Structure based multi-targeted screening, docking, DFT and simulation of anticancer natural compounds against gallbladder cancer

基于结构的抗胆囊癌天然化合物的多靶点筛选、分子对接、DFT计算和模拟

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Abstract

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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