Abstract
The present study explores the epidermal growth factor receptor (EGFR) tyrosine kinase inhibition efficacy of secondary metabolites in Trichoderma spp. through molecular docking, molecular dynamics (MD) simulation and MM-PBSA approach. The result of molecular docking confirmed that out of 200 metabolites screened, three metabolites such as Harzianelactone A, Pretrichodermamide G and Aspochalasin M, potentially bound with the active binding site of EGFR tyrosine kinase domain(PDB ID: 1M17) with a threshold docking score of ≤- 9.0 kcal/mol when compared with the standard EGFR inhibitor (Erlotinib). The MD simulation was run to investigate the potential for stable complex formation in EGFR tyrosine kinase domain-unbound/lead metabolite (Aspochalasin M)-bound/standard inhibitor (Erlotinib)-bound complex. The MD simulation analysis at 100 ns revealed that Aspochalasin M formed the stable complex with EGFR. Besides, the in silico predication of pharmacokinetic properties further confirmed that Aspochalasin M qualified the drug-likeness rules with no harmful side effects (viz., hERG toxicity, hepatotoxicity and skin sensitization), nonmutagenicity and favourable logBB value. Moreover, the BOILED-Egg model predicted that Aspochalasin M showed a higher gastrointestinal absorption with improved bioavailability when administered orally and removed from the central nervous system (CNS). The results of the computational studies concluded that Aspochalasin M possessed significant efficacy in binding EGFR's active sites compared to the known standard inhibitor (Erlotinib). Therefore, Aspochalasin M can be used as a possible anticancer drug candidate and further in vitro and in vivo experimental validation of Aspochalasin M of Trichoderma spp. are required to determine its anticancer potential.
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CITATION STYLE
Gowtham, H. G., Revanasiddappa, P. D., Murali, M., Singh, S. B., Abhilash, M. R., Pradeep, S., … Kollur, S. P. (2024). Secondary metabolites of Trichoderma spp. as EGFR tyrosine kinase inhibitors: Evaluation of anticancer efficacy through computational approach. PLoS ONE, 19(1 January). https://doi.org/10.1371/journal.pone.0296010
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