Integration of pharmacophore-based virtual screening, molecular docking, ADMET analysis, and MD simulation for targeting EGFR: A comprehensive drug discovery study using commercial databases.

IF 2.6 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
PLoS ONE Pub Date : 2024-12-09 eCollection Date: 2024-01-01 DOI:10.1371/journal.pone.0311527
Abdullah R Alanzi, Ashaimaa Y Moussa, Mohammed S Alsalhi, Tayyab Nawaz, Ijaz Ali
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引用次数: 0

Abstract

The epidermal growth factor receptor (EGFR), a crucial component of cellular signaling pathways, is frequently dysregulated in a range of cancers. EGFR targeting has become a viable approach in the development of anti-cancer medications. This study employs an integrated approach to drug discovery, combining multiple computational methodologies to identify potential EGFR inhibitors. The co-crystal ligand for the EGFR protein (R85) (PDB ID: 7AEI) was employed as a model for developing pharmacophore hypotheses. Nine databases underwent a ligand-based virtual screening, and 1271 hits meeting the screening criteria were chosen. EGFR protein crystal structure was obtained from the PDB database (PDB ID: 7AEI) and prepared. The hit compounds identified during virtual screening were docked to the prepared EGFR receptor to predict binding affinities by using the glide tool's standard precision mode. The top ten compounds were chosen, and their affinities of binding ranged from -7.691 to -7.338 kcal/mol. The ADMET properties of the selected compounds were predicted, and three compounds MCULE-6473175764, CSC048452634, and CSC070083626 showed better QPPCaco values compared to other identified compounds, so these were selected for further stability analysis. To confirm the stability of the protein-ligand complexes, a 200 ns molecular dynamics (MD) simulation was run using the binding sites of the top three compounds against the EGFR receptor. These results suggest that the selected compounds may be lead compounds in suppressing the biological activity of EGFR, additional experimental investigation is required.

整合基于药物团的虚拟筛选、分子对接、ADMET分析和靶向EGFR的MD模拟:一项使用商业数据库的综合药物发现研究。
表皮生长因子受体(EGFR)是细胞信号通路的重要组成部分,在一系列癌症中经常失调。EGFR靶向已成为开发抗癌药物的一种可行方法。本研究采用了一种综合的药物发现方法,结合多种计算方法来识别潜在的EGFR抑制剂。EGFR蛋白的共晶配体(R85) (PDB ID: 7AEI)被用作药效团假设的模型。对9个数据库进行了基于配体的虚拟筛选,选出了1271个符合筛选标准的hit。从PDB数据库(PDB ID: 7AEI)中获得EGFR蛋白晶体结构并制备。在虚拟筛选过程中确定的命中化合物与制备的EGFR受体对接,通过使用滑翔工具的标准精度模式来预测结合亲和力。结果表明,前10位化合物的结合亲和力在-7.691 ~ -7.338 kcal/mol之间。结果表明,MCULE-6473175764、CSC048452634和CSC070083626三个化合物的QPPCaco值较其他化合物高,因此选择这些化合物进行进一步的稳定性分析。为了证实蛋白质配体复合物的稳定性,利用前三种化合物与EGFR受体的结合位点进行了200 ns分子动力学(MD)模拟。这些结果提示所选化合物可能是抑制EGFR生物活性的先导化合物,还需要进一步的实验研究。
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来源期刊
PLoS ONE
PLoS ONE 生物-生物学
CiteScore
6.20
自引率
5.40%
发文量
14242
审稿时长
3.7 months
期刊介绍: PLOS ONE is an international, peer-reviewed, open-access, online publication. PLOS ONE welcomes reports on primary research from any scientific discipline. It provides: * Open-access—freely accessible online, authors retain copyright * Fast publication times * Peer review by expert, practicing researchers * Post-publication tools to indicate quality and impact * Community-based dialogue on articles * Worldwide media coverage
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