Modeling and selection of flexible proteins for structure-based drug design: backbone and side chain movements in p38...

Receptor rearrangement upon ligand binding (induced fit) is a major stumbling block in docking and virtual screening. Even though numerous studies have stressed the importance of including protein flexibility in ligand docking, currently available methods provide only a partial solution to the problem. Most of these methods, being computer intensive, are often impractical to use in actual drug discovery settings. We had earlier shown that ligand-induced receptor side-chain conformational changes could be modeled statistically using data on known receptor-ligand complexes. In this paper, we show that a similar approach can be used to model more complex changes like backbone flips and loop movements. We have used p38 MAPK as a test case and have shown that a few simple structural features of ligands are sufficient to predict the induced variation in receptor conformations. Rigorous validation, both by internal resampling methods and on an external test set, corroborates this finding and demonstrates the robustness of the models. We have also compared our results with those from an earlier molecular dynamics simulation study on DFG loop conformations of p38 MAPK, and found that the results matched in the two cases. Our statistical approach enables one to predict the final ligand-induced conformation of the active site of a protein, based on a few ligand properties, prior to docking the ligand. We can do this without having to trace the step-by-step process by which this state is arrived at (as in molecular dynamics simulations), thereby drastically reducing computational effort.