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Automated Procedure for Contact-Map-Based Protein Structure Reconstruction

Knowledge of the three-dimensional structures of ion channels allows for modeling their conductivity characteristics using biophysical models and can lead to discovering their cellular functionality. Recent studies show that quality of structure predictions can be significantly improved using protei...

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Autores principales: Konopka, Bogumil M., Ciombor, Marika, Kurczynska, Monika, Kotulska, Malgorzata
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983884/
https://www.ncbi.nlm.nih.gov/pubmed/24682239
http://dx.doi.org/10.1007/s00232-014-9648-x
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author Konopka, Bogumil M.
Ciombor, Marika
Kurczynska, Monika
Kotulska, Malgorzata
author_facet Konopka, Bogumil M.
Ciombor, Marika
Kurczynska, Monika
Kotulska, Malgorzata
author_sort Konopka, Bogumil M.
collection PubMed
description Knowledge of the three-dimensional structures of ion channels allows for modeling their conductivity characteristics using biophysical models and can lead to discovering their cellular functionality. Recent studies show that quality of structure predictions can be significantly improved using protein contact site information. Therefore, a number of procedures for protein structure prediction based on their contact-map have been proposed. Their comparison is difficult due to different methodologies used for validation. In this work, a Contact Map-to-Structure pipeline (C2S_pipeline) for contact-based protein structure reconstruction is designed and validated. The C2S_pipeline can be used to reconstruct monomeric and multimeric proteins. The median RMSD of structures obtained during validation on a representative set of protein structures, equaled 5.27 Å, and the best structure was reconstructed with RMSD of 1.59 Å. The validation is followed by a detailed case study on the KcsA ion channel. Models of KcsA are reconstructed based on different portions of contact site information. Structural feature analysis of acquired KcsA models is supported by a thorough analysis of electrostatic potential distributions inside the channels. The study shows that electrostatic parameters are correlated with structural quality of models. Therefore, they can be used to discriminate between high and low quality structures. We show that 30 % of contact information is needed to obtain accurate structures of KcsA, if contacts are selected randomly. This number increases to 70 % in case of erroneous maps in which the remaining contacts or non-contacts are changed to the opposite. Furthermore, the study reveals that local reconstruction accuracy is correlated with the number of contacts in which amino acid are involved. This results in higher reconstruction accuracy in the structure core than peripheral regions.
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spelling pubmed-39838842014-04-16 Automated Procedure for Contact-Map-Based Protein Structure Reconstruction Konopka, Bogumil M. Ciombor, Marika Kurczynska, Monika Kotulska, Malgorzata J Membr Biol Article Knowledge of the three-dimensional structures of ion channels allows for modeling their conductivity characteristics using biophysical models and can lead to discovering their cellular functionality. Recent studies show that quality of structure predictions can be significantly improved using protein contact site information. Therefore, a number of procedures for protein structure prediction based on their contact-map have been proposed. Their comparison is difficult due to different methodologies used for validation. In this work, a Contact Map-to-Structure pipeline (C2S_pipeline) for contact-based protein structure reconstruction is designed and validated. The C2S_pipeline can be used to reconstruct monomeric and multimeric proteins. The median RMSD of structures obtained during validation on a representative set of protein structures, equaled 5.27 Å, and the best structure was reconstructed with RMSD of 1.59 Å. The validation is followed by a detailed case study on the KcsA ion channel. Models of KcsA are reconstructed based on different portions of contact site information. Structural feature analysis of acquired KcsA models is supported by a thorough analysis of electrostatic potential distributions inside the channels. The study shows that electrostatic parameters are correlated with structural quality of models. Therefore, they can be used to discriminate between high and low quality structures. We show that 30 % of contact information is needed to obtain accurate structures of KcsA, if contacts are selected randomly. This number increases to 70 % in case of erroneous maps in which the remaining contacts or non-contacts are changed to the opposite. Furthermore, the study reveals that local reconstruction accuracy is correlated with the number of contacts in which amino acid are involved. This results in higher reconstruction accuracy in the structure core than peripheral regions. Springer US 2014-03-29 2014 /pmc/articles/PMC3983884/ /pubmed/24682239 http://dx.doi.org/10.1007/s00232-014-9648-x Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Konopka, Bogumil M.
Ciombor, Marika
Kurczynska, Monika
Kotulska, Malgorzata
Automated Procedure for Contact-Map-Based Protein Structure Reconstruction
title Automated Procedure for Contact-Map-Based Protein Structure Reconstruction
title_full Automated Procedure for Contact-Map-Based Protein Structure Reconstruction
title_fullStr Automated Procedure for Contact-Map-Based Protein Structure Reconstruction
title_full_unstemmed Automated Procedure for Contact-Map-Based Protein Structure Reconstruction
title_short Automated Procedure for Contact-Map-Based Protein Structure Reconstruction
title_sort automated procedure for contact-map-based protein structure reconstruction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983884/
https://www.ncbi.nlm.nih.gov/pubmed/24682239
http://dx.doi.org/10.1007/s00232-014-9648-x
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