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用于计算机虚拟靶点筛选的工具。

Tools for in silico target fishing.

作者信息

Cereto-Massagué Adrià, Ojeda María José, Valls Cristina, Mulero Miquel, Pujadas Gerard, Garcia-Vallve Santiago

机构信息

Group of Cheminformatics & Nutrition, Biochemistry and Biotechnology Department, Universitat Rovira i Virgili (URV), Tarragona, Catalonia, Spain.

Group of Cheminformatics & Nutrition, Biochemistry and Biotechnology Department, Universitat Rovira i Virgili (URV), Tarragona, Catalonia, Spain; Centre Tecnològic de Nutrició i Salut (CTNS), TECNIO, Reus, Spain.

出版信息

Methods. 2015 Jan;71:98-103. doi: 10.1016/j.ymeth.2014.09.006. Epub 2014 Sep 30.

Abstract

Computational target fishing methods are designed to identify the most probable target of a query molecule. This process may allow the prediction of the bioactivity of a compound, the identification of the mode of action of known drugs, the detection of drug polypharmacology, drug repositioning or the prediction of the adverse effects of a compound. The large amount of information regarding the bioactivity of thousands of small molecules now allows the development of these types of methods. In recent years, we have witnessed the emergence of many methods for in silico target fishing. Most of these methods are based on the similarity principle, i.e., that similar molecules might bind to the same targets and have similar bioactivities. However, the difficult validation of target fishing methods hinders comparisons of the performance of each method. In this review, we describe the different methods developed for target prediction, the bioactivity databases most frequently used by these methods, and the publicly available programs and servers that enable non-specialist users to obtain these types of predictions. It is expected that target prediction will have a large impact on drug development and on the functional food industry.

摘要

计算靶点筛选方法旨在识别查询分子最可能的靶点。这一过程可用于预测化合物的生物活性、确定已知药物的作用模式、检测药物的多药理学特性、进行药物重新定位或预测化合物的不良反应。如今,关于数千种小分子生物活性的大量信息使得这类方法得以发展。近年来,我们见证了许多计算机靶点筛选方法的出现。这些方法大多基于相似性原则,即相似的分子可能结合相同的靶点并具有相似的生物活性。然而,靶点筛选方法难以验证,这阻碍了对每种方法性能的比较。在本综述中,我们描述了为靶点预测开发的不同方法、这些方法最常使用的生物活性数据库,以及使非专业用户能够获得这类预测的公开可用程序和服务器。预计靶点预测将对药物开发和功能食品行业产生重大影响。

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