EXPLORING ENZYMATIC CATALYSIS ALONG EVOLUTION USING QM/MM METHODS

QM/MM methods are a useful strategy for exploring enzymatic reactions. By partitioning in a different theoretical approach, it is possible to distribute computational cost and complexity in large systems. Quantum chemistry methods are known to give good reaction coordinates, and have ample usage in the literature. However, due to computational time restraints, semi-empirical methods like PM6 have been used. These methods also show good results in terms of computational cost, but they have low precision in generating energies. Modern gene synthesis technology allows for the production of ancient proteins, whose sequences can be inferred by ancestral reconstruction. Here we use QM/MM to investigate how an enzymatic reaction varied in different evolutionary periods. Particularly, we investigate modern and ancestral 5-hydroxy-isourate hydrolases, evaluating the changes in energy barriers, the role of residues on the active site and thermodynamic properties along evolution. In the evolutionary history of these proteins we observed, in some primates, a pseudogenization of the hydrolases and in the enzymes responsible for the previous reaction, the Uricases. Essentially, purine metabolism and uric acid degradation both have a complex evolutionary path along vertebrates, where most of them still metabolize these substances. So, could this purine degradation path have some evolutionary pressure to disappear? To evaluate that, we used EasyHybrid/pDynamo for the calculation of energy barriers, while the thermodynamics of the system was assessed by Umbrella Sampling. We also propose a Molecular Mechanics approach using MMPBSA. We obtained barriers that showed low differences in terms of kcal, but using the Eyring equation we could measure better parameters like the kinetic constant, and further increase in theoretical level could give us better results and better precision. Finally, the molecular mechanics approach showed bad affinities when considering entropy contributions, which is hard to simulate. Otherwise, the electrostatic contributions showed consistency in the binding affinities.