INTERNAL MOTIONS IN FOLDED AND UNFOLDED STATES OF GBI

This proposal is focused on studying side-chain and backbone motional dynamics in Streptococcal protein G B1 domain by using 13/C and 15/N-NMR relaxation and rotational model analyses. GB1 has only 56 amino acid residues arranged in a fold with a central alpha-helix packed against a four-stranded beta-sheet. Despite its small size, the thermodynamic properties are similar to those observed in larger proteins. GB1 lends itself well to selective 13/C/15/N isotropic enrichment via peptide synthesis and to experimental study using both NMR relaxation-derived auto-and cross-peptide synthesis and to experimental study using both NMR relation-derived auto-and cross-peptide synthesis and to experimental study using both NMR relation-derived auto- and cross-correlation spectral densities for analysis of all backbone and side-chain N-H and C-H motional vectors. The specific aims of this project are: (1) to determine internal motions of all side-chain and backbone positions in unfolded states of GB1, and (3) to develop novel approaches and motional models to analyzes these NMR relaxation data. Most NMR dynamics studies reported to data, while qualitatively informative, are limited to analysis of auto-correlation parameters [usually from a single motional vector in a residue, i.e., backbone 15/N-H or 13/C/alpha-H] derived by using some model free approach. This grant stands apart from previous studies in that it will use both auto- and cross-correlation parameters from all available motional vectors (backbone and side-chain) and various rotational models and model free approaches to provide a more detailed description of motional dynamics in a protein. Dipolar and dipolar-CSA cross-correlation spectral densities, T/1, T/1p, T/2 and heteronuclear NOEs at at least two frequencies will be determined. For backbone motions, 13/C/alpha/H, 13/CO and 15/NH relaxation rates will be measured, while for side-chain motions, 13CH n auto- and cross- correlations will provide unique motional information.