ArticleJournal of computer-aided molecular design2020
SAMPL6 blind predictions of water-octanol partition coefficients using nonequilibrium alchemical approaches.
Article in Journal of computer-aided molecular design, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Development and test of highly accurate endpoint free energy methods. 2: Prediction of logarithm of n-octanol-water partition coefficient (logP) for druglike molecules using MM-PBSA method.Journal of computational chemistry · 2023Article
- 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
- Non-equilibrium approach for binding free energies in cyclodextrins in SAMPL7: force fields and software.Journal of computer-aided molecular design · 2021Article
- Virtual Double-System Single-Box: A Nonequilibrium Alchemical Technique for Absolute Binding Free Energy Calculations: Application to Ligands of the SARS-CoV-2 Main Protease.Journal of chemical theory and computation · 2020Article
- Enhanced Jarzynski free energy calculations using weighted ensemble.The Journal of chemical physics · 2020Article
- A remark on the efficiency of the double-system/single-box nonequilibrium approach in the SAMPL6 SAMPLing challenge.Journal of computer-aided molecular design · 2020Article
- SAMPL6 Octanol-water partition coefficients from alchemical free energy calculations with MBIS atomic charges.Journal of computer-aided molecular design · 2020Article
- Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge.Journal of computer-aided molecular design · 2020Article
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Authors and funding
2 authors.
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Abstract
In this paper, we compute, by means of a non equilibrium alchemical technique, the water-octanol partition coefficients (LogP) for a series of drug-like compounds in the context of the SAMPL6 challenge initiative. Our blind predictions are based on three of the most popular non-polarizable force fields, CGenFF, GAFF2, and OPLS-AA and are critically compared to other MD-based predictions produced using free energy perturbation or thermodynamic integration approaches with stratification. The proposed non-equilibrium method emerges has a reliable tool for LogP prediction, systematically being among the top performing submissions in all force field classes for at least two among the various indicators such as the Pearson or the Kendall correlation coefficients or the mean unsigned error. Contrarily to the widespread equilibrium approaches, that yielded apparently very disparate results in the SAMPL6 challenge, all our independent prediction sets, irrespective of the adopted force field and of the adopted estimate (unidirectional or bidirectional) are, mutually, from moderately to strongly correlated.
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