Recent applications of multiway data modeling for protein analysis by IR spectroscopy

Abstract

Multiway data analysis holds high potential for the evaluation of spectroscopic data, in particular for information-rich mid-infrared spectra. This chapter provides an overview of recent applications of multiway data analysis in (laser-based) infrared spectroscopy of proteins. Correlation-optimized warping and wavelet transform are presented as useful techniques to alleviate instrument imperfections and improve noise levels of experimentally recorded data with optical setups. Multivariate curve resolution-alternating least squares was found to be an excellent tool to predict percentages of individual secondary structures in static protein spectra and to reveal profiles of spectral components and display their progression when monitoring dynamic changes in protein secondary structure. Finally, the outlined examples demonstrate that (laser-based) IR spectroscopy paired with multiway analysis is a powerful combination for monitoring and in-depth interpreting of protein folding.