal adducts of cisplatin to DNA: 1,2-intra > 1,3 –intra >
1,2-interstrand.
QM calculations on 1st coordination models show clear division of each kind of adduct
but do not explain the relative frequency observed between 1,2 and 1,3 intrastrands.
1 2 3 4
5 6 7 Different organometallic
compunds used in this study
(top).
Plot of the results obtained with
both structures of the ligand),
fixed protein and ASP Scoring
Function (bottom).
The present study shows that scoring
functions are efficient for predicting most
of the structural and energetic features of
the binding of organometallic compounds
to proteins.
1,2-intrastrand 1,2-interstrand 1,3-intrastrand