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A simple method for finding a protein’s ligand-binding pockets
BACKGROUND: This paper provides a simple and rapid method for a protein-clustering strategy. The basic idea implemented here is to use computational geometry methods to predict and characterize ligand-binding pockets of a given protein structure. In addition to geometrical characteristics of the pro...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112621/ https://www.ncbi.nlm.nih.gov/pubmed/25038637 http://dx.doi.org/10.1186/1472-6807-14-18 |
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author | Saberi Fathi, Seyed Majid Tuszynski, Jack A |
author_facet | Saberi Fathi, Seyed Majid Tuszynski, Jack A |
author_sort | Saberi Fathi, Seyed Majid |
collection | PubMed |
description | BACKGROUND: This paper provides a simple and rapid method for a protein-clustering strategy. The basic idea implemented here is to use computational geometry methods to predict and characterize ligand-binding pockets of a given protein structure. In addition to geometrical characteristics of the protein structure, we consider some simple biochemical properties that help recognize the best candidates for pockets in a protein’s active site. RESULTS: Our results are shown to produce good agreement with known empirical results. CONCLUSIONS: The method presented in this paper is a low-cost rapid computational method that could be used to classify proteins and other biomolecules, and furthermore could be useful in reducing the cost and time of drug discovery. |
format | Online Article Text |
id | pubmed-4112621 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41126212014-08-05 A simple method for finding a protein’s ligand-binding pockets Saberi Fathi, Seyed Majid Tuszynski, Jack A BMC Struct Biol Research Article BACKGROUND: This paper provides a simple and rapid method for a protein-clustering strategy. The basic idea implemented here is to use computational geometry methods to predict and characterize ligand-binding pockets of a given protein structure. In addition to geometrical characteristics of the protein structure, we consider some simple biochemical properties that help recognize the best candidates for pockets in a protein’s active site. RESULTS: Our results are shown to produce good agreement with known empirical results. CONCLUSIONS: The method presented in this paper is a low-cost rapid computational method that could be used to classify proteins and other biomolecules, and furthermore could be useful in reducing the cost and time of drug discovery. BioMed Central 2014-07-19 /pmc/articles/PMC4112621/ /pubmed/25038637 http://dx.doi.org/10.1186/1472-6807-14-18 Text en Copyright © 2014 Saberi Fathi and Tuszynski; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Saberi Fathi, Seyed Majid Tuszynski, Jack A A simple method for finding a protein’s ligand-binding pockets |
title | A simple method for finding a protein’s ligand-binding pockets |
title_full | A simple method for finding a protein’s ligand-binding pockets |
title_fullStr | A simple method for finding a protein’s ligand-binding pockets |
title_full_unstemmed | A simple method for finding a protein’s ligand-binding pockets |
title_short | A simple method for finding a protein’s ligand-binding pockets |
title_sort | simple method for finding a protein’s ligand-binding pockets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112621/ https://www.ncbi.nlm.nih.gov/pubmed/25038637 http://dx.doi.org/10.1186/1472-6807-14-18 |
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