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Using 3dRPC for RNA–protein complex structure prediction

3dRPC is a computational method designed for three-dimensional RNA–protein complex structure prediction. Starting from a protein structure and a RNA structure, 3dRPC first generates presumptive complex structures by RPDOCK and then evaluates the structures by RPRANK. RPDOCK is an FFT-based docking a...

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Detalles Bibliográficos
Autores principales: Huang, Yangyu, Li, Haotian, Xiao, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5334405/
https://www.ncbi.nlm.nih.gov/pubmed/28317012
http://dx.doi.org/10.1007/s41048-017-0034-y
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author Huang, Yangyu
Li, Haotian
Xiao, Yi
author_facet Huang, Yangyu
Li, Haotian
Xiao, Yi
author_sort Huang, Yangyu
collection PubMed
description 3dRPC is a computational method designed for three-dimensional RNA–protein complex structure prediction. Starting from a protein structure and a RNA structure, 3dRPC first generates presumptive complex structures by RPDOCK and then evaluates the structures by RPRANK. RPDOCK is an FFT-based docking algorithm that takes features of RNA–protein interactions into consideration, and RPRANK is a knowledge-based potential using root mean square deviation as a measure. Here we give a detailed description of the usage of 3dRPC. The source code is available at http://biophy.hust.edu.cn/3dRPC.html.
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spelling pubmed-53344052017-03-15 Using 3dRPC for RNA–protein complex structure prediction Huang, Yangyu Li, Haotian Xiao, Yi Biophys Rep Resource 3dRPC is a computational method designed for three-dimensional RNA–protein complex structure prediction. Starting from a protein structure and a RNA structure, 3dRPC first generates presumptive complex structures by RPDOCK and then evaluates the structures by RPRANK. RPDOCK is an FFT-based docking algorithm that takes features of RNA–protein interactions into consideration, and RPRANK is a knowledge-based potential using root mean square deviation as a measure. Here we give a detailed description of the usage of 3dRPC. The source code is available at http://biophy.hust.edu.cn/3dRPC.html. Springer Berlin Heidelberg 2017-02-10 2016 /pmc/articles/PMC5334405/ /pubmed/28317012 http://dx.doi.org/10.1007/s41048-017-0034-y Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Resource
Huang, Yangyu
Li, Haotian
Xiao, Yi
Using 3dRPC for RNA–protein complex structure prediction
title Using 3dRPC for RNA–protein complex structure prediction
title_full Using 3dRPC for RNA–protein complex structure prediction
title_fullStr Using 3dRPC for RNA–protein complex structure prediction
title_full_unstemmed Using 3dRPC for RNA–protein complex structure prediction
title_short Using 3dRPC for RNA–protein complex structure prediction
title_sort using 3drpc for rna–protein complex structure prediction
topic Resource
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5334405/
https://www.ncbi.nlm.nih.gov/pubmed/28317012
http://dx.doi.org/10.1007/s41048-017-0034-y
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