title: Probabilistic reconstruction of ancestral protein sequences.
abstract: Using a maximum-likelihood formalism, we have developed a method with which to reconstruct the sequences of ancestral proteins. Our approach allows the calculation of not only the most probable ancestral sequence but also of the probability of any amino acid at any given node in the evolutionary tree. Because we consider evolution on the amino acid level, we are better able to include effects of evolutionary pressure and take advantage of structural information about the protein through the use of mutation matrices that depend on secondary structure and surface accessibility. The computational complexity of this method scales linearly with the number of homologous proteins used to reconstruct the ancestral sequence.
authors.affiliation: Biophysics Research Division, University of Michigan, Ann Arbor 48109-1055, USA.
authors.forename: J M
authors.initials: JM
authors.lastname: Koshi
authors.forename: R A
authors.initials: RA
authors.lastname: Goldstein
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D001499:Bayes Theorem; D019143:Evolution, Molecular; D006801:Humans; D016013:Likelihood Functions; D008969:Molecular Sequence Data; D015394:Molecular Structure; D010802:Phylogeny; D011336:Probability; D011506:Proteins / Q000235:genetics*; D012260:Ribonucleases / Q000737:chemistry / Q000235:genetics; D017386:Sequence Homology, Amino Acid
chemical_list: D011506:Proteins; D012260:Ribonucleases