Related Experiment Video
Updated: Aug 14, 2026

Nuclear Magnetic Resonance Spectroscopy for the Identification of Multiple Phosphorylations of Intrinsically Disordered Proteins
Published on: December 27, 2016
Quantitative analysis of protein far UV circular dichroism spectra by neural networks
1Institut für Biophysik und Physikalische Biochemie, Universität Regensburg, Germany.
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.
Related Concept Videos
¹H NMR: Interpreting Distorted and Overlapping Signals
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
UV–Vis Spectrum
The UV–Vis spectrum of a molecule is the plot of its absorbance versus wavelength. The plot is drawn by taking molar absorptivity (ε) or log ε on the y-axis (ordinate)...
UV–Vis Spectroscopy of Conjugated Systems
One of the factors influencing λmax is the extent of conjugation in the...
UV–Vis Spectroscopy: Molecular Electronic Transitions
UV–Vis Spectroscopy: Woodward–Fieser Rules

