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BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions

机译:BioLiP:半手动管理的数据库,用于生物学相关的配体-蛋白质相互作用

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BioLiP (http://zhanglab.ccmb.med.umich.edu/BioLiP/) is a semi-manually curated database for biologically relevant ligand–protein interactions. Establishing interactions between protein and biologically relevant ligands is an important step toward understanding the protein functions. Most ligand-binding sites prediction methods use the protein structures from the Protein Data Bank (PDB) as templates. However, not all ligands present in the PDB are biologically relevant, as small molecules are often used as additives for solving the protein structures. To facilitate template-based ligand–protein docking, virtual ligand screening and protein function annotations, we develop a hierarchical procedure for assessing the biological relevance of ligands present in the PDB structures, which involves a four-step biological feature filtering followed by careful manual verifications. This procedure is used for BioLiP construction. Each entry in BioLiP contains annotations on: ligand-binding residues, ligand-binding affinity, catalytic sites, Enzyme Commission numbers, Gene Ontology terms and cross-links to the other databases. In addition, to facilitate the use of BioLiP for function annotation of uncharacterized proteins, a new consensus-based algorithm COACH is developed to predict ligand-binding sites from protein sequence or using 3D structure. The BioLiP database is updated weekly and the current release contains 204 223 entries.
机译:BioLiP(http://zhanglab.ccmb.med.umich.edu/BioLiP/)是与生物相关的配体-蛋白质相互作用的半手动数据库。在蛋白质与生物学相关配体之间建立相互作用是理解蛋白质功能的重要一步。大多数配体结合位点的预测方法都使用蛋白质数据库(PDB)中的蛋白质结构作为模板。但是,并非全部存在于PDB中的配体在生物学上都是相关的,因为小分子通常被用作解决蛋白质结构的添加剂。为了促进基于模板的配体-蛋白质对接,虚拟配体筛选和蛋白质功能注释,我们开发了一种分级程序来评估PDB结构中存在的配体的生物学相关性,其中包括四步生物特征过滤,然后进行仔细的手动验证。此过程用于BioLiP构建。 BioLiP中的每个条目都包含以下注释:配体结合残基,配体结合亲和力,催化位点,酶委员会编号,基因本体论术语以及与其他数据库的交叉链接。另外,为了促进将BioLiP用于未表征蛋白质的功能注释,开发了一种基于共识的新算法COACH,可从蛋白质序列或使用3D结构预测配体结合位点。 BioLiP数据库每周更新一次,当前版本包含204 223个条目。

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