This project focuses on deciphering the complexities of molecular recognition at a peptide 7TM receptor, the angiotensin AT1 receptor, by an integration of the information derived from analog preparation, 3D QSAR, receptor modeling and receptor mutational studies. Integration of such studies is uniquely positioned to provide insight into the molecular details of interaction of AT agonists and antagonists with their specific sites, ant to develop novel classes of non-peptide agonists and antagonists of AT to validate this understanding. It is the goal of this project ot extract the encoded information on receptor transduction inherent in the large amount of SAR data which has been gathered. The 3D model of the peptide pharmacophore of angiotensin (AT) will be employed to design peptide and non-peptide AT agonists and antagonists presumably binding to the same receptor subsite. To achieve these goals, we intend to implement the following steps: (1) Develop a reliable model for the AT agonist peptide pharmacophore to be the basis for design of new constrained peptide analogs of AT. These analogs will be synthesized using unnatural, chimeric, amino acids. Synthesized analogs will be tested for binding to AT1 and AT2 receptors as well as agonist activity in the rat aorta assay. (2) To check the relevance of suggested model(s) of the AT pharmacophore, we will use an independent approach, based on molecular recognition procedures. We will develop and employ a refined 3D model of the AT1 seven transmembrane receptor to find best matches for various AT conformers considering as candidates for the pharmacophore model. The same molecular recognition procedures will be validated on the X-ray data on MAb-131 antibody to find the AT conformer with the best match to the antibody. (3) We intend to use the emerging models of AT pharmacophore to develop 3D QSAR models (ComFA) distinguishing AT agonists from antagonists. (4) After developing pharmacophore models for AT peptide agonists and antagonists, we will proceed with design of non-peptide compounds. The general result should allow us to design non-peptide AT agonists bearing the same functional groups responsible for efficacy, as the parent peptide. We will modify these groups to create non-peptide AT antagonists. Interaction of AT analogs with the receptor model will be tested by mutational analysis of the receptor. By iterative employing molecular modeling, analog design and synthesis, 3D QSAR analysis with experimental measurement of affinity for specific receptors and their mutants, a self- consistent view of molecular recognition of AT agonists and antagonists will be derived. At the same time, we will gain insight into the allosteric model of G-protein coupled receptors.
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