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RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets
Protein structure exhibits greater complexity and diversity than DNA structure, and usually affects the interpretation of the function, interactions and biological annotations. Reduced amino acid alphabets (Raaa) exhibit a powerful ability to decrease protein complexity and identify functional conse...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252778/ https://www.ncbi.nlm.nih.gov/pubmed/35639512 http://dx.doi.org/10.1093/nar/gkac415 |
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author | Zheng, Lei Liu, Dongyang Li, Yuan Alex Yang, Siqi Liang, Yuchao Xing, Yongqiang Zuo, Yongchun |
author_facet | Zheng, Lei Liu, Dongyang Li, Yuan Alex Yang, Siqi Liang, Yuchao Xing, Yongqiang Zuo, Yongchun |
author_sort | Zheng, Lei |
collection | PubMed |
description | Protein structure exhibits greater complexity and diversity than DNA structure, and usually affects the interpretation of the function, interactions and biological annotations. Reduced amino acid alphabets (Raaa) exhibit a powerful ability to decrease protein complexity and identify functional conserved regions, which motivated us to create RaacFold. The RaacFold provides 687 reduced amino acid clusters (Raac) based on 58 reduction methods and offers three analysis tools: Protein Analysis, Align Analysis, and Multi Analysis. The Protein Analysis and Align Analysis provide reduced representations of sequence-structure according to physicochemical similarities and computational biology strategies. With the simplified representations, the protein structure can be viewed more concise and clearer to capture biological insight than the unreduced structure. Thus, the design of artificial protein will be more convenient, and redundant interference is avoided. In addition, Multi Analysis allows users to explore biophysical variation and conservation in the evolution of protein structure and function. This supplies important information for the identification and exploration of the nonhomologous functions of paralogs. Simultaneously, RaacFold provides powerful 2D and 3D rendering performance with advanced parameters for sequences, structures, and related annotations. RaacFold is freely available at http://bioinfor.imu.edu.cn/raacfold. |
format | Online Article Text |
id | pubmed-9252778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92527782022-07-05 RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets Zheng, Lei Liu, Dongyang Li, Yuan Alex Yang, Siqi Liang, Yuchao Xing, Yongqiang Zuo, Yongchun Nucleic Acids Res Web Server Issue Protein structure exhibits greater complexity and diversity than DNA structure, and usually affects the interpretation of the function, interactions and biological annotations. Reduced amino acid alphabets (Raaa) exhibit a powerful ability to decrease protein complexity and identify functional conserved regions, which motivated us to create RaacFold. The RaacFold provides 687 reduced amino acid clusters (Raac) based on 58 reduction methods and offers three analysis tools: Protein Analysis, Align Analysis, and Multi Analysis. The Protein Analysis and Align Analysis provide reduced representations of sequence-structure according to physicochemical similarities and computational biology strategies. With the simplified representations, the protein structure can be viewed more concise and clearer to capture biological insight than the unreduced structure. Thus, the design of artificial protein will be more convenient, and redundant interference is avoided. In addition, Multi Analysis allows users to explore biophysical variation and conservation in the evolution of protein structure and function. This supplies important information for the identification and exploration of the nonhomologous functions of paralogs. Simultaneously, RaacFold provides powerful 2D and 3D rendering performance with advanced parameters for sequences, structures, and related annotations. RaacFold is freely available at http://bioinfor.imu.edu.cn/raacfold. Oxford University Press 2022-05-25 /pmc/articles/PMC9252778/ /pubmed/35639512 http://dx.doi.org/10.1093/nar/gkac415 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://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 Zheng, Lei Liu, Dongyang Li, Yuan Alex Yang, Siqi Liang, Yuchao Xing, Yongqiang Zuo, Yongchun RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets |
title | RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets |
title_full | RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets |
title_fullStr | RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets |
title_full_unstemmed | RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets |
title_short | RaacFold: a webserver for 3D visualization and analysis of protein structure by using reduced amino acid alphabets |
title_sort | raacfold: a webserver for 3d visualization and analysis of protein structure by using reduced amino acid alphabets |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252778/ https://www.ncbi.nlm.nih.gov/pubmed/35639512 http://dx.doi.org/10.1093/nar/gkac415 |
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