Adrian K. Arakaki

TASSER: An automated method for the prediction of protein tertiary structures in CASP6†

The recently developed TASSER (Threading/ASSembly/Refinement) method is applied to predict the tertiary structures of all CASP6 targets. TASSER is a hierarchical approach that consists of template identification by the threading program PROSPECTOR_3, followed by tertiary structure assembly via rearranging continuous template fragments. Assembly occurs using parallel hyperbolic Monte Carlo sampling under the guide of an optimized, reduced force field that includes knowledge‐based statistical potentials and spatial restraints extracted from threading alignments. Models are automatically selected from the Monte Carlo trajectories in the low‐temperature replicas using the clustering program SPICKER. For all 90 CASP targets/domains, PROSPECTOR_3 generates initial alignments with an average root‐mean‐square deviation (RMSD) to native of 8.4 Å with 79% coverage. After TASSER reassembly, the average RMSD decreases to 5.4 Å over the same aligned residues; the overall cumulative TM‐score increases from 39.44 to 52.53. Despite significant improvements over the PROSPECTOR_3 template alignment observed in all target categories, the overall quality of the final models is essentially dictated by the quality of threading templates: The average TM‐scores of TASSER models in the three categories are, respectively, 0.79 [comparative modeling (CM), 43 targets/domains], 0.47 [fold recognition (FR), 37 targets/domains], and 0.30 [new fold (NF), 10 targets/domains]. This highlights the need to develop novel (or improved) approaches to identify very distant targets as well as better NF algorithms. Proteins 2005;Suppl 7:91–98.

The Mosaic Genome of Anaeromyxobacter dehalogenans Strain 2CP-C Suggests an Aerobic Common Ancestor to the Delta-Proteobacteria

Anaeromyxobacter dehalogenans strain 2CP-C is a versaphilic delta-Proteobacterium distributed throughout many diverse soil and sediment environments. 16S rRNA gene phylogenetic analysis groups A. dehalogenans together with the myxobacteria, which have distinguishing characteristics including strictly aerobic metabolism, sporulation, fruiting body formation, and surface motility. Analysis of the 5.01 Mb strain 2CP-C genome substantiated that this organism is a myxobacterium but shares genotypic traits with the anaerobic majority of the delta-Proteobacteria (i.e., the Desulfuromonadales). Reflective of its respiratory versatility, strain 2CP-C possesses 68 genes coding for putative c-type cytochromes, including one gene with 40 heme binding motifs. Consistent with its relatedness to the myxobacteria, surface motility was observed in strain 2CP-C and multiple types of motility genes are present, including 28 genes for gliding, adventurous (A-) motility and 17 genes for type IV pilus-based motility (i.e., social (S-) motility) that all have homologs in Myxococcus xanthus. Although A. dehalogenans shares many metabolic traits with the anaerobic majority of the delta-Proteobacteria, strain 2CP-C grows under microaerophilic conditions and possesses detoxification systems for reactive oxygen species. Accordingly, two gene clusters coding for NADH dehydrogenase subunits and two cytochrome oxidase gene clusters in strain 2CP-C are similar to those in M. xanthus. Remarkably, strain 2CP-C possesses a third NADH dehydrogenase gene cluster and a cytochrome cbb 3 oxidase gene cluster, apparently acquired through ancient horizontal gene transfer from a strictly anaerobic green sulfur bacterium. The mosaic nature of the A. dehalogenans strain 2CP-C genome suggests that the metabolically versatile, anaerobic members of the delta-Proteobacteria may have descended from aerobic ancestors with complex lifestyles.

Evolutionary Relationships among Eubacterial Groups as Inferred from GroEL (Chaperonin) Sequence Comparisons

The essential GroEL proteins represent a subset of molecular chaperones ubiquitously distributed among species of the eubacterial lineage, as well as in eukaryote organelles. We employed these highly conserved proteins to infer eubacterial phylogenies. GroEL from the species analyzed clustered in distinct groups in evolutionary trees drawn by either the distance or the parsimony method, which were in general agreement with those found by 16S rRNA comparisons (i.e., proteobacteria, chlamydiae, bacteroids, spirochetes, firmicutes [gram-positive bacteria], and cyanobacteria-chloroplasts). Moreover, the analysis indicated specific relationships between some of the aforementioned groups which appeared not to be clearly defined or controversial in rRNA-based phylogenetic studies. For instance, a monophyletic origin for the low-G+C and high-G+C subgroups among the firmicutes, as well as their specific relationship to the cyanobacteria-chloroplasts, was inferred. The general observations suggest that GroEL proteins provide valuable evolutionary tools for defining evolutionary relationships among the eubacterial lineage of life.

