Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins
A statistical thermodynamics approach is proposed to determine structurally and functionally important residues in native proteins that are involved in energy exchange with a ligand and other residues along an interaction pathway. The structure-function relationships, ligand binding and allosteric a...
Autores principales: | , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2900293/ https://www.ncbi.nlm.nih.gov/pubmed/20628622 http://dx.doi.org/10.1371/journal.pcbi.1000845 |
_version_ | 1782183619678175232 |
---|---|
author | Haliloglu, Turkan Gul, Ahmet Erman, Burak |
author_facet | Haliloglu, Turkan Gul, Ahmet Erman, Burak |
author_sort | Haliloglu, Turkan |
collection | PubMed |
description | A statistical thermodynamics approach is proposed to determine structurally and functionally important residues in native proteins that are involved in energy exchange with a ligand and other residues along an interaction pathway. The structure-function relationships, ligand binding and allosteric activities of ten structures of HLA Class I proteins of the immune system are studied by the Gaussian Network Model. Five of these models are associated with inflammatory rheumatic disease and the remaining five are properly functioning. In the Gaussian Network Model, the protein structures are modeled as an elastic network where the inter-residue interactions are harmonic. Important residues and the interaction pathways in the proteins are identified by focusing on the largest eigenvalue of the residue interaction matrix. Predicted important residues match those known from previous experimental and clinical work. Graph perturbation is used to determine the response of the important residues along the interaction pathway. Differences in response patterns of the two sets of proteins are identified and their relations to disease are discussed. |
format | Text |
id | pubmed-2900293 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-29002932010-07-13 Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins Haliloglu, Turkan Gul, Ahmet Erman, Burak PLoS Comput Biol Research Article A statistical thermodynamics approach is proposed to determine structurally and functionally important residues in native proteins that are involved in energy exchange with a ligand and other residues along an interaction pathway. The structure-function relationships, ligand binding and allosteric activities of ten structures of HLA Class I proteins of the immune system are studied by the Gaussian Network Model. Five of these models are associated with inflammatory rheumatic disease and the remaining five are properly functioning. In the Gaussian Network Model, the protein structures are modeled as an elastic network where the inter-residue interactions are harmonic. Important residues and the interaction pathways in the proteins are identified by focusing on the largest eigenvalue of the residue interaction matrix. Predicted important residues match those known from previous experimental and clinical work. Graph perturbation is used to determine the response of the important residues along the interaction pathway. Differences in response patterns of the two sets of proteins are identified and their relations to disease are discussed. Public Library of Science 2010-07-08 /pmc/articles/PMC2900293/ /pubmed/20628622 http://dx.doi.org/10.1371/journal.pcbi.1000845 Text en Haliloglu et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Haliloglu, Turkan Gul, Ahmet Erman, Burak Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins |
title | Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins |
title_full | Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins |
title_fullStr | Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins |
title_full_unstemmed | Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins |
title_short | Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins |
title_sort | predicting important residues and interaction pathways in proteins using gaussian network model: binding and stability of hla proteins |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2900293/ https://www.ncbi.nlm.nih.gov/pubmed/20628622 http://dx.doi.org/10.1371/journal.pcbi.1000845 |
work_keys_str_mv | AT halilogluturkan predictingimportantresiduesandinteractionpathwaysinproteinsusinggaussiannetworkmodelbindingandstabilityofhlaproteins AT gulahmet predictingimportantresiduesandinteractionpathwaysinproteinsusinggaussiannetworkmodelbindingandstabilityofhlaproteins AT ermanburak predictingimportantresiduesandinteractionpathwaysinproteinsusinggaussiannetworkmodelbindingandstabilityofhlaproteins |