Modeling Protein Functional Properties from Amino Acid Composition

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• 作者：Karl J. Siebert
• 刊名：Journal of Agricultural and Food Chemistry
• 出版年：2003
• 出版时间：December 17, 2003
• 年：2003
• 卷：51
• 期：26
• 页码：7792 - 7797
• 全文大小：97K
• 年卷期：v.51,no.26(December 17, 2003)
• ISSN：1520-5118

文摘

Physicochemical and functional properties of proteins were modeled as a function of the contributionsof each of the 20 coded amino acids to three (z-scores) or five (extended z-scores) amino acid principalproperties using partial least squares regression. The five term models were in all cases stronger inboth fit and prediction than the three term models, indicating that useful information is contained inthe fourth and fifth property scores. Models predicting protein hydrophobicity (R = 0.932), viscosity(R = 0.737), and foam capacity (R = 0.880) from amino acid composition rather than sequencewere obtained. It is likely that additional functional and physicochemical properties of proteins canbe modeled in this way.Keywords: QSAR; functional properties; principal components analysis; partial least squares regression