Benchmark of different charges for prediction of the partitioning coefficient through the hydrophilic/lipophilic index View Full Text


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Article Info

DATE

2018-06

AUTHORS

Oksana Fizer, Maksym Fizer, Vasyl Sidey, Yaroslav Studenyak, Ruslan Mariychuk

ABSTRACT

A few different theoretical methods for assigning the partial atomic charges were benchmarked for calculation of the hydrophilic/lipophilic index (HLI). The coefficients were selected to produce the best correlation of the HLI values with the experimental octanol-water partition. Different parameters were checked in calculations of partial charges to get the best performance of the HLI values obtained. Thus, four partitioning schemes (Coulson, Mulliken, Merz-Kollman, Ford-Wang) were benchmarked for calculations of atomic charges with six semiempirical methods (AM1, PM3, RM1, PM6, PM6-D3H4, PM7). Moreover, five distinct types of partial atomic charges (Mulliken, Hirshfeld, Löwdin, CHELPG, NPA), obtained at the Hartree-Fock and DFT levels of theory with three basis sets, were tested for their ability to produce the HLI values with the best correlation to experimental logP coefficients of 50 mono-charged organic anions. In the case of the semiempirical methods, the best correlation between the HLI and logP values (the correlation coefficient r = 0.9216) was obtained with the AM1 Ford-Wang parametric electrostatic potential charges. The Mulliken and Coulson charges calculated with the PM7 method can be used as an alternative to AM1, with the r values of 0.9107 and 0.8984, respectively. In the case of the DFT, the PBE/def2-TZVP natural population analysis charges produce the best correlation (r = 0.9220). Nevertheless, in spite of a marginally lower performance (r = 0.9159), the NPA charges computed at the PBE/def2-SVP level are more robust and can be regarded as the optimum choice for calculating the HLI values. Graphical abstract The hydrophilic/lipophilic index (HLI). More... »

PAGES

141

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00894-018-3692-x

DOI

http://dx.doi.org/10.1007/s00894-018-3692-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104331469

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29855716


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