0

Full Content is available to subscribers

Subscribe/Learn More  >

A Robust Framework for Adaptive Multiscale Modeling of Biopolymers Using Highly Parallelizable Methods

[+] Author Affiliations
Imad M. Khan, Kurt S. Anderson

Rensselaer Polytechnic Institute, Troy, NY

Paper No. NEMB2013-93099, pp. V001T05A008; 2 pages
doi:10.1115/NEMB2013-93099
From:
  • ASME 2013 2nd Global Congress on NanoEngineering for Medicine and Biology
  • ASME 2013 2nd Global Congress on NanoEngineering for Medicine and Biology
  • Boston, Massachusetts, USA, February 4–6, 2013
  • Conference Sponsors: Nanotechnology Institute, Bioengineering Division
  • ISBN: 978-0-7918-4533-2
  • Copyright © 2013 by ASME

abstract

For many biopolymers (RNA, DNA, enzymes and proteins) the nature of the molecules interaction within the cell has been determined to be highly a function of its conformational structure. Understanding how to influence and control this structure thus is of critical importance if one wishes to manipulate the intercellular processes of which these biopolymers play such a central role. In molecular dynamics (MD) simulations, a fully atomistic model represents the system at the finest scale and as such captures all the dynamics of the system. If the simulation is permitted to run sufficiently long important emergent behaviors can develop and show themselves. Such MD simulations represent a direct applications of Newton’s Laws of Motion to the individual atoms in the system, and are conceptually the easiest to implement. An advantage of this procedure is that the simulation yields important information not only about the intermediate states and the mechanisms which produced them, but also provides the rates at which these processes occur. These intermediate conformational states have repeatedly been implicated in many known biological function [1], [2]. Unfortunately, this albeit correct, but naive approach quickly leads to intractable models and prohibitive computational expense when applied to systems involving many atoms. As a result, researcher often grossly over simplify the system move to non-deterministic methods such as Monte Carlo, which effectively remove dynamics from the system, or use undesirably gross model simplification. Because of these forward dynamics performance difficulties, potentially important mechanisms governing biopolymer structure have not been adequately explored and/or identified. The methods and algorithms described in this paper are intended to extend the capabilities of the simulation techniques for such systems so that the forward dynamics can better predict the non-equilibrium behavior of these systems, thus complementing Monte Carlo, while retaining much useful intermediate process and temporal information.

Copyright © 2013 by ASME

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In