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Identification of native protein structures captured by principal interactions

BACKGROUND: Evaluation of protein structure is based on trustworthy potential function. The total potential of a protein structure is approximated as the summation of all pair-wise interaction potentials. Knowledge-based potentials (KBP) are one type of potential functions derived by known experimen...

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Autor principal: Mirzaie, Mehdi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873546/
https://www.ncbi.nlm.nih.gov/pubmed/31752663
http://dx.doi.org/10.1186/s12859-019-3186-6
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author Mirzaie, Mehdi
author_facet Mirzaie, Mehdi
author_sort Mirzaie, Mehdi
collection PubMed
description BACKGROUND: Evaluation of protein structure is based on trustworthy potential function. The total potential of a protein structure is approximated as the summation of all pair-wise interaction potentials. Knowledge-based potentials (KBP) are one type of potential functions derived by known experimentally determined protein structures. Although several KBP functions with different methods have been introduced, the key interactions that capture the total potential have not studied yet. RESULTS: In this study, we seek the interaction types that preserve as much of the total potential as possible. We employ a procedure based on the principal component analysis (PCA) to extract the significant and key interactions in native protein structures. We call these interactions as principal interactions and show that the results of the model that considers only these interactions are very close to the full interaction model that considers all interactions in protein fold recognition. In fact, the principal interactions maintain the discriminative power of the full interaction model. This method was evaluated on 3 KBPs with different contact definitions and thresholds of distance and revealed that their corresponding principal interactions are very similar and have a lot in common. Additionally, the principal interactions consisted of 20 % of the full interactions on average, and they are between residues, which are considered important in protein folding. CONCLUSIONS: This work shows that all interaction types are not equally important in discrimination of native structure. The results of the reduced model based on principal interactions that were very close to the full interaction model suggest that a new strategy is needed to capture the role of remaining interactions (non-principal interactions) to improve the power of knowledge-based potential functions.
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spelling pubmed-68735462019-11-25 Identification of native protein structures captured by principal interactions Mirzaie, Mehdi BMC Bioinformatics Research Article BACKGROUND: Evaluation of protein structure is based on trustworthy potential function. The total potential of a protein structure is approximated as the summation of all pair-wise interaction potentials. Knowledge-based potentials (KBP) are one type of potential functions derived by known experimentally determined protein structures. Although several KBP functions with different methods have been introduced, the key interactions that capture the total potential have not studied yet. RESULTS: In this study, we seek the interaction types that preserve as much of the total potential as possible. We employ a procedure based on the principal component analysis (PCA) to extract the significant and key interactions in native protein structures. We call these interactions as principal interactions and show that the results of the model that considers only these interactions are very close to the full interaction model that considers all interactions in protein fold recognition. In fact, the principal interactions maintain the discriminative power of the full interaction model. This method was evaluated on 3 KBPs with different contact definitions and thresholds of distance and revealed that their corresponding principal interactions are very similar and have a lot in common. Additionally, the principal interactions consisted of 20 % of the full interactions on average, and they are between residues, which are considered important in protein folding. CONCLUSIONS: This work shows that all interaction types are not equally important in discrimination of native structure. The results of the reduced model based on principal interactions that were very close to the full interaction model suggest that a new strategy is needed to capture the role of remaining interactions (non-principal interactions) to improve the power of knowledge-based potential functions. BioMed Central 2019-11-21 /pmc/articles/PMC6873546/ /pubmed/31752663 http://dx.doi.org/10.1186/s12859-019-3186-6 Text en © The Author(s). 2019 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Mirzaie, Mehdi
Identification of native protein structures captured by principal interactions
title Identification of native protein structures captured by principal interactions
title_full Identification of native protein structures captured by principal interactions
title_fullStr Identification of native protein structures captured by principal interactions
title_full_unstemmed Identification of native protein structures captured by principal interactions
title_short Identification of native protein structures captured by principal interactions
title_sort identification of native protein structures captured by principal interactions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873546/
https://www.ncbi.nlm.nih.gov/pubmed/31752663
http://dx.doi.org/10.1186/s12859-019-3186-6
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