title: Distance-dependent classification of amino acids by information theory.
abstract: Reduced amino acid alphabets are useful to understand molecular evolution as they reveal basal, shared properties of amino acids, which the structures and functions of proteins rely on. Several previous studies derived such reduced alphabets and linked them to the origin of life and biotechnological applications. However, all this previous work presupposes that only direct contacts of amino acids in native protein structures are relevant. We show in this work, using information-theoretical measures, that an appropriate alphabet reduction scheme is in fact a function of the maximum distance amino acids interact at. Although for small distances our results agree with previous ones, we show how long-range interactions change the overall picture and prompt for a revised understanding of the protein design process.
authors.affiliation: Department of Mathematics, Technische Universität Darmstadt, 64287 Darmstadt, Germany.
authors.forename: Susanne
authors.initials: S
authors.lastname: Pape
authors.forename: Franziska
authors.initials: F
authors.lastname: Hoffgaard
authors.forename: Kay
authors.initials: K
authors.lastname: Hamacher
mesh_terms: D000596:Amino Acids / Q000737:chemistry* / Q000145:classification*; D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D019143:Evolution, Molecular; D007257:Information Theory; D008970:Molecular Weight; D025341:Principal Component Analysis; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*
chemical_list: D000596:Amino Acids; D011506:Proteins