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PubMed2001

A database and tools for 3-D protein structure comparison and alignment using the Combinatorial Extension (CE) algorithm.

The database reported here is derived using the Combinatorial Extension (CE) algorithm which compares pairs of protein polypeptide chains and provides a list of structurally similar proteins along with their structure alignments. Using CE, structure-structure alignments can provide insights into biological function. When a protein of known function is shown to be structurally similar to a protein of unknown function, a relationship might be inferred; a relationship not necessarily detectable from sequence comparison alone. Establishing structure-structure relationships in this way is of great importance as we enter an era of structural genomics where there is a likelihood of an increasing number of structures with unknown functions being determined. Thus the CE database is an example of a useful tool in the annotation of protein structures of unknown function. Comparisons can be performed on the complete PDB or on a structurally representative subset of proteins. The source protein(s) can be from the PDB (updated monthly) or uploaded by the user. CE provides sequence alignments resulting from structural alignments and Cartesian coordinates for the aligned structures, which may be analyzed using the supplied Compare3D Java applet, or downloaded for further local analysis. Searches can be run from the CE web site, http://cl.sdsc.edu/ce.html, or the database and software downloaded from the site for local use.

Algorithms↗
PubMed2004

Only one of the two annotated Lactococcus lactis fabG genes encodes a functional beta-ketoacyl-acyl carrier protein reductase.

The small genome of the Gram-positive bacterium Lactococcus lactis ssp. lactis IL1403 contains two genes that encode proteins annotated as homologues of Escherichia coli beta-hydroxyacyl-acyl carrier protein (ACP) reductase. E. coli fabG encodes beta-ketoacyl-acyl carrier protein (ACP) reductase, the enzyme responsible for the first reductive step of the fatty acid synthetic cycle. Both of the L. lactis genes are adjacent to (and predicted to be cotranscribed with) other genes that encode proteins having homology to known fatty acid synthetic enzymes. Such relationships have often been used to strengthen annotations based on sequence alignments. Annotation in the case of beta-ketoacyl-ACP reductase is particularly problematic because the protein is a member of a vast protein family, the short-chain alcohol dehydrogenase/reductase (SDR) family. The recent isolation of an E. coli fabG mutant strain encoding a conditionally active beta-ketoacyl-ACP reductase allowed physiological and biochemical testing of the putative L. lactishomologues. We report that expression of only one of the two L. lactis proteins (that annotated as FabG1) allows growth of the E. coli fabG strain under nonpermissive conditions and restores in vitro fatty acid synthetic ability to extracts of the mutant strain. Therefore, like E. coli, L. lactis has a single beta-ketoacyl-ACP reductase active with substrates of all fatty acid chain lengths. The second protein (annotated as FabG2), although inactive in fatty acid synthesis both in vivo and in vitro, was highly active in reduction of the model substrate, beta-ketobutyryl-CoA. As expected from work on the E. coli enzyme, the FabG1 beta-ketobutyryl-CoA reductase activity was inhibited by ACP (which blocks access to the active site) whereas the activity of FabG2 was unaffected by the presence of ACP. These results seem to be an example of a gene duplication event followed by divergence of one copy of the gene to encode a protein having a new function.

Alcohol Oxidoreductases↗
PubMed2000

Genome-wide protein interaction maps using two-hybrid systems.

