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Prediction of indirect interactions in proteins

BACKGROUND: Both direct and indirect interactions determine molecular recognition of ligands by proteins. Indirect interactions can be defined as effects on recognition controlled from distant sites in the proteins, e.g. by changes in protein conformation and mobility, whereas direct interactions oc...

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Autores principales: Prusis, Peteris, Uhlén, Staffan, Petrovska, Ramona, Lapinsh, Maris, Wikberg, Jarl ES
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1435945/
https://www.ncbi.nlm.nih.gov/pubmed/16553946
http://dx.doi.org/10.1186/1471-2105-7-167
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author Prusis, Peteris
Uhlén, Staffan
Petrovska, Ramona
Lapinsh, Maris
Wikberg, Jarl ES
author_facet Prusis, Peteris
Uhlén, Staffan
Petrovska, Ramona
Lapinsh, Maris
Wikberg, Jarl ES
author_sort Prusis, Peteris
collection PubMed
description BACKGROUND: Both direct and indirect interactions determine molecular recognition of ligands by proteins. Indirect interactions can be defined as effects on recognition controlled from distant sites in the proteins, e.g. by changes in protein conformation and mobility, whereas direct interactions occur in close proximity of the protein's amino acids and the ligand. Molecular recognition is traditionally studied using three-dimensional methods, but with such techniques it is difficult to predict the effects caused by mutational changes of amino acids located far away from the ligand-binding site. We recently developed an approach, proteochemometrics, to the study of molecular recognition that models the chemical effects involved in the recognition of ligands by proteins using statistical sampling and mathematical modelling. RESULTS: A proteochemometric model was built, based on a statistically designed protein library's (melanocortin receptors') interaction with three peptides and used to predict which amino acids and sequence fragments that are involved in direct and indirect ligand interactions. The model predictions were confirmed by directed mutagenesis. The predicted presumed direct interactions were in good agreement with previous three-dimensional studies of ligand recognition. However, in addition the model could also correctly predict the location of indirect effects on ligand recognition arising from distant sites in the receptors, something that three-dimensional modelling could not afford. CONCLUSION: We demonstrate experimentally that proteochemometric modelling can be used with high accuracy to predict the site of origin of direct and indirect effects on ligand recognitions by proteins.
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spelling pubmed-14359452006-04-21 Prediction of indirect interactions in proteins Prusis, Peteris Uhlén, Staffan Petrovska, Ramona Lapinsh, Maris Wikberg, Jarl ES BMC Bioinformatics Research Article BACKGROUND: Both direct and indirect interactions determine molecular recognition of ligands by proteins. Indirect interactions can be defined as effects on recognition controlled from distant sites in the proteins, e.g. by changes in protein conformation and mobility, whereas direct interactions occur in close proximity of the protein's amino acids and the ligand. Molecular recognition is traditionally studied using three-dimensional methods, but with such techniques it is difficult to predict the effects caused by mutational changes of amino acids located far away from the ligand-binding site. We recently developed an approach, proteochemometrics, to the study of molecular recognition that models the chemical effects involved in the recognition of ligands by proteins using statistical sampling and mathematical modelling. RESULTS: A proteochemometric model was built, based on a statistically designed protein library's (melanocortin receptors') interaction with three peptides and used to predict which amino acids and sequence fragments that are involved in direct and indirect ligand interactions. The model predictions were confirmed by directed mutagenesis. The predicted presumed direct interactions were in good agreement with previous three-dimensional studies of ligand recognition. However, in addition the model could also correctly predict the location of indirect effects on ligand recognition arising from distant sites in the receptors, something that three-dimensional modelling could not afford. CONCLUSION: We demonstrate experimentally that proteochemometric modelling can be used with high accuracy to predict the site of origin of direct and indirect effects on ligand recognitions by proteins. BioMed Central 2006-03-22 /pmc/articles/PMC1435945/ /pubmed/16553946 http://dx.doi.org/10.1186/1471-2105-7-167 Text en Copyright © 2006 Prusis et al; licensee BioMed Central Ltd.
spellingShingle Research Article
Prusis, Peteris
Uhlén, Staffan
Petrovska, Ramona
Lapinsh, Maris
Wikberg, Jarl ES
Prediction of indirect interactions in proteins
title Prediction of indirect interactions in proteins
title_full Prediction of indirect interactions in proteins
title_fullStr Prediction of indirect interactions in proteins
title_full_unstemmed Prediction of indirect interactions in proteins
title_short Prediction of indirect interactions in proteins
title_sort prediction of indirect interactions in proteins
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1435945/
https://www.ncbi.nlm.nih.gov/pubmed/16553946
http://dx.doi.org/10.1186/1471-2105-7-167
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