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Visualization of Protein-Drug Interactions for the Analysis of Drug Resistance in Lung Cancer

机译:可视化蛋白 - 药物相互作用,用于肺癌耐药性分析

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Non-small cell lung cancer (NSCLC) caused by mutation of the epidermal growth factor receptor (EGFR) is a major cause of death worldwide. Tyrosine kinase inhibitors (TKIs) of EGFR have been developed and show promising results at the initial stage of therapy. However, in most cases, their efficacy becomes limited due to the emergence of secondary mutations causing drug resistance after about a year. In this work, we investigated the mechanism of drug resistance due to these mutations. We performed molecular dynamics (MD) simulations of EGFR-drug interactions to obtain Euclidean distance and binding free energy values to analyse drug resistance and visualize drug-protein interactions. A PCA-based method is proposed to find normal, rigid, flexible, and critical residues. We have established a systematic method for the visualization of protein-drug interactions, which provides an effective framework for the analysis of drug resistance in lung cancer at the atomic level.
机译:由表皮生长因子受体(EGFR)突变引起的非小细胞肺癌(NSCLC)是全世界死亡的主要原因。 EGFR的酪氨酸激酶抑制剂(TKIS)已经开发并显示了在初始治疗阶段的有希望的结果。 然而,在大多数情况下,由于在大约一年后引起耐药性的二次突变的出现,它们的疗效受到限制。 在这项工作中,我们调查了由于这些突变引起的耐药机制。 我们对EGFR-药物相互作用进行了分子动力学(MD)模拟,以获得Euclidean距离和结合自由能值,以分析耐药性和可视化药物 - 蛋白质相互作用。 提出了一种基于PCA的方法,以找到正常,刚性,灵活和临界残留物。 我们已经建立了一种系统的可视化蛋白质 - 药物相互作用的方法,为原子水平的肺癌耐药性分析提供了有效框架。

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