Automated sequence technology has rendered functional biology amenable to genomic scale analysis. Among genome-wide exploratory approaches, the two-hybrid system in yeast (Y2H) has outranked other techniques because it is the system of choice to detect protein-protein interactions. Deciphering the cascade of binding events in a whole cell helps define signal transduction and metabolic pathways or enzymatic complexes. The function of proteins is eventually attributed through whole cell protein interaction maps where totally unknown proteins are partnered with fully annotated proteins belonging to the same functional category. Since its first description in the late 1980's, several versions of the Y2H have been developed in order to overcome the major limitations of the system, namely false positives and false negatives. Optimized versions have been recently applied at multi-molecular and genomic scale. These genome-wide surveys can be methodologically divided into two types of approaches: one either tests combinations of predefined polypeptides (the so-called matrix approach) using various short-cuts to speed up the process, or one screens with a given polypeptide (bait) for potential partners (preys) present in complex libraries of genomic or complementary DNA (library screening). In the former strategy, one tests what one knows, for example pair-wise interactions between full-length open reading frames from recently sequenced and annotated genomes. Although based on a one-by-one scheme, this method is reported to be amenable to large-scale genomics thanks to multicloning strategies and to the use of small robotics workstations. In the latter, highly complex cDNA or genomic libraries of protein domains can be screened to saturation with high-throughput screening systems allowing the discovery of yet unidentified proteins. Both approaches have strengths and drawbacks that will be discussed here. None yields a full proteome-wide screening since certain proteins (e.g. some transcription factors) are not usable in Y2H. Novel two-hybrid assays have been recently described in bacteria. Applications of these time- and cost-effective assays to genomic screening will be discussed and compared to the Y2H technology.

Animals↗
PubMed2001

[DNA arrays: technological aspects and applications].

The Human Genome Project has allowed considerable progress in the construction of physical and genetic maps and the identification of genes involved in human sicknesses. The accelerated accumulation of biological information and knowledge is due in large part to the sequencing projects of other organisms, which in fact paved the way for the Human Genome Project. In parallel, recently developed techniques which take advantage of genomic sequences allow large scale molecular analyses resulting in the functional annotation of many of the proteins represented by these genes. This is the goal of functional genomics. These progresses are at the origin of the present revolution in biomedical research. DNA microarrays are playing a dominant role compared to the other developing technologies since they are relatively easy to make and use and are applicable to numerous scientific inquiries. They allow the simultaneous analysis of several thousands of genes in biological samples from sick or healthy tissues, at the genome or transcriptome level. The data obtained is expected to result in major advances in the health sciences. In addition to an improved understanding of the complex molecular interaction networks of healthy cells and tissues, a more precise genetic characterization of the molecular mechanisms involved in pathology should result in the identification of new therapeutic targets and the development of new medicines. The genetic profiles thus obtained should also permit the definition of new pathologic subclasses not recognizable by traditional clinical factors, as well as new markers for susceptibility to certain illnesses, and new prognostic markers or methods of predicting responses to treatment. In this article, we present the different approaches and potential applications of DNA microarray technology, in particular as applied to cancer research.

Chromosome Mapping↗
PubMed1998

Selection system for genes encoding nuclear-targeted proteins.

Nuclear proteins have essential roles in cell proliferation and differentiation. We have developed a yeast selection system-the nuclear transportation trap (NTT)-to identify genes encoding nuclear transport signals. Both unknown and previously identified nuclear localization signals were identified from a human fetal brain cDNA library. The majority (75%) of the unknown proteins examined were exclusively localized to the nucleus in COS-7 cells. We propose that NTT is an efficient method for isolating cDNAs that encode nuclear targeted proteins that can be applied to the retrieval of novel nuclear proteins and to annotate gene function.

Amino Acid Sequence↗
PubMed2005

CLIP: a method for identifying protein-RNA interaction sites in living cells.

Nucleic-acid binding proteins constitute nearly one-fourth of all functionally annotated human genes. Genome-wide analysis of protein-nucleic acid contacts has not yet been performed for most of these proteins, restricting attempts to establish a comprehensive understanding of protein function. UV cross-linking is a method typically used to determine the position of direct interactions between proteins and nucleic acids. We have developed the cross-linking and immunoprecipitation assay, which exploits the covalent protein-nucleic acid cross-linking to stringently purify a specific protein-RNA complex using immunoprecipitation followed by SDS-PAGE separation. In this way, the vast majority of non-specific contaminating RNA, which can bind to co-immunoprecipitated proteins or beads, can be removed. Here, we present an improved protocol that performs RNA linker ligation before the SDS-PAGE step, and describe its application to the specific purification and amplification of RNA ligands of Nova in neurons.

Animals↗
PubMed2003

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.

ATP-Binding Cassette Transporters↗
PubMed2026

Genomic and transcriptomic characterization of genes expressed at 20 MPa by the marine actinobacterium Kocuria flava.

A marine hydrocarbonoclastic actinobacterium Kocuria flava IOS11 was isolated from 3500 m deep-sea water of the Indian Ocean. The isolate efficiently degraded phenanthrene (250 mg/L) achieving 82 and 98% of degradation at 0.1 MPa and 20 MPa, respectively within a period of 5 days. Whole genome, transcriptomee and metabolomic analysis elucidated its phenanthrene biodegradation efficiency under in situ deep-sea conditions. The genome sequence comprises 3.47 Mb distributed across 88 scaffolds with a high GC content of 74.30%. The genome analysis encoded 3126 genes including 3052 protein coding sequences with functional annotation identifying a broad array of genes associated with PAHs degradation, environmental stress adaptation, biosurfactant and siderophore synthesis. Transcriptome profiling under 0.1 and 20 MPa conditions with phenanthrene as a sole carbon source revealed enhanced expression of hydrocarbon degrading genes, transporters, biosurfactant associated enzymes and stress responsive genes including integrases, DNA repair protein Rad, alanine ligase, heat and cold shock proteins under high pressure conditions underscoring the deep-sea adaptation capabilities of the strain. The degradation pathway of phenanthrene was proposed through integrated genome, transcriptome and metabolomic analysis. These studies provided K. flava IOS11 as a metabolically versatile and pressure adapted bacterium with promising potential for bioremediation application in extreme marine environment.

Transcriptome↗
PubMed2006

EST-PAC a web package for EST annotation and protein sequence prediction.

With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST) from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST) annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1) searching local or remote biological databases for sequence similarities using Blast services, 2) predicting protein coding sequence from EST data and, 3) annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics.

Journal Article↗
PubMed2003

Affinity purification-mass spectrometry. Powerful tools for the characterization of protein complexes.

Multi-protein complexes are emerging as important entities of biological activity inside cells that serve to create functional diversity by contextual combination of gene products and, at the same time, organize the large number of different proteins into functional units. Many a time, when studying protein complexes rather than individual proteins, the biological insight gained has been fundamental, particularly in cases in which proteins with no previous functional annotation could be placed into a functional context derived from their 'molecular environment'. In this minireview, we summarize the current state of the art for the retrieval of multiprotein complexes by affinity purification and their analysis by mass spectrometry. The advances in technology made over the past few years now enable the study of protein complexes on a proteomic scale and it can be anticipated that the knowledge gathered from such projects will fuel drug target discovery and validation pipelines and that the technology is also going to prove valuable in the emerging field of systems biology.

Animals↗
PubMed2005

Functional annotation of deubiquitinating enzymes using RNA interference.

Protein ubiquitination is a dynamic process, depending on a tightly regulated balance between the activity of ubiquitin ligases and their antagonists, the ubiquitin-specific proteases or deubiquitinating enzymes. The family of ubiquitin ligases has been studied intensively and it is well established that their deregulation contributes to diverse disease processes, including cancer. Much less is known about the function and regulation of the large group of deubiquitinating enzymes. This chapter describes how RNA interference against deubiquitinating enzymes can be used to elucidate their function. The application of this technology will greatly improve the functional annotation of this family of proteases.

Cell Line, Tumor↗
PubMed2001

Sequence- and structure-based protein function prediction from genomic information.

