Abstract
This chapter discusses the combination of nonlinear regression with auxiliary data analysis methods to extract secondary structural features of a protein from its infrared spectrum. Proteins are biopolymers made up of linear chains of amino acid molecules linked end-to-end in peptide bonds. They are also known as polypeptides. The sequence of amino acids in the polypeptide chain is called the primary structure. The secondary structure of a protein is the way in which it is folded in the native state. Proteins called enzymes are catalysts for life-supporting reactions whose activity and function depend intimately on their secondary structures. Other proteins serve as structural components of living organisms, and their function also relies on the secondary structure. The chapter explains that secondary structures of proteins are characterized by helices, sheets, and extended regions within the polypeptide backbone. The backbone of a polypeptide chain absorbs infrared radiation, which excites vibrational modes of the peptide bonds. Infrared spectroscopy measures the amount of light absorbed by these vibrations over a range of frequencies of the incident light.
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