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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Multilevel Parallelization of AutoDock 4.2.

Andrew P Norgan1, Paul K Coffman, Jean-Pierre A Kocher

  • 1IBM, Rochester, MN, USA. cpsosa@us.ibm.com.

Journal of Cheminformatics
|April 30, 2011
PubMed
Summary
This summary is machine-generated.

This study presents mpAD4, a parallelized version of AutoDock for faster virtual screening. It significantly reduces computational time for molecular docking by optimizing system-level and node-level parallelization.

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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Bioinformatics

Background:

  • Virtual screening is crucial for drug discovery.
  • AutoDock is a widely used serial software for molecular docking.
  • Previous attempts to parallelize AutoDock have been limited.

Purpose of the Study:

  • To develop a multi-level parallelized version of AutoDock 4.2, named mpAD4.
  • To enhance the computational efficiency of molecular docking simulations.

Main Methods:

  • Parallelization of AutoDock 4.2 using Message Passing Interface (MPI) and OpenMP.
  • Implementation of code to reduce input/output (I/O) traffic by reusing grid maps.
  • Performance evaluation of mpAD4 on multiprocessor systems.

Main Results:

  • mpAD4 demonstrates near-linear scaling on multiprocessor systems.
  • Grid map reuse effectively reduces I/O traffic and overall screening time.
  • OpenMP multithreading accelerates individual docking jobs.

Conclusions:

  • mpAD4 significantly reduces execution time for virtual screening workloads.
  • The software allows users to optimize MPI and OpenMP parallelization for specific resources.
  • This advancement enhances the speed and efficiency of molecular docking in drug discovery.