Abstract
Protein–protein interfaces represent challenging but very promising targets to discover novel drugs with exquisite specificity profiles. We herewith chart for the first time all biologically relevant protein–protein interfaces of known X-ray structure and detect potentially druggable cavities at and nearby the interface. These cavities are then converted in simple 3D pharmacophore queries for identifying potential modulators (inhibitors, stabilizers) of druggable interfaces.
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References
Scott DE, Bayly AR, Abell C, Skidmore J (2016) Small molecules, big targets: drug discovery faces the protein-protein interaction challenge. Nat Rev Drug Discov 15:533–550
Arkin MR, Tang Y, Wells JA (2014) Small-molecule inhibitors of protein-protein interactions: progressing toward the reality. Chem Biol 21:1102–1114
Thiel P, Kaiser M, Ottmann C (2012) Small-molecule stabilization of protein-protein interactions: an underestimated concept in drug discovery? Angew Chem Int Ed Engl 51:2012–2018
Fischer G, Rossmann M, Hyvonen M (2015) Alternative modulation of protein-protein interactions by small molecules. Curr Opin Biotechnol 35:78–85
Kuenemann MA, Sperandio O, Labbe CM, Lagorce D, Miteva MA, Villoutreix BO (2015) In silico design of low molecular weight protein-protein interaction inhibitors: overall concept and recent advances. Prog Biophys Mol Biol 119:20–32
Marcou G, Rognan D (2007) Optimizing fragment and scaffold docking by use of molecular interaction fingerprints. J Chem Inf Model 47:195–207
Desaphy J, Raimbaud E, Ducrot P, Rognan D (2013) Encoding protein-ligand interaction patterns in fingerprints and graphs. J Chem Inf Model 53:623–637
Da Silva F, Desaphy J, Bret G, Rognan D (2015) IChemPIC: a random forest classifier of biological and crystallographic protein-protein interfaces. J Chem Inf Model 55:2005–2014
Desaphy J, Azdimousa K, Kellenberger E, Rognan D (2012) Comparison and druggability prediction of protein-ligand binding sites from pharmacophore-annotated cavity shapes. J Chem Inf Model 52:2287–2299
Bietz S, Urbaczek S, Schulz B, Rarey M (2014) Protoss: a holistic approach to predict tautomers and protonation states in protein-ligand complexes. J Cheminform 6:12
Acknowledgments
This work was supported by a PhD grant from CNRS (Institut de Chimie) and the Alsace Region to FSD. We thank Prof. M. Rarey (University of Hamburg, Germany) for providing an executable version of ProToss. The High-performance Computing Center (University of Strasbourg, France) and the Calculation Center of the IN2P3 (CNRS, Villeurbanne, France) are acknowledged for allocation of computing time and excellent support.
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Da Silva, F., Rognan, D. (2018). Structure-Based Detection of Orthosteric and Allosteric Pockets at Protein–Protein Interfaces. In: Brown, J. (eds) Computational Chemogenomics. Methods in Molecular Biology, vol 1825. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8639-2_8
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DOI: https://doi.org/10.1007/978-1-4939-8639-2_8
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