Singh Suchitra, Yadav Janhavi, Singh Surbhi, Sahu Sumanta Kumar, Puneet Puneet, Singh Royana
Department of Anatomy, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India.
Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar India.
In Silico Pharmacol. 2025 Mar 6;13(1):39. doi: 10.1007/s40203-025-00326-4. eCollection 2025.
Gallbladder cancer is among the sixth most common gastrointestinal malignancies, with a meager prognosis. The progression of the disease is influenced by factors like chronic inflammation and geographical locations. Current treatment options are limited and often ineffective, emphasizing the need for novel therapeutic approaches. This paper explores potential multi-targeted natural compounds by targeting key signaling proteins associated with various hallmarks of Gallbladder cancer. In silico methods, including virtual screening, molecular docking, and molecular dynamics simulations, were utilized to assess the interactions of natural compounds with five critical targets: PD-L1, VEGFR, EGFR, HER2, and c-MET. To identify potential inhibitors, a library of anticancer natural compounds was screened against each target protein. The top ten compounds for each target were then selected for precise molecular docking. A common, promising compound was identified based on the lowest binding energy. Furthermore, DFT, bioavailability, and toxicity profiles of the selected compound were analyzed, and it was subsequently subjected to molecular dynamics simulations. Among the compounds studied, 13-beta, 21-Dihydroxyeurycomanol was a common and promising compound for each protein target, exhibiting strong binding affinities and favorable interactions. DFT analysis predicted high reactivity and strong binding interactions. Furthermore, ADMET analysis showed that it was non-toxic and safe. Molecular dynamics simulation analysis revealed that 13-beta, 21-Dihydroxyeurycomanol maintains stable complexes with all the protein targets. These findings indicate that it has the potential to be an effective multi-targeted therapeutic agent for gallbladder cancer and may aid in the development of conventional medicine-based treatments for this disease.
胆囊癌是第六大常见的胃肠道恶性肿瘤,预后较差。该疾病的进展受慢性炎症和地理位置等因素影响。目前的治疗选择有限且往往无效,这凸显了新型治疗方法的必要性。本文通过靶向与胆囊癌各种特征相关的关键信号蛋白,探索潜在的多靶点天然化合物。利用包括虚拟筛选、分子对接和分子动力学模拟在内的计算机方法,评估天然化合物与五个关键靶点(程序性死亡受体配体1(PD-L1)、血管内皮生长因子受体(VEGFR)、表皮生长因子受体(EGFR)、人表皮生长因子受体2(HER2)和肝细胞生长因子受体(c-MET))的相互作用。为了识别潜在的抑制剂,针对每个靶蛋白筛选了一个抗癌天然化合物库。然后为每个靶点选择前十种化合物进行精确的分子对接。根据最低结合能确定了一种常见且有前景的化合物。此外,分析了所选化合物的密度泛函理论(DFT)、生物利用度和毒性概况,并随后对其进行了分子动力学模拟。在所研究的化合物中,13-β,21-二羟基刺蒺藜醇是每个蛋白质靶点常见且有前景的化合物,表现出强结合亲和力和良好的相互作用。DFT分析预测其具有高反应性和强结合相互作用。此外,药物代谢动力学(ADMET)分析表明它无毒且安全。分子动力学模拟分析表明,13-β,21-二羟基刺蒺藜醇与所有蛋白质靶点保持稳定的复合物。这些发现表明,它有可能成为一种有效的胆囊癌多靶点治疗剂,并可能有助于开发基于传统医学的该疾病治疗方法。