Exploring Protein Kinase Conformation Using Swarm-Enhanced Sampling Molecular Dynamics
Author(s) -
Alessio Atzori,
Neil J. Bruce,
Kepa K. Burusco,
Berthold Wroblowski,
Pascal Bonnet,
Richard A. Bryce
Publication year - 2014
Publication title -
journal of chemical information and modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 160
eISSN - 1549-960X
pISSN - 1549-9596
DOI - 10.1021/ci5003334
Subject(s) - druggability , swarm behaviour , molecular dynamics , replica , biological system , computer science , protein dynamics , function (biology) , computational biology , chemistry , biology , computational chemistry , artificial intelligence , biochemistry , visual arts , gene , art , evolutionary biology
Protein plasticity, while often linked to biological function, also provides opportunities for rational design of selective and potent inhibitors of their function. The application of computational methods to the prediction of concealed protein concavities is challenging, as the motions involved can be significant and occur over long time scales. Here we introduce the swarm-enhanced sampling molecular dynamics (sesMD) method as a tool to improve sampling of conformational landscapes. In this approach, a swarm of replica simulations interact cooperatively via a set of pairwise potentials incorporating attractive and repulsive components. We apply the sesMD approach to explore the conformations of the DFG motif in the protein p38α mitogen-activated protein kinase. In contrast to multiple MD simulations, sesMD trajectories sample a range of DFG conformations, some of which map onto existing crystal structures. Simulated structures intermediate between the DFG-in and DFG-out conformations are predicted to have druggable pockets of interest for structure-based ligand design.
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