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PDBspheres: a method for finding 3D similarities in local regions in proteins
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9549786/ https://www.ncbi.nlm.nih.gov/pubmed/36225529 http://dx.doi.org/10.1093/nargab/lqac078 |
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author | Zemla, Adam T Allen, Jonathan E Kirshner, Dan Lightstone, Felice C |
author_facet | Zemla, Adam T Allen, Jonathan E Kirshner, Dan Lightstone, Felice C |
author_sort | Zemla, Adam T |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9549786 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-95497862022-10-11 PDBspheres: a method for finding 3D similarities in local regions in proteins Zemla, Adam T Allen, Jonathan E Kirshner, Dan Lightstone, Felice C NAR Genom Bioinform Methods Article 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. Oxford University Press 2022-10-10 /pmc/articles/PMC9549786/ /pubmed/36225529 http://dx.doi.org/10.1093/nargab/lqac078 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Article Zemla, Adam T Allen, Jonathan E Kirshner, Dan Lightstone, Felice C PDBspheres: a method for finding 3D similarities in local regions in proteins |
title | PDBspheres: a method for finding 3D similarities in local regions in proteins |
title_full | PDBspheres: a method for finding 3D similarities in local regions in proteins |
title_fullStr | PDBspheres: a method for finding 3D similarities in local regions in proteins |
title_full_unstemmed | PDBspheres: a method for finding 3D similarities in local regions in proteins |
title_short | PDBspheres: a method for finding 3D similarities in local regions in proteins |
title_sort | pdbspheres: a method for finding 3d similarities in local regions in proteins |
topic | Methods Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9549786/ https://www.ncbi.nlm.nih.gov/pubmed/36225529 http://dx.doi.org/10.1093/nargab/lqac078 |
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