A novel approach for large-scale polypeptide folding based on elastic networks using continuous optimization

Rakshit, Sourav and Ananthasuresh, GK (2010) A novel approach for large-scale polypeptide folding based on elastic networks using continuous optimization. In: Journal of Theoretical Biology, 262 (3). pp. 488-497.

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Abstract

We present a new computationally efficient method for large-scale polypeptide folding using coarse-grained elastic networks and gradient-based continuous optimization techniques. The folding is governed by minimization of energy based on Miyazawa–Jernigan contact potentials. Using this method we are able to substantially reduce the computation time on ordinary desktop computers for simulation of polypeptide folding starting from a fully unfolded state. We compare our results with available native state structures from Protein Data Bank (PDB) for a few de-novo proteins and two natural proteins, Ubiquitin and Lysozyme. Based on our simulations we are able to draw the energy landscape for a small de-novo protein, Chignolin. We also use two well known protein structure prediction software, MODELLER and GROMACS to compare our results. In the end, we show how a modification of normal elastic network model can lead to higher accuracy and lower time required for simulation.

Item Type:	Journal Article
Publication:	Journal of Theoretical Biology
Publisher:	Elsevier Science
Additional Information:	Copyright of this article belongs to Elsevier Science.
Keywords:	MJ potential; Native state; Energy modeling; Folding funnel; Protein folding; Rigid body
Department/Centre:	Division of Mechanical Sciences > Mechanical Engineering
Date Deposited:	15 Jul 2010 06:29
Last Modified:	24 Oct 2011 05:00
URI:	http://eprints.iisc.ac.in/id/eprint/28902

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