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Prediction of indirect interactions in proteins
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Pharmaceutical Pharmacology. (Proteochemometric group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Pharmaceutical Pharmacology. (Proteochemometric group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Pharmaceutical Pharmacology. (Proteochemometric group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Pharmaceutical Pharmacology. (Proteochemometric group)
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2006 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 7, 167- p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2006. Vol. 7, 167- p.
Keyword [en]
Amino Acid Sequence, Binding Sites, Computer Simulation, Models; Chemical, Molecular Sequence Data, Peptides/*chemistry, Protein Binding, Protein Interaction Mapping/*methods, Receptors; Melanocortin/*chemistry, Sequence Analysis; Protein/*methods
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-104266DOI: 10.1186/1471-2105-7-167PubMedID: 16553946OAI: oai:DiVA.org:uu-104266DiVA: diva2:219582
Available from: 2009-05-28 Created: 2009-05-28 Last updated: 2017-12-13Bibliographically approved

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