The chaperone connection to the origins of the eukaryotic organelles

The heat‐shock 60 proteins (Hsp60) constitute a subset of molecular chaperones essential for the survival of the cell, present in eubacteria as well as in eukaryotic organelles. Here, we have employed these highly conserved proteins for the inferences of the origins of the organelles. Hsp60s present in mitochondria from different eukaryotic lineages formed a clade, which showed the closest relationship to that of the Ehrlichia/Rickettsia cluster among the α‐Proteobacteria. This, in addition to phenotypic characteristics, suggests that these obligate intracellular parasites and the lineage that generated the mitochondrion shared last common ancestry. In turn, Hsp60s present in chloroplasts from plants and a red alga, respectively, clustered specifically with those of the cyanobacteria, suggesting that all plastids derive exclusively from this eubacterial lineage.

Marker metabolites can be therapeutic targets as well

SIR — In the obituary of Anatol Zhabotinsky (Nature 455, 1053; 2008), Irving Epstein mentions Boris Belousov, with whom Zhabotinsky shared the Lenin Prize in 1980 for their contributions to the Belousov– Zhabotinsky oscillatory chemical reaction system. Epstein says “Belousov tried to publish his results in peerreviewed journals, but eventually gave up after referees and editors insisted that such behaviour contradicted the Second Law of Thermodynamics. He instead published a one-page description of his observations in an obscure conference proceedings on radiation medicine.” That paper, ‘A periodic reaction and its mechanism’, gained little attention at the time. Papers published in symposium proceedings do not usually merit citation, because they are not peer-reviewed. They receive little recognition. Very few are even indexed in the main journal databases — one notable exception being PubMed’s listing of the annual Cold Spring Harbor Symposium on Quantitative Biology. However, other ‘hidden’ conference papers have also subsequently provoked acclaim. The pioneering work of physicist Abdus Salam and chemist Koichi Tanaka aroused little interest when it was first published in this way. Fortunately, these findings were later recognized for their originality and importance: Salam went on to win the 1979 Nobel Prize in Physics, and Tanaka was awarded the 2002 Nobel Prize in Chemistry. Min-Liang Wong Department of Veterinary Medicine, National Chung-Hsing University, Taichung 402, Taiwan e-mail: mlwong@dragon.nchu.edu.tw 1. Belousov, B. P. Compil. Abstr. Radiat. Med. 147, 145 (1959). 2. Salam, A. in Elementary Particle Theory, Proceedings of the Nobel Symposium held in 1968 at Lerum, Sweden (ed. Svartholm, N.) 367–377 (Almqvist & Wiksell, 1968). 3. Tanaka, K. et al. in Proceedings of the Second Japan–China Joint Symposium on Mass Spectrometry (eds Matsuda, H. and Liang X. T.) 185–188 (Bando, 1987).

TOUCHSTONE: A Unified Approach to Protein Structure Prediction

We have applied the TOUCHSTONE structure prediction algorithm that spans the range from homology modeling to ab initio folding to all protein targets in CASP5. Using our threading algorithm PROSPECTOR that does not utilize input from metaservers, one threads against a representative set of PDB templates. If a template is significantly hit, Generalized Comparative Modeling designed to span the range from closely to distantly related proteins from the template is done. This involves freezing the aligned regions and relaxing the remaining structure to accommodate insertions or deletions with respect to the template. For all targets, consensus predicted side chain contacts from at least weakly threading templates are pooled and incorporated into ab initio folding. Often, TOUCHSTONE performs well in the CM to FR categories, with PROSPECTOR showing significant ability to identify analogous templates. When ab initio folding is done, frequently the best models are closer to the native state than the initial template. Among the particularly good predictions are T0130 in the CM/FR category, T0138 in the FR(H) category, T0135 in the FR(A) category, T0170 in the FR/NF category and T0181 in the NF category. Improvements in the approach are needed in the FR/NF and NF categories. Nevertheless, TOUCHSTONE was one of the best performing algorithms over all categories in CASP5. Proteins 2003;53:469–479.

The continuity of protein structure space is an intrinsic property of proteins

The classical view of the space of protein structures is that it is populated by a discrete set of protein folds. For proteins up to 200 residues long, by using structural alignments and building upon ideas of the completeness and continuity of structure space, we show that nearly any structure is significantly related to any other using a transitive set of no more than 7 intermediate structurally related proteins. This result holds for all structures in the Protein Data Bank, even when structural relationships between evolutionary related proteins (as detected by threading or functional analyses) are excluded. A similar picture holds for an artificial library of compact, hydrogen-bonded, homopolypeptide structures. The 3 sets share the global connectivity features of random graphs, in which the local connectivity of each node (i.e., the number of neighboring structures per protein) is preserved. This high connectivity supports the continuous view of single-domain protein structure space. More importantly, these results do not depend on evolution, rather just on the physics of protein structures. The fact that evolutionary divergence need not be invoked to explain the continuous nature of protein structure space has implications for how the universe of protein structures might have originated, and how function should be transferred between proteins of similar structure.

