Parallel strategies for an inverse docking method

  • Authors:
  • Romain Vasseur;Stéphanie Baud;Luiz Angelo Steffenel;Xavier Vigouroux;Laurent Martiny;Michaël Krajecki;Manuel Dauchez

  • Affiliations:
  • University of Reims Champagne-Ardenne, France and BULL SAS, Education & Research, Echirolles, France;University of Reims Champagne-Ardenne, France;University of Reims Champagne-Ardenne, France;BULL SAS, Education & Research, Echirolles, France;University of Reims Champagne-Ardenne, France;University of Reims Champagne-Ardenne, France;University of Reims Champagne-Ardenne, France

  • Venue:
  • Proceedings of the 20th European MPI Users' Group Meeting
  • Year:
  • 2013

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Abstract

Molecular docking is a widely used computational technique that allows studying structure-based interactions complexes between biological objects at the molecular scale. The purpose of the current work is to develop a set of tools that allows performing inverse docking, i.e., to test at a large scale a chemical ligand on a large dataset of proteins, which has several applications on the field of drug research. We developed different strategies to parallelize/distribute the docking procedure, as a way to efficiently exploit the computational performance of multi-core and multi-machine (cluster) environments. The experiments conducted to compare these different strategies encourage the search for decomposing strategies as a way to improve the execution of inverse docking.