Mixed QM MM Methods - MOE and ONIOM
Detailed understanding of electronic effects are critical for properly understanding enzymatic reactions, or processes that occur in solution (as just two examples). However, it remains impractical to apply quantum mechanical (QM) approaches to such large biological systems. As a compromise between computational cost and predictive accuracy, mixed method approaches allow us to rigorously partition a system into regions that are treated classically (using molecular mechanics) and (typically) smaller regions that are treated using QM. This partitioning scheme allows the user to focus the more realistic electronic treatment to where it is most needed, providing the practical balance of accuracy and timeliness. The ONIOM scheme, as implemented in the Gaussian electronic structure package, allows for the partitioning of a system into multiple regions, each of which can employ a different level of theory. In MOE 2020 we have created a simple and intuitive interface to set up ONIOM calculations. Using MOE’s powerful ‘selection language’, the assignment of layers is trivial, as is the creation of all required Gaussian input files. These calculations can leverage the new high-performance compute framework available in MOE 2020 to seamlessly be executed, either locally or remotely, using MOE as a simple front-end to your computational queuing system. During this webinar we provide a brief theoretical orientation to the ONIOM method, followed by a demonstration of how to set up, execute, and analyze ONIOM calculations directly from within the MOE platform.
Airdate: March 18, 2021
