BACKGROUND Epidermal growth factor receptor (EGFR) mutation-induced drug resistance is a difficult problem in lung cancer treatment. Studying the molecular mechanisms of drug resistance can help to develop corresponding treatment strategies and benefit new drug design. METHODS In this study, Rosetta was employed to model the EGFR mutant structures. Then Amber was carried out to conduct molecular dynamics (MD) simulation. Afterwards, we used Computational Geometry Algorithms Library (CGAL) to compute the alpha shape model of the mutants. RESULTS We analyzed the EGFR mutation-induced drug resistance based on the motion trajectories obtained from MD simulation. We computed alpha shape model of all the trajectory frames for each mutation type. Solid angle was used to characterize the curvature of the atoms at the drug binding site. We measured the knob level of the drug binding pocket of each mutant from two ways and analyzed its relationship with the drug response level. Results show that 90 % of the mutants can be grouped correctly by setting a certain knob level threshold. CONCLUSIONS There is a strong correlation between the geometric properties of the drug binding pocket of the EGFR mutants and the corresponding drug responses, which can be used to predict the response of a new EGFR mutant to a drug molecule.

中文翻译：

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基于动力学的α形状模型分析，确定EGFR突变诱导的耐药性。

背景技术表皮生长因子受体（EGFR）突变诱导的耐药性是肺癌治疗中的难题。研究耐药性的分子机制可以帮助制定相应的治疗策略并有益于新药设计。方法在本研究中，Rosetta被用于模拟EGFR突变体结构。然后进行Amber进行分子动力学（MD）模拟。之后，我们使用计算几何算法库（CGAL）来计算突变体的alpha形状模型。结果我们根据从MD模拟获得的运动轨迹分析了EGFR突变诱导的耐药性。我们为每种突变类型计算了所有轨迹框架的alpha形状模型。立体角用于表征药物结合位点处原子的曲率。我们从两种方法测量了每个突变体的药物结合口袋的旋钮水平，并分析了其与药物反应水平的关系。结果表明，通过设置一定的旋钮水平阈值，可以正确分组90％的突变体。结论EGFR突变体的药物结合口袋的几何特性与相应的药物反应之间存在很强的相关性，可用于预测新的EGFR突变体对药物分子的反应。