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靶向mTOR蛋白的ATP竞争性抑制剂的虚拟筛选与分子动力学模拟研究

Virtual screening and molecular dynamics simulation study of ATP-competitive inhibitors targeting mTOR protein.

作者信息

Jin Mei-Yu, Yu Hao, Deng Qiong, Wang Zhu, Wang Jie-Yan, Li Hao-Long, Liang Hui

机构信息

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Department of Urology, People's Hospital of Longhua, Shenzhen, China.

出版信息

PLoS One. 2025 May 5;20(5):e0319608. doi: 10.1371/journal.pone.0319608. eCollection 2025.

Abstract

In order to explore efficient ATP-competitive mTOR inhibitors and aid the development of targeted anticancer drugs, this study focuses on virtual screening and molecular dynamics simulations. The compounds were sourced from the ChemDiv commercial compound library, and through virtual screening, 50 ligands with favorable binding modes and excellent docking scores were selected from 902,998 compounds. Molecular dynamics simulations, including RMSD (Root Mean Square Deviation) and RMSF (Root Mean Square Fluctuation), were used to further evaluate these 50 ligands. Structural stability, key residue interactions, hydrogen bonding, binding free energy, and other factors were quantitatively and qualitatively analyzed. Top1, top2, and top6, which exhibited outstanding performance, were identified. Simulations revealed that they bind stably in the active region of the mTOR protein, forming hydrogen bonds, π-π interactions, and hydrophobic interactions with key amino acid residues such as VAL-2240 and TRP-2239. This study provides a solid theoretical foundation for the development of mTOR inhibitors. Subsequent efforts will focus on optimizing these compounds, targeting structural adjustments to enhance their biological activity and specificity towards mTOR, thereby achieving more precise targeting and treatment of tumors.

摘要

为了探索高效的ATP竞争性mTOR抑制剂并助力靶向抗癌药物的研发,本研究聚焦于虚拟筛选和分子动力学模拟。化合物来源于ChemDiv商业化合物库,通过虚拟筛选,从902,998种化合物中选出了50种具有良好结合模式和出色对接分数的配体。利用包括均方根偏差(RMSD)和均方根波动(RMSF)在内的分子动力学模拟进一步评估这50种配体。对结构稳定性、关键残基相互作用、氢键、结合自由能等因素进行了定量和定性分析。确定了表现优异的Top1、Top2和Top6。模拟结果表明,它们在mTOR蛋白的活性区域稳定结合,与VAL-2240和TRP-2239等关键氨基酸残基形成氢键、π-π相互作用和疏水相互作用。本研究为mTOR抑制剂的研发提供了坚实的理论基础。后续工作将集中于优化这些化合物,针对结构进行调整以增强其对mTOR的生物活性和特异性,从而实现对肿瘤更精准的靶向治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f77/12052163/12e1c19b4abc/pone.0319608.g001.jpg

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