dorsal/arxiv
View SchemaOptimization and evaluation of a coarse-grained model of protein motion using X-ray crystal data
| Authors | Dmitry A. Kondrashov, Qiang Cui, George N. Phillips Jr |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0604007 |
| URL | https://arxiv.org/abs/q-bio/0604007 |
| DOI | 10.1529/biophysj.106.085894 |
| Journal | Biophysical Journal, vol 91 (8), 2006 |
Abstract
Simple coarse-grained models, such as the Gaussian Network Model, have been shown to capture some of the features of equilibrium protein dynamics. We extend this model by using atomic contacts to define residue interactions and introducing more than one interaction parameter between residues. We use B-factors from 98 ultra-high resolution X-ray crystal structures to optimize the interaction parameters. The average correlation between GNM fluctuation predictions and the B-factors is 0.64 for the data set, consistent with a previous large-scale study. By separating residue interactions into covalent and noncovalent, we achieve an average correlation of 0.74, and addition of ligands and cofactors further improves the correlation to 0.75. However, further separating the noncovalent interactions into nonpolar, polar, and mixed yields no significant improvement. The addition of simple chemical information results in better prediction quality without increasing the size of the coarse-grained model.
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"abstract": "Simple coarse-grained models, such as the Gaussian Network Model, have been\nshown to capture some of the features of equilibrium protein dynamics. We\nextend this model by using atomic contacts to define residue interactions and\nintroducing more than one interaction parameter between residues. We use\nB-factors from 98 ultra-high resolution X-ray crystal structures to optimize\nthe interaction parameters. The average correlation between GNM fluctuation\npredictions and the B-factors is 0.64 for the data set, consistent with a\nprevious large-scale study. By separating residue interactions into covalent\nand noncovalent, we achieve an average correlation of 0.74, and addition of\nligands and cofactors further improves the correlation to 0.75. However,\nfurther separating the noncovalent interactions into nonpolar, polar, and mixed\nyields no significant improvement. The addition of simple chemical information\nresults in better prediction quality without increasing the size of the\ncoarse-grained model.",
"arxiv_id": "q-bio/0604007",
"authors": [
"Dmitry A. Kondrashov",
"Qiang Cui",
"George N. Phillips Jr"
],
"categories": [
"q-bio.BM"
],
"doi": "10.1529/biophysj.106.085894",
"journal_ref": "Biophysical Journal, vol 91 (8), 2006",
"title": "Optimization and evaluation of a coarse-grained model of protein motion using X-ray crystal data",
"url": "https://arxiv.org/abs/q-bio/0604007"
},
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