  Fragment Molecular Orbital (FMO) calculations provide a framework to speed up
quantum mechanical calculations and so can be used to explore structure-energy
relationships in large and complex biomolecular systems. These calculations are
still onerous, especially when applied to large sets of molecules. Therefore,
cyberinfrastructure that provides mechanisms and user interfaces that manage
job submissions, failed job resubmissions, data retrieval, and data storage for
these calculations are needed. Motivated by the need to rapidly identify drugs
that are likely to bind to targets implicated in SARS-CoV-2, the virus that
causes COVID-19, we developed a static parameter sweeping framework with Apache
Airavata middleware to apply to complexes formed between SARS-CoV-2 M-pro (the
main protease in SARS-CoV-2) and 2820 small-molecules in a drug-repurposing
library. Here we describe the implementation of our framework for managing the
executions of the high-throughput FMO calculations. The approach is general and
so should find utility in large-scale FMO calculations on biomolecular systems.
