Enhanced Van der Waals calculations in genetic algorithms for protein structure prediction. (14th August 2012)
- Record Type:
- Journal Article
- Title:
- Enhanced Van der Waals calculations in genetic algorithms for protein structure prediction. (14th August 2012)
- Main Title:
- Enhanced Van der Waals calculations in genetic algorithms for protein structure prediction
- Authors:
- Bonetti, Daniel R.F.
Delbem, Alexandre C.B.
Travieso, Gonzalo
de, Paulo Sergio L. - Abstract:
- <abstract abstract-type="main" id="cpe2913-abs-0001"> <title>SUMMARY</title> <p id="cpe2913-para-0001">Several <italic>ab initio</italic> computational methods for protein structure prediction have been designed using full‐atom models and force field potentials to describe interactions among atoms. Those methods involve the solution of a combinatorial problem with a huge search space. Genetic algorithms (GAs) have shown significant performance increases for such methods. However, even a small protein may require hundreds of thousands of energy function evaluations making GAs suitable only for the prediction of very small proteins. We propose an efficient technique to compute the van der Waals energy (the greatest contributor to protein stability) speeding up the whole GA. First, we developed a Cell‐List Reconstruction procedure that divides the tridimensional space into a cell grid for each new structure that the GA generates. The cells restrict the calculations of van der Waals potentials to ranges in which they are significant, reducing the complexity of such calculations from quadratic to linear. Moreover, the proposal also uses the structure of the cell grid to parallelize the computation of the van der Waals energy, achieving additional speedup. The results have shown a significant reduction in the run time required by a GA. For example, the run time for the prediction of a protein with 147, 980 atoms can be reduced from 217 days to 7 h. Copyright © 2012 John Wiley<abstract abstract-type="main" id="cpe2913-abs-0001"> <title>SUMMARY</title> <p id="cpe2913-para-0001">Several <italic>ab initio</italic> computational methods for protein structure prediction have been designed using full‐atom models and force field potentials to describe interactions among atoms. Those methods involve the solution of a combinatorial problem with a huge search space. Genetic algorithms (GAs) have shown significant performance increases for such methods. However, even a small protein may require hundreds of thousands of energy function evaluations making GAs suitable only for the prediction of very small proteins. We propose an efficient technique to compute the van der Waals energy (the greatest contributor to protein stability) speeding up the whole GA. First, we developed a Cell‐List Reconstruction procedure that divides the tridimensional space into a cell grid for each new structure that the GA generates. The cells restrict the calculations of van der Waals potentials to ranges in which they are significant, reducing the complexity of such calculations from quadratic to linear. Moreover, the proposal also uses the structure of the cell grid to parallelize the computation of the van der Waals energy, achieving additional speedup. The results have shown a significant reduction in the run time required by a GA. For example, the run time for the prediction of a protein with 147, 980 atoms can be reduced from 217 days to 7 h. Copyright © 2012 John Wiley &amp; Sons, Ltd.</p> </abstract> … (more)
- Is Part Of:
- Concurrency and computation. Volume 25:Number 15(2013:Oct.)
- Journal:
- Concurrency and computation
- Issue:
- Volume 25:Number 15(2013:Oct.)
- Issue Display:
- Volume 25, Issue 15 (2013)
- Year:
- 2013
- Volume:
- 25
- Issue:
- 15
- Issue Sort Value:
- 2013-0025-0015-0000
- Page Start:
- 2170
- Page End:
- 2186
- Publication Date:
- 2012-08-14
- Subjects:
- Parallel processing (Electronic computers) -- Periodicals
Parallel computers -- Periodicals
004.35 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/cpe.2913 ↗
- Languages:
- English
- ISSNs:
- 1532-0626
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3405.622000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 4109.xml