Integrating transcriptomics with disease–gene network and identification of EGFR kinase target: inhibitor discovery through virtual screening of natural compounds for brain cancer therapy

Brain cancer represents a highly aggressive malignant tumor with a challenging prognosis and limited treatment options. Employing advanced analytical methods, including Kinase Enrichment Analysis and Disease-Gene Network integration, the research identifies EGFR as a crucial therapeutic target for brain cancer. EGFR, a key player in cellular functions and elevated in various cancers, particularly brain cancer, is targeted using small molecule inhibitors like erlotinib and gefitinib. Despite promising results, challenges such as drug resistance and adverse effects necessitate exploration of alternative therapies. Natural compounds show significant potential for cancer with minimal associated toxicity. Thus, the natural compounds database was explored for EGFR kinase inhibitors. Utilizing molecular docking and dynamic simulation, our study identified five natural compounds—citicoline, silodosin, picroside I, canertinib, and tauroursodeoxycholic acid—as potential EGFR kinase inhibitors. Detailed exploration of their binding attributes, including pose, interacting residues, molecular interactions, dynamic behavior, and predicted binding energy, along with comparisons to the native inhibitor, underscored their potential. Notably, among the five natural compounds screened, canertinib is a known covalent inhibitor of EGFR kinase. However, its specific binding pose remains unexplored. Thus, to uncover the precise binding orientation, covalent docking simulation for canertinib was conducted. Additionally, it is noteworthy that all the five proposed compounds predicted to penetrate the blood-brain barrier, meeting the essential criteria for reaching brain. We anticipate that this study will provide valuable leads for experimental testing in the laboratory, advancing the prospects of brain cancer management.

脑癌是一类极具侵袭性的恶性肿瘤，其预后凶险且治疗选择有限。本研究采用激酶富集分析（Kinase Enrichment Analysis）、疾病-基因网络整合（Disease-Gene Network integration）等先进分析方法，确定表皮生长因子受体（Epidermal Growth Factor Receptor, EGFR）是脑癌的关键治疗靶点。EGFR在细胞功能调控中发挥核心作用，且在多种癌症尤其是脑癌中表达上调，可通过厄洛替尼（erlotinib）、吉非替尼（gefitinib）等小分子抑制剂实现靶向干预。尽管该类疗法已展现出可观的应用前景，但耐药性、不良反应等临床挑战仍亟待解决，亟需探索新型替代治疗方案。天然化合物在癌症治疗领域展现出巨大潜力，且相关毒性极低，因此本研究通过天然化合物数据库筛选靶向EGFR的激酶抑制剂。借助分子对接与分子动力学模拟技术，本研究筛选得到5种潜在EGFR激酶抑制剂，分别为胞磷胆碱（citicoline）、西洛多辛（silodosin）、胡黄连苷I（picroside I）、卡奈替尼（canertinib）与牛磺熊去氧胆酸（tauroursodeoxycholic acid）。本研究对这5种化合物的结合特性展开了详细解析，包括结合构象、相互作用残基、分子互作模式、动力学行为以及预测结合能，并与阳性对照抑制剂进行对比，进一步验证了其潜在的治疗价值。值得注意的是，在筛选得到的5种化合物中，卡奈替尼是已被证实的EGFR激酶共价抑制剂，但其具体结合构象尚未被阐明，因此本研究针对卡奈替尼开展了共价对接模拟，以揭示其精准的结合取向。此外，本研究预测这5种候选化合物均可穿透血脑屏障（blood-brain barrier），满足抵达脑部发挥药效的核心条件。本研究预期可为后续实验室实验验证提供有价值的先导化合物，助力脑癌临床管理方案的优化与发展。