Efficient coarse-grained molecular simulations in the multibody dynamics scheme

Mohammad Poursina, Kurt S. Anderson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations


The numerical simulation of highly complex biomolecular systems such as DNAs, RNAs, and proteins become intractable as the size and fidelity of these systems increase. Herein, efficient techniques to accelerate multibody-based coarsegrained simulations of such systems are presented. First, an adaptive coarse-graining framework is explained which is capable of determining when and where the system model needs to change to achieve an optimal combination of speed and accuracy. The metrics to guide these on-the-fly instantaneous model adjustments and the issues associated with post-transition system's states are addressed in this book chapter. Due to its highly modular and parallel nature, the Generalized Divide-and- Conquer Algorithm (GDCA) forms the bases for a suite of dynamics simulation tools used in this work. For completeness, the fundamental aspects of the GDCA are presented herein. Finally, a novel method for the efficient and accurate approximation of far-field force and moment terms are developed. This aspect is key to the success of any large molecular simulation since more than 90 % of the computational load in such simulations is associated with pairwise force calculations. The presented approximations are efficient, accurate, and highly compatible with multibody-based coarse-grained models.

Original languageEnglish (US)
Title of host publicationComputational Methods in Applied Sciences
PublisherSpringer Netherland
Number of pages26
ISBN (Print)9789400754034
StatePublished - 2013
Externally publishedYes
EventECCOMAS Thematic Conference on Multibody Dynamics, 2003 - Barcelona, Spain
Duration: Jun 30 2003Jul 3 2003

Publication series

NameComputational Methods in Applied Sciences
ISSN (Print)18713033


OtherECCOMAS Thematic Conference on Multibody Dynamics, 2003

ASJC Scopus subject areas

  • Computational Mathematics
  • Modeling and Simulation
  • Fluid Flow and Transfer Processes
  • Computer Science Applications
  • Civil and Structural Engineering
  • Electrical and Electronic Engineering
  • Biomedical Engineering

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