Abstract

Determining the amino acid content of a protein involves the hydrolysis of that protein, usually in acid, until the protein-bound amino acids are released and made available for detection. Both the variability in the ease of peptide bond cleavage and differences in the acid stability of certain amino acids can significantly affect determination of a protein's amino acid content. By using multiple hydrolysis intervals, a greater degree of accuracy can be obtained in amino acid analysis. Correction factors derived by linear extrapolation of serial hydrolysis data are currently used. Compartmental modeling of the simultaneous hydrolysis (yield) and degradation (decay) of amino acids by nonlinear multiple regression of serial hydrolysis data has also been validated and applied to determine the amino acid composition of various biological samples, including egg-white lysozyme, human milk protein, and hair. Implicit in the routine application of serial hydrolysis in amino acid analysis, however, is an understanding that correction factors, derived either linearly or through the more accurate nonlinear multiple regression approach, need to be determined for individual proteins rather than be applied uniformly across all protein types.

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