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Bulk transcriptomes are an essential data resource for understanding basic and disease biology. However, integrating information from different experiments remains challenging because of the batch effect generated by various technological and biological variations in the transcriptome. Numerous batch-correction methods to deal with this batch effect have been developed in the past. However, a user-friendly workflow to select the most appropriate batch-correction method for the given set of experiments is still missing. We present the SelectBCM tool that prioritizes the most appropriate batch-correction method for a given set of bulk transcriptomic experiments, improving biological clustering and gene differential expression analysis. We demonstrate the applicability of the SelectBCM tool on analyses of real data for two common diseases, rheumatoid arthritis and osteoarthritis, and one example to characterize a biological state, where we performed a meta-analysis of the macrophage activation state. The R package is available at https://github.com/ebi-gene-expression-group/selectBCM.

The Protein Data Bank in Europe – Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive., ELIXIR [IDP implementation study]; Biotechnology and Biological Sciences Research Council via the 3D-Gateway [BB/T01959X/1]; FunPDBe [BB/P024351/1]; European Molecular Biology Laboratory-European Bioinformatics Institute who supported this work; J.D. acknowledges support from the Ministry of Education, Youth and Sport of the Czech Republic [INBIO CZ.02.1.01/0.0/0.0/16_026/0008451]; R.S., K.B. and J.D. also acknowledge support from the Ministry of Education, Youth and Sport of the Czech Republic [ELIXIR-CZ LM2018131]; L.M. acknowledges support from the European Union's Horizon 2020 Programme (H2020-INFRAIA-2018-1) [823839]; Research Foundation Flanders (FWO) [G032816N, G042518N, G028821N]; W.V. acknowledges support from the Research Foundation Flanders (FWO) [G032816N, G028821N]; A.R. acknowledges support from the Fondazione Cassa Di Risparmio di Firenze [24316]; European Commission [101017567]; M.H.C. acknowledges the AIRC project to MHC [IG 23539]; J.F.-R. acknowledges support from the Spanish Ministry of Science and Innovation [PID2019-110167RB-I00]; N.R. acknowledges support from the Norwegian Research Council (Norges Forskningsråd) [288008]; E.D.L. acknowledges support from the European Union's Horizon 2020 research and innovation programme [819318]; M.J.E.S. acknowledges support from the Wellcome Trust [104955/Z/14/Z, 218242/Z/19/Z]. Funding for open access charge: Biotechnology and Biological Sciences Research Council grant [BB/T01959X/1]; Wellcome Trust [104955/Z/14/Z and 218242/Z/19/Z].

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages—the PDBe-KB aggregated views of structure data—which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession.

Significance Aging is the main risk factor for the costliest diseases in today’s world. However, significant gaps remain in understanding how different cell types modulate this most common physