Pharmacophore-based virtual screening approaches to identify novel molecular candidates against EGFR through comprehensive computational approaches and in-vitro studies

基于药效团的虚拟筛选方法,通过综合计算方法和体外研究,鉴定针对 EGFR 的新型分子候选药物。

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Abstract

Alterations to the EGFR (epidermal growth factor receptor) gene, which primarily occur in the axon 18-21 position, have been linked to a variety of cancers, including ovarian, breast, colon, and lung cancer. The use of TK inhibitors (gefitinib, erlotinib, lapatinib, and afatinib) and monoclonal antibodies (cetuximab, panitumumab, and matuzumab) in the treatment of advanced-stage cancer is very common. These drugs are becoming less effective in EGFR targeted cancer treatment and developing resistance to cancer cell eradication, which sometimes necessitates stopping treatment due to the side effects. One in silico study has been conducted to identify EGFR antagonists using other compounds, databases without providing the toxicity profile, comparative analyses, or morphological cell death pattern. The goal of our study was to identify potential lead compounds, and we identified seven compounds based on the docking score and four compounds that were chosen for our study, utilizing toxicity analysis. Molecular docking, virtual screening, dynamic simulation, and in-vitro screening indicated that these compounds' effects were superior to those of already marketed medication (gefitinib). The four compounds obtained, ZINC96937394, ZINC14611940, ZINC103239230, and ZINC96933670, demonstrated improved binding affinity (-9.9 kcal/mol, -9.6 kcal/mol, -9.5 kcal/mol, and -9.2 kcal/mol, respectively), interaction stability, and a lower toxicity profile. In silico toxicity analysis showed that our compounds have a lower toxicity profile and a higher LD(50) value. At the same time, a selected compound, i.e., ZINC103239230, was revealed to attach to a particular active site and bind more tightly to the protein, as well as show better in-vitro results when compared to our selected gefitinib medication. MTT assay, gene expression analysis (BAX, BCL-2, and β-catenin), apoptosis analysis, TEM, cell cycle assay, ELISA, and cell migration assays were conducted to perform the cell death analysis of lung cancer and breast cancer, compared to the marketed product. The MTT assay exhibited 80% cell death for 75 µM and 100µM; however, flow cytometry analysis with the IC(50) value demonstrated that the selected compound induced higher apoptosis in MCF-7 (30.8%) than in A549.

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