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Fpocket: An open source platform for ligand pocket detection
BACKGROUND: Virtual screening methods start to be well established as effective approaches to identify hits, candidates and leads for drug discovery research. Among those, structure based virtual screening (SBVS) approaches aim at docking collections of small compounds in the target structure to ide...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2700099/ https://www.ncbi.nlm.nih.gov/pubmed/19486540 http://dx.doi.org/10.1186/1471-2105-10-168 |
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author | Le Guilloux, Vincent Schmidtke, Peter Tuffery, Pierre |
author_facet | Le Guilloux, Vincent Schmidtke, Peter Tuffery, Pierre |
author_sort | Le Guilloux, Vincent |
collection | PubMed |
description | BACKGROUND: Virtual screening methods start to be well established as effective approaches to identify hits, candidates and leads for drug discovery research. Among those, structure based virtual screening (SBVS) approaches aim at docking collections of small compounds in the target structure to identify potent compounds. For SBVS, the identification of candidate pockets in protein structures is a key feature, and the recent years have seen increasing interest in developing methods for pocket and cavity detection on protein surfaces. RESULTS: Fpocket is an open source pocket detection package based on Voronoi tessellation and alpha spheres built on top of the publicly available package Qhull. The modular source code is organised around a central library of functions, a basis for three main programs: (i) Fpocket, to perform pocket identification, (ii) Tpocket, to organise pocket detection benchmarking on a set of known protein-ligand complexes, and (iii) Dpocket, to collect pocket descriptor values on a set of proteins. Fpocket is written in the C programming language, which makes it a platform well suited for the scientific community willing to develop new scoring functions and extract various pocket descriptors on a large scale level. Fpocket 1.0, relying on a simple scoring function, is able to detect 94% and 92% of the pockets within the best three ranked pockets from the holo and apo proteins respectively, outperforming the standards of the field, while being faster. CONCLUSION: Fpocket provides a rapid, open source and stable basis for further developments related to protein pocket detection, efficient pocket descriptor extraction, or drugablity prediction purposes. Fpocket is freely available under the GNU GPL license at . |
format | Text |
id | pubmed-2700099 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27000992009-06-23 Fpocket: An open source platform for ligand pocket detection Le Guilloux, Vincent Schmidtke, Peter Tuffery, Pierre BMC Bioinformatics Software BACKGROUND: Virtual screening methods start to be well established as effective approaches to identify hits, candidates and leads for drug discovery research. Among those, structure based virtual screening (SBVS) approaches aim at docking collections of small compounds in the target structure to identify potent compounds. For SBVS, the identification of candidate pockets in protein structures is a key feature, and the recent years have seen increasing interest in developing methods for pocket and cavity detection on protein surfaces. RESULTS: Fpocket is an open source pocket detection package based on Voronoi tessellation and alpha spheres built on top of the publicly available package Qhull. The modular source code is organised around a central library of functions, a basis for three main programs: (i) Fpocket, to perform pocket identification, (ii) Tpocket, to organise pocket detection benchmarking on a set of known protein-ligand complexes, and (iii) Dpocket, to collect pocket descriptor values on a set of proteins. Fpocket is written in the C programming language, which makes it a platform well suited for the scientific community willing to develop new scoring functions and extract various pocket descriptors on a large scale level. Fpocket 1.0, relying on a simple scoring function, is able to detect 94% and 92% of the pockets within the best three ranked pockets from the holo and apo proteins respectively, outperforming the standards of the field, while being faster. CONCLUSION: Fpocket provides a rapid, open source and stable basis for further developments related to protein pocket detection, efficient pocket descriptor extraction, or drugablity prediction purposes. Fpocket is freely available under the GNU GPL license at . BioMed Central 2009-06-02 /pmc/articles/PMC2700099/ /pubmed/19486540 http://dx.doi.org/10.1186/1471-2105-10-168 Text en Copyright © 2009 Le Guilloux et al; 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 cited. |
spellingShingle | Software Le Guilloux, Vincent Schmidtke, Peter Tuffery, Pierre Fpocket: An open source platform for ligand pocket detection |
title | Fpocket: An open source platform for ligand pocket detection |
title_full | Fpocket: An open source platform for ligand pocket detection |
title_fullStr | Fpocket: An open source platform for ligand pocket detection |
title_full_unstemmed | Fpocket: An open source platform for ligand pocket detection |
title_short | Fpocket: An open source platform for ligand pocket detection |
title_sort | fpocket: an open source platform for ligand pocket detection |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2700099/ https://www.ncbi.nlm.nih.gov/pubmed/19486540 http://dx.doi.org/10.1186/1471-2105-10-168 |
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