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基于系统知识的药物发现的计算化学基因组学方法。

Computational chemogenomics approaches to systematic knowledge-based drug discovery.

作者信息

Mestres Jordi

机构信息

Chemogenomics Laboratory, Research Unit on Biomedical Informatics, Institut Municipal d'Investigació Mèdica, Universitat Pompeu Fabra, Passeig Marítim de la Barceloneta 37-49, Barcelona 08003, Spain.

出版信息

Curr Opin Drug Discov Devel. 2004 May;7(3):304-13.

Abstract

Chemogenomics, the identification of all possible drugs for all possible targets, has recently emerged as a new paradigm in drug discovery in which efficiency in the compound design and optimization process is achieved through the gain and reuse of targeted knowledge. As targeted knowledge resides at the interface between chemistry and biology, computational tools aimed at integrating the chemical and biological spaces play a central role in chemogenomics. This review covers the recent progress made in integrative computational approaches to data annotation and knowledge generation for the systematic knowledge-based design and screening of chemical libraries.

摘要

化学基因组学,即确定针对所有可能靶点的所有可能药物,最近已成为药物研发中的一种新范式,其中通过获取和重用靶向知识来提高化合物设计和优化过程的效率。由于靶向知识存在于化学与生物学的交叉领域,旨在整合化学和生物空间的计算工具在化学基因组学中发挥着核心作用。本综述涵盖了在基于系统知识的化学文库设计和筛选的数据注释及知识生成的综合计算方法方面取得的最新进展。

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