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Prediction of enzyme function based on 3D templates of evolutionarily important amino acids.

ABSTRACT: Structural genomics projects such as the Protein Structure Initiative (PSI) yield many new structures, but often these have no known molecular functions. One approach to recover this information is to use 3D templates - structure-function motifs that consist of a few functionally critical amino acids and may suggest functional similarity when geometrically matched to other structures. Since experimentally determined functional sites are not common enough to define 3D templates on a large scale, this work tests a computational strategy to select relevant residues for 3D templates.Based on evolutionary information and heuristics, an Evolutionary Trace Annotation (ETA) pipeline built templates for 98 enzymes, half taken from the PSI, and sought matches in a non-redundant structure database. On average each template matched 2.7 distinct proteins, of which 2.0 share the first three Enzyme Commission digits as the template's enzyme of origin. In many cases (61%) a single most likely function could be predicted as the annotation with the most matches, and in these cases such a plurality vote identified the correct function with 87% accuracy. ETA was also found to be complementary to sequence homology-based annotations. When matches are required to both geometrically match the 3D template and to be sequence homologs found by BLAST or PSI-BLAST, the annotation accuracy is greater than either method alone, especially in the region of lower sequence identity where homology-based annotations are least reliable.These data suggest that knowledge of evolutionarily important residues improves functional annotation among distant enzyme homologs. Since, unlike other 3D template approaches, the ETA method bypasses the need for experimental knowledge of the catalytic mechanism, it should prove a useful, large scale, and general adjunct to combine with other methods to decipher protein function in the structural proteome.

SUBMITTER: Kristensen DM

PROVIDER: S-EPMC2219985 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

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Prediction of enzyme function based on 3D templates of evolutionarily important amino acids.

Kristensen David M DM Ward R Matthew RM Lisewski Andreas Martin AM Erdin Serkan S Chen Brian Y BY Fofanov Viacheslav Y VY Kimmel Marek M Kavraki Lydia E LE Lichtarge Olivier O

BMC bioinformatics 20080111

<h4>Background</h4>Structural genomics projects such as the Protein Structure Initiative (PSI) yield many new structures, but often these have no known molecular functions. One approach to recover this information is to use 3D templates - structure-function motifs that consist of a few functionally critical amino acids and may suggest functional similarity when geometrically matched to other structures. Since experimentally determined functional sites are not common enough to define 3D templates ...[more]

PMID: 18190718

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Project description:BackgroundWell-performing automated protein function recognition approaches usually comprise several complementary techniques. Beside constructing better consensus, their predictive power can be improved by either adding or refining independent modules that explore orthogonal features of proteins. In this work, we demonstrated how the exploration of global atomic distributions can be used to indicate functionally important residues.ResultsUsing a set of carefully selected globular proteins, we parametrized continuous probability density functions describing preferred central distances of individual protein atoms. Relative preferred burials were estimated using mixture models of radial density functions dependent on the amino acid composition of a protein under consideration. The unexpectedness of extraordinary locations of atoms was evaluated in the information-theoretic manner and used directly for the identification of key amino acids. In the validation study, we tested capabilities of a tool built upon our approach, called SurpResi, by searching for binding sites interacting with ligands. The tool indicated multiple candidate sites achieving success rates comparable to several geometric methods. We also showed that the unexpectedness is a property of regions involved in protein-protein interactions, and thus can be used for the ranking of protein docking predictions. The computational approach implemented in this work is freely available via a Web interface at http://www.bioinformatics.org/surpresi.ConclusionsProbabilistic analysis of atomic central distances in globular proteins is capable of capturing distinct orientational preferences of amino acids as resulting from different sizes, charges and hydrophobic characters of their side chains. When idealized spatial preferences can be inferred from the sole amino acid composition of a protein, residues located in hydrophobically unfavorable environments can be easily detected. Such residues turn out to be often directly involved in binding ligands or interfacing with other proteins.

Project description:We have determined the nucleotide sequences of eight ethyl methanesulphonate-induced mutants in Drosophila alcohol dehydrogenase (ADH), of which six were previously characterized by Hollocher and Place [(1988) Genetics 116, 253-263 and 265-274]. Four of these ADH mutants contain a single amino acid change: glycine-17 to arginine, glycine-93 to glutamic acid, alanine-159 to threonine, and glycine-184 to aspartic acid. Although these mutants are inactive, three mutants (Gly17Arg, Gly93Glu and Gly184Asp) form stable homodimers, as well as heterodimers with wild-type ADH, in which the wild-type ADH subunit retains full enzyme activity [Hollocher and Place (1988) Genetics 116, 265-274]. Interestingly, the Ala159Thr mutant does not form either stable homodimers or heterodimers with wild-type ADH, suggesting that alanine-159 is important in stabilizing ADH dimers. The mutations were analysed in terms of a three-dimensional model of ADH using bacterial 20 beta-hydroxysteroid dehydrogenase and rat dihydropteridine reductase as templates. The model indicates that mutations in glycine-17 and glycine-93 affect the binding of NAD+. It also shows that alanine-159 is part of a hydrophobic anchor on the dimer interface of ADH. Replacement of alanine-159 with threonine, which has a larger side chain and can hydrogen bond with water, is likely to reduce the strength of the hydrophobic interaction. The three-dimensional model shows that glycine-184 is close to the substrate binding site. Replacement of glycine-184 with aspartic acid is likely to alter the position of threonine-186, which we propose hydrogen bonds to the carboxamide moiety of NAD+. Also, the negative charge on the aspartic acid side chain may interact with the substrate and/or residues in the substrate binding site. These mutations provide information about ADH catalysis and the stability of dimers, which may also be useful in understanding homologous dehydrogenases, which include the human 17 beta-hydroxysteroid, 11 beta-hydroxysteroid and 15-hydroxyprostaglandin dehydrogenases.

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Prediction of enzyme function based on 3D templates of evolutionarily important amino acids.

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Prediction of enzyme function based on 3D templates of evolutionarily important amino acids.

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