Name
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. (C) 2002 John Wiley & Sons, Inc. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1002/jcc.1160 | JOURNAL OF COMPUTATIONAL CHEMISTRY |
Keywords | Field | DocType |
Gaussian network model,anisotropic fluctuations,vibration dynamics,collective motions,influenza virus hemagglutinin | Orders of magnitude (numbers),Crystallography,Biological system,Residue (complex analysis),Elastic network models,Computational chemistry,Chemistry,Anisotropic Network Model,Gaussian network model,Normal mode,Network model,Protein structure | Journal |
Volume | Issue | ISSN |
23 | 1 | 0192-8651 |
Citations | PageRank | References |
20 | 4.20 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pemra Doruker | 1 | 26 | 5.78 |
| Robert L Jernigan | 2 | 224 | 25.36 |
| Ivet Bahar | 3 | 361 | 39.41 |