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3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures

Many studies have used position-specific scoring matrices (PSSM) profiles to characterize residues in protein structures and to predict a broad range of protein features. Moreover, PSSM profiles of Protein Data Bank (PDB) entries have been recalculated in many works for different purposes. Although...

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Detalles Bibliográficos
Autores principales: Sanchez-Garcia, Ruben, Sorzano, Carlos Oscar Sanchez, Carazo, Jose Maria, Segura, Joan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6149929/
https://www.ncbi.nlm.nih.gov/pubmed/29244774
http://dx.doi.org/10.3390/molecules22122230
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author Sanchez-Garcia, Ruben
Sorzano, Carlos Oscar Sanchez
Carazo, Jose Maria
Segura, Joan
author_facet Sanchez-Garcia, Ruben
Sorzano, Carlos Oscar Sanchez
Carazo, Jose Maria
Segura, Joan
author_sort Sanchez-Garcia, Ruben
collection PubMed
description Many studies have used position-specific scoring matrices (PSSM) profiles to characterize residues in protein structures and to predict a broad range of protein features. Moreover, PSSM profiles of Protein Data Bank (PDB) entries have been recalculated in many works for different purposes. Although the computational cost of calculating a single PSSM profile is affordable, many statistical studies or machine learning-based methods used thousands of profiles to achieve their goals, thereby leading to a substantial increase of the computational cost. In this work we present a new database compiling PSSM profiles for the proteins of the PDB. Currently, the database contains 333,532 protein chain profiles involving 123,135 different PDB entries.
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spelling pubmed-61499292018-11-13 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures Sanchez-Garcia, Ruben Sorzano, Carlos Oscar Sanchez Carazo, Jose Maria Segura, Joan Molecules Technical Note Many studies have used position-specific scoring matrices (PSSM) profiles to characterize residues in protein structures and to predict a broad range of protein features. Moreover, PSSM profiles of Protein Data Bank (PDB) entries have been recalculated in many works for different purposes. Although the computational cost of calculating a single PSSM profile is affordable, many statistical studies or machine learning-based methods used thousands of profiles to achieve their goals, thereby leading to a substantial increase of the computational cost. In this work we present a new database compiling PSSM profiles for the proteins of the PDB. Currently, the database contains 333,532 protein chain profiles involving 123,135 different PDB entries. MDPI 2017-12-15 /pmc/articles/PMC6149929/ /pubmed/29244774 http://dx.doi.org/10.3390/molecules22122230 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Technical Note
Sanchez-Garcia, Ruben
Sorzano, Carlos Oscar Sanchez
Carazo, Jose Maria
Segura, Joan
3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures
title 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures
title_full 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures
title_fullStr 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures
title_full_unstemmed 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures
title_short 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures
title_sort 3dcons-db: a database of position-specific scoring matrices in protein structures
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6149929/
https://www.ncbi.nlm.nih.gov/pubmed/29244774
http://dx.doi.org/10.3390/molecules22122230
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