Zemla Adam T, Allen Jonathan E, Kirshner Dan, Lightstone Felice C
Global Security Computing Applications, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.
Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.
NAR Genom Bioinform. 2022 Oct 10;4(4):lqac078. doi: 10.1093/nargab/lqac078. eCollection 2022 Dec.
We present a structure-based method for finding and evaluating structural similarities in protein regions relevant to ligand binding. PDBspheres comprises an exhaustive library of protein structure regions ('spheres') adjacent to complexed ligands derived from the Protein Data Bank (PDB), along with methods to find and evaluate structural matches between a protein of interest and spheres in the library. PDBspheres uses the LGA (Local-Global Alignment) structure alignment algorithm as the main engine for detecting structural similarities between the protein of interest and template spheres from the library, which currently contains >2 million spheres. To assess confidence in structural matches, an all-atom-based similarity metric takes side chain placement into account. Here, we describe the PDBspheres method, demonstrate its ability to detect and characterize binding sites in protein structures, show how PDBspheres-a strictly structure-based method-performs on a curated dataset of 2528 ligand-bound and ligand-free crystal structures, and use PDBspheres to cluster pockets and assess structural similarities among protein binding sites of 4876 structures in the 'refined set' of the PDBbind 2019 dataset.
我们提出了一种基于结构的方法，用于发现和评估与配体结合相关的蛋白质区域中的结构相似性。PDBspheres包含一个详尽的蛋白质结构区域库（“球体”），这些区域与源自蛋白质数据库（PDB）的复合配体相邻，同时还包括用于查找和评估目标蛋白质与库中球体之间结构匹配的方法。PDBspheres使用LGA（局部-全局比对）结构比对算法作为主要引擎，以检测目标蛋白质与库中模板球体之间的结构相似性，该库目前包含超过200万个球体。为了评估结构匹配的可信度，基于全原子的相似性度量会考虑侧链的位置。在此，我们描述了PDBspheres方法，展示了其在检测和表征蛋白质结构中结合位点方面的能力，展示了PDBspheres（一种严格基于结构的方法）在2528个配体结合和无配体晶体结构的精选数据集上的表现，并使用PDBspheres对口袋进行聚类，以及评估PDBbind 2019数据集“精炼集”中4876个结构的蛋白质结合位点之间的结构相似性。
