Journal of Pharmacy & Pharmacognosy Research (Nov 2023)

QSAR study of benzylidene hydrazine benzamides derivatives with in vitro anticancer activity against human lung cancer cell line A459

  • Galih Satrio Putra,
  • Melanny Ika Sulistyowaty,
  • Tegar Achsendo Yuniarta,
  • Yahmin Yahmin,
  • Sumari Sumari,
  • Charinrat Saechan,
  • Takayasu Yamauchi

DOI
https://doi.org/10.56499/jppres23.1718_11.6.1123
Journal volume & issue
Vol. 11, no. 6
pp. 1123 – 1136

Abstract

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Context: In the last decade, resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) in lung cancer cases has been widespread. The discovery and development of new drugs need to be done to overcome the case. Aims: To develop lung anticancer candidates with benzylidene hydrazine benzamides derivatives that can inhibit the growth of human lung cancer cell line A459. Methods: The in silico approach method, along with the QSAR technique, plays an important role in the process of discovery and development of new drugs. In this study, we focused on developing benzylidene hydrazine benzamides derivatives that are much more potent by making the best QSAR equation of 11 benzylidene hydrazine benzamides that have been tested in vitro for its anticancer activity against human lung cancer cell line A459. Results: The best QSAR equation was obtained from benzylidene hydrazine benzamides derivatives as anticancer activity against human lung cancer cell line A459, with PIC50 = 0.738 (± 0.217) Log S – 0.031 (± 0.007) rerank + 0.017 (± 0.016) MR -1.359 ± (1.381) (n = 11; Sig = 0.003; r = 0.921; R2 = 0.849; F= 13.096; Q2 = 0.61). Conclusions: The best QSAR equation can be a tool to obtain a new chemical structure model with more potential and reduce trials and errors.

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