Unit: Structural Bioinformatics - CNRS URA 2185
Director: Nilges Michael
The principal role of structural bioinformatics is to complement experimental structural studies in various ways by in silico studies. We are involved on the areas of calculation methods for structure determination with NMR; prediction of protein structure by comparative modelling to answer specific biological questions; and genomic analysis from large-scale structure prediction of genomic DNA. A focal point is the study of protein-protein interactions and protein ligand interactions, where we try to contribute to the fundamental understanding of binding mechanisms on the one hand, and to the search for potential therapeutic agents on the other, by including docking and virtual screening calculations. Most of the work is based on computer simulations, but we are directly involved in experimental work (X-ray crystal structure determination, neutraon scattering).
Development of a probabilistic structure determination method for NMR (M. Habeck, M. Nilges, W. Rieping)
Macromolecular structure determination is an inference problem: the measured quantities are noisy and incomplete, therefore insufficient to determine the structure uniquely. The objective should therefore be to explore all regions of conformational space compatible with the information at hand. Currently, this is attempted in a rather approximate way by repeated structure calculations with the same data (NOE-derived distances, torsion angles/ scalar couplings, residual dipolar couplings).
We have developed a probabilistic method that directly generates a posterior probability distribution. The latter represents the full knowledge about the target structure. The calculation of the probability distribution is computationally much more demanding than minimization because of its very high dimensionality. We could show that by a combination of several sampling methods the probability distribution can be simulated for medium-sized proteins by means of a new Markov Chain Monte Carlo strategy (so far these strategies had been used to simulate small peptides. A major advantage of the new method is that additional parameters necessary for the modelling but that cannot be measured (such as weighting factors) need not be guessed but can be determined in parallel with the structure. The method is the only method to date that gives a reliable estimate of the precision of a structure determined from NMR data. We used the method with several experimental and synthetic data sets, and we are working on several extensions and generalizations. We expect that in the long run, in particular with ever faster computers, the method will replace standard methods.
Study of 6--phosphogluconolactonase (6PGL) from T. Brucei by NMR and X-Ray crystallography (V. Stoven)
The parasitic protozoa Trypanosoma brucei are the causative agents of African sleeping sickness. The pentose phosphate pathway plays a crucial role in the host--parasite relationship. In order to evaluate this pathway as a potential drug target, it is necessary to study the associated enzymes in detail. Very little information was available for 6PGL (6--phosphogluconolactonase) the second enzyme in the cycle. In order to better understand the specificity and the mechanism of this enzyme, we have undertaken 3D structure determination of 6PGL, by NMR and by X-Ray crystallography (collaboration with Marc Delarue, Unité de Biochimie Structurale, Institut Pasteur). We have obtained X--ray diffraction data at 2.8 angstrom, and additional data on a mercury derivative was obtained at 2.1 angstrom. Structure refinement is currently in progress. An NMR study was undertaken in parallel, in order to perform structural and dynamic studies, in absence and in presence of the substrate (collaboration with the group of Geoffrey Bodenhausen, Ecole Normale Supérieure).
Complementarity of structure ensembles in protein-protein binding (R. Grünberg, J. Leckner, M. Nilges)
Protein-protein association is often accompanied by changes in receptor and ligand structure. This interplay between protein flexibility and protein-protein recognition is currently the largest obstacle both to our understanding of and to the reliable prediction of protein complexes. We performed two sets of molecular dynamics simulations for the unbound receptor and ligand structures of 17 protein complexes and applied shape-driven rigid body docking to all combinations of representative snapshots. The crossdocking of structure ensembles increased the likelihood of finding near-native solutions. The free ensembles appeared to contain multiple complementary conformations. These were in general not related to the bound structure. We suggest that protein-protein binding follows a three-step mechanism of diffusion, free conformer selection, and refolding. This model combines previously conflicting ideas and is in better agreement with the current data on interaction forces, time scales, and kinetics. The current model combines aspects from the induced fit model and the free conformer selection model, which in turn is based on the model of allosteric transitions by Jaques Monod, Jeffery Wyman and Jean-Pierre Changeux. Using extended molecular dynamics calculations we are currently investigating the dynamic properties of protein interaction surfaces in more detail. We also study the entropic costs of complex formation.
