Colin Smith, MD - US grants

The human immunodeficiency virus (HIV), a lentivirus, is an important target of anti-AIDS therapy. An essential step of the HIV lifecycle, and therefore a potential anti-HIV target, is transcriptional transactivation in which the HIV Tat protein recognizes the HIV TAR hairpin by weak but specific binding of its arginine-rich domain, with the participation of a cellular factor binding the TAR loop to stabilize the interaction. In contrast, bovine immunodeficiency virus (BIV) Tat recognizes BIV TAR with high affinity by its arginine-rich domain, with no requirement for cellular factors. Solution state modeling of HIV TAR-argininamide and BIV TAR-peptide complexes derived from NMR data indicate no obvious reason why BIV peptide cannot bind to HIV TAR with the same high affinity as to BIV TAR. Biochemical analysis indicates that HIV TAR is defective for BIV peptide binding because of sequences flanking the binding site. As a result of these studies, we have found TARs and peptides that can function with both HIV and BIV Tats and TARs, respectively. We are using these bifunctional molecules to explore the inhibition of lentiviral transactivation and to direct our search for peptides that will inhibit HIV transactivation and have anti-AIDS therapeutic potential. Our project relies upon visualization of NMR-derived and constructed models for rational design. The Computer Graphics Lab provides access to MidasPlus which we use to visualize existing models and help interpret how designed peptides bind to HIV TAR.

PROJECT SUMMARY/ABSTRACT To advance the understanding of atomic-level mechanisms behind critical protein functions like enzyme catalysis and allosteric regulation, it is important to first elucidate a true representation of the protein in solution. In an effort to achieve this long term goal, we will use the recently developed Kinetic Ensemble approach to transform the way in which nuclear magnetic resonance (NMR) data is computationally modeled to solve protein structures and measure protein motions. NMR is one of the most powerful techniques for elucidating the structure and dynamics of proteins. It enables their study in solution (unlike x-ray crystallography) and can capture critical structural rearrangements as they happen at room temperature (unlike cryo-electron microscopy). However, despite these advantages, there have been relatively few practical improvements to one of the foundational aspects behind the way protein structures are solved, namely the calculation of interatomic distances from nuclear Overhauser effect (NOE) experiments. Such methods have remained largely qualitative, resulting in large uncertainties in the atomic positions for most NMR structures. Also, the field has almost completely ignored how angular motion and kinetics affect the NOE, resulting in atoms appearing much further away from one another than they actually are. To overcome these significant deficiencies, we will implement and test new Kinetic Ensemble-based refinement algorithms that are considerably more accurate and physically realistic than previous approaches, accounting for both angular motion and kinetics. To eliminate a significant fraction of the systematic and random structural errors resulting from poorly quantified NMR spectra, we will also integrate advances made by the FitNMR peak quantification software recently developed by our lab. These methods will be used to create better experimental NMR structures, more exhaustive models of side chain dynamics, and determine differences between solution and crystal states with unprecedented detail. This work will allow much more accurate determination of the structural dynamics in parts of the protein exhibiting significant fluctuations, including protein active sites, regulatory regions, and hidden binding sites. Such knowledge will advance our fundamental understanding of protein biophysics and facilitate rational design of new therapeutics.