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PSAIA – Protein Structure and Interaction Analyzer

BACKGROUND: PSAIA (Protein Structure and Interaction Analyzer) was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. RESULTS: In addition to most relevant established algorithms, PSAIA offers a new me...

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Autores principales: Mihel, Josip, Šikić, Mile, Tomić, Sanja, Jeren, Branko, Vlahoviček, Kristian
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2364630/
https://www.ncbi.nlm.nih.gov/pubmed/18400099
http://dx.doi.org/10.1186/1472-6807-8-21
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author Mihel, Josip
Šikić, Mile
Tomić, Sanja
Jeren, Branko
Vlahoviček, Kristian
author_facet Mihel, Josip
Šikić, Mile
Tomić, Sanja
Jeren, Branko
Vlahoviček, Kristian
author_sort Mihel, Josip
collection PubMed
description BACKGROUND: PSAIA (Protein Structure and Interaction Analyzer) was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. RESULTS: In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm) for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. CONCLUSION: In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.
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spelling pubmed-23646302008-05-02 PSAIA – Protein Structure and Interaction Analyzer Mihel, Josip Šikić, Mile Tomić, Sanja Jeren, Branko Vlahoviček, Kristian BMC Struct Biol Software BACKGROUND: PSAIA (Protein Structure and Interaction Analyzer) was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. RESULTS: In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm) for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. CONCLUSION: In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites. BioMed Central 2008-04-09 /pmc/articles/PMC2364630/ /pubmed/18400099 http://dx.doi.org/10.1186/1472-6807-8-21 Text en Copyright © 2008 Mihel 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
Mihel, Josip
Šikić, Mile
Tomić, Sanja
Jeren, Branko
Vlahoviček, Kristian
PSAIA – Protein Structure and Interaction Analyzer
title PSAIA – Protein Structure and Interaction Analyzer
title_full PSAIA – Protein Structure and Interaction Analyzer
title_fullStr PSAIA – Protein Structure and Interaction Analyzer
title_full_unstemmed PSAIA – Protein Structure and Interaction Analyzer
title_short PSAIA – Protein Structure and Interaction Analyzer
title_sort psaia – protein structure and interaction analyzer
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2364630/
https://www.ncbi.nlm.nih.gov/pubmed/18400099
http://dx.doi.org/10.1186/1472-6807-8-21
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