PDBspheres: a method for finding 3D similarities in local regions in proteins

Author:

Zemla Adam T1ORCID,Allen Jonathan E1,Kirshner Dan2,Lightstone Felice C2

Affiliation:

1. Global Security Computing Applications, Lawrence Livermore National Laboratory , Livermore, CA 94550, USA

2. Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory , Livermore, CA 94550, USA

Abstract

Abstract 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.

Funder

American Heart Association

Laboratory Directed Research and Development

DTRA

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Computer Science Applications,Genetics,Molecular Biology,Structural Biology

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