T6496 targeting EGFR mediated by T790M or C797S mutant: machine learning, virtual screening and bioactivity evaluation study
Related Experiment Video
Updated: Jul 6, 2025

Establishing Dual Resistance to EGFR-TKI and MET-TKI in Lung Adenocarcinoma Cells In Vitro with a 2-step Dose-escalation Procedure
Published on: August 11, 2017
Linxiao Wang1, Dang Fan1, Wei Ruan1
1Jiangxi Provincial Key Laboratory of Drug Design and Evaluation, School of Pharmacy, Jiangxi Science & Technology Normal University, Nanchang, China.
Abstract:
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 μM. 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 μM. 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.
Insights
Novel compounds were identified to combat drug-resistant lung cancer. Compound T6496 effectively targets epidermal growth factor receptor (EGFR) mutations, showing potent anticancer activity and inducing apoptosis in cancer cells.
Area of Science:
- Medicinal Chemistry
- Oncology
- Computational Drug Discovery
Background:
- Acquired resistance to epidermal growth factor receptor (EGFR) inhibitors is a significant challenge in non-small cell lung cancer (NSCLC) treatment.
- Emergence of resistance mutations like T790M and C797S necessitates the development of novel therapeutic agents.
- Targeting specific EGFR mutations is crucial for overcoming acquired drug resistance.
Purpose of the Study:
- To discover novel small molecules capable of inhibiting drug-resistant EGFR variants (EGFRT790M/L858R and EGFRT790M/C797S/L858R).
- To identify potential anticancer agents that can overcome EGFR-mediated drug resistance in lung cancer.
- To evaluate the preclinical efficacy and mechanism of action of newly identified compounds.
Main Methods:
- Utilized ROC-guided machine learning and virtual screening of over 220,000 compounds to identify potential drug candidates.
- Employed cluster analysis and binding model analysis to select promising compounds.
- Conducted kinase assays, cellular assays (H1975 cell lines), apoptosis assays (AO and JC-1 staining), and ROS experiments to evaluate compound activity and mechanism.
Main Results:
- Identified six potential compounds with higher sensitivity to EGFR than c-Met.
- Compound T6496 demonstrated significant inhibition of EGFRT790M/L858R (IC50 = 3.30 μM) and EGFRT790M/C797S/L858R (IC50 = 8.72 μM).
- T6496 exhibited potent anticancer activity against H1975 cells (IC50 = 2.7 μM) and induced apoptosis in a time- and concentration-dependent manner, with favorable toxicity profiles.
Conclusions:
- Compound T6496 is a promising novel agent that can overcome acquired resistance to EGFR inhibitors caused by T790M or C797S mutations.
- T6496 demonstrates potent antitumor effects and induces apoptosis, suggesting its potential as a therapeutic candidate for resistant lung cancer.
- Further structural optimization of T6496 is warranted for clinical development.
More Related Videos
13:34A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
09:38Establishment and Characterization of Three Afatinib-resistant Lung Adenocarcinoma PC-9 Cell Lines Developed with Increasing Doses of Afatinib
Published on: June 26, 2019
Related Concept Videos
Mitogens and the Cell Cycle
Targeted Cancer Therapies
There are several types of targeted therapies against...