Molecular modeling annual

, Volume 7, Issue 12, pp 445–453 | Cite as

New quantitative descriptors of amino acids based on multidimensional scaling of a large number of physical–chemical properties

  • Mathura S. Venkatarajan
  • Werner Braun
Original Paper


We derive new quantitative descriptors for the 20 naturally occurring amino acids based on multidimensional scaling of 237 physical–chemical properties. We show that a five-dimensional property space can be constructed such that the amino acids are in a similar spatial distribution to that in the original high-dimensional property space. Properties that correlate well with the five major components were hydrophobicity, size, preferences for amino acids to occur in α-helices, number of degenerate triplet codons and the frequency of occurrence of amino acid residues in β-strands. Distances computed for pairs of amino acids in the five-dimensional property space are highly correlated with corresponding scores from similarity matrices derived from sequence and 3D structure comparison. We used the five-dimensional property distances to cluster the amino acids in groups depending on a cutoff distance. These groups define a reduced amino acid alphabet for protein folding studies. Our descriptors should provide a quantitative means to identify property motifs in sequences of protein families. Electronic supplementary material to this paper can be obtained by using the Springer Link server located at


Multidimensional scaling – Amino acid – Substitution matrices – BLOSUM – PAM – Physical–chemical properties – Cluster analysis 

Supplementary material

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Copyright information

© Springer-Verlag 2001

Authors and Affiliations

  • Mathura S. Venkatarajan
    • 1
  • Werner Braun
    • 1
  1. 1.Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, 301 University Boulevard, The University of Texas Medical Branch, Galveston, TX 77555-1157, USA E-mail: Phone: +1 409 747-6810 Fax: +1 409 747-6850US

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