Events 8th International Electronic Conference on Medicinal Chemistry

Event submissions

Published

10.3390/ECMC2022-13418 (registering DOI)

This submission belongs to the session S4. Small molecules as drug candidates of the event 8th International Electronic Conference on Medicinal Chemistry

Published date

01 Nov, 2022

Academic Editor

Alfredo Berzal-Herranz

Citation

Mouad Mouhsin, Mustapha OUBENALI, Samir CHTITA, Mohamed MBARKI, Ahmed GAMOUH, 2D-Quantitative structure-activity relationship (QSAR) modeling of 1,3,4-thiadiazole derivatives as antiproliferative agents, in Proceedings of 8th International Electronic Conference on Medicinal Chemistry, 1 November–30 November 2022, MDPI: Basel, Switzerland, doi: 10.3390/ECMC2022-13418

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2D-Quantitative structure-activity relationship (QSAR) modeling of 1,3,4-thiadiazole derivatives as antiproliferative agents

Mouad Mouhsin ¹

Mustapha OUBENALI ¹

Samir CHTITA ²

Mohamed MBARKI ¹

Ahmed GAMOUH ¹

1. Team of ACCNE - Laboratory of Engineering in Chemistry and Physics of Matter, Faculty of Science and Technologies, Beni Mellal, Morocco.

2. Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Sidi Othman, Box 7955, Casablanca, Morocco

Abstract

This study was aimed at building a robust quantitative structure–activity relationship
(QSAR) to predict the anti-proliferate activity of 1,3,4-thiadiazole derivatives against the A549
lung cancer cell lines. The semi-empirical PM7 parametrization approach was used to optimize
the complete set of 1,3,4-thiadiazole derivatives and various classes of molecular descriptors
have been calculated. We built models using Fisher score and the best subset selection for
feature selection, and the final model was developed using the multiple linear regression
technique, all in accordance with the rigorous Organization for Economic Co-operation and
Development (OECD) requirements. Furthermore, various internationally agreed severe
validation parameters were used to validate the model. Overall, our established model for quick
prediction should be relevant to new, untested, or not yet produced compounds that fall within
the applicability domain (AD) of the model. The drug-likeness properties of the 10 compounds
with the greatest activity value were also calculated using Lipinski&#39;s rule properties.
Keywords: QSAR, Thiadiazole derivatives, A549, PM7, OECD

Keywords

QSAR

Thiadiazole derivatives

A549

PM7

OECD

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