Existing functional annotation transfer is fraught with inaccuracies that may hinder forward interpretation and mining of genomic data. Hand-curation of the annotation placed into databases is not practical. In lieu of experimental evidence, computational biological approaches offer high-throughput tools to predict function accurately; however, these methods are still notably deficient in defining and describing the complexity of protein function. Enriching genomic sequences obtained from sequencing efforts and expression array methods with protein function information and classification will be an efficient first step for incorporating genomic data into drug discovery programs.

Computational Biology↗
PubMed2004

Accurate prediction of solvent accessibility using neural networks-based regression.

Accurate prediction of relative solvent accessibilities (RSAs) of amino acid residues in proteins may be used to facilitate protein structure prediction and functional annotation. Toward that goal we developed a novel method for improved prediction of RSAs. Contrary to other machine learning-based methods from the literature, we do not impose a classification problem with arbitrary boundaries between the classes. Instead, we seek a continuous approximation of the real-value RSA using nonlinear regression, with several feed forward and recurrent neural networks, which are then combined into a consensus predictor. A set of 860 protein structures derived from the PFAM database was used for training, whereas validation of the results was carefully performed on several nonredundant control sets comprising a total of 603 structures derived from new Protein Data Bank structures and had no homology to proteins included in the training. Two classes of alternative predictors were developed for comparison with the regression-based approach: one based on the standard classification approach and the other based on a semicontinuous approximation with the so-called thermometer encoding. Furthermore, a weighted approximation, with errors being scaled by the observed levels of variability in RSA for equivalent residues in families of homologous structures, was applied in order to improve the results. The effects of including evolutionary profiles and the growth of sequence databases were assessed. In accord with the observed levels of variability in RSA for different ranges of RSA values, the regression accuracy is higher for buried than for exposed residues, with overall 15.3-15.8% mean absolute errors and correlation coefficients between the predicted and experimental values of 0.64-0.67 on different control sets. The new method outperforms classification-based algorithms when the real value predictions are projected onto two-class classification problems with several commonly used thresholds to separate exposed and buried residues. For example, classification accuracy of about 77% is consistently achieved on all control sets with a threshold of 25% RSA. A web server that enables RSA prediction using the new method and provides customizable graphical representation of the results is available at http://sable.cchmc.org.

Artificial Intelligence↗
PubMed2003

Using electrostatic potentials to predict DNA-binding sites on DNA-binding proteins.

A method to detect DNA-binding sites on the surface of a protein structure is important for functional annotation. This work describes the analysis of residue patches on the surface of DNA-binding proteins and the development of a method of predicting DNA-binding sites using a single feature of these surface patches. Surface patches and the DNA-binding sites were initially analysed for accessibility, electrostatic potential, residue propensity, hydrophobicity and residue conservation. From this, it was observed that the DNA-binding sites were, in general, amongst the top 10% of patches with the largest positive electrostatic scores. This knowledge led to the development of a prediction method in which patches of surface residues were selected such that they excluded residues with negative electrostatic scores. This method was used to make predictions for a data set of 56 non-homologous DNA-binding proteins. Correct predictions made for 68% of the data set.

Binding Sites↗
PubMed2004

A first-draft human protein-interaction map.

BACKGROUND: Protein-interaction maps are powerful tools for suggesting the cellular functions of genes. Although large-scale protein-interaction maps have been generated for several invertebrate species, projects of a similar scale have not yet been described for any mammal. Because many physical interactions are conserved between species, it should be possible to infer information about human protein interactions (and hence protein function) using model organism protein-interaction datasets. RESULTS: Here we describe a network of over 70,000 predicted physical interactions between around 6,200 human proteins generated using the data from lower eukaryotic protein-interaction maps. The physiological relevance of this network is supported by its ability to preferentially connect human proteins that share the same functional annotations, and we show how the network can be used to successfully predict the functions of human proteins. We find that combining interaction datasets from a single organism (but generated using independent assays) and combining interaction datasets from two organisms (but generated using the same assay) are both very effective ways of further improving the accuracy of protein-interaction maps. CONCLUSIONS: The complete network predicts interactions for a third of human genes, including 448 human disease genes and 1,482 genes of unknown function, and so provides a rich framework for biomedical research.

