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Identification and analysis of conserved pockets on protein surfaces

机译:鉴定和分析蛋白质表面上保守的口袋

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BackgroundThe interaction between proteins and ligands occurs at pockets that are often lined by conserved amino acids. These pockets can represent the targets for low molecular weight drugs. In order to make the research for new medicines as productive as possible, it is necessary to exploit "in silico" techniques, high throughput and fragment-based screenings that require the identification of druggable pockets on the surface of proteins, which may or may not correspond to active sites.ResultsWe developed a tool to evaluate the conservation of each pocket detected on the protein surface by CastP. This tool was named DrosteP because it recursively searches for optimal input sequences to be used to calculate conservation. DrosteP uses a descriptor of statistical significance, Poisson p-value, as a target to optimize the choice of input sequences. To benchmark DrosteP we used monomeric or homodimer human proteins with known 3D-structure whose active site had been annotated in UniProt. DrosteP is able to detect the active site with high accuracy because in 81% of the cases it coincides with the most conserved pocket. Comparing DrosteP with analogous programs is difficult because the outputs are different. Nonetheless we could assess the efficacy of the recursive algorithm in the identification of active site pockets by calculating conservation with the same input sequences used by other programs.We analyzed the amino-acid composition of conserved pockets identified by DrosteP and we found that it differs significantly from the amino-acid composition of non conserved pockets.ConclusionsSeveral methods for predicting ligand binding sites on protein surfaces, that combine 3D-structure and evolutionary sequence conservation, have been proposed. Any method relying on conservation mainly depends on the choice of the input sequences. DrosteP chooses how deeply distant homologs must be collected to evaluate conservation and thus optimizes the identification of active site pockets. Moreover it recognizes conserved pockets other than those coinciding with the sites annotated in UniProt that might represent useful druggable sites. The distinctive amino-acid composition of conserved pockets provides useful hints on the fundamental principles underlying protein-ligand interaction.Availabilityhttp://www.icb.cnr.it/project/drosteppy/
机译:背景技术蛋白质和配体之间的相互作用发生在通常由保守氨基酸排列的口袋中。这些口袋可以代表低分子量药物的目标。为了使对新药的研究尽可能高效,有必要利用“计算机模拟”技术,高通量和基于片段的筛选方法,这些方法需要鉴定蛋白质表面上可能存在或不存在的可药用囊袋结果我们开发了一种工具,用于评估CastP在蛋白质表面检测到的每个口袋的保守性。该工具之所以被命名为DrosteP,是因为它以递归方式搜索了用于计算保守性的最佳输入序列。 DrosteP使用具有统计意义的描述符Poisson p值作为优化输入序列选择的目标。为了对DrosteP进行基准测试,我们使用了具有已知3D结构的单体或同二聚体人类蛋白质,其活性位点已在UniProt中进行了注释。 DrosteP能够高精度检测活动位点,因为在81%的情况下,它与最保守的口袋重合。比较DrosteP和类似程序是困难的,因为输出是不同的。尽管如此,我们可以通过使用其他程序使用的相同输入序列计算保守性来评估递归算法在识别活动位点口袋中的功效。结论:提出了几种预测蛋白质表面配体结合位点的方法,这些方法结合了3D结构和进化序列保守性。任何依赖于保守性的方法主要取决于输入序列的选择。 DrosteP选择必须收集多远的同源物以评估保守性,从而优化对活动位点袋的鉴定。此外,除了那些与UniProt注释的位点(可能代表有用的可药用位点)一致的位点外,它还可以识别出保守的位点。保守的口袋中独特的氨基酸组成为蛋白质-配体相互作用的基本原理提供了有用的提示。可用性http://www.icb.cnr.it/project/drosteppy/

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