Elucidating factors governing ligand-repeptor interactions (Pak-Lee Chau)
My research aims to elucidate the factors governing ligand-receptor interactions in two model systems: (1) the interaction of small molecules with proteins (2) the interaction of small molecules with cell membranes.
Most drugs are small molecules, which interact with proteins in the human body. Using molecular dynamics simulations, we have developed unbinding methods and novel analysis procedures to unbind small ligands from protein receptors, to evaluate the free energy change of unbinding, and to define the role of water in the unbinding process. This method has been successfully applied to the retinol/serum retinol-binding protein complex and the complex formed between 5-HT_3 receptor and its agonists or antagonists. I am now extending this work to the GABA_A receptor, in collaboration with Kenji Mizuguchi (Department of Applied Mathematics and Theoretical Physics, University of Cambridge), Ian Martin (Department of Pharmacology, Aston University, Birmingham), Vasiliy Bavro (Department of Biochemistry, University of Cambridge), Nikolay Todorov (De Novo Pharmaceuticals Ltd, Cambridge) and Susan Dunn (Department of Pharmacology, University of Alberta, Canada).
A small number of drugs, the general anaesthetics, probably exert their action partly through interaction with the cell membrane. We are performing neutron scattering experiments to define the localisation of general anaesthetics in the cell membrane. The experiments are complemented by molecular dynamics simulations. This work is a collaboration with Nobuyuki Matubayasi (Institute for Chemical Research, University of Kyoto), Steven Roser (Department of Chemistry, University of Bath) and Paul Hoang (Universite de Franche-Comte, Besancon, France).
New free energy methods to analyze protein-ligand associations (L. Masgrau, A. Blondel)
The aim of this work is to analyze and predict the affinity of therapeutic molecules to propose new ligands of high affinity. The application systems are enzymes implied in the pathogenicity of parasites. For that purpose, we have developed modeling methods and programs in the laboratory. These developments were motivated was motivated by an in depth study of the association of the protomers of R67 DHFR by both experimental and theoretical approaches (see previous rapports from the "Protein Folding and Modeling" and "Structural BioInformatics" units). It is thus possible to better predict the strength of the associations with a new formalism to optimize the ensemble fluctuations during the thermodynamic integration, which allows to significantly reduce the uncertainties and to accelerate the numerical convergence. A detailed analysis of the results showed that the uncertainties were lower than 1 kcal/mol and a good agreement with the experimental results (~0.4 kcal/mol differences). The comparison with experimental data showed that it is possible to reach similar accuracy than the experiments provided that the structural relaxations are taken into account correctly.
Receptor conformation and ligand affinity (L. Masgrau, A. Blondel)
For its function, a protein may change its "shape" or conformation. These conformation changes may be local or extended. At the binding site of the ligand, they change the strength of the association. Thus, we try to identify conformations that are important for protein-ligand association for various reasons. The first one is to better understand enzymatic reactions involving steps. An other reason is to better determine the protein conformation against which it is most advantageous to design of a new drug. Hence, we studied the free energy profiles of the sugar transfer reaction of an enzyme that is essential for the pathogenicity of the causative agents of the sleeping sickness and of the Chagas disease (collaboration with Pedro Alzari, laboratory of Structural Biochemistry). Similarly, we studied the motion that an other enzyme of one of these parasites has to undergo to identify intermediate conformations offering new binding possibilities and thus allow the quest for new type of inhibitors. For these studies, we have developed powerful reaction path calculation methods allowing the treatment of mechanisms of complex geometry.
Docking and virtual screening of potential therapeutic agents (N. Duclert-Savatier, V. Stoven)
Whereas a very high accuracy can be achieved in state-of-the-art free energy calculation, these calculations are not suitable and too slow to screen the large compound data bases to find a potential binding partner for a protein with known 3D structure. This speed is offered by less accurate docking methods that characterize protein--ligand interactions empirically and use approximate rules to calculate binding free energies from molecular conformation. We employ different empirical docking strategies in combination with the aim to perform virtual screening. A first target is a subtilisin that is essential for the malaria parasite to enter the host cell. We also take part in the project coordinated by Stewart Cole, with the aim to identify lead compounds against Mycobacterium Tuberculosis. Methods developments aim at integrating results from several different docking strategies in an intelligent way (by machine learning techniques).
Keywords: Protein structure, protein function, protein dynamics, molecular recognition, sequence analysis