基于人工智能的中药虚拟筛选和 TCTP 新型抑制剂的发现。

Juxia Bai, Yangyang Ni, Yuqi Zhang, Junfeng Wan, Liqun Liang, Haoran Qiao, Yanyan Zhu, Qingjie Zhao, Huiyu Li
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引用次数: 0

摘要

背景:转化控制肿瘤蛋白(TCTP)与乳腺癌等肿瘤疾病有关,其抑制剂可减少肿瘤细胞的生长。遗憾的是,目前还没有治疗与 TCTP 相关的乳腺癌的有效药物:本研究旨在探索天然化合物中治疗与 TCTP 蛋白相关的乳腺癌的候选抑制剂:为了探索TCTP的潜在抑制剂,我们首先基于人工智能虚拟筛选,利用对接法筛选出4种潜在的中药癌症抑制剂,然后利用分子对接和分子动力学(MD)方法揭示了TCTP与4种候选中药抑制剂的相互作用机制:根据四个主要化合物的构象特征和 MD 特性,我们利用 MolAICal 软件,采用 AI 方法设计了新的骨架分子。我们的 MD 模拟发现,不同的小分子与 TCTP 的不同位点结合,但其柔性区域和信号传导途径几乎相同,VDW 和疏水相互作用在 TCTP 与配体的相互作用中至关重要:结论:我们提出了 TCTP 的候选抑制剂。我们的研究为探索中药抑制剂提供了一种潜在的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI-based Virtual Screening of Traditional Chinese Medicine and the Discovery of Novel Inhibitors of TCTP.

Background: Translationally controlled tumour protein (TCTP) is associated with tumor diseases, such as breast cancer, and its inhibitor can reduce the growth of tumor cells. Unfortunately, there is currently no effective medication available for treating TCTP-related breast cancer.

Objective: The objective of this study was to explore the inhibitor candidates among natural compounds for the treatment of breast cancer related to TCTP protein.

Methods: To explore the potential inhibitors of TCTP, we first screened out four potential inhibitors in the Traditional Chinese Medicine (TCM) for cancer based on AI virtual screening using the docking method, and then revealed the interaction mechanism of TCTP and four candidate inhibitors from TCM with molecular docking and molecular dynamics (MD) methods.

Results: Based on the conformational characteristics and the MD properties of the four leading compounds, we designed the new skeleton molecules with the AI method using MolAICal software. Our MD simulations have revealed that different small molecules bind to different sites of TCTP, but the flexible regions and the signaling pathways are almost the same, and the VDW and hydrophobic interactions are crucial in the interactions between TCTP and ligands.

Conclusion: We have proposed the candidate inhibitor of TCTP. Our study has provided a potential new method for exploring inhibitors from Traditional Chinese Medicine (TCM).

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