Structural annotation of Mycobacterium tuberculosis proteome

Of the ～4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB) H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a structural annotation for the genome, using computational methods. Structural models were obtained and validated for ～2877 ORFs, covering ～70% of the genome. Functional annotation of each protein was based on fold-based functional assignments and a novel binding site based ligand association. New algorithms for binding site detection and genome scale binding site comparison at the structural level, recently reported from the laboratory, were utilized. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides an opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses. The resource (http://proline.physics.iisc.ernet.in/Tbstructuralannotation), being one of the first to be based on structure-derived functional annotations at a genome scale, is expected to be useful for better understanding of TB and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well.     

Structure- and sequence-based function prediction for non-homologous proteins

The structural genomics projects have been accumulating an increasing number of protein structures, many of which remain functionally unknown. In parallel effort to experimental methods, computational methods are expected to make a significant contribution for functional elucidation of such proteins. However, conventional computational methods that transfer functions from homologous proteins do not help much for these uncharacterized protein structures because they do not have apparent structural or sequence similarity with the known proteins. Here, we briefly review two avenues of computational function prediction methods, i.e. structure-based methods and sequence-based methods. The focus is on our recent developments of local structure-based and sequence-based methods, which can effectively extract function information from distantly related proteins. Two structure-based methods, Pocket-Surfer and Patch-Surfer, identify similar known ligand binding sites for pocket regions in a query protein without using global protein fold similarity information. Two sequence-based methods, protein function prediction and extended similarity group, make use of weakly similar sequences that are conventionally discarded in homology based function annotation. Combined together with experimental methods we hope that computational methods will make leading contribution in functional elucidation of the protein structures.     

Prediction and assignment of function for a divergent N-succinyl amino acid racemase

The protein databases contain many proteins with unknown function. A computational approach for predicting ligand specificity that requires only the sequence of the unknown protein would be valuable for directing experiment-based assignment of function. We focused on a family of unknown proteins in the mechanistically diverse enolase superfamily and used two approaches to assign function: (i) enzymatic assays using libraries of potential substrates, and (ii) in silico docking of the same libraries using a homology model based on the most similar (35% sequence identity) characterized protein. The results matched closely; an experimentally determined structure confirmed the predicted structure of the substrate-liganded complex. We assigned the N-succinyl arginine/lysine racemase function to the family, correcting the annotation (L-Ala-D/L-Glu epimerase) based on the function of the most similar characterized homolog. These studies establish that ligand docking to a homology model can facilitate functional assignment of unknown proteins by restricting the identities of the possible substrates that must be experimentally tested.     

Identification of functional subclasses in the DJ-1 superfamily proteins

Genomics has posed the challenge of determination of protein function from sequence and/or 3-D structure. Functional assignment from sequence relationships can be misleading, and structural similarity does not necessarily imply functional similarity. Proteins in the DJ-1 family, many of which are of unknown function, are examples of proteins with both sequence and fold similarity that span multiple functional classes. THEMATICS (theoretical microscopic titration curves), an electrostatics-based computational approach to functional site prediction, is used to sort proteins in the DJ-1 family into different functional classes. Active site residues are predicted for the eight distinct DJ-1 proteins with available 3-D structures. Placement of the predicted residues onto a structural alignment for six of these proteins reveals three distinct types of active sites. Each type overlaps only partially with the others, with only one residue in common across all six sets of predicted residues. Human DJ-1 and YajL from Escherichia coli have very similar predicted active sites and belong to the same probable functional group. Protease I, a known cysteine protease from Pyrococcus horikoshii, and PfpI/YhbO from E. coli, a hypothetical protein of unknown function, belong to a separate class. THEMATICS predicts a set of residues that is typical of a cysteine protease for Protease I; the prediction for PfpI/YhbO bears some similarity. YDR533Cp from Saccharomyces cerevisiae, of unknown function, and the known chaperone Hsp31 from E. coli constitute a third group with nearly identical predicted active sites. While the first four proteins have predicted active sites at dimer interfaces, YDR533Cp and Hsp31 both have predicted sites contained within each subunit. Although YDR533Cp and Hsp31 form different dimers with different orientations between the subunits, the predicted active sites are superimposable within the monomer structures. Thus, the three predicted functional classes form four different types of quaternary structures. The computational prediction of the functional sites for protein structures of unknown function provides valuable clues for functional classification.     

