Gregori-Puigjané Elisabet, Mestres Jordi
Chemotargets SL and Chemogenomics Laboratory, GRIB, Institut Municipal d'Investigació Mèdica and Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.
Curr Opin Chem Biol. 2008 Jun;12(3):359-65. doi: 10.1016/j.cbpa.2008.03.015. Epub 2008 May 2.
The design of chemical libraries directed to target classes is an activity that requires the availability of ligand pharmacological data and/or protein structural data. On the basis of the knowledge derived from these data, chemical libraries directed mainly to G protein-coupled receptors, kinases, proteases, and nuclear receptors have been assembled. However, current design strategies widely overlook assessing the potential ability of the compounds contained in a focused library to provide uniform ample coverage of the protein family they intend to target. Here, we discuss the use of in silico target profiling methods as a means to estimate the actual scope of chemical libraries to probe entire protein families and illustrate its applicability in optimizing the composition of compound sets to achieve maximum coverage of the family with minimum bias to particular targets.
针对目标类别设计化学文库是一项需要配体药理学数据和/或蛋白质结构数据的活动。基于从这些数据中获得的知识,已经构建了主要针对G蛋白偶联受体、激酶、蛋白酶和核受体的化学文库。然而,当前的设计策略广泛忽视了评估聚焦文库中所含化合物为其打算靶向的蛋白质家族提供均匀充分覆盖的潜在能力。在此,我们讨论使用计算机靶点分析方法作为一种手段来估计化学文库探测整个蛋白质家族的实际范围,并说明其在优化化合物集组成以实现家族最大覆盖且对特定靶点偏差最小化方面的适用性。