Accuracy of Secondary Structure and Solvent Accessibility Predictions for a Clostridial Neurotoxin C-Fragment |
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Authors: | Frank J Lebeda Timothy C Umland Martin Sax and Mark A Olson |
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Institution: | (1) U.S. Army Medical Research Institute of Infectious Diseases, Toxinology Division, Department of Cell Biology and Biochemistry, Frederick, Maryland;, 21702-5011;;(2) Biocrystallography Laboratory, VA Medical Center, P.O. Box 12055, Pittsburgh, Pennsylvania, 15240;(3) Department of Crystallography, University of Pittsburgh, Pittsburgh, Pennsylvania, 15260;(4) Present address: Laboratory of Molecular Biology, Bldg. 5, Rm 335, NIDDK, NIH, Bethesda, Maryland, 20892-0560 |
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Abstract: | Earlier studies used Rost and Sander's artificial neural network (1993a), J. Mol. Biol.
232, 584–599] to predict the secondary structures Lebeda and Olson (1994), Proteins
20, 293–300] and residue solvent accessibilities Lebeda and Olson (1997), J. Protein Chem.
16, 607–618] of the clostridial neurotoxins. Because the X-ray crystal structure of the 50-kDa C-terminal half of the heavy chain of tetanus toxin was recently determined, this report evaluates the accuracy of these network-derived predictions. For this predominantly -strand-containing fragment, predictions, on a per-residue basis, for both secondary structure and solvent accessibility were about 70% accurate. A more flexible and realistic analysis based on overlapping segments yielded accuracies of over 80% for the three-state secondary structure and for the two-state accessibility predictions. Because the accuracies of these predictions are comparable to those made by Rost and Sander using a dataset of 126 nonhomologous globular proteins, our predictions provide a quantitative foundation for gauging the results when building by homology the structures of related proteins. |
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Keywords: | Artificial neural network crystal structure statistics tetanus toxin botulinum neurotoxin |
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