Beyond average protein secondary structure content prediction using FTIR spectroscopy.

Joachim A Hering; Peter R Innocent; Parvez I Haris

doi:10.2165/00822942-200403010-00003

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Beyond average protein secondary structure content prediction using FTIR spectroscopy.

Joachim A Hering·Peter R Innocent·Parvez I Haris

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Abstract

This paper demonstrates that secondary structure information beyond purely protein secondary structure content can be predicted from FTIR (Fourier transform infrared spectroscopy) spectra of proteins with a high degree of accuracy. Both neural networks and adaptive neuro-fuzzy inference systems (ANFISs) were employed to predict helix/sheet segment information. The best results were achieved using ANFISs with fuzzy subtractive clustering based on normalised, compressed amide I data with an average SEP (standard error of prediction, root mean of squared errors) of 1.51. Predictions for average helix/sheet length based merely on the amide I band maximum position in combination with the full-width at half-height resulted in a comparable average SEP of 1.62. This suggests the importance of information on the position and width of the amide I band maximum for the prediction of helix/sheet segment information. Finally, the most promising pattern recognition approaches found in this study were applied to a protein with an as yet unknown x-ray structure: native a1-antichymotrypsin (a1-ACT).

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Algorithms Artificial Intelligence Cluster Analysis Fuzzy Logic Pattern Recognition, Automated Protein Structure, Secondary Proteins Spectroscopy, Fourier Transform Infrared Evaluation Study Journal Article

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Joachim A Hering, Peter R Innocent, Parvez I Haris. 2004. Beyond average protein secondary structure content prediction using FTIR spectroscopy.. https://doi.org/10.2165/00822942-200403010-00003

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