title: Prediction of amino acid sequence from structure.
abstract: We have developed a method for the prediction of an amino acid sequence that is compatible with a three-dimensional backbone structure. Using only a backbone structure of a protein as input, the algorithm is capable of designing sequences that closely resemble natural members of the protein family to which the template structure belongs. In general, the predicted sequences are shown to have multiple sequence profile scores that are dramatically higher than those of random sequences, and sometimes better than some of the natural sequences that make up the superfamily. As anticipated, highly conserved but poorly predicted residues are often those that contribute to the functional rather than structural properties of the protein. Overall, our analysis suggests that statistical profile scores of designed sequences are a novel and valuable figure of merit for assessing and improving protein design algorithms.
authors.affiliation: Integrative Biosciences Program, Pennsylvania State University, University Park, Pennsylvania 16803, USA.
authors.forename: K
authors.initials: K
authors.lastname: Raha
authors.forename: A M
authors.initials: AM
authors.lastname: Wollacott
authors.forename: M J
authors.initials: MJ
authors.lastname: Italia
authors.forename: J R
authors.initials: JR
authors.lastname: Desjarlais
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011487:Protein Conformation; D017386:Sequence Homology, Amino Acid