Abstract

The mutations concerned with non-small cell lung cancer involving epidermal growth factor receptor of tyrosine kinase family have primarily targeted. EGFR inhibitors binding allosterically to C797S mutant EGFR enzyme have been developed. Here, database building, library screening performing R-group enumeration and scaffold hopping technique for increasing the EGFR binding affinity of compounds have been carried out. Virtual screening was performed subjecting to HTVS, SP and XP docking protocol along with its relative binding free energy calculations. Molecular docking studies provided the information about binding pockets and interactions of molecules on mutant (PDB: 5D41) as well as wild type (PDB: 4I23) EGFR enzyme. This was supported with ADMET and molecular simulation studies. On the basis of glide score and protein-ligand interactions, highest scoring molecule was selected for molecular dynamic simulation providing a complete insight into the conformational stability. The virtually screened molecules can act as potential EGFR inhibitors in the management of drug resistance.

Communicated by Ramaswamy H. Sarma

摘要

与非小细胞肺癌相关的突变涉及酪氨酸激酶家族的表皮生长因子受体。已经开发了与 C797S 突变型 EGFR 酶变构结合的 EGFR 抑制剂。在这里，已经进行了数据库构建、库筛选执行 R 组枚举和支架跳跃技术以增加化合物的 EGFR 结合亲和力。根据 HTVS、SP 和 XP 对接协议及其相对结合自由能计算进行虚拟筛选。分子对接研究提供了关于结合口袋和分子在突变型 (PDB: 5D41) 和野生型 (PDB: 4I23) EGFR 酶上的相互作用的信息。这得到了 ADMET 和分子模拟研究的支持。在滑动评分和蛋白质-配体相互作用的基础上，选择得分最高的分子进行分子动力学模拟，提供对构象稳定性的完整洞察。虚拟筛选的分子可以在耐药性管理中作为潜在的 EGFR 抑制剂。

由 Ramaswamy H. Sarma 交流