Smart execution of molecular docking simulations of a fully-flexible receptor model

Abstract

Molecular docking simulations of Fully-Flexible Receptor (FFR) models are coming of age. However, they demand parallelization of computing activities for their executions and generate huge amounts of data that needs to be analyzed. Many Task Computing (MTC) is an attractive paradigm routinely applied to execute intensive tasks. In this work we propose an environment to execute molecular docking simulations of FFR models to small molecules integrated with an MTC middleware. This environment is based on a new pattern called Self-adapting Multiple Instances (P-SaMI) that provide rules to reduce the number of experiments, providing a Reduced Fully-Flexible Receptor (RFFR) model. The main contribution of this research is to prove that P-SaMI rules can be used on Molecular Docking Simulations through a web environment integrated with an MTC middleware.