A Cloud-Based Workflow Approach for Optimizing Molecular Docking Simulations of Fully-Flexible Receptor Models and Multiple Ligands

The use of conformations achieved from MolecularDynamics (MD) simulations in docking experiments is the mostaccurate approach to simulate the natural interactions betweenreceptor and ligands at molecular environments. However, suchsimulations are computational costly and their overall executionmay become unfeasible due to the large quantities of structuralinformation needed to represent a Fully-Flexible Receptor (FFR) model. The problem is even more challenging when FFR modelsare used to perform docking-based virtual screening in a largedatabase of ligands. This study aims at developing a cloud-basedworkflow to efficiently optimize docking experiments betweena FFR model and multiple ligands in two strategic ways: bydiscarding groups of unpromising MD conformations for specificligands at docking execution time, and by exploiting on-demandresources from the Microsoft Azure cloud platform. The proposedenvironment is built on e-Science Central, which is a powerfulcloud-based workflow enactment system designed to handlescientific high-throughput tasks. As a result, we expect to reducethe number of docking experiments per ligand without affectingthe quality of the produced models and, therefore, considerablydecreasing the time consumed by docking experiments.