In silico design of novel Pyrazole derivatives containing thiourea skeleton as anti-cancer agents using: 3D QSAR, Drug-Likeness studies, ADMET prediction and molecular docking. (2021)

• Record Type: Journal Article
• Authors: El Mchichi, L.; El Aissouq, A.; Kasmi, R.; Belhassan, A.; El-Mernissi, R.; Ouammou, A.; Lakhlifi, T.; Bouachrine, M.
• Is Part Of: Materials today. Volume 45:Part 8(2021)
• Page Start: 7661
• Page End: 7674
• Publication Date: 2021
• Subjects: Pyrazole -- 3D-QSAR -- CoMFA -- CoMSIA -- EGFR kinase inhibitors; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2021.03.152
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: A forty-two compounds series of potential epidermal growth factor receptor kinase inhibitors of Pyrazole derivatives containing thiourea analogs have been subjected to 3D-QSAR (3-Dimensional Quantitative Structural-Activity Relationship) studies using CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis). The training set and the test set of pyrazole derivatives have been used for the generation and validation of QSAR model, respectively. Dataset alignment has been performed using the lowest energy conformer of the most active compound. The best-generated CoMFA and CoMSIA models exhibit conventional determination coefficients R 2 of 0.982 and 0.980 as well as the Leave One Out cross validation determination coefficients Q 2 of 0.734 and 0.801, respectively. Moreover, the predictive ability of those models was evaluated by the external validation using a test set of five compounds with predicted determination coefficients R 2 test of 0.932 and 0.846, respectively. Based on those satisfactory results, ten new compounds have been designed and predicted by in silico Drug likeness and ADMET method. In addition, molecular docking studies were carried out to explore the binding interactions of the selected compounds with the enzyme. This study could expand the understanding of pyrazole derivatives as anti-cancer agent and would be of great help in lead optimization for early drug discovery of highly potent anticancer activity.