dorsal/arxiv
View SchemaProtein structural variation in computational models and crystallographic data
| Authors | Dmitry A. Kondrashov, Adam W. Van Wynsberghe, Ryan M. Bannen, Qiang Cui, George N. Phillips Jr |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0611039 |
| URL | https://arxiv.org/abs/q-bio/0611039 |
Abstract
Normal mode analysis offers an efficient way of modeling the conformational flexibility of protein structures. Simple models defined by contact topology, known as elastic network models, have been used to model a variety of systems, but the validation is typically limited to individual modes for a single protein. We use anisotropic displacement parameters from crystallography to test the quality of prediction of both the magnitude and directionality of conformational variance. Normal modes from four simple elastic network model potentials and from the CHARMM forcefield are calculated for a data set of 83 diverse, ultrahigh resolution crystal structures. While all five potentials provide good predictions of the magnitude of flexibility, the methods that consider all atoms have a clear edge at prediction of directionality, and the CHARMM potential produces the best agreement. The low-frequency modes from different potentials are similar, but those computed from the CHARMM potential show the greatest difference from the elastic network models. This was illustrated by computing the dynamic correlation matrices from different potentials for a PDZ domain structure. Comparison of normal mode results with anisotropic temperature factors opens the possibility of using ultrahigh resolution crystallographic data as a quantitative measure of molecular flexibility. The comprehensive evaluation demonstrates the costs and benefits of using normal mode potentials of varying complexity. Comparison of the dynamic correlation matrices suggests that a combination of topological and chemical potentials may help identify residues in which chemical forces make large contributions to intramolecular coupling.
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"abstract": "Normal mode analysis offers an efficient way of modeling the conformational\nflexibility of protein structures. Simple models defined by contact topology,\nknown as elastic network models, have been used to model a variety of systems,\nbut the validation is typically limited to individual modes for a single\nprotein. We use anisotropic displacement parameters from crystallography to\ntest the quality of prediction of both the magnitude and directionality of\nconformational variance. Normal modes from four simple elastic network model\npotentials and from the CHARMM forcefield are calculated for a data set of 83\ndiverse, ultrahigh resolution crystal structures. While all five potentials\nprovide good predictions of the magnitude of flexibility, the methods that\nconsider all atoms have a clear edge at prediction of directionality, and the\nCHARMM potential produces the best agreement. The low-frequency modes from\ndifferent potentials are similar, but those computed from the CHARMM potential\nshow the greatest difference from the elastic network models. This was\nillustrated by computing the dynamic correlation matrices from different\npotentials for a PDZ domain structure. Comparison of normal mode results with\nanisotropic temperature factors opens the possibility of using ultrahigh\nresolution crystallographic data as a quantitative measure of molecular\nflexibility. The comprehensive evaluation demonstrates the costs and benefits\nof using normal mode potentials of varying complexity. Comparison of the\ndynamic correlation matrices suggests that a combination of topological and\nchemical potentials may help identify residues in which chemical forces make\nlarge contributions to intramolecular coupling.",
"arxiv_id": "q-bio/0611039",
"authors": [
"Dmitry A. Kondrashov",
"Adam W. Van Wynsberghe",
"Ryan M. Bannen",
"Qiang Cui",
"George N. Phillips Jr"
],
"categories": [
"q-bio.BM",
"q-bio.QM"
],
"title": "Protein structural variation in computational models and crystallographic data",
"url": "https://arxiv.org/abs/q-bio/0611039"
},
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