Comparisons of Experimental and Computed Protein Anisotropic Temperature Factors

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2009-07-01
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Yang, Lei
Song, Guang
Jernigan, Robert
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Jernigan, Robert
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Computer Science

Computer Science—the theory, representation, processing, communication and use of information—is fundamentally transforming every aspect of human endeavor. The Department of Computer Science at Iowa State University advances computational and information sciences through; 1. educational and research programs within and beyond the university; 2. active engagement to help define national and international research, and 3. educational agendas, and sustained commitment to graduating leaders for academia, industry and government.

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The Computer Science Department was officially established in 1969, with Robert Stewart serving as the founding Department Chair. Faculty were composed of joint appointments with Mathematics, Statistics, and Electrical Engineering. In 1969, the building which now houses the Computer Science department, then simply called the Computer Science building, was completed. Later it was named Atanasoff Hall. Throughout the 1980s to present, the department expanded and developed its teaching and research agendas to cover many areas of computing.

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1969-present

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Bioinformatics and Computational Biology
The Bioinformatics and Computational Biology (BCB) Program at Iowa State University is an interdepartmental graduate major offering outstanding opportunities for graduate study toward the Ph.D. degree in Bioinformatics and Computational Biology. The BCB program involves more than 80 nationally and internationally known faculty—biologists, computer scientists, mathematicians, statisticians, and physicists—who participate in a wide range of collaborative projects.
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Biochemistry, Biophysics and Molecular BiologyComputer ScienceBioinformatics and Computational Biology
Abstract

Because of its appealing simplicity, the anisotropic network model (ANM) has been widely accepted and applied to study many molecular motion problems: such as ribosome motions, the molecular mechanisms of GroEL-GroES function, allosteric changes in hemoglobin, motor-protein motions, and conformational changes in general. However, the validity of the ANM has not been closely examined. In this work, we use ANM to predict the anisotropic temperature factors of proteins obtained from X-ray and NMR data. The rich, directional anisotropic temperature factor data available for hundreds of proteins in the Protein Data Bank (PDB) are used as validation data to closely test the ANM model. The significance of this work is that it presents a timely, important evaluation of the model, shows the extent of its accuracy in reproducing experimental anisotropic temperature factors, and suggests ways to improve the model. An improved model will help us better understand the internal dynamics of proteins, which in turn can greatly expand the usefulness of the models, which has already been demonstrated in many applications.

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This is the peer reviewed version of the following article: Yang, Lei, Guang Song, and Robert L. Jernigan. "Comparisons of experimental and computed protein anisotropic temperature factors." Proteins: Structure, Function, and Bioinformatics 76, no. 1 (2009): 164-175, which has been published in final form at doi: 10.1002/prot.22328. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

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Tue Jan 01 00:00:00 UTC 2008
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