T6496 targeting EGFR mediated by T790M or C797S mutant: machine learning, virtual screening and bioactivity evaluation study

JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS(2023)

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摘要
Acquired resistance to EGFR is a major impediment in lung cancer treatment, highlighting the urgent need to discover novel compounds to overcome EGFR drug resistance. In this study, we utilized in silico methods and bioactivity evaluation for drug discovery to identify novel active anticancer agents targeting EGFRT790M/L858R and EGFRT790M/C797S/L858R. Firstly, we employed ROC-guided machine learning to retrieve nearly 7,765 compounds from a collection of three libraries (comprising over 220,000 compounds). Next, virtual screening, cluster analysis, and binding model analysis were employed to identify six potential compounds. Additionally, the kinase assay revealed that these six compounds demonstrated higher sensitivity to EGFR than c-Met. Among these compounds, T6496 inhibited both EGFRT790M/L858R and EGFRT790M/C797S/L858R kinases, with an IC50 of 3.30 and 8.72 mu M. Furthermore, we evaluated the antitumor effects of the six selected compounds, and compound T6496 exhibited the strongest anticancer activity against H1975 cell lines, with an IC50 value of 2.7 mu M. These results suggest that T6496 may mitigate EGFR resistance caused by T790M or C797S mutations. Moreover, the AO staining assay, JC-1 staining, ROS experiment and hemolytic toxicity evaluation revealed that T6496 could induce apoptosis in H1975 cell lines in a time-dependent and concentration-dependent manner, and is a potential compound for further structural optimization.Communicated by Ramaswamy H. Sarma EGFR drug resistance is a major challenge in lung cancer treatment. This study used in silico methods and bioactivity evaluation to discover novel compounds targeting resistant EGFR mutations. Through machine learning and virtual screening, we identified five potential compounds with higher sensitivity to EGFR than c-Met. T6496 showed potent inhibition of EGFRT790M-L858R and EGFRT790M/C797S/L858R kinases, with IC50 values of 3.30 and 8.72 mu M. It also exhibited strong anticancer activity against H1975 cell lines, inducing apoptosis in a time and concentration-dependent manner. These findings suggest T6496 as a potential candidate for further optimization. ROC guided machine learning, virtual screening and bioevaluation was applied to discover six hit compounds for overcoming EGFR resistance mediated by T790M or C797S.The promising compound T6496 could both inhibit EGFRT790M/L858R and EGFRT790M/C797S/L858R, with an IC50 of 3.30 and 8.72 mu M.In addition, T6496 and AO-365/43489452 show excellent anticancer activity even better than AZD9291.AO staining assay, JC-1 staining, and ROS experiment revealed that compounds T6496 could induce apoptosis in H1975 cell lines in a time-dependent and concentration-dependent manner.
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EGFR resistance mediated by T790M or C797S,machine learning,virtual screening,bioactivity evaluation,anticancer agent
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