"Unraveling Mechanisms of RNA Catalysis and Enhancing Drug Discovery with Multiscale Quantum Simulations"
Multiscale modeling methods have transformed the way scientists study complex biomolecular systems. Two areas where these methods have had great impact have been in the study of catalytic mechanisms of protein and more recently nucleic acid enzymes, and in the prediction of free energies, including metal ion and ligand binding affinities, redox potentials and pKa shifts, and the effect of mutations on protein-protein and protein-nucleic acid interactions. This talk will summarize recent advances in the study of enzymes using a computational enzymology approach that integrates a wide range of multiscale computational methods, including ab initio quantum mechanical/molecular mechanical simulations, to elucidate detailed catalytic mechanism. Emphasis is placed on aiding in the interpretation of a wide range of experiments, including X-ray diffraction, NMR, mutagenesis and precision stereospecific chemical modifications, pH and metal ion dependence of kinetics, linear free energy relations and kinetic isotope effects. These methods will be discussed in the context of site-specific RNA-cleaving enzymes, including several recently characterized endonucleolytic ribozyme classes that are of interest as models to understand principles of RNA catalysis. Further, very recent advances and emerging technology for GPU-accelerated alchemical free energy simulations with both classical and quantum mechanical force fields for drug discovery will be discussed. These high-throughput methods enable predictions for lead compounds that target metal ion binding sites in metalloenzymes and covalent inhibitors, and add powerful new drug discovery tools to the AMBER molecular
simulation software suite.
~Coffee/tea will be served prior to lecture~