

Antiproliferative potential, quantitative structure-activity relationship, cheminformatic and molecular docking analysis of quinoline and benzofuran derivatives
Praveen Kumar (1,*)







(1) Department of Biochemistry, Kuvempu University, Jnana Sahyadri, Shimoga, Karnataka, 577451, India
(2) Center of Excellence in Molecular Biology and Regenerative Medicine Laboratory, Department of Biochemistry, Jagadguru Sri Shivarathreeshwara Medical College, Jagadguru Sri Shivarathreeshwara Academy of Higher Education and Research, Mysuru, Karnataka, 570015, India
(3) Department of Pharmaceutical Chemistry, Kuvempu University Post Graduate Centre, Kadur, Karnataka-577548, India
(4) Department of Pharmaceutical Chemistry, Kuvempu University Post Graduate Centre, Kadur, Karnataka-577548, India
(5) Center of Excellence in Molecular Biology and Regenerative Medicine Laboratory, Department of Biochemistry, Jagadguru Sri Shivarathreeshwara Medical College, Jagadguru Sri Shivarathreeshwara Academy of Higher Education and Research, Mysuru, Karnataka, 570015, India
(6) Department of Biotechnology, Kuvempu University, Jnana Sahyadri, Shimoga, Karnataka, 577451, India
(7) Department of Biochemistry, Kuvempu University, Jnana Sahyadri, Shimoga, Karnataka, 577451, India
(*) Corresponding Author
Received: 10 Jul 2020 | Revised: 25 Aug 2020 | Accepted: 27 Aug 2020 | Published: 30 Sep 2020 | Issue Date: September 2020
Abstract
Quinoline and benzofuran moieties are commonly used for the synthesis of therapeutically beneficial molecules and drugs since they possess a wide range of pharmacological activities including potent anticancer activity as compared to other heterocyclic compounds. Many of well-known antimalarial, antimicrobial, anti-helminthic, analgesic, anti-inflammatory, antiprotozoal, and antitumor compounds contain quinoline/benzofuran skeleton. The aim of this study was to analyze ten new quinoline and eighteen benzofuran derivatives for carcinoma cell line growth inhibition and to predict possible interactions with the target. The anticancer activity of these compounds against colon cancer (HCT-116) and triple-negative breast cancer (MDA-MB-468) cell lines was determined and performed molecular docking to predict the possible interactions. Among ten quinoline derivatives, Q1, Q4, Q6, Q9, and Q10 were found to be the most potent against HCT-116 and MDA-MB-468 with IC50 values ranging from 6.2-99.6 and 2.7-23.6 μM, respectively. Using the IC50 values, a model equation with quantitative structure activity relationship (QSAR) was generated with their descriptors such as HBA1, HBA2, kappa (1, 2 and 3), Balaban index, Wiener index, number of rotatable bonds, log S, log P and total polar surface area (TPSA). The effect of benzofuran derivatives was moderate in cytotoxicity tests and hence only quinolines were considered for further analysis. The molecular docking indicated the mammalian / mechanistic target of rapamycin (mTOR), Topoisomerase I and II as possible targets for these molecules. The predicted results obtained from QSAR and molecular docking analysis of quinoline derivatives showed high correlation in comparison to the results of the cytotoxic assay. Overall, this study indicated that quinolines are more potent as anticancer agents compared to benzofurans. Further, compound Q9 has emerged as a lead molecule which could be the base for further development of more potent anticancer agents.
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DOI: 10.5155/eurjchem.11.3.223-234.2004
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Kuvempu University, Jnana Sahyadri, Shimoga, Karnataka, 577451, India and Jagadguru Sri Shivarathreeshwara Academy of Higher Education and Research, Mysuru, Karnataka, 570015, India.
Citations
[1]. Sanjay D. Hadiyal, Jaydeep N. Lalpara, Bhavin B. Dhaduk, H. S. Joshi
Rational synthesis, anticancer activity, and molecular docking studies of novel benzofuran liked thiazole hybrids
Molecular Diversity 27(3), 1345, 2023
DOI: 10.1007/s11030-022-10493-7

[2]. Praveen Kumar, Santhosha Sangapurada Mahantheshappa, Sakthivel Balasubramaniyan, Nayak Devappa Satyanarayan, Rajeshwara Achur
Quinoline analogue as a potential inhibitor of SARS-CoV-2 main protease: ADMET prediction, molecular docking and dynamics simulation analysis
European Journal of Chemistry 14(1), 30, 2023
DOI: 10.5155/eurjchem.14.1.30-38.2350

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