title: Prediction of amino acid positions specific for functional groups in a protein family based on local sequence similarity.
abstract: The exchange of single amino acid residue in protein can substantially affect the specificity of molecular recognition. Many protein families can be divided into the groups based on specificity to recognized ligands. Prediction of group-discriminating residues within the certain family is extremely necessary for theoretical studies, enzyme engineering, drug design, and so on. The most existing methods use the multiple sequence alignment. They have the limitations in prediction accuracy due to the family sequence divergence and ligand-based grouping. We developed a new method SPrOS (Specificity Projection On Sequence) for estimating the specificity of residues to user-defined groups. SPrOS compares the sequence segments from the test protein and training proteins. Contrary to other segment-comparison approaches extracting the string motifs, SPrOS calculates the scores for single positions by the similarity of their surroundings. The method was evaluated on the simulated sequences and real protein families. The high-prediction accuracy was achieved for simulated sequences, in which SPrOS detected specific positions not predicted with the alignment-based method. For bacterial transcription factors (LacI/GalR) clearly divided into functional groups, the predicted specific residues corresponded to the published experimental data. In a more complicated case of protein kinases classified by inhibitor specificity, the positions predicted with high significance were located in ligand-binding areas. As the ligand specificity is not necessary coincided with phylogeny, evolutionary-coupled mutations could disturb the detection of ligand-specific residues. Excluding proximate homologs of the test protein kinase from the training set, we improved the prediction of the ligand-specific residues. The SPrOS is available at http://www.way2drug.com/spros/
authors.affiliation: Russian National Research Medical University, Moscow, Russia.|Laboratory of Structure-Function Based Drug Design, Institute of Biomedical Chemistry (IBMC), Moscow, Russia.
authors.forename: Dmitry A
authors.initials: DA
authors.lastname: Karasev
authors.affiliation: Laboratory of Structure Bioinformatics, Institute of Biomedical Chemistry (IBMC), Moscow, Russia.
authors.forename: Alexander V
authors.initials: AV
authors.lastname: Veselovsky
authors.affiliation: Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.|Engelhardt Institute of Molecular Biology, Moscow, Russia.
authors.forename: Nina Yu
authors.initials: NY
authors.lastname: Oparina
authors.affiliation: Laboratory of Structure Bioinformatics, Institute of Biomedical Chemistry (IBMC), Moscow, Russia.
authors.forename: Dmitry A
authors.initials: DA
authors.lastname: Filimonov
authors.affiliation: Laboratory of Structure-Function Based Drug Design, Institute of Biomedical Chemistry (IBMC), Moscow, Russia.
authors.forename: Boris N
authors.initials: BN
authors.lastname: Sobolev
mesh_terms: D000596:Amino Acids / Q000737:chemistry*; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D008958:Models, Molecular; D005810:Multigene Family; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D064878:Web Browser
chemical_list: D000596:Amino Acids; D011506:Proteins
keywords: local sequence similarity; prediction of specific residues; protein family; protein-ligand interaction