基于结构的胆囊癌抗癌天然化合物的多靶向筛选、对接、DFT及模拟。

In silico pharmacology Pub Date : 2025-03-06 eCollection Date: 2025-01-01 DOI:10.1007/s40203-025-00326-4
Suchitra Singh, Janhavi Yadav, Surbhi Singh, Sumanta Kumar Sahu, Puneet Puneet, Royana Singh
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引用次数: 0

摘要

胆囊癌是第六大最常见的胃肠道恶性肿瘤之一,预后差。疾病的进展受慢性炎症和地理位置等因素的影响。目前的治疗方案是有限的,往往无效,强调需要新的治疗方法。本文通过靶向与胆囊癌各种标志物相关的关键信号蛋白,探索潜在的多靶点天然化合物。利用虚拟筛选、分子对接和分子动力学模拟等计算机方法,评估天然化合物与5个关键靶点(PD-L1、VEGFR、EGFR、HER2和c-MET)的相互作用。为了确定潜在的抑制剂,针对每个靶蛋白筛选了抗癌天然化合物库。然后选择每个靶标的前10个化合物进行精确的分子对接。根据最低结合能,确定了一种常见的、有前途的化合物。此外,对所选化合物的DFT、生物利用度和毒性进行了分析,并随后进行了分子动力学模拟。在所研究的化合物中,13- β, 21-二羟基脲醇是每个蛋白靶点的常见和有前途的化合物,具有很强的结合亲和力和良好的相互作用。DFT分析预测了高反应性和强结合相互作用。此外,ADMET分析表明,它是无毒和安全的。分子动力学模拟分析表明,13- β, 21-二羟基脲醇与所有蛋白靶点保持稳定的络合物。这些发现表明,它有潜力成为一种有效的多靶点治疗胆囊癌的药物,并可能有助于开发这种疾病的传统药物治疗方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structure based multi-targeted screening, docking, DFT and simulation of anticancer natural compounds against gallbladder cancer.

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.

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