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Predicting octanol/water partition coefficients using molecular simulation for the SAMPL7 challenge: comparing the use of neat and water saturated 1-octanol.
Sabatino, Spencer J; Paluch, Andrew S.
Afiliación
  • Sabatino SJ; Department of Chemical, Paper, and Biomedical Engineering, Miami University, Oxford, OH, 45056, USA.
  • Paluch AS; Department of Chemical, Paper, and Biomedical Engineering, Miami University, Oxford, OH, 45056, USA. PaluchAS@MiamiOH.edu.
J Comput Aided Mol Des ; 35(10): 1009-1024, 2021 10.
Article en En | MEDLINE | ID: mdl-34495430
Blind predictions of octanol/water partition coefficients at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. The octanol/water partition coefficients were predicted using solvation free energies computed using molecular dynamics simulations, wherein we considered the use of both pure and water-saturated 1-octanol to model the octanol-rich phase. Water and 1-octanol were modeled using TIP4P and TrAPPE-UA, respectively, which have been shown to well reproduce the experimental mutual solubility, and the solutes were modeled using GAFF. After the close of the SAMPL7 challenge, we additionally made predictions using TIP4P/2005 water. We found that the predictions were sensitive to the choice of water force field. However, the effect of water in the octanol-rich phase was found to be even more significant and non-negligible. The effect of inclusion of water was additionally sensitive to the chemical structure of the solute.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Termodinámica / Agua / 1-Octanol / Simulación de Dinámica Molecular / Modelos Químicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Comput Aided Mol Des Asunto de la revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Termodinámica / Agua / 1-Octanol / Simulación de Dinámica Molecular / Modelos Químicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Comput Aided Mol Des Asunto de la revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Año: 2021 Tipo del documento: Article