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Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces

BACKGROUND: Many newly detected point mutations are located in protein-coding regions of the human genome. Knowledge of their effects on the protein's 3D structure provides insight into the protein's mechanism, can aid the design of further experiments, and eventually can lead to the devel...

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Autores principales: Venselaar, Hanka, te Beek, Tim AH, Kuipers, Remko KP, Hekkelman, Maarten L, Vriend, Gert
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2992548/
https://www.ncbi.nlm.nih.gov/pubmed/21059217
http://dx.doi.org/10.1186/1471-2105-11-548
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author Venselaar, Hanka
te Beek, Tim AH
Kuipers, Remko KP
Hekkelman, Maarten L
Vriend, Gert
author_facet Venselaar, Hanka
te Beek, Tim AH
Kuipers, Remko KP
Hekkelman, Maarten L
Vriend, Gert
author_sort Venselaar, Hanka
collection PubMed
description BACKGROUND: Many newly detected point mutations are located in protein-coding regions of the human genome. Knowledge of their effects on the protein's 3D structure provides insight into the protein's mechanism, can aid the design of further experiments, and eventually can lead to the development of new medicines and diagnostic tools. RESULTS: In this article we describe HOPE, a fully automatic program that analyzes the structural and functional effects of point mutations. HOPE collects information from a wide range of information sources including calculations on the 3D coordinates of the protein by using WHAT IF Web services, sequence annotations from the UniProt database, and predictions by DAS services. Homology models are built with YASARA. Data is stored in a database and used in a decision scheme to identify the effects of a mutation on the protein's 3D structure and function. HOPE builds a report with text, figures, and animations that is easy to use and understandable for (bio)medical researchers. CONCLUSIONS: We tested HOPE by comparing its output to the results of manually performed projects. In all straightforward cases HOPE performed similar to a trained bioinformatician. The use of 3D structures helps optimize the results in terms of reliability and details. HOPE's results are easy to understand and are presented in a way that is attractive for researchers without an extensive bioinformatics background.
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spelling pubmed-29925482010-11-27 Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces Venselaar, Hanka te Beek, Tim AH Kuipers, Remko KP Hekkelman, Maarten L Vriend, Gert BMC Bioinformatics Methodology Article BACKGROUND: Many newly detected point mutations are located in protein-coding regions of the human genome. Knowledge of their effects on the protein's 3D structure provides insight into the protein's mechanism, can aid the design of further experiments, and eventually can lead to the development of new medicines and diagnostic tools. RESULTS: In this article we describe HOPE, a fully automatic program that analyzes the structural and functional effects of point mutations. HOPE collects information from a wide range of information sources including calculations on the 3D coordinates of the protein by using WHAT IF Web services, sequence annotations from the UniProt database, and predictions by DAS services. Homology models are built with YASARA. Data is stored in a database and used in a decision scheme to identify the effects of a mutation on the protein's 3D structure and function. HOPE builds a report with text, figures, and animations that is easy to use and understandable for (bio)medical researchers. CONCLUSIONS: We tested HOPE by comparing its output to the results of manually performed projects. In all straightforward cases HOPE performed similar to a trained bioinformatician. The use of 3D structures helps optimize the results in terms of reliability and details. HOPE's results are easy to understand and are presented in a way that is attractive for researchers without an extensive bioinformatics background. BioMed Central 2010-11-08 /pmc/articles/PMC2992548/ /pubmed/21059217 http://dx.doi.org/10.1186/1471-2105-11-548 Text en Copyright ©2010 Venselaar 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 Methodology Article
Venselaar, Hanka
te Beek, Tim AH
Kuipers, Remko KP
Hekkelman, Maarten L
Vriend, Gert
Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces
title Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces
title_full Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces
title_fullStr Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces
title_full_unstemmed Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces
title_short Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces
title_sort protein structure analysis of mutations causing inheritable diseases. an e-science approach with life scientist friendly interfaces
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2992548/
https://www.ncbi.nlm.nih.gov/pubmed/21059217
http://dx.doi.org/10.1186/1471-2105-11-548
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