Structural Biology Seminar

Computational solvent mapping samples a protein surface for regions of favorable electrostatics, desolvation, and surface complementarity in order to predict, identify, and characterize protein binding sites. Using as probes small organic molecules containing a wide range of functional groups, mapping reveals regions on the protein surface where multiple probe types cluster that often correspond to ligand binding site(s). Additionally, the specific interactions made by the protein with the various probes resemble those occurring between the protein and its natural ligand(s). As part of my doctoral research, I applied this computational methodology to a number of well-characterized proteins, including thermolysin, elastase, haloalkane dehalogenase, protein tyrosine phosphatase 1B, and other glycolytic and proteolytic enzymes in order to validate the method and to investigate numerous structural and biochemical questions pertaining to these proteins. The first part of this work assesses the computational mapping methodology with respect to its ability to correctly simulate the results of experimentally-derived solvent mapping studies and to identify and characterize protein binding sites in both ligand-bound and apostructures. The second part addresses mechanistic and structural questions using mapping to probe protein-ligand affinity and specificity, substrate-access and binding mechanisms, and allosteric interactions and conformational changes. The results demonstrate the versatility of this algorithm in locating and characterizing binding sites as well as investigating the various biochemical properties that underlie molecular recognition.