Prediction of cyclohexane-water distribution coefficient for SAMPL5 drug-like compounds with the QMPFF3 and ARROW polarizable force fields

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• 作者：Ganesh Kamath ; Igor Kurnikov ; Boris Fain…
• 关键词：QMPFF3 ; ARROW ; Polarizable force fields ; Free energies ; SAMPL5 ; GAFF
• 刊名：Journal of Computer-Aided Molecular Design
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：30
• 期：11
• 页码：977-988
• 全文大小：803KB
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Physical Chemistry; Computer Applications in Chemistry; Animal Anatomy / Morphology / Histology;
• 出版者：Springer International Publishing
• ISSN：1573-4951
• 卷排序：30

文摘

We present the performance of blind predictions of water—cyclohexane distribution coefficients for 53 drug-like compounds in the SAMPL5 challenge by three methods currently in use within our group. Two of them utilize QMPFF3 and ARROW, polarizable force-fields of varying complexity, and the third uses the General Amber Force-Field (GAFF). The polarizable FF’s are implemented in an in-house MD package, Arbalest. We find that when we had time to parametrize the functional groups with care (batch 0), the polarizable force-fields outperformed the non-polarizable one. Conversely, on the full set of 53 compounds, GAFF performed better than both QMPFF3 and ARROW. We also describe the torsion-restrain method we used to improve sampling of molecular conformational space and thus the overall accuracy of prediction. The SAMPL5 challenge highlighted several drawbacks of our force-fields, such as our significant systematic over-estimation of hydrophobic interactions, specifically for alkanes and aromatic rings.