Computational characterization of protein hot spots
Zerbe, Brandon S.
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Protein hot spots provide a large portion of the binding free energy during interact ions, and detecting and characterizing these hot spot regions provides insight that can be used in the development of novel drugs for t he purpose of regulating pathological pathways. In t his dissertation, I first compare t he FTMap algorithm, which detects hot spots by identifying locations where different simulated solvent-sized molecules are consistently found to have favorable interactions, to experimental methods that detect hot spots by alternative means. Specifically, I show that FTMap detects the hot spots detected by alanine scanning, and I discover two roles for residues near hot spots in protein-protein interaction (PPI) complexes. Furthermore, additional insights into the binding energetics of PPis are uniquely provided by FTMap, and these insights are important for drug-design. FTMap is then shown to detect the hot spots identified by successful fragment-screening experiments, and the additional sites detected by FTMap are shown to provide insight into the optimal regions for ligand extension for the molecules identified by t he fragment-screening experiment. Since binding sites are composed of multiple hot spots, we have recently used FTMap for binding site detection. I examine the highly accurate binding site detection algorithm, show that the success of this algorithm is a consequence of only a portion of the scoring protocol, and develop a faster protocol for binding site detection based on this insight. I also quantitate the improvement in precision obtained by using multiple probes and argue t hat the principle biophysical considerations in hot spot detection are hydrophobicity and complexity. Finally, I develop a functional-group clustering algorithm, which is informative for evaluation of the binding locations of pre-determined chemical moieties. I then provide evidence that other approaches employing FTMap results may lead to insight into selectivity. I conclude with a discussion on the nature of hot spots, and I suggest that evolutionary studies of protein divergence should provide insight into the emergence of chemical-selectivity thus providing biophysical insight into the factors that drive selectivity within hot spots.
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