A coarse-grained dynamic Monte Carlo method is proposed for investigating the conformational dynamics of proteins. Each residue is represented by two interaction sites, one at the ␣-carbon, and the other on the amino acid sidechain. Geometry and energy parameters extracted from databank structures a
Dynamics of large proteins through hierarchical levels of coarse-grained structures
✍ Scribed by Pemra Doruker; Robert L. Jernigan; Ivet Bahar
- Publisher
- John Wiley and Sons
- Year
- 2001
- Tongue
- English
- Weight
- 329 KB
- Volume
- 23
- Category
- Article
- ISSN
- 0192-8651
- DOI
- 10.1002/jcc.1160
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
Elastic network models have been successful in elucidating the largest scale collective motions of proteins. These models are based on a set of highly coupled springs, where only the close neighboring amino acids interact, without any residue specificity. Our objective here is to determine whether the equivalent cooperative motions can be obtained upon further coarse‐graining of the protein structure along the backbone. The influenza virus hemagglutinin A (HA), composed of N=1509 residues, is utilized for this analysis. Elastic network model calculations are performed for coarse‐grained HA structures containing only N/2, N/10, N/20, and N/40 residues along the backbone. High correlations (>0.95) between residue fluctuations are obtained for the first dominant (slowest) mode of motion between the original model and the coarse‐grained models. In the case of coarse‐graining by a factor of 1/40, the slowest mode shape for HA is reconstructed for all residues by successively selecting different subsets of residues, shifting one residue at a time. The correlation for this reconstructed first mode shape with the original all‐residue case is 0.73, while the computational time is reduced by about three orders of magnitude. The reduction in computational time will be much more significant for larger targeted structures. Thus, the dominant motions of protein structures are robust enough to be captured at extremely high levels of coarse‐graining. And more importantly, the dynamics of extremely large complexes are now accessible with this new methodology. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 119–127, 2002
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