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虚拟筛选及其与现代药物设计技术的整合。

Virtual screening and its integration with modern drug design technologies.

作者信息

Guido Rafael V C, Oliva Glaucius, Andricopulo Adriano D

机构信息

Laboratório de Química Medicinal e Computacional, Centro de Biotecnologia Molecular Estrutural, Instituto de Física de São Carlos, Universidade de São Paulo, São Carlos-SP, Brazil.

出版信息

Curr Med Chem. 2008;15(1):37-46. doi: 10.2174/092986708783330683.

Abstract

Drug discovery is a highly complex and costly process, which demands integrated efforts in several relevant aspects involving innovation, knowledge, information, technologies, expertise, R&D investments and management skills. The shift from traditional to genomics- and proteomics-based drug research has fundamentally transformed key R&D strategies in the pharmaceutical industry addressed to the design of new chemical entities as drug candidates against a variety of biological targets. Therefore, drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. The combination of available knowledge of several 3D protein structures with hundreds of thousands of small-molecules have attracted the attention of scientists from all over the world for the application of structure- and ligand-based drug design approaches. In this context, virtual screening technologies have largely enhanced the impact of computational methods applied to chemistry and biology and the goal of applying such methods is to reduce large compound databases and to select a limited number of promising candidates for drug design. This review provides a perspective of the utility of virtual screening in drug design and its integration with other important drug discovery technologies such as high-throughput screening (HTS) and QSAR, highlighting the present challenges, limitations, and future perspectives in medicinal chemistry.

摘要

药物研发是一个高度复杂且成本高昂的过程,需要在创新、知识、信息、技术、专业知识、研发投资和管理技能等多个相关方面进行综合努力。从传统药物研究向基于基因组学和蛋白质组学的药物研究的转变,从根本上改变了制药行业关键的研发策略,这些策略旨在设计新的化学实体作为针对各种生物靶点的候选药物。因此,基于我们对蛋白质 - 配体相互作用基本原理的日益深入理解,药物研发已朝着更合理的策略发展。将多种三维蛋白质结构的现有知识与数十万种小分子相结合,吸引了世界各地科学家对基于结构和配体的药物设计方法的关注。在这种背景下,虚拟筛选技术极大地增强了应用于化学和生物学的计算方法的影响力,应用此类方法的目的是减少庞大的化合物数据库,并为药物设计选择有限数量的有前景的候选物。本综述提供了虚拟筛选在药物设计中的效用及其与其他重要药物研发技术(如高通量筛选(HTS)和定量构效关系(QSAR))整合的观点,突出了药物化学当前面临的挑战、局限性以及未来前景。

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