Two-dimensional correlation spectroscopy (2D-COS) is a versatile technique to sort out important information in spectral variations under various external perturbations. A series of dynamic spectra exhibiting perturbation-induced changes can be readily transformed into two-dimensional correlation spectra based on cross-correlation analysis. 2D-COS has many advantages, such as enhanced spectral resolution, identification of inter- or intramolecular interactions, and chemical bond changes. It has been well-accepted as a powerful analytical technique in many fields of spectroscopic studies, such as biomedicine, pharmacy, food science, environmental science, and polymer materials. Firstly introduced by Noda in 1986, the generalized two-dimensional correlation algorithm had been extended to more two-dimensional correlation algorithms, such as projection two-dimensional correlation, tandem two-dimensional correlation, model-based two-dimensional correlation, hetero-mass spectrum two-dimensional correlation and moving window two-dimensional correlation, have been proposed and widely applied. With the rapid development of biotechnology in recent years, the structure (especially advanced structure) analysis of peptides, proteins, enzymes and other protein substances is the key factor inthe quality and efficacy of protein substances due to their participation in important physiological and chemical reaction processes of the human body. 2D-COS provides a fast, nondestructive qualitative and quantitative analysis method for studying protein structure in biomedicine. It can be used to analyze further the microstructures, such as protein secondary structure, which provides strong support for the mechanism research of biological macromolecule drugs. This article reviews both the technology and application development of 2D-COS and systematically summarizes the basic method principles, algorithm implementation and application progress in protein analysis, which provides a ready reference and overview for the applications of 2D-COS. © 2023 Science Press. All rights reserved.