Databases, Protein↗
PubMed2024

Large language models improve annotation of prokaryotic viral proteins.

Viral genomes are poorly annotated in metagenomic samples, representing an obstacle to understanding viral diversity and function. Current annotation approaches rely on alignment-based sequence homology methods, which are limited by the paucity of characterized viral proteins and divergence among viral sequences. Here we show that protein language models can capture prokaryotic viral protein function, enabling new portions of viral sequence space to be assigned biologically meaningful labels. When applied to global ocean virome data, our classifier expanded the annotated fraction of viral protein families by 29%. Among previously unannotated sequences, we highlight the identification of an integrase defining a mobile element in marine picocyanobacteria and a capsid protein that anchors globally widespread viral elements. Furthermore, improved high-level functional annotation provides a means to characterize similarities in genomic organization among diverse viral sequences. Protein language models thus enhance remote homology detection of viral proteins, serving as a useful complement to existing approaches.

Viral Proteins↗
PubMed2006

The relationship between protein sequences and their gene ontology functions.

BACKGROUND: One main research challenge in the post-genomic era is to understand the relationship between protein sequences and their biological functions. In recent years, several automated annotation systems have been developed for the functional assignment of uncharacterized proteins. The underlying assumption of these systems is that similar sequences imply similar biological functions. However, it has been noted that matching sequences do not always infer similar functions. RESULTS: In this paper, we present the correlation between protein sequences and protein functions for the yeast proteome in the context of gene ontology. A novel measure is introduced to define the overall similarity between two protein sequences. The effects of the level as well as the size of a gene ontology group on the degree of similarity were studied. The similarity distributions at different levels of gene ontology trees are presented. To evaluate the theoretical prediction power of similar sequences, we computed the posterior probability of correct predictions. CONCLUSION: The results indicate that protein pairs of similar biological functions tend to have higher sequence similarity, although the similarity distribution in each functional group is heterogeneous and varies from group to group. We conclude that sequence similarity can serve as a key measure in protein function prediction. However, the resulting annotations must be verified through other means. A method that combines a broader range of measures is more likely to provide more accurate prediction. Our study indicates that the posterior probability of a correct prediction could serve as one of the key measures.

Amino Acid Sequence↗
PubMed2003

Small envelope protein E of SARS: cloning, expression, purification, CD determination, and bioinformatics analysis.

AIM: To obtain the pure sample of SARS small envelope E protein (SARS E protein), study its properties and analyze its possible functions. METHODS: The plasmid of SARS E protein was constructed by the polymerase chain reaction (PCR), and the protein was expressed in the E coli strain. The secondary structure feature of the protein was determined by circular dichroism (CD) technique. The possible functions of this protein were annotated by bioinformatics methods, and its possible three-dimensional model was constructed by molecular modeling. RESULTS: The pure sample of SARS E protein was obtained. The secondary structure feature derived from CD determination is similar to that from the secondary structure prediction. Bioinformatics analysis indicated that the key residues of SARS E protein were much conserved compared to the E proteins of other coronaviruses. In particular, the primary amino acid sequence of SARS E protein is much more similar to that of murine hepatitis virus (MHV) and other mammal coronaviruses. The transmembrane (TM) segment of the SARS E protein is relatively more conserved in the whole protein than other regions. CONCLUSION: The success of expressing the SARS E protein is a good starting point for investigating the structure and functions of this protein and SARS coronavirus itself as well. The SARS E protein may fold in water solution in a similar way as it in membrane-water mixed environment. It is possible that beta-sheet I of the SARS E protein interacts with the membrane surface via hydrogen bonding, this beta-sheet may uncoil to a random structure in water solution.

Circular Dichroism↗