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

The use of conformations achieved from Molecular Dynamics (MD) simulations in docking experiments is the most accurate approach to simulate the natural interactions between receptor and ligands at molecular environments. However, such simulations are computational costly and their overall execution may become unfeasible due to the large quantities of structural information needed to represent a Fully-Flexible Receptor (FFR) model. The problem is even more challenging when FFR models are used to perform docking-based virtual screening in a large database of ligands. This study aims at developing a cloud-based workflow to efficiently optimize docking experiments between a FFR model and multiple ligands in two strategic ways: by discarding groups of unpromising MD conformations for specific ligands at docking execution time, and by exploiting on-demand resources from the Microsoft Azure cloud platform. The proposed environment is built on e-Science Central, which is a powerful cloud-based workflow enactment system designed to handle scientific high-throughput tasks. As a result, we expect to reduce the number of docking experiments per ligand without affecting the quality of the produced models and, therefore, considerably decreasing the time consumed by docking experiments.