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ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly
We develop a hierarchical pipeline, ThreaDomEx, for both continuous domain (CD) and discontinuous domain (DCD) structure predictions. Starting from a query sequence, ThreaDomEx first threads it through the PDB to identify multiple structure templates, where a profile of domain conservation score (DC...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5793814/ https://www.ncbi.nlm.nih.gov/pubmed/28498994 http://dx.doi.org/10.1093/nar/gkx410 |
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author | Wang, Yan Wang, Jian Li, Ruiming Shi, Qiang Xue, Zhidong Zhang, Yang |
author_facet | Wang, Yan Wang, Jian Li, Ruiming Shi, Qiang Xue, Zhidong Zhang, Yang |
author_sort | Wang, Yan |
collection | PubMed |
description | We develop a hierarchical pipeline, ThreaDomEx, for both continuous domain (CD) and discontinuous domain (DCD) structure predictions. Starting from a query sequence, ThreaDomEx first threads it through the PDB to identify multiple structure templates, where a profile of domain conservation score (DC-score) is derived for domain-segment assignment. To further detect DCDs that consist of separated segments along the sequence, a boundary-clustering algorithm is used to refine the DCD-linker locations. In case that the templates do not contain DCDs, a domain-segment assembly process, guided by symmetry comparison, is applied for further DCD detections. ThreaDomEx was tested a set of 1111 proteins and achieved a normalized domain overlap score of 89.3% compared to experimental data, which is significantly higher than other state-of-the-art methods. It also recalls 26.7% of DCDs with 72.7% precision on the proteins for which threading failed to detect any DCDs. The server provides facilities for users to interactively refine the domain models by adjusting DC-score threshold, deleting and adding domain linkers, and assembling domain segments, which are particularly helpful for the hard targets for which current methods have a low accuracy while human-expert knowledge and experimental insights can be used for refining models. ThreaDomEX server is available at http://zhanglab.ccmb.med.umich.edu/ThreaDomEx. |
format | Online Article Text |
id | pubmed-5793814 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57938142018-02-06 ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly Wang, Yan Wang, Jian Li, Ruiming Shi, Qiang Xue, Zhidong Zhang, Yang Nucleic Acids Res Web Server Issue We develop a hierarchical pipeline, ThreaDomEx, for both continuous domain (CD) and discontinuous domain (DCD) structure predictions. Starting from a query sequence, ThreaDomEx first threads it through the PDB to identify multiple structure templates, where a profile of domain conservation score (DC-score) is derived for domain-segment assignment. To further detect DCDs that consist of separated segments along the sequence, a boundary-clustering algorithm is used to refine the DCD-linker locations. In case that the templates do not contain DCDs, a domain-segment assembly process, guided by symmetry comparison, is applied for further DCD detections. ThreaDomEx was tested a set of 1111 proteins and achieved a normalized domain overlap score of 89.3% compared to experimental data, which is significantly higher than other state-of-the-art methods. It also recalls 26.7% of DCDs with 72.7% precision on the proteins for which threading failed to detect any DCDs. The server provides facilities for users to interactively refine the domain models by adjusting DC-score threshold, deleting and adding domain linkers, and assembling domain segments, which are particularly helpful for the hard targets for which current methods have a low accuracy while human-expert knowledge and experimental insights can be used for refining models. ThreaDomEX server is available at http://zhanglab.ccmb.med.umich.edu/ThreaDomEx. Oxford University Press 2017-07-03 2017-05-11 /pmc/articles/PMC5793814/ /pubmed/28498994 http://dx.doi.org/10.1093/nar/gkx410 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Wang, Yan Wang, Jian Li, Ruiming Shi, Qiang Xue, Zhidong Zhang, Yang ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly |
title | ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly |
title_full | ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly |
title_fullStr | ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly |
title_full_unstemmed | ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly |
title_short | ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly |
title_sort | threadomex: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5793814/ https://www.ncbi.nlm.nih.gov/pubmed/28498994 http://dx.doi.org/10.1093/nar/gkx410 |
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