Fold independent structural comparisons of protein-ligand binding sites for exploring functional relationships

The rapid growth in protein structural data and the emergence of structural genomics projects have increased the need for automatic structure analysis and tools for function prediction. Small molecule recognition is critical to the function of many proteins; therefore, determination of ligand binding site similarity is important for understanding ligand interactions and may allow their functional classification. Here, we present a binding sites database (SitesBase) that given a known protein-ligand binding site allows rapid retrieval of other binding sites with similar structure independent of overall sequence or fold similarity. However, each match is also annotated with sequence similarity and fold information to aid interpretation of structure and functional similarity. Similarity in ligand binding sites can indicate common binding modes and recognition of similar molecules, allowing potential inference of function for an uncharacterised protein or providing additional evidence of common function where sequence or fold similarity is already known. Alternatively, the resource can provide valuable information for detailed studies of molecular recognition including structure-based ligand design and in understanding ligand cross-reactivity. Here, we show examples of atomic similarity between superfamily or more distant fold relatives as well as between seemingly unrelated proteins. Assignment of unclassified proteins to structural superfamiles is also undertaken and in most cases substantiates assignments made using sequence similarity. Correct assignment is also possible where sequence similarity fails to find significant matches, illustrating the potential use of binding site comparisons for newly determined proteins.     

The role of protein structure in genomics

The genome projects produce an enormous amount of sequence data that needs to be annotated in terms of molecular structure and biological function. These tasks have triggered additional initiatives like structural genomics. The intention is to determine as many protein structures as possible, in the most efficient way, and to exploit the solved structures for the assignment of biological function to hypothetical proteins. We discuss the impact of these developments on protein classification, gene function prediction, and protein structure prediction.     

CoPS: Comprehensive Peptide Signature database

We present the development of a Comprehensive database of 12 076 invariant Peptide Signatures (CoPS) derived from 52 bacterial genomes with a minimum occurrence in at least seven organisms. These peptides were observed in functionally similar proteins and are distributed over nearly 1250 different functional proteins. The database provides function, structure and occurrence in biochemical pathways of the proteins containing these signature peptides. It houses additional information on the signature peptides, such as identical match in other motif/pattern (e.g. PROSITE, BLOCKS, PRINTS and Pfam) databases and the database of interacting proteins, human proteome and mutation effect on these signature peptides. There is a wide applicability of this database in the identification of critical functional residues in proteins. The database also facilitates the identification of folding nucleus/structural determinants in proteins and functional assignment to yet unknown proteins. We demonstrate functional assignment to 2605 hypothetical proteins in bacterial genomes and 112 unknown proteins in human using this database. AVAILABILITY: The database can be freely accessed through the following URL: http://203.195.151.46/copsv2/index.html or http://203.90.127.70/copsv2/index.html     

Structure and functional annotation of hypothetical proteins having putative Rubisco activase function from Vitis vinifera

Rubisco is a very large, complex and one of the most abundant proteins in the world and comprises up to 50% of all soluble protein in plants. The activity of Rubisco, the enzyme that catalyzes CO₂ assimilation in photosynthesis, is regulated by Rubisco activase (Rca). In the present study, we searched for hypothetical protein of Vitis vinifera which has putative Rubisco activase function. The Arabidopsis and tobacco Rubisco activase protein sequences were used as seed sequences to search against Vitis vinifera in UniprotKB database. The selected hypothetical proteins of Vitis vinifera were subjected to sequence, structural and functional annotation. Subcellular localization predictions suggested it to be cytoplasmic protein. Homology modelling was used to define the three-dimensional (3D) structure of selected hypothetical proteins of Vitis vinifera. Template search revealed that all the hypothetical proteins share more than 80% sequence identity with structure of green-type Rubisco activase from tobacco, indicating proteins are evolutionary conserved. The homology modelling was generated using SWISS-MODEL. Several quality assessment and validation parameters computed indicated that homology models are reliable. Further, functional annotation through PFAM, CATH, SUPERFAMILY, CDART suggested that selected hypothetical proteins of Vitis vinifera contain ATPase family associated with various cellular activities (AAA) and belong to the AAA+ super family of ring-shaped P-loop containing nucleoside triphosphate hydrolases. This study will lead to research in the optimization of the functionality of Rubisco which has large implication in the improvement of plant productivity and resource use efficiency.     

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris

High efficiency capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine the proteins extracted from Desulfovibrio vulgaris cells across six treatment conditions. While our previous study provided a proteomic overview of the cellular metabolism based on proteins with known functions [W. Zhang, M.A. Gritsenko, R.J. Moore, D.E. Culley, L. Nie, K. Petritis, E.F. Strittmatter, D.G. Camp II, R.D. Smith, F.J. Brockman, A proteomic view of the metabolism in Desulfovibrio vulgaris determined by liquid chromatography coupled with tandem mass spectrometry, Proteomics 6 (2006) 4286-4299], this study describes the global detection and functional inference for hypothetical D. vulgaris proteins. Using criteria that a given peptide of a protein is identified from at least two out of three independent LC-MS/MS measurements and that for any protein at least two different peptides are identified among the three measurements, 129 open reading frames (ORFs) originally annotated as hypothetical proteins were found to encode expressed proteins. Functional inference for the conserved hypothetical proteins was performed by a combination of several non-homology based methods: genomic context analysis, phylogenomic profiling, and analysis of a combination of experimental information, including peptide detection in cells grown under specific culture conditions and cellular location of the proteins. Using this approach we were able to assign possible functions to 20 conserved hypothetical proteins. This study demonstrated that a combination of proteomics and bioinformatics methodologies can provide verification of the expression of hypothetical proteins and improve genome annotation.     

