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QSAR study of benzofuran and indole derivatives to predict new compounds as histone lysine methyl transferase inhibitors
Kaushik Sarkar (1)
, Sraboni Ghosh (2) , Rajesh Kumar Das (3,*) (1) Department of Chemistry, University of North Bengal, Darjeeling, 734013, India
(2) Department of Chemistry, University of North Bengal, Darjeeling, 734013, India
(3) Department of Chemistry, University of North Bengal, Darjeeling, 734013, India
(*) Corresponding Author
Received: 27 Dec 2022 | Revised: 03 Feb 2023 | Accepted: 21 Feb 2023 | Published: 30 Jun 2023 | Issue Date: June 2023
Abstract
Initiation and progression of several diseases by post-translational histone modifications are considered a worldwide problem. Enhancer of Zeste Homologue 2 (EZH2), which belongs to the histone-lysine N-methyl transferase (HKMT) family, has been emphasised as a promising target for cancer therapy. It is a major challenge for the scientific community to find novel approaches to treating this disease. In this study, a series of 51 derivatives of the benzofuran and indole families, previously experimentally evaluated against HKMT, was used to develop the best model with promising anticancer activity. The multiple linear regression (MLR) method, implemented in QSARINS software, was used with a genetic algorithm for variable selection. According to QSARINS, the model with two descriptors (minHBint4 and Wlambdal.unity) was found to be the best and its parameters fit well, and its validation was well established. The applicability domain was also validated for this model. Furthermore, its robustness (R2 = 0.9328), stability (Q2LOO = 0.9212, Q2LMO = 0.9187), and good predictive power (R2ext = 0.929) were also verified. Hence, this model was assumed to have predictive HKMT anticancer activity for designing active compounds. Molecular docking was also performed to identify binding interactions, and new molecules with better predicted biological activity (pIC50) were designed. The binding energy of the three designed compounds demonstrated higher binding activity at the target receptor, followed by complex stability, determined by a 100 ns molecular dynamics simulation and binding free energy calculation. Density functional theory (DFT) and pharmacokinetic analyses also confirmed their drug-like properties. Finally, it can be declared that the proposed tools allow rapid and economical identification of potential anti-HKMT drugs (anticancer drugs) for further development.
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DOI: 10.5155/eurjchem.14.2.231-245.2413
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Funding information
University Grants Commission, New Delhi, for the project F.30-515/2020(BSR), 12.02.2020, F.D. Diary No. 9719, 23.01.2020 and University Grants Commission, New Delhi, for the NET-JRF fellowship, India.
Citations
[1]. Kaushik Sarkar, Bipasha Das, Rajesh Kumar Das
Discovery of new oxadiazolo pyridine derivatives as potent ghrelin O-acyltransferase inhibitors using molecular modeling techniques
In Silico Pharmacology 11(1), , 2023
DOI: 10.1007/s40203-023-00167-z
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