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Functional annotation strategy for protein structures
Whole-genome sequencing projects are a major source of unknown function proteins. However, as predicting protein function from sequence remains a difficult task, research groups recently started to use 3D protein structures and structural models to bypass it. MED-SuMo compares protein surfaces analy...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics Publishing Group
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891723/ https://www.ncbi.nlm.nih.gov/pubmed/17597920 |
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author | Doppelt, Olivia Moriaud, Fabrice Bornot, Aurélie de Brevern, Alexandre G |
author_facet | Doppelt, Olivia Moriaud, Fabrice Bornot, Aurélie de Brevern, Alexandre G |
author_sort | Doppelt, Olivia |
collection | PubMed |
description | Whole-genome sequencing projects are a major source of unknown function proteins. However, as predicting protein function from sequence remains a difficult task, research groups recently started to use 3D protein structures and structural models to bypass it. MED-SuMo compares protein surfaces analyzing the composition and spatial distribution of specific chemical groups (hydrogen bond donor, acceptor, positive, negative, aromatic, hydrophobic, guanidinium, hydroxyl, acyl and glycine). It is able to recognize proteins that have similar binding sites and thus, may perform similar functions. We present here a fine example which points out the interest of MED-SuMo approach for functional structural annotation. |
format | Text |
id | pubmed-1891723 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Biomedical Informatics Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-18917232007-06-27 Functional annotation strategy for protein structures Doppelt, Olivia Moriaud, Fabrice Bornot, Aurélie de Brevern, Alexandre G Bioinformation Views & Challenges Whole-genome sequencing projects are a major source of unknown function proteins. However, as predicting protein function from sequence remains a difficult task, research groups recently started to use 3D protein structures and structural models to bypass it. MED-SuMo compares protein surfaces analyzing the composition and spatial distribution of specific chemical groups (hydrogen bond donor, acceptor, positive, negative, aromatic, hydrophobic, guanidinium, hydroxyl, acyl and glycine). It is able to recognize proteins that have similar binding sites and thus, may perform similar functions. We present here a fine example which points out the interest of MED-SuMo approach for functional structural annotation. Biomedical Informatics Publishing Group 2007-03-19 /pmc/articles/PMC1891723/ /pubmed/17597920 Text en © 2006 Biomedical Informatics Publishing Group This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited. |
spellingShingle | Views & Challenges Doppelt, Olivia Moriaud, Fabrice Bornot, Aurélie de Brevern, Alexandre G Functional annotation strategy for protein structures |
title | Functional annotation strategy for protein structures |
title_full | Functional annotation strategy for protein structures |
title_fullStr | Functional annotation strategy for protein structures |
title_full_unstemmed | Functional annotation strategy for protein structures |
title_short | Functional annotation strategy for protein structures |
title_sort | functional annotation strategy for protein structures |
topic | Views & Challenges |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891723/ https://www.ncbi.nlm.nih.gov/pubmed/17597920 |
work_keys_str_mv | AT doppeltolivia functionalannotationstrategyforproteinstructures AT moriaudfabrice functionalannotationstrategyforproteinstructures AT bornotaurelie functionalannotationstrategyforproteinstructures AT debrevernalexandreg functionalannotationstrategyforproteinstructures |