Suppr超能文献

运用计算方法发现和开发 ATP 竞争性 mTOR 抑制剂。

Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches.

机构信息

Pre-Incubator for Innovative Drugs & Medicine, School of Bioscience and Bioengineering, South China University of Technology, Guangzhou 510006, China.

出版信息

Curr Pharm Des. 2017 Nov 16;23(29):4321-4331. doi: 10.2174/1381612823666170710150604.

Abstract

The mammalian target of rapamycin (mTOR) is a central controller of cell growth, proliferation, metabolism, and angiogenesis. This protein is an attractive target for new anticancer drug development. Significant progress has been made in hit discovery, lead optimization, drug candidate development and determination of the three-dimensional (3D) structure of mTOR. Computational methods have been applied to accelerate the discovery and development of mTOR inhibitors helping to model the structure of mTOR, screen compound databases, uncover structure-activity relationship (SAR) and optimize the hits, mine the privileged fragments and design focused libraries. Besides, computational approaches were also applied to study protein-ligand interactions mechanisms and in natural product-driven drug discovery. Herein, we survey the most recent progress on the application of computational approaches to advance the discovery and development of compounds targeting mTOR. Future directions in the discovery of new mTOR inhibitors using computational methods are also discussed.

摘要

哺乳动物雷帕霉素靶蛋白(mTOR)是细胞生长、增殖、代谢和血管生成的中央控制器。该蛋白是开发新型抗癌药物的有吸引力的靶标。在发现靶标、优化先导化合物、候选药物开发以及确定 mTOR 的三维(3D)结构方面取得了重大进展。计算方法已被应用于加速 mTOR 抑制剂的发现和开发,有助于模拟 mTOR 的结构、筛选化合物数据库、揭示结构-活性关系(SAR)和优化命中化合物、挖掘优势片段以及设计重点文库。此外,计算方法还被应用于研究蛋白质-配体相互作用机制和基于天然产物的药物发现。本文综述了应用计算方法推进 mTOR 靶向化合物发现和开发的最新进展。还讨论了使用计算方法发现新型 mTOR 抑制剂的未来方向。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验