TR
EN
Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole
Öz
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.
Anahtar Kelimeler
Kaynakça
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Ayrıntılar
Birincil Dil
İngilizce
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
31 Mayıs 2022
Gönderilme Tarihi
4 Ağustos 2021
Kabul Tarihi
24 Kasım 2021
Yayımlandığı Sayı
Yıl 2022 Cilt: 9 Sayı: 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. ECJSE. 2022;9(2):567-575. doi:10.31202/ecjse.978741
Chicago
Serin, Sümeyya, ve 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 (01 Mayıs 2022) Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole. El-Cezeri 9 2 567–575.
IEEE
[1]S. Serin ve A. Bayri, “Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole”, ECJSE, c. 9, sy 2, ss. 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 (01 Mayıs 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. ECJSE. 2022;9:567–575.
MLA
Serin, Sümeyya, ve Ali Bayri. “Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole”. El-Cezeri, c. 9, sy 2, Mayıs 2022, ss. 567-75, doi:10.31202/ecjse.978741.
Vancouver
1.Sümeyya Serin, Ali Bayri. Benchmark Study of Computational Methods for Predicting Partition Coefficient of Chlormethiazole. ECJSE. 01 Mayıs 2022;9(2):567-75. doi:10.31202/ecjse.978741


