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Proteochemometric modeling reveals the interaction site for Trp9 modified alpha-MSH peptides in melanocortin receptors
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Proteochemometric group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Proteochemometric group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Proteochemometric group)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Proteochemometric group)
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2007 (English)In: Proteins: Structure, Function, and Genetics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 67, no 3, 653-660 p.Article in journal (Refereed) Published
Abstract [en]

The interactions of α-MSH peptides with melanocortin receptors (MCRs) were located by proteochemometric modeling. Nine α-MSH peptide analogues were constructed by exchanging the Trp9 residue in the α-MSH core with the natural or artificial amino acids Arg, Asp, Cys, Gly, Leu, Nal, d-Nal, Pro, or d-Trp. The nine peptides created, and α-MSH itself, were evaluated for their interactions with the 4 wild-type MC1,3-5Rs and 15 multichimeric MCRs, each of the latter being constructed from three sequence segments, each taken from a different wild-type MC1,3-5R. The segments of the chimeric MCRs were selected according to the principles of statistical molecular design and were arranged so as to divide the receptors into five parts. By this approach, a set of 19 maximally diverse MC receptor proteins was obtained for which the interaction activity with the 10 peptides were measured by radioligand binding thus creating data for 190 ligand-protein pairs, which were subsequently analyzed by use of proteochemometric modeling. In proteochemometrics, the structural or physicochemical properties of both interaction partners, which represent the complementarity of the interacting entities, are used to create multivariate mathematical descriptions. (Here, physicochemical property descriptors of the receptors' and peptides' amino acids were used). A valid, highly predictive (Q2 = 0.74) and easily interpretable model was then obtained. The model was further validated by its ability to correctly predicting the affinity of α-MSH for new point and cassette-mutated MC4/MC1RS, and it was then used to identify the receptor residues that are important for affording the high affinity and selectivity of α-MSH for the MC1R. It was revealed that these residues are located in several quite distant parts of the receptors' transmembrane cavity and must therefore cause their influence at various stages of the dynamic ligand-binding process, such as by affecting the conformation of the ligand at the vicinity of the receptor and taking part in the path of the ligand's entry into its binding pocket. Our study can be used as a template how to create high resolution proteochemometric models when there are a limited number of natural proteins and ligands available.

Place, publisher, year, edition, pages
2007. Vol. 67, no 3, 653-660 p.
Keyword [en]
G-protein-coupled receptors, melanocortin receptors, peptide library, multipart chimeric receptors, experimental design, proteochemometrics
National Category
Pharmaceutical Sciences
URN: urn:nbn:se:uu:diva-95044DOI: 10.1002/prot.21323ISI: 000245743100014PubMedID: 17357163OAI: oai:DiVA.org:uu-95044DiVA: diva2:169104
Available from: 2006-11-03 Created: 2006-11-03 Last updated: 2011-02-04Bibliographically approved
In thesis
1. Development of Proteochemometrics—A New Approach for Analysis of Protein-Ligand Interactions
Open this publication in new window or tab >>Development of Proteochemometrics—A New Approach for Analysis of Protein-Ligand Interactions
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A new approach to analysis of protein-ligand interactions, termed proteochemometrics, has been developed. Contrary to traditional quantitative structure-activity relationship (QSAR) methods that aim to correlate a description of ligands to their interactions with one particular target protein, proteochemometrics considers many targets simultaneously.

Proteochemometrics thus analyzes the experimentally determined protein-ligand interaction activity data by correlating the data to a complex description of all interaction partners and; in a more general case even to interaction environment and assaying conditions, as well. In this way, a proteochemometric model analyzes an “interaction space,” from which only one cross-section would be contemplated by any one QSAR model.

Proteochemometric models reveal the physicochemical and structural properties that are essential for protein-ligand complementarity and determine specificity of molecular interactions. From a drug design perspective, models may find use in the design of drugs with improved selectivity and in the design of drugs for multiple targets, such as mutated proteins (e.g., drug resistant mutations of pathogens).

In this thesis, a general concept for creating of proteochemometric models and approaches for validation and interpretation of models are presented. Different types of physicochemical and structural description of ligands and macromolecules are evaluated; mathematical algorithms for proteochemometric modeling, in particular for analysis of large-scale data sets, are developed. Artificial chimeric proteins constructed according to principles of statistical design are used to derive high-resolution models for small classes of proteins.

The studies of this thesis use data sets comprising ligand interactions with several families of G protein-coupled receptors. The presented approach is, however, general and can be applied to study molecular recognition mechanisms of any class of drug targets.

Place, publisher, year, edition, pages
Uppsala: Institutionen för farmaceutisk biovetenskap, 2006. 64 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 40
Pharmaceutical pharmacology, chemometrics, QSAR, G-protein coupled receptors, Melanocortin receptors, protein-ligand interactions, Farmaceutisk farmakologi
urn:nbn:se:uu:diva-7211 (URN)91-554-6695-8 (ISBN)
Public defence
2006-11-24, B21, BMC, Husargatan 3, Uppsala, 09:15
Available from: 2006-11-03 Created: 2006-11-03Bibliographically approved

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