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Quantitative analysis of protein far UV circular dichroism spectra by neural networks
Abstract
A new method based on neural network theory is presented to analyze and quantify the information content of far UV circular dichroism spectra. Using a backpropagation network model with a single hidden layer between input and output, it was possible to deduce five different secondary structure fractions (helix, parallel and antiparallel beta-sheet, beta-turn and random coil) with satisfactory correlations between calculated and measured secondary structure data. We demonstrate that for each wavelength interval a specific network is suitable. The remaining discrepancy between the secondary structure data from neural network prediction and crystallography may be attributed to errors in the determination of protein concentration and random noise in the CD signal, as indicated by simulations.
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Chi, Z., Chen, X. G., Holtz, J. S. W., & Asher, S. A. (1998) · Biochemistry · doi:10.1021/bi971160z · Cited by 301
Extending Serum Half-life of Albumin by Engineering Neonatal Fc Receptor (FcRn) Binding
Andersen, J. T., Dalhus, B., Viuff, D., Ravn, B. T., Gunnarsen, K. S., Plumridge, A., Bunting, K., Antunes, F., Williamson, R., Athwal, S., et al. (2014) · Journal of Biological Chemistry · doi:10.1074/jbc.m114.549832 · Cited by 167
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Dong, S., Fan, L., Ma, Y., Du, J., & Xiang, Q. (2021) · LWT · doi:10.1016/j.lwt.2021.111322 · Cited by 62
Ishikawa, Y., & Bächinger, H. P. (2014) · Journal of Biological Chemistry · doi:10.1074/jbc.m114.561944 · Cited by 52
Baumann, A., Jorge-Finnigan, A., Jung-KC, K., Sauter, A., Horvath, I., Morozova-Roche, L. A., & Martinez, A. (2016) · Scientific Reports · doi:10.1038/srep39488 · Cited by 20
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Metadata
- Authors
- Böhm, G., Muhr, R., & Jaenicke, R.
- Venue
- "Protein Engineering, Design and Selection"
- Publisher
- Oxford University Press (OUP)
- Published
- 1992
- Volume
- 5
- Issue
- 3
- Pages
- 191-195
- ISSN
- 0269-2139 (ISSN-L)
- 1741-0126
- 1741-0134
- OpenAlex
- W2052749821
- Cited by
- 1,107
- References
- 0
- FWCI
- 1.15
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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