Suppr超能文献

计算 G 蛋白偶联受体药物发现的最新趋势和未来展望:从虚拟筛选到多药理学。

Recent trends and future prospects in computational GPCR drug discovery: from virtual screening to polypharmacology.

机构信息

Dipartimento di Farmacia- Scienze del Farmaco, Università degli Studi di Bari Aldo Moro Via Orabona 4, 70125 Bari, Italy.

出版信息

Curr Top Med Chem. 2013;13(9):1069-97. doi: 10.2174/15680266113139990028.

Abstract

Extending virtual screening approaches to deal with multi-target drug design and polypharmacology is an increasingly important aspect in drug design. In light of this, the concept of accessible chemical space and its exploration should be reviewed. The great advantages of re-using drugs with safe pharmacological profiles with favourable pharmacokinetic properties highlights drug repositioning as a valid alternative to rational drug design, massive drug development efforts, and high-throughput screening, especially when supported by in silico techniques. Here, we discuss some of the advantages of multi-target approaches, and we review some significant examples of their application in the last decade to that well known class of pharmaceutical targets, the G-protein coupled receptors.

摘要

将虚拟筛选方法扩展到多靶标药物设计和多药理学是药物设计中一个日益重要的方面。有鉴于此,应该对可及化学空间的概念及其探索进行回顾。重新利用具有安全药理学特性和有利药代动力学特性的药物的巨大优势突出了药物重定位作为合理药物设计、大量药物开发努力和高通量筛选的有效替代方案,尤其是在计算机技术的支持下。在这里,我们讨论了多靶标方法的一些优势,并回顾了过去十年中它们在众所周知的药物靶点 G 蛋白偶联受体这一类别中的一些重要应用实例。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验