An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences

Computational modelling of proteins has been a major catalyst in structural biology. Bioinformatics groups have exploited the repositories of known structures to predict high-quality structural models with high efficiency at low cost. This article provides an overview of comparative modelling, revie...

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Detalles Bibliográficos
Autores principales: Lam, Su Datt, Das, Sayoni, Sillitoe, Ian, Orengo, Christine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2017
Materias:
Topical Reviews
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5571743/
https://www.ncbi.nlm.nih.gov/pubmed/28777078
http://dx.doi.org/10.1107/S2059798317008920
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author Lam, Su Datt
Das, Sayoni
Sillitoe, Ian
Orengo, Christine
author_facet Lam, Su Datt
Das, Sayoni
Sillitoe, Ian
Orengo, Christine
author_sort Lam, Su Datt
collection PubMed
description Computational modelling of proteins has been a major catalyst in structural biology. Bioinformatics groups have exploited the repositories of known structures to predict high-quality structural models with high efficiency at low cost. This article provides an overview of comparative modelling, reviews recent developments and describes resources dedicated to large-scale comparative modelling of genome sequences. The value of subclustering protein domain superfamilies to guide the template-selection process is investigated. Some recent cases in which structural modelling has aided experimental work to determine very large macromolecular complexes are also cited.
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spelling pubmed-55717432017-09-05 An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences Lam, Su Datt Das, Sayoni Sillitoe, Ian Orengo, Christine Acta Crystallogr D Struct Biol Topical Reviews Computational modelling of proteins has been a major catalyst in structural biology. Bioinformatics groups have exploited the repositories of known structures to predict high-quality structural models with high efficiency at low cost. This article provides an overview of comparative modelling, reviews recent developments and describes resources dedicated to large-scale comparative modelling of genome sequences. The value of subclustering protein domain superfamilies to guide the template-selection process is investigated. Some recent cases in which structural modelling has aided experimental work to determine very large macromolecular complexes are also cited. International Union of Crystallography 2017-07-28 /pmc/articles/PMC5571743/ /pubmed/28777078 http://dx.doi.org/10.1107/S2059798317008920 Text en © Lam et al. 2017 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.http://creativecommons.org/licenses/by/2.0/uk/
spellingShingle Topical Reviews
Lam, Su Datt
Das, Sayoni
Sillitoe, Ian
Orengo, Christine
An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences
title An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences
title_full An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences
title_fullStr An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences
title_full_unstemmed An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences
title_short An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences
title_sort overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences
topic Topical Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5571743/
https://www.ncbi.nlm.nih.gov/pubmed/28777078
http://dx.doi.org/10.1107/S2059798317008920
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