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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...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2006
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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. |
format | Text |
id | pubmed-1435945 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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