Assignment of protein function and discovery of novel nucleolar proteins based on automatic analysis of MEDLINE

Attribution of the most probable functions to proteins identified by proteomics is a significant challenge that requires extensive literature analysis. We have developed a system for automated prediction of implicit and explicit biologically meaningful functions for a proteomics study of the nucleolus. This approach uses a set of vocabulary terms to map and integrate the information from the entire MEDLINE database. Based on a combination of cross-species sequence homology searches and the corresponding literature, our approach facilitated the direct association between sequence data and information from biological texts describing function. Comparison of our automated functional assignment to manual annotation demonstrated our method to be highly effective. To establish the sensitivity, we defined the functional subtleties within a family containing a highly conserved sequence. Clustering of the DEAD-box protein family of RNA helicases confirmed that these proteins shared similar morphology although functional subfamilies were accurately identified by our approach. We visualized the nucleolar proteome in terms of protein functions using multi-dimensional scaling, showing functional associations between nucleolar proteins that were not previously realized. Finally, by clustering the functional properties of the established nucleolar proteins, we predicted novel nucleolar proteins. Subsequently, nonproteomics studies confirmed the predictions of previously unidentified nucleolar proteins.     

Structural and functional characterization of solute binding proteins for aromatic compounds derived from lignin: p‐Coumaric acid and related aromatic acids

Lignin comprises 15–25% of plant biomass and represents a major environmental carbon source for utilization by soil microorganisms. Access to this energy resource requires the action of fungal and bacterial enzymes to break down the lignin polymer into a complex assortment of aromatic compounds that can be transported into the cells. To improve our understanding of the utilization of lignin by microorganisms, we characterized the molecular properties of solute binding proteins of ATP‐binding cassette transporter proteins that interact with these compounds. A combination of functional screens and structural studies characterized the binding specificity of the solute binding proteins for aromatic compounds derived from lignin such as p‐coumarate, 3‐phenylpropionic acid and compounds with more complex ring substitutions. A ligand screen based on thermal stabilization identified several binding protein clusters that exhibit preferences based on the size or number of aromatic ring substituents. Multiple X‐ray crystal structures of protein–ligand complexes for these clusters identified the molecular basis of the binding specificity for the lignin‐derived aromatic compounds. The screens and structural data provide new functional assignments for these solute‐binding proteins which can be used to infer their transport specificity. This knowledge of the functional roles and molecular binding specificity of these proteins will support the identification of the specific enzymes and regulatory proteins of peripheral pathways that funnel these compounds to central metabolic pathways and will improve the predictive power of sequence‐based functional annotation methods for this family of proteins.Proteins 2013; 81:1709–1726. © 2013 Wiley Periodicals, Inc.     

Klebsiella Phage vB_KleM-RaK2 — A Giant Singleton Virus of the Family Myoviridae

At 346 kbp in size, the genome of a jumbo bacteriophage vB_KleM-RaK2 (RaK2) is the largest Klebsiella infecting myovirus genome sequenced to date. In total, 272 out of 534 RaK2 ORFs lack detectable database homologues. Based on the similarity to biologically defined proteins and/or MS/MS analysis, 117 of RaK2 ORFs were given a functional annotation, including 28 RaK2 ORFs coding for structural proteins that have no reliable homologues to annotated structural proteins in other organisms. The electron micrographs revealed elaborate spike-like structures on the tail fibers of Rak2, suggesting that this phage is an atypical myovirus. While head and tail proteins of RaK2 are mostly myoviridae-related, the bioinformatics analysis indicate that tail fibers/spikes of this phage are formed from podovirus-like peptides predominantly. Overall, these results provide evidence that bacteriophage RaK2 differs profoundly from previously studied viruses of the Myoviridae family.     

A computational study of Shewanella oneidensis MR-1: structural prediction and functional inference of hypothetical proteins

The genomes of many organisms have been sequenced in the last 5 years. Typically about 30% of predicted genes from a newly sequenced genome cannot be given functional assignments using sequence comparison methods. In these situations three-dimensional structural predictions combined with a suite of computational tools can suggest possible functions for these hypothetical proteins. Suggesting functions may allow better interpretation of experimental data (e.g., microarray data and mass spectroscopy data) and help experimentalists design new experiments. In this paper, we focus on three hypothetical proteins of Shewanella oneidensis MR-1 that are potentially related to iron transport/metabolism based on microarray experiments. The threading program PROSPECT was used for protein structural predictions and functional annotation, in conjunction with literature search and other computational tools. Computational tools were used to perform transmembrane domain predictions, coiled coil predictions, signal peptide predictions, sub-cellular localization predictions, motif prediction, and operon structure evaluations. Combined computational results from all tools were used to predict roles for the hypothetical proteins. This method, which uses a suite of computational tools that are freely available to academic users, can be used to annotate hypothetical proteins in general.     

