Classification of amino acids by multivariate data analysis, based on thermodynamic and structural characteristics

Abstract

Principal component analysis (PCA) and cluster analysis (CA) were applied to classify 20 natural amino acids. We selected 18 characteristics, properties available from literature, as a basis for the classification. The correlations between these characteristics and their classification were investigated, as well as the classification of the amino acids. The results are presented as score plots of the first 3 principal components and as dendrograms obtained by clustering analysis. The resulting classification is consistent with the chemical behavior of amino acids and their mutual substitution possibilities in peptides and proteins.