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J Chem Theory Comput. 2016 Aug 9;12(8):4100-13. doi: 10.1021/acs.jctc.6b00101. Epub 2016 Jul 25.

Perturbation Approaches for Exploring Protein Binding Site Flexibility to Predict Transient Binding Pockets.

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Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies , 69118 Heidelberg, Germany.
Global Computational Chemistry, Merck KGaA , 64293 Darmstadt, Germany.
Zentrum für Molekulare Biologie, DKFZ-ZMBH Alliance, Heidelberg University , 69120 Heidelberg, Germany.
Interdisciplinary Center for Scientific Computing, Heidelberg University , 69120 Heidelberg, Germany.


Simulations of the long-time scale motions of a ligand binding pocket in a protein may open up new perspectives for the design of compounds with steric or chemical properties differing from those of known binders. However, slow motions of proteins are difficult to access using standard molecular dynamics (MD) simulations and are thus usually neglected in computational drug design. Here, we introduce two nonequilibrium MD approaches to identify conformational changes of a binding site and detect transient pockets associated with these motions. The methods proposed are based on the rotamerically induced perturbation (RIP) MD approach, which employs perturbation of side-chain torsional motion for initiating large-scale protein movement. The first approach, Langevin-RIP (L-RIP), entails a series of short Langevin MD simulations, each starting with perturbation of one of the side-chains lining the binding site of interest. L-RIP provides extensive sampling of conformational changes of the binding site. In less than 1 ns of MD simulation with L-RIP, we observed distortions of the α-helix in the ATP binding site of HSP90 and flipping of the DFG loop in Src kinase. In the second approach, RIPlig, a perturbation is applied to a pseudoligand placed in different parts of a binding pocket, which enables flexible regions of the binding site to be identified in a small number of 10 ps MD simulations. The methods were evaluated for four test proteins displaying different types and degrees of binding site flexibility. Both methods reveal all transient pocket regions in less than a total of 10 ns of simulations, even though many of these regions remained closed in 100 ns conventional MD. The proposed methods provide computationally efficient tools to explore binding site flexibility and can aid in the functional characterization of protein pockets, and the identification of transient pockets for ligand design.

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