Literature DB >> 31972487

A general linear free energy relationship for predicting partition coefficients of neutral organic compounds.

Deliang Chen1, Qingyun Wang2, Yibao Li3, Yongdong Li3, Hui Zhou3, Yulan Fan4.   

Abstract

Predicting the effects of organic compounds on environments and biological systems is an important objective for environmental chemistry and human health. The logarithm (to base 10) of the n-octanoll-water partition coefficient has been widely used to predict the mentioned properties. However, the suitability of this parameter for the purpose has been questioned, since the environments relating to the properties may be quite different from that of bulk n-octanol. In this study, we used a theoretical derivation approach to develop a model for predicting the partition coefficients of solutes between water and an organic solvent that may be similar to n-octanol or quite different from it. Our model relies on solute descriptors that can be calculated based on solute structures. It was used to predict the n-octanoll-water, hexadecanel-water and chloroforml-water partition coefficients of solutes. The calculated values of the examined parameters agreed well with their experimental counterparts. The model can find application in the accurate prediction of the effects of organic compounds on environments and the physicochemical properties of organic compounds by a full in-silico approach and can provide useful guidance for improving some properties of organic compounds.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Computational chemistry; Hydrogen bonding capability; Linear free energy relationship; Partition coefficient; Physicochemical property; Quantitative structure-property relationship

Mesh:

Substances:

Year:  2020        PMID: 31972487     DOI: 10.1016/j.chemosphere.2020.125869

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  2 in total

1.  Key difference between transition state stabilization and ground state destabilization: increasing atomic charge densities before or during enzyme-substrate binding.

Authors:  Deliang Chen; Yibao Li; Xun Li; Xuechuan Hong; Xiaolin Fan; Tor Savidge
Journal:  Chem Sci       Date:  2022-06-21       Impact factor: 9.969

2.  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

  2 in total

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