Publication: Investigations on Anticancer and Antimalarial Activities of Indole-Sulfonamide Derivatives and in Silico Studies
Issued Date
2021-11-30
Resource Type
ISSN
24701343
Other identifier(s)
2-s2.0-85120177827
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
ACS Omega. Vol.6, No.47 (2021), 31854-31868
Suggested Citation
Ratchanok Pingaew, Prasit Mandi, Veda Prachayasittikul, Anusit Thongnum, Supaluk Prachayasittikul, Somsak Ruchirawat, Virapong Prachayasittikul Investigations on Anticancer and Antimalarial Activities of Indole-Sulfonamide Derivatives and in Silico Studies. ACS Omega. Vol.6, No.47 (2021), 31854-31868. doi:10.1021/acsomega.1c04552 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/76492
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Investigations on Anticancer and Antimalarial Activities of Indole-Sulfonamide Derivatives and in Silico Studies
Abstract
A library of 44 indole-sulfonamide derivatives (1-44) were investigated for their cytotoxic activities against four cancer cell lines (i.e., HuCCA-1, HepG2, A549, and MOLT-3) and antimalarial effect. Most of the studied indoles exhibit anticancer activity against the MOLT-3 cell line, whereas only hydroxyl-containing bisindoles displayed anticancer activities against the other tested cancer cells as well as antimalarial effect. The most promising anticancer compounds were noted to be CF3, Cl, and NO2 derivatives of hydroxyl-bearing bisindoles (30, 31, and 36), while the most promising antimalarial compound was an OCH3 derivative of non-hydroxyl-containing bisindole 11. Five quantitative structure-activity relationship (QSAR) models were successfully constructed, providing acceptable predictive performance (training set: R = 0.6186-0.9488, RMSE = 0.0938-0.2432; validation set: R = 0.4242-0.9252, RMSE = 0.1100-0.2785). QSAR modeling revealed that mass, charge, polarizability, van der Waals volume, and electronegativity are key properties governing activities of the compounds. QSAR models were further applied to guide the rational design of an additional set of 22 compounds (P1-P22) in which their activities were predicted. The prediction revealed a set of promising virtually constructed compounds (P1, P3, P9, P10, and P16) for further synthesis and development as anticancer and antimalarial agents. Molecular docking was also performed to reveal possible modes of bindings and interactions between the studied compounds and target proteins. Taken together, insightful structure-activity relationship information obtained herein would be beneficial for future screening, design, and structural optimization of the related compounds.