Multi-phase Boltzmann weighting: accounting for local inhomogeneity in molecular simulations of water–octanol partition coefficients in the SAMPL6 challenge-Reference-Cited by-同舟云学术

Multi-phase Boltzmann weighting: accounting for local inhomogeneity in molecular simulations of water–octanol partition coefficients in the SAMPL6 challenge

Published:2020-02-14 Issue:5 Volume:34 Page:471-483
ISSN:0920-654X
Container-title:Journal of Computer-Aided Molecular Design
language:en
Short-container-title:J Comput Aided Mol Des

Author:

Krämer Andreas^ORCID,Hudson Phillip S.,Jones Michael R.,Brooks Bernard R.

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,Computer Science Applications,Drug Discovery

Link

http://link.springer.com/content/pdf/10.1007/s10822-020-00285-2.pdf

Reference82 articles.

1. Sangster J (1997) Octanol–water partition coefficients: fundamentals and physical chemistry. Eur J Med Chem 32(11):842. https://doi.org/10.1016/s0223-5234(97)82764-x

2. Bannan CC, Burley KH, Chiu M, Shirts MR, Gilson MK, Mobley DL (2016) Blind prediction of cyclohexane–water distribution coefficients from the SAMPL5 challenge. J Comput Aided Mol Des 30(11):927–944

3. Guthrie JP (2009) A blind challenge for computational solvation free energies: introduction and overview. J Phys Chem B 113(14):4501–4507. https://doi.org/10.1021/jp806724u

4. Geballe MT, Skillman AG, Nicholls A, Guthrie JP, Taylor PJ (2010) The SAMPL2 blind prediction challenge: introduction and overview. J Comput Aided Mol Des 24(4):259–279. https://doi.org/10.1007/s10822-010-9350-8

5. Muddana HS, Daniel Varnado C, Bielawski CW, Urbach AR, Isaacs L, Geballe MT, Gilson MK (2012) Blind prediction of host–guest binding affinities: a new SAMPL3 challenge. J Comput Aided Mol Des 26(5):475–487. https://doi.org/10.1007/s10822-012-9554-1

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Obtaining QM/MM binding free energies in the SAMPL8 drugs of abuse challenge: indirect approaches;Journal of Computer-Aided Molecular Design;2022-04

2. Importance of Physicochemical and Physical Properties for Toxicological Risk Assessment;Regulatory Toxicology;2021

3. Importance of Physicochemical and Physical Properties for Toxicological Risk Assessment;Regulatory Toxicology;2021

4. Membrane permeability of small molecules from unbiased molecular dynamics simulations;The Journal of Chemical Physics;2020-09-28

5. Assessing the accuracy of octanol–water partition coefficient predictions in the SAMPL6 Part II log P Challenge;Journal of Computer-Aided Molecular Design;2020-02-27