Molecular docking for substrate identification: The short-chain dehydrogenases/reductases
Molecular docking for substrate identification: The short-chain dehydrogenases/reductases
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DOI：
10.1016/j.jmb.2007.10.065
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发表时间：
2008-01-18
影响因子：
5.6
通讯作者：
Thornton, Janet M.
中科院分区：
文献类型：
--
作者：
Favia, Angelo D.;Nobeli, Irene;Thornton, Janet M.
蛋白质配体对接作为蛋白质功能鉴定的一种工具，在鉴定蛋白质的已知和未知底物方面取得了一定的成功。然而，当大量的酶和它们的同源配体交叉对接时，识别蛋白质的底物仍然是一个挑战。为了更详细地探索一个更有限但实际上重要和及时的问题，我们已经使用对接来识别具有显着底物多样性的单个蛋白质家族的底物，短链脱氢酶/还原酶。我们研究了不同的协议，用于识别已知催化功能的27个短链脱氢酶/还原酶蛋白的候选底物。我们呈现了将来自人类代谢组的> 900种代谢物与这些蛋白质中的每一种及其已知同源底物和产物对接的结果，并且我们研究了对接的能力，以（a）再现底物的可行结合模式和（B）将底物在其他代谢物的数据集中高度排名。此外，我们还根据数据集中得分最高的代谢物，检查我们的对接结果是否提供了有关底物性质的信息。我们比较了两种不同的对接方法和两种替代的评分函数的对接方法之一，我们试图合理化的成功和失败。最后，我们引入了一个新的协议，即我们对接只有一组代表性的结构（medoids）的每一个蛋白质，在每个结合位点的配体的喜好，希望以减少计算成本的特点。我们比较从这个协议与我们原来的对接实验的结果，我们发现，虽然代表的排名相关以及与它们所属的集群的平均排名，一个简单的基于结构的聚类是太天真的基板识别的目的。许多簇包含对相同蛋白质具有广泛变化的亲和力的配体;因此，如果使用单个代表，则可能错过重要的候选物。(c)2007爱思唯尔有限公司保留所有权利。
Protein ligand docking has recently been investigated as a tool for protein function identification, with some success in identifying both known and unknown substrates of proteins. However, identifying a protein's substrate when cross-docking a large number of enzymes and their cognate ligands remains a challenge. To explore a more limited yet practically important and timely problem in more detail, we have used docking for identifying the substrates of a single protein family with remarkable substrate diversity, the short-chain dehydrogenases/reductases.We examine different protocols for identifying candidate substrates for 27 short-chain dehydrogenase/reductase proteins of known catalytic function. We present the results of docking > 900 metabolites from the human metabolome to each of these proteins together with their known cognate substrates and products, and we investigate the ability of docking to (a) reproduce a viable binding mode for the substrate and (b) to rank the substrate highly amongst the dataset of other metabolites. In addition, we examine whether our docking results provide information about the nature of the substrate, based on the best-scoring metabolites in the dataset. We compare two different docking methods and two alternative scoring functions for one of the docking methods, and we attempt to rationalise both successes and failures.Finally, we introduce a new protocol, whereby we dock only a set of representative structures (medoids) to each of the proteins, in the hope of characterising each binding site in terms of its ligand preferences, with a reduced computational cost. We compare the results from this protocol with our original docking experiments, and we find that although the rank of the representatives correlates well with the mean rank of the clusters to which they belong, a simple structure-based clustering is too naive for the purpose of substrate identification. Many clusters comprise ligands with widely varying affinities for the same protein; hence important candidates can be missed if a single representative is used. (c) 2007 Elsevier Ltd. All rights reserved.