Structural biology sheds light on the puzzle of genomic ORFans

Genomic ORFans are orphan open reading frames (ORFs) with no significant sequence similarity to other ORFs. ORFans comprise 20-30% of the ORFs of most completely sequenced genomes. Because nothing can be learnt about ORFans via sequence homology, the functions and evolutionary origins of ORFans remain a mystery. Furthermore, because relatively few ORFans have been experimentally characterized, it has been suggested that most ORFans are not likely to correspond to functional, expressed proteins, but rather to spurious ORFs, pseudo-genes or to rapidly evolving proteins with non-essential roles. As a snapshot view of current ORFan structural studies, we searched for ORFans among proteins whose three-dimensional structures have been recently determined. We find that functional and structural studies of ORFans are not as underemphasized as previously suggested. These recently determined structures correspond to ORFans from all Kingdoms of life, and include proteins that have previously been functionally characterized, as well as structural genomics targets of unknown function labeled as "hypothetical proteins". This suggests that many of the ORFans in the databases are likely to correspond to expressed, functional (and even essential) proteins. Furthermore, the recently determined structures include examples of the various types of ORFans, suggesting that the functions and evolutionary origins of ORFans are diverse. Although this survey sheds some light on the ORFan mystery, further experimental studies are required to gain a better understanding of the role and origins of the tens of thousands of ORFans awaiting characterization.     

Analysis of the first genome fragment from the marine sponge-associated, novel candidate phylum Poribacteria by environmental genomics

The novel candidate phylum Poribacteria is specifically associated with several marine demosponge genera. Because no representatives of Poribacteria have been cultivated, an environmental genomic approach was used to gain insights into genomic properties and possibly physiological/functional features of this elusive candidate division. In a large-insert library harbouring an estimated 1.1 Gb of microbial community DNA from Aplysina aerophoba, a Poribacteria-positive 16S rRNA gene locus was identified. Sequencing and sequence annotation of the 39 kb size insert revealed 27 open reading frames (ORFs) and two genes for stable RNAs. The fragment exhibited an overall G+C content of 50.5% and a coding density of 86.1%. The 16S rRNA gene was unlinked from a conventional rrn operon. Its flanking regions did not show any synteny to other 16S rRNA encoding loci from microorganisms with unlinked rrn operons. Two of the predicted hypothetical proteins were highly similar to homologues from Rhodopirellula baltica. Furthermore, a novel kind of molybdenum containing oxidoreductase was predicted as well as a series of eight ORFs encoding for unusual transporters, channel or pore forming proteins. This environmental genomics approach provides, for the first time, genomic and, by inference, functional information on the so far uncultivated, sponge-associated candidate division Poribacteria.     

3D profile-based approach to proteome-wide discovery of novel human chemokines

Chemokines are small secreted proteins with important roles in immune responses. They consist of a conserved three-dimensional (3D) structure, so-called IL8-like chemokine fold, which is supported by disulfide bridges characteristic of this protein family. Sequence- and profile-based computational methods have been proficient in discovering novel chemokines by making use of their sequence-conserved cysteine patterns. However, it has been recently shown that some chemokines escaped annotation by these methods due to low sequence similarity to known chemokines and to different arrangement of cysteines in sequence and in 3D. Innovative methods overcoming the limitations of current techniques may allow the discovery of new remote homologs in the still functionally uncharacterized fraction of the human genome. We report a novel computational approach for proteome-wide identification of remote homologs of the chemokine family that uses fold recognition techniques in combination with a scaffold-based automatic mapping of disulfide bonds to define a 3D profile of the chemokine protein family. By applying our methodology to all currently uncharacterized human protein sequences, we have discovered two novel proteins that, without having significant sequence similarity to known chemokines or characteristic cysteine patterns, show strong structural resemblance to known anti-HIV chemokines. Detailed computational analysis and experimental structural investigations based on mass spectrometry and circular dichroism support our structural predictions and highlight several other chemokine-like features. The results obtained support their functional annotation as putative novel chemokines and encourage further experimental characterization. The identification of remote homologs of human chemokines may provide new insights into the molecular mechanisms causing pathologies such as cancer or AIDS, and may contribute to the development of novel treatments. Besides, the genome-wide applicability of our methodology based on 3D protein family profiles may open up new possibilities for improving and accelerating protein function annotation processes.