AI-based Virtual Screening of Traditional Chinese Medicine and the Discovery of Novel Inhibitors of TCTP

虚拟筛选 对接(动物) 药物发现 化学 计算生物学 医学 生物 生物化学 护理部
作者
J. Bai,Yangyang Ni,Yuqi Zhang,Junfeng Wan,Liqun Liang,Haoran Qiao,Yanyan Zhu,Qingjie Zhao,Huiyu Li
出处
期刊:Current Computer - Aided Drug Design [Bentham Science Publishers]
卷期号:20
标识
DOI:10.2174/0115734099277605231218071503
摘要

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. method: To explore the potential inhibitors of TCTP, we firstly screened out four potential inhibitors in the major agent of the traditional Chinese herbal medicines (TCMs) for cancer based on AI Virtual Screening using the Docking method, and then revealed the interaction mechanism of TCTP and four candidate inhibitors from TCMs 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. result: Based on the conformational characteristics and the MD properties of the four leading compounds, we designed the new skeleton molecules with AI method using MolAICal software. Our MD simulations reveal that different small molecules bind to different sites of TCTP, but the flexible regions and the signaling pathways are almost the same, the VDW and hydrophobic interactions play important roles in the interactions between ligands and TCTP. 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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