QSAR Study of Anthranilic Acid Sulfonamides as Inhibitors of Methionine Aminopeptidase-2 using different chemometrics tools | ||
| Trends in Pharmaceutical Sciences and Technologies | ||
| مقاله 2، دوره 9، شماره 1، بهار 2023، صفحه 15-26 اصل مقاله (528.56 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.30476/tips.2023.97427.1176 | ||
| نویسندگان | ||
| Pooria Zare1، 2؛ Maryam Sabet3؛ Razieh Sabet* 4 | ||
| 1Department of Pathology, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran | ||
| 2Department of Master in Public Health, Faculty of Pharmacy, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran | ||
| 3Department of Computer Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran. | ||
| 4Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran | ||
| چکیده | ||
| Quantitative structure activity relationships (QSAR) studies, as one of the most important areas in chemometrics, play a fundamental role in predicting the biological activity of new compounds and identifying ligand-receptor interactions. Quantitative relationships between molecular structure and methionine aminopeptidase-2 inhibitory activity of a series of anthranilic acid sulfonamides derivatives were discovered by different chemometrics tools including factor analysis based multiple linear regressions (FA-MLR), principale component regression analysis (PCRA) and genetic algorithm-partial least squares GA-PLS. The FA-MLR describes the effect of geometrical and quantum indices on enzyme inhibition activity of the studied molecules. The quality of PCRA equation is better than those derived from FA-MLR. GA-PLS analysis indicated that the topological (IC4 and MPC06), constitutional (nf) and geometrical (G (N..S)) parameters were the most significant parameters on methionine aminopeptidase-2 inhibitory activity. A comparison between the different statistical methods employed revealed that GA-PLS represented superior results and it could explain and predict 85% and 77% of variances in the pIC50 data, respectively. | ||
| کلیدواژهها | ||
| Anthranilic acid sulfonamides؛ MetAP-2 inhibitors؛ QSAR؛ GA-PLS؛ PCRA؛ FA-MLR | ||
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