ArticleJournal of computer-aided molecular design2016
Prediction of cyclohexane-water distribution coefficients for the SAMPL5 data set using molecular dynamics simulations with the OPLS-AA force field.
Article in Journal of computer-aided molecular design, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- How Long Is Long Enough? Extrapolation of Machine-Learning Interatomic Potentials for Oligomeric and Polymeric Systems.Journal of chemical theory and computation · 2026Article
- Exploring the Inhibitory Effects of Fucosylated Chondroitin Sulfate (FCS) Oligosaccharide Isolated fromMarine drugs · 2025Article
- Advancing Rare-Earth Separation by Machine Learning.JACS Au · 2022Article
- Development and Benchmarking of Open Force Field v1.0.0-the Parsley Small-Molecule Force Field.Journal of chemical theory and computation · 2021Article
- Precise force-field-based calculations of octanol-water partition coefficients for the SAMPL7 molecules.Journal of computer-aided molecular design · 2021Article
- SAMPL7 blind challenge: quantum-mechanical prediction of partition coefficients and acid dissociation constants for small drug-like molecules.Journal of computer-aided molecular design · 2021Article
- Prediction of octanol-water partition coefficients for the SAMPL6-Journal of computer-aided molecular design · 2020Article
- Escaping Atom Types in Force Fields Using Direct Chemical Perception.Journal of chemical theory and computation · 2018Article
- SAMPL6: calculation of macroscopic pKJournal of computer-aided molecular design · 2018Article
- Ligandbook: an online repository for small and drug-like molecule force field parameters.Bioinformatics (Oxford, England) · 2017Article
- Blind prediction of cyclohexane-water distribution coefficients from the SAMPL5 challenge.Journal of computer-aided molecular design · 2016Article
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3 authors.
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Abstract
All-atom molecular dynamics simulations were used to predict water-cyclohexane distribution coefficients [Formula: see text] of a range of small molecules as part of the SAMPL5 blind prediction challenge. Molecules were parameterized with the transferable all-atom OPLS-AA force field, which required the derivation of new parameters for sulfamides and heterocycles and validation of cyclohexane parameters as a solvent. The distribution coefficient was calculated from the solvation free energies of the compound in water and cyclohexane. Absolute solvation free energies were computed by an established protocol using windowed alchemical free energy perturbation with thermodynamic integration. This protocol resulted in an overall root mean square error in [Formula: see text] of almost 4 log units and an overall signed error of -3 compared to experimental data. There was no substantial overall difference in accuracy between simulating in NVT and NPT ensembles. The signed error suggests a systematic error but the experimental [Formula: see text] data on their own are insufficient to uncover the source of this error. Preliminary work suggests that the major source of error lies in the hydration free energy calculations.
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