EFICAz2: enzyme function inference by a combined approach enhanced by machine learning.

BackgroundWe previously developed EFICAz, an enzyme function inference approach that combines predictions from non-completely overlapping component methods. Two of the four components in the original EFICAz are based on the detection of functionally discriminating residues (FDRs). FDRs distinguish between member of an enzyme family that are homofunctional (classified under the EC number of interest) or heterofunctional (annotated with another EC number or lacking enzymatic activity). Each of the two FDR-based components is associated to one of two specific kinds of enzyme families. EFICAz exhibits high precision performance, except when the maximal test to training sequence identity (MTTSI) is lower than 30%. To improve EFICAzs performance in this regime, we: i) increased the number of predictive components and ii) took advantage of consensual information from the different components to make the final EC number assignment.ResultsWe have developed two new EFICAz components, analogs to the two FDR-based components, where the discrimination between homo and heterofunctional members is based on the evaluation, via Support Vector Machine models, of all the aligned positions between the query sequence and the multiple sequence alignments associated to the enzyme families. Benchmark results indicate that: i) the new SVM-based components outperform their FDR-based counterparts, and ii) both SVM-based and FDR-based components generate unique predictions. We developed classification tree models to optimally combine the results from the six EFICAz components into a final EC number prediction. The new implementation of our approach, EFICAz2, exhibits a highly improved prediction precision at MTTSI < 30% compared to the original EFICAz, with only a slight decrease in prediction recall. A comparative analysis of enzyme function annotation of the human proteome by EFICAz2 and KEGG shows that: i) when both sources make EC number assignments for the same protein sequence, the assignments tend to be consistent and ii) EFICAz2 generates considerably more unique assignments than KEGG.ConclusionPerformance benchmarks and the comparison with KEGG demonstrate that EFICAz2 is a powerful and precise tool for enzyme function annotation, with multiple applications in genome analysis and metabolic pathway reconstruction. The EFICAz2 web service is available at: http://cssb.biology.gatech.edu/skolnick/webservice/EFICAz2/index.html

Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment

MOTIVATION Several protein function prediction methods employ structural features captured in three-dimensional (3D) descriptors of biologically relevant sites. These methods are successful when applied to high-resolution structures, but their detection ability in lower resolution predicted structures has only been tested for a few cases. RESULTS A method that automatically generates a library of 3D functional descriptors for the structure-based prediction of enzyme active sites (automated functional templates, 593 in total for 162 different enzymes), based on functional and structural information automatically extracted from public databases, has been developed and evaluated using decoy structures. The applicability to predicted structures was investigated by analyzing decoys of varying quality, derived from enzyme native structures. For 35% of decoy structures, our method identifies the active site in models having 3-4 A coordinate root mean square deviation from the native structure, a quality that is reachable using state of the art protein structure prediction algorithms. AVAILABILITY See http://www.bioinformatics.buffalo.edu/resources/aft/

High precision multi-genome scale reannotation of enzyme function by EFICAz

BackgroundThe functional annotation of most genes in newly sequenced genomes is inferred from similarity to previously characterized sequences, an annotation strategy that often leads to erroneous assignments. We have performed a reannotation of 245 genomes using an updated version of EFICAz, a highly precise method for enzyme function prediction.ResultsBased on our three-field EC number predictions, we have obtained lower-bound estimates for the average enzyme content in Archaea (29%), Bacteria (30%) and Eukarya (18%). Most annotations added in KEGG from 2005 to 2006 agree with EFICAz predictions made in 2005. The coverage of EFICAz predictions is significantly higher than that of KEGG, especially for eukaryotes. Thousands of our novel predictions correspond to hypothetical proteins. We have identified a subset of 64 hypothetical proteins with low sequence identity to EFICAz training enzymes, whose biochemical functions have been recently characterized and find that in 96% (84%) of the cases we correctly identified their three-field (four-field) EC numbers. For two of the 64 hypothetical proteins: PA1167 from Pseudomonas aeruginosa, an alginate lyase (EC 4.2.2.3) and Rv1700 of Mycobacterium tuberculosis H37Rv, an ADP-ribose diphosphatase (EC 3.6.1.13), we have detected annotation lag of more than two years in databases. Two examples are presented where EFICAz predictions act as hypothesis generators for understanding the functional roles of hypothetical proteins: FLJ11151, a human protein overexpressed in cancer that EFICAz identifies as an endopolyphosphatase (EC 3.6.1.10), and MW0119, a protein of Staphylococcus aureus strain MW2 that we propose as candidate virulence factor based on its EFICAz predicted activity, sphingomyelin phosphodiesterase (EC 3.1.4.12).ConclusionOur results suggest that we have generated enzyme function annotations of high precision and recall. These predictions can be mined and correlated with other information sources to generate biologically significant hypotheses and can be useful for comparative genome analysis and automated metabolic pathway reconstruction.