Neural-network analysis of the vibrational spectra of N-acetyl L-alanyl N'-methyl amide conformational states.

Density-functional theory (DFT) calculations utilizing the Becke 3LYP hybrid functional have been carried out for N-acetyl L-alanine N'-methylamide and examined with respect to the effect of water on the structure, the vibrational frequencies, vibrational absorption (VA), vibrational circular dichroism (VCD), Raman spectra, and Raman optical activity (ROA) intensities. The large changes due to hydration in the structures, and the relative stability of the conformer, reflected in the VA, VCD, Raman spectra, and ROA spectra observed experimentally, are reproduced by the DFT calculations. A neural network has been constructed for reproducing the inverse scattering data (we infer the structural coordinates from spectroscopic data) that the DFT method could produce.

Protein distance constraints predicted by neural networks and probability density functions.

We predict interatomic Calpha distances by two independent data driven methods. The first method uses statistically derived probability distributions of the pairwise distance between two amino acids, whilst the latter method consists of a neural network prediction approach equipped with windows taking the context of the two residues into account. These two methods are used to predict whether distances in independent test sets were above or below given thresholds.