Understanding the molecular origin of enzyme catalysis is one of the most fundamental problems in biochemistry. We propose a continuation of our long-range project aimed at finding a quantitative way of correlating the structures of enzyme-substrate complexes and their catalytic activities. We are aiming at reaching the stage needed for predicting the effect of specific genetic modifications. Previously, we developed methods capable of evaluating the activation energies of enzymatic reactions and the corresponding reactions in solutions. These approaches indicated that the catalytic energy can be correlated with the difference between the electrostatic (solvation) energies of the relevant resonance structures in the protein active site and in solution. Thus we dedicated a significant effort to the examination of the performance of our electrostatic models, calculating the intrinsic pKa's of the acidic groups of BPTI. This study indicated that our models have reached the level of qualitative estimate of catalytic energies, but a concerted major effort is needed to achieve a more quantitative level. We propose to increase the predictive power of our models by the following studies; (i) Performing an extensive reparameterization of the intermolecular interactions potential by fitting calculated and observed properties of amino acid crystals, taking into account the microscopic dielectric effect due to the atomic induced dipoles. Iii) Increasing the reliability of our Protein Dipoles Langevin Dipoled (PDLD) electrostatic model by averaging its energy over the protein configurations. This will be done by a hierarchy of approaches including a molecular dynamics simulation of a system composed of the protein with a limited number of all-atom model of water molecules surrounded by Langevin dipples. Our static models indicate that there might be a linear relationship between the activation free energies and the corresponding free energies of the relevant resonance structures. The validity of this crucial assumption will be examined by molecular dynamics simulation of the activation free energies for proton transfer reactions in proteins. In parallel to our fundamental studies we will start to explore the predictive power of our models by simulating the effect of site-directed mutagenesis on rate enhancement of enzymatic reactions.
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