Mohd Rehan, Wejdan M AlZahrani, Firoz Ahmed, Mohammad Imran Khan, Hifzur Rahman Ansari, Shazi Shakil, Moustafa E El-Araby, Salman Hosawi, Mohammad Saleem
{"title":"整合转录组学与疾病基因网络和EGFR激酶靶点的鉴定:通过虚拟筛选天然化合物发现脑癌治疗抑制剂。","authors":"Mohd Rehan, Wejdan M AlZahrani, Firoz Ahmed, Mohammad Imran Khan, Hifzur Rahman Ansari, Shazi Shakil, Moustafa E El-Araby, Salman Hosawi, Mohammad Saleem","doi":"10.1080/07391102.2025.2501672","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15272,"journal":{"name":"Journal of Biomolecular Structure & Dynamics","volume":" ","pages":"1-18"},"PeriodicalIF":2.7000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating transcriptomics with disease-gene network and identification of EGFR kinase target: inhibitor discovery through virtual screening of natural compounds for brain cancer therapy.\",\"authors\":\"Mohd Rehan, Wejdan M AlZahrani, Firoz Ahmed, Mohammad Imran Khan, Hifzur Rahman Ansari, Shazi Shakil, Moustafa E El-Araby, Salman Hosawi, Mohammad Saleem\",\"doi\":\"10.1080/07391102.2025.2501672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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. 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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.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.