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QSAR model optimizes new EGFR antagonists enhancing binding affinity in lung cancer, suggesting potential drug candidates.
The high mortality and morbidity rates associated with lung cancer pose serious health burden globally. This worrisome circumstance is aggravated by challenges of non-specific targeting, drug resistance, among others. This has necessitated a deliberate search for newer alternatives. In this study, a validated QSAR model (R2train = 0.901, R2adj = 0.870, Q2CV = 0.852, R2Test = 0.813) was used to design potent pyridineamide-based inhibitors of EGFR through structural optimization of the most active member of the dataset selected as template molecule (Tm). The new ligands were found to bind more spontaneously to the receptor with average Gibb’s free energy change (∆G) that ranges from − 9.7 to − 10.3 kcal/mol. When compared with ∆G value of − 7.1 kcal/mol calculated for Erlotinib (Erlo), an approved anti-lung cancer drug used herein as positive control, the design ligands form more stable complexes. Additionally, the designed ligands display sound pharmacokinetics and toxicity profiles. Thus, they could be potential sources of novel drug candidates against lung cancer. Hence, they are recommended for further in vitro and in vivo investigations.
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Ameji et al. (2026) studied this question.
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