Dave Ritchie, INRIA Nancy Grand-Est, France

Protein Docking and 3D Ligand-Based Virtual Screening
Protein-protein interactions (PPIs) and the formation of protein-protein complexes are central to many biological processes.  Protein docking is the task of calculating the three-dimensional structure of a protein complex starting from the two individual structures of the component proteins [1].  On the other hand, virtual screening is the computational task of finding small molecules which might block or modulate specific protein-protein interactions for therapeutic purposes. Hence protein docking and virtual screening are intimately linked [2].

In the past, drug development programmes often assumed that a single drug molecule could be designed to modulate a specific protein target.  However, it is becoming increasingly apparent that small drug molecules often interact with both their intended target but also other off-target proteins as well [3].  Hence we should adopt "systems" or "network" [4] based models of diseases and drug screening.  In order to achieve this at the molecular level, we will need to develop efficient algorithms which can process, at least approximately, large networks of PPIs and potential protein-drug interactions.

In this series of talks, I will first give an overview of the current state of the art in protein docking, with particular reference to the CAPRI blind docking experiment [5, 6].  I will also describe some recent developments regarding my own "Hex" polar Fourier docking algorithm [7, 8]. I will then describe some current trends and emerging challenges in using docking techniques to model larger systems such as multi-component assemblies [9] and even to perform genome-wide docking experiments [10, 11]. I will also describe the growing use of databases and data-based approaches to help constrain and guide docking calculations [12, 13].

Finally, I will describe some recent work from my group on using Fourier-based ligand shape clustering techniques to explain how multiple diverse ligands can bind within a protein pocket [14], and to predict off-target interactions without the computational expense of performing all-against-all protein-ligand docking.

References

[1] I. Halperin, B. Ma, H.J. Wolfson, R. Nussinov (2002),
Principles of docking: An overview of search algorithms and a guide to scoring functions.
Proteins: Struct. Func. Genet., 47:409-443.

[2] S. Grosdidier, M. Totrov, J. Fernandez-Recio (2009),
Computer applications for prediction of protein-protein interactions and rational drug design.
Adv. App. Bioinf. Chem., 2: 101-123

[3] A. L. Hopkins (2008),
Network pharmacology: the next paradigm in drug discovery.
Nature Chem. Biol., 4:682-690

[4] A. Pujol, R. Mosca, J. Farres, P. Aloy (2010),
Unveiling the role of network and systems biology in drug discovery.
Trends Pharm. Sci., 31:115-123.

[5] M. Lensink, S. Wodak (2010),
Docking and scoring protein interactions: CAPRI 2009.
Proteins: Struct. Func. Genet., 78:3073-3084.

[6] J. Janin (2010)
Protein-Protein docking tested in blind predictions: the CAPRI experiment.
Mol. BioSyst., 6:2351-2362.

[7] D.W. Ritchie, G.J.L. Kemp (2000),
Protein Docking Using Spherical Polar Fourier Correlations.
Proteins: Struct. Func. Genet., 39:178-194.

[8] D.W. Ritchie, V. Venkatraman (2010),
Ultra-Fast {FFT} Protein Docking On Graphics Processors.
Bioinformatics, 26: 2398--2405.

[9] F. Alber, F, Forster, D. Korkin, M. Topf, A. Sail (2008)
Integrating diverse data for structure determination of macromolecular assemblies.
Ann. Rev. Biochem., 77:443-77.

[10] P.J. Kundrotas, Z. Zhu, I.A. Vakser (2010),
GWIDD: Genome-wide protein docking database.
Nucl. Acids. Res. 38(Suppl 1):D513-D517.

[11] M. N. Wass, G. Fuentes, F. Pazos, A. Valencia (2011),
Towards the prediction of protein interaction partners using physical docking.
Mol. Sys. Biol., 7:1-8.

[12]
A.D.J. van Dijk, R. Boelens, A.M.J.J. Bonvin (2005),
Data-driven docking for the study of biomolecular complexes.
FEBS J., 272:293-312.

[13] D.W. Ritchie (2008),
Recent progress and future directions in protein-protein docking.
Curr. Prot. Pep. Sci., 9:1-15.

[14] V.I. Perez-Nueno, D.W. Ritchie, O. Rabal, R. Pascual, J.I. Borrell, J. Teixido (2008),
Comparison of ligand-based and receptor-based virtual screening of HIV entry inhibitors
for the CXCR4 and CCR5 receptors using 3D ligand shape matching and ligand-receptor docking.
J. Chem. Inf. Model., 48:509-533.