Comparative molecular studies of physiologically functional molecules, focused on voltage-gated potassium channels and metabotropic serotonin receptors
We have created a database of potassium channels http://vkcdb.biology.ualberta.ca/
that is generally useful for structure/function analyses, and have used that data for a machine learning analysis of how the sequence of channels affects the voltage sensitivity of channel opening. We are also isolating channel homologues from a variety of marine invertebrate phyla. Sequences of these channels differ substantially form the more well characterized vertebrate and model organism channels, and many of them have unusual electrophysiological properties that help to illuminate the general mechanisms of voltage sensitivity. We are using GFP-tagged serotonin receptors to screen combinatorial libraries of small molecules synthesized on solid beads. In first pass screens we have identified compounds whose binding is subtype-specific and species-specific. We are currently evaluating the pharmacological activity of these compounds on an in vivo model system, designing a second round of library synthesis to improve selectivity and affinity, and tagging more receptors to increase the breadth of the screen. We are applying bioinformatic analyses to the data that we obtain in all of our projects. In particular, we are implementing machine learning approaches to decompose the complex relationship between protein sequence and the details of protein function. We are also beginning to apply chemoinformatics methods and machine learning to development of a quantitative structure/function model of receptor/ligand interactions for the serotonin receptors.