Ensemble-Based Docking Using Biased Molecular Dynamics

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• 作者：Arthur J. Campbell ; Michelle L. Lamb ; Diane Joseph-McCarthy
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2014
• 出版时间：July 28, 2014
• 年：2014
• 卷：54
• 期：7
• 页码：2127-2138
• 全文大小：794K
• ISSN：1549-960X

文摘

Proteins are dynamic molecules, and understanding their movements, especially as they relate to molecular recognition and protein鈥搇igand interactions, poses a significant challenge to structure-based drug discovery. In most instances, protein flexibility is underrepresented in computer-aided drug design due to uncertainties on how it should be accurately modeled as well as the computational cost associated with attempting to incorporate flexibility in the calculations. One approach that aims to address these issues is ensemble-based docking. With this technique, ligands are docked to an ensemble of rigid protein conformations. Molecular dynamics (MD) simulations can be used to generate the ensemble of protein conformations for the subsequent docking. Here we present a novel approach that uses biased-MD simulations to generate the docking ensemble. The MD simulations are biased toward an initial protein鈥搇igand X-ray complex structure. The biasing maintains some of the original crystallographic pocket-ligand information and thereby enhances sampling of the more relevant conformational space of the protein. Resulting trajectories are clustered to select a representative set of protein conformations, and ligands are docked to that reduced set of conformations. Cross-docking to this ensemble and then selecting the lowest scoring pose enables reliable identification of the correct binding mode. Various levels of biasing are investigated, and the method is validated for cyclin-dependent kinase 2 and factor Xa.