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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 MC_1,3-5Rs and 15 multichimeric MCRs, each of the latter being constructed from three sequence segments, each taken from a different wild-type MC_1,3-5R. 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.