Literature DB >> 30694667

Assessment of GAFF2 and OPLS-AA General Force Fields in Combination with the Water Models TIP3P, SPCE, and OPC3 for the Solvation Free Energy of Druglike Organic Molecules.

Dario Vassetti1, Marco Pagliai1, Piero Procacci1.   

Abstract

Molecular dynamics simulations have been performed to compute the solvation free energy and the octanol/water partition coefficients for a challenging set of selected organic molecules, characterized by the simultaneous presence of functional groups coarsely spanning a large portion of the chemical space in druglike compounds and, in many cases, by a complex conformational landscape (2-propoxyethanol, acetylsalicylic acid, cyclohexanamine, dialifor, ketoprofen, nitralin, profluralin, terbacil). OPLS-AA and GAFF2 parametrizations of the organic molecules and of 1-octanol have been done via the Web-based automatic parameter generators, LigParGen [ Dodda et al. Nucl. Acids Res. 2017 , 121 , 3864 ] and PrimaDORAC [ Procacci J. Chem. Inf. Model. 2017 , 57 , 1240 ], respectively. For the water solvent, three popular three-point site models, TIP3P, SPCE, and OPC3, were tested. Solvation free energies in water and 1-octanol are evaluated using a recently developed nonequilibrium alchemical technology [ Procacci et al. J. Chem. Theory Comput. 2014 , 10 , 2813 ]. Extensive and accurate simulations, including all possible combinations of organic molecule, solvent, and solvent model, are allowed to assess the accuracy with regard to solvation free energies of the latest release of two widespread force fields, OPLS and GAFF. The collected data are relevant in the evaluation of the predictive power of these classical force fields (and of the related support software for automated parametrization) with regard to binding free energies in a drug-receptor system for industrial applications.

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Year:  2019        PMID: 30694667     DOI: 10.1021/acs.jctc.8b01039

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  20 in total

1.  Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge.

Authors:  Mehtap Işık; Teresa Danielle Bergazin; Thomas Fox; Andrea Rizzi; John D Chodera; David L Mobley
Journal:  J Comput Aided Mol Des       Date:  2020-02-27       Impact factor: 3.686

2.  Deciphering the mechanistic effects of eIF4E phosphorylation on mRNA-cap recognition.

Authors:  Dilraj Lama; Chandra S Verma
Journal:  Protein Sci       Date:  2019-12-16       Impact factor: 6.725

3.  SAMPL6 blind predictions of water-octanol partition coefficients using nonequilibrium alchemical approaches.

Authors:  Piero Procacci; Guido Guarnieri
Journal:  J Comput Aided Mol Des       Date:  2019-10-17       Impact factor: 3.686

4.  Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure.

Authors:  Xiao Liu; Lei Zheng; Chu Qin; John Z H Zhang; Zhaoxi Sun
Journal:  J Comput Aided Mol Des       Date:  2022-09-22       Impact factor: 4.179

5.  FFParam: Standalone package for CHARMM additive and Drude polarizable force field parametrization of small molecules.

Authors:  Anmol Kumar; Ozge Yoluk; Alexander D MacKerell
Journal:  J Comput Chem       Date:  2019-12-30       Impact factor: 3.376

6.  Structure-based identification of inhibitors disrupting the CD2-CD58 interactions.

Authors:  Neha Tripathi; Laurence Leherte; Daniel P Vercauteren; Adèle D Laurent
Journal:  J Comput Aided Mol Des       Date:  2021-02-03       Impact factor: 3.686

7.  Predicting partition coefficients for the SAMPL7 physical property challenge using the ClassicalGSG method.

Authors:  Nazanin Donyapour; Alex Dickson
Journal:  J Comput Aided Mol Des       Date:  2021-06-28       Impact factor: 4.179

8.  ClassicalGSG: Prediction of log P using classical molecular force fields and geometric scattering for graphs.

Authors:  Nazanin Donyapour; Matthew Hirn; Alex Dickson
Journal:  J Comput Chem       Date:  2021-03-30       Impact factor: 3.672

9.  SAMPL7 blind predictions using nonequilibrium alchemical approaches.

Authors:  Piero Procacci; Guido Guarnieri
Journal:  J Comput Aided Mol Des       Date:  2021-01-04       Impact factor: 3.686

10.  Evaluation of log P, pKa, and log D predictions from the SAMPL7 blind challenge.

Authors:  Teresa Danielle Bergazin; Nicolas Tielker; Yingying Zhang; Junjun Mao; M R Gunner; Karol Francisco; Carlo Ballatore; Stefan M Kast; David L Mobley
Journal:  J Comput Aided Mol Des       Date:  2021-06-24       Impact factor: 3.686

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