Research Article

Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole

Volume: 9 Number: 2 May 31, 2022
TR EN

Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole

Abstract

The present study contains the evaluations of lipophilicity estimation, HOMO-LUMO analysis, and electrostatic surface properties of Chlormethiazole molecule by using quantum chemical calculation techniques. All geometrical optimizations, energy and frequency calculations were carried out with six different basis sets by choosing the Hartree-Fock (HF) method and two different Density Functional Theory (DFT) functionals B3LYP and B3PW91. All calculations were repeated for the water and n-octanol phases by using SMD solvation model in order to investigate the solvent effect and also to obtain the Gibbs free energies of solvation that help to estimate partition coefficients. As a result, among the applied theoretical methods, the best agreement with the experimental logP value was obtained with the HF/6-31G(d,p) method. Also, it is concluded that the forecast performance of the computational methods decreases in the following order: HF> B3LYP> B3PW91.

Keywords

References

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Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Publication Date

May 31, 2022

Submission Date

August 4, 2021

Acceptance Date

November 24, 2021

Published in Issue

Year 2022 Volume: 9 Number: 2

APA
Serin, S., & Bayri, A. (2022). Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole. El-Cezeri, 9(2), 567-575. https://doi.org/10.31202/ecjse.978741
AMA
1.Serin S, Bayri A. Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole. El-Cezeri Journal of Science and Engineering. 2022;9(2):567-575. doi:10.31202/ecjse.978741
Chicago
Serin, Sümeyya, and Ali Bayri. 2022. “Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole”. El-Cezeri 9 (2): 567-75. https://doi.org/10.31202/ecjse.978741.
EndNote
Serin S, Bayri A (May 1, 2022) Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole. El-Cezeri 9 2 567–575.
IEEE
[1]S. Serin and A. Bayri, “Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole”, El-Cezeri Journal of Science and Engineering, vol. 9, no. 2, pp. 567–575, May 2022, doi: 10.31202/ecjse.978741.
ISNAD
Serin, Sümeyya - Bayri, Ali. “Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole”. El-Cezeri 9/2 (May 1, 2022): 567-575. https://doi.org/10.31202/ecjse.978741.
JAMA
1.Serin S, Bayri A. Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole. El-Cezeri Journal of Science and Engineering. 2022;9:567–575.
MLA
Serin, Sümeyya, and Ali Bayri. “Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole”. El-Cezeri, vol. 9, no. 2, May 2022, pp. 567-75, doi:10.31202/ecjse.978741.
Vancouver
1.Sümeyya Serin, Ali Bayri. Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole. El-Cezeri Journal of Science and Engineering. 2022 May 1;9(2):567-75. doi:10.31202/ecjse.978741
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