Towards identification of novel inhibitors of EGFR mutants through In- silico approach.

This study employed molecular docking techniques to identify potential inhibitors against wild-type EGFR and its clinically relevant mutations, including the exon 19 deletion and T790M/L858R resistance mutations. Nine compounds, comprising five irreversible tyrosine kinase inhibitors (TKIs) and four small molecule natural compounds, were systematically screened using CB-dock2 computational tool. The drug-likeness and toxicity of these molecules were also examined based on their ADMET and Toxicity Prediction profiles. Among the tested compounds, Tetrandrine, Dauricine, and Olmutinib exhibited robust binding affinities across both wild-type and mutant EGFR configurations, highlighting their potential as effective inhibitors. These findings align with existing literature, reinforcing the importance of natural compounds and targeted inhibitors in combating EGFR-driven cancers. The integrated approach of combining molecular docking using CB-dock2, ADMET profiling, and Lipinski's rule of five provides a robust framework for preliminary drug candidate screening, potentially accelerating the development of more precise and effective EGFR-targeted therapies. The findings contribute to the growing body of research exploring alternative and more nuanced strategies for inhibiting EGFR-driven oncogenic mechanisms, highlighting the importance of computational methods in identifying novel molecular targets with improved specificity and reduced side effects.本研究采用分子对接技术，筛选针对野生型表皮生长因子受体（EGFR）及其临床相关突变（包括19号外显子缺失突变与T790M/L858R耐药突变）的潜在抑制剂。本研究借助CB-dock2计算工具，对9种化合物进行了系统性筛选，其中包含5种不可逆酪氨酸激酶抑制剂（TKIs）与4种小分子天然化合物。同时，基于ADMET性质与毒性预测特征谱，本研究对这些分子的类药性与毒性进行了评估。在受试化合物中，粉防己碱（Tetrandrine）、蝙蝠葛碱（Dauricine）与奥美替尼（Olmutinib）在野生型与突变型EGFR两种构型下均表现出优异的结合亲和力，彰显了其作为高效抑制剂的潜力。本研究结果与现有文献相符，进一步印证了天然化合物与靶向抑制剂在对抗EGFR驱动型癌症中的重要价值。本研究所采用的整合策略——结合CB-dock2分子对接、ADMET特征谱分析与类药五规则（Lipinski's rule of five）——为候选药物的初步筛选提供了一套严谨的框架，有望加速更精准、高效的EGFR靶向治疗药物的开发。本研究结果为日益壮大的研究领域贡献了新的证据，该领域旨在探索抑制EGFR驱动型致癌机制的替代方案与更精细化的策略，同时凸显了计算方法在筛选特异性更强、副作用更低的新型分子靶点中的重要意义。