title: UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.
abstract: The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/.
authors.affiliation: Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
authors.forename: Rhonald C
authors.initials: RC
authors.lastname: Lua
authors.affiliation: Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA.
authors.forename: Stephen J
authors.identifier: http://orcid.org/0000-0003-2480-5666
authors.initials: SJ
authors.lastname: Wilson
authors.affiliation: Department of Structural and Computational Biology and Molecular Biophysics, Houston, TX 77030, USA.
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Konecki
authors.affiliation: Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Houston, TX 77030, USA.
authors.forename: Angela D
authors.initials: AD
authors.lastname: Wilkins
authors.affiliation: Department of Structural and Computational Biology and Molecular Biophysics, Houston, TX 77030, USA.
authors.forename: Eric
authors.initials: E
authors.lastname: Venner
authors.affiliation: Department of Structural and Computational Biology and Molecular Biophysics, Houston, TX 77030, USA.
authors.forename: Daniel H
authors.initials: DH
authors.lastname: Morgan
authors.affiliation: Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA Department of Structural and Computational Biology and Molecular Biophysics, Houston, TX 77030, USA Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Houston, TX 77030, USA Department of Pharmacology, Baylor College of Medicine, Houston, TX 77030, USA lichtarge@bcm.edu.
authors.forename: Olivier
authors.initials: O
authors.lastname: Lichtarge
mesh_terms: D030562:Databases, Protein; D019143:Evolution, Molecular; D011487:Protein Conformation; D020539:Sequence Analysis, Protein