There has been a recent flurry of research on the identification and characterization of a number of new small self-cleaving ribozymes, most notably, the twister ribozyme. In addition to a number of crystallographic structures, a wide array of biochemical experiments have been performed and yet a unified model for the active state in solution remains elusive. Here we present a holistic approach to computational RNA enzymology and its application to the twister ribozyme, in order to develop such a unified model that is consistent will all of the available experimental data. First and foremost, a careful analysis of each currently available crystallographic structure was performed in an effort minimize the impact of crystal packing contacts and deactivating mutations on simulations of the active ribozyme in solution. Next a wide array of GPU-accelerated molecular dynamics simulations and free energy calculations were completed and allowed for the development of a mechanistic model consistent with the available experimental data. These simulations explored the structure and dynamics of the twister ribozyme in solution at various points along the reaction pathway, and provided predictions for the pK<sub>a</sub> of active site nucleobases directly participating in catalysis.  The reaction kinetics of a variety of mechanistic models were then explored with <i>ab initio</i> QM/MM simulations and a number of experimentally testable predictions (e.g. kinetic isotope effects, mutations of the catalytic nucleobases, etc.) were developed. In summary, we present the first end-to-end computational study of a small nucleolytic ribozyme and highlight the need for close integration of theory and experiment.

Computational RNA enzymology: Unravelling the catalytic mechanism of the twister ribozyme

255th National Meeting (2018)

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