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Proteochemometric analysis of small cyclic peptides' interaction with wild-type and chimeric melanocortin receptors
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
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2007 (English)In: Proteins: Structure, Function, and Genetics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 69, no 1, 83-96 p.Article in journal (Refereed) Published
Abstract [en]

The melanocortin (MC) system confines unique G-protein coupled receptor pathways, which include the MC1-5 receptors and their endogenous agonists and antagonists, the MCs and the agouti and agouti-related proteins. The MC4 receptor is an important target for development of drugs for treatment of obesity and cachexia. While natural MC peptides are selective for the MC1 receptor, some cyclic pentapeptides, such as the HS-129 peptide, show high selectivity for the MC4 receptor. Here we gained insight into the mechanisms for its recognition by MC receptors. To this end we correlated the interaction data of four HS peptide analogues with four wild-type and 14 multiple chimeric MC receptors to the binary and physicochemical descriptions of the studied entities by use of partial least squares regression, which resulted in highly valid proteochemometric models. Analysis of the models revealed that the recognition sites of the HS peptides are different from the earlier proteochemometrically mapped linear MSH peptides' recognitions sites, although they overlap partially. The analysis also revealed important amino acids that explain the selectivity of the HS-129 peptide for the MC4 receptor.

Place, publisher, year, edition, pages
2007. Vol. 69, no 1, 83-96 p.
Keyword [en]
proteochemometrics, G-protein coupled receptors, multipart chimeric receptors, melanocortin receptors, HS peptides, recognition site, selectivity
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-97331DOI: 10.1002/prot.21461ISI: 000249189000009PubMedID: 17557335OAI: oai:DiVA.org:uu-97331DiVA: diva2:172218
Available from: 2008-05-15 Created: 2008-05-15 Last updated: 2011-01-25Bibliographically approved
In thesis
1. Modeling the Interaction Space of Biological Macromolecules: A Proteochemometric Approach: Applications for Drug Discovery and Development
Open this publication in new window or tab >>Modeling the Interaction Space of Biological Macromolecules: A Proteochemometric Approach: Applications for Drug Discovery and Development
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Molecular interactions lie at the heart of myriad biological processes. Knowledge of molecular recognition processes and the ability to model and predict interactions of any biological molecule to any chemical compound are the key for better understanding of cell functions and discovery of more efficacious medicines.

This thesis presents contributions to the development of a novel chemo-bioinformatics approach called proteochemometrics; a general method for interaction space analysis of biological macromolecules and their ligands. In this work we explore proteochemometrics-based interaction models over broad groups of protein families, evaluate their validity and scope, and compare proteochemometrics to traditional modeling approaches.

Through the proteochemometric analysis of large interaction data sets of multiple retroviral proteases from various viral species we investigate complex mechanisms of drug resistance in HIV-1 and discover general physicochemical determinants of substrate cleavage efficiency and binding in retroviral proteases. We further demonstrate how global proteochemometric models can be used for design of protease inhibitors with broad activity on drug-resistant viral mutants, for monitoring drug resistance mechanisms in the physicochemical sense and prediction of potential HIV-1 evolution trajectories. We provide novel insights into the complexity of HIV-1 protease specificity by constructing a generalized IF-THEN rule model based on bioinformatics analysis of the largest set of HIV-1 protease substrates and non-substrates.

We discuss how proteochemometrics can be used to map recognition sites of entire protein families in great detail and demonstrate how it can incorporate target variability into drug discovery process. Finally, we assess the utility of the proteochemometric approach in evaluation of ADMET properties of drug candidates with a special focus on inhibition of cytochrome P450 enzymes and investigate application of the approach in the pharmacogenomics field.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2008. 77 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 444
Keyword
Bioinformatics, proteochemometrics, bioinformatics, chemoinformatics, chemical space, QSAR, retroviral proteases, HIV-1, drug resistance, pharmacogenomics, cytochrome P450, GPCRs, melanocortin receptors, interactome, machine-learning, rough sets, Bioinformatik
Identifiers
urn:nbn:se:uu:diva-8916 (URN)978-91-554-7229-0 (ISBN)
Public defence
2008-06-04, C10:305, BMC, Husargatan 3, Uppsala, 09:00
Opponent
Supervisors
Available from: 2008-05-15 Created: 2008-05-15Bibliographically approved

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