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


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.

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The authors are grateful to the organizers and participants of SAMPL5 for arranging this competition on distribution coefficients, which enabled us to test our in-house software and assess our force-fields. We also would like to thank Anthony Stone for a beautiful and succinct way of visualizing potential maps [57] that inspired us to do the same. We are also thankful to everyone else in our company (in particular Meredith Robert) for supporting our participation.

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Correspondence to Leonid Pereyaslavets.

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Ganesh Kamath, Igor Kurnikov, Boris Fain and Leonid Pereyaslavets have contributed equally to this work.

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Kamath, G., Kurnikov, I., Fain, B. et al. Prediction of cyclohexane-water distribution coefficient for SAMPL5 drug-like compounds with the QMPFF3 and ARROW polarizable force fields. J Comput Aided Mol Des 30, 977–988 (2016).

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  • QMPFF3
  • Polarizable force fields
  • Free energies
  • SAMPL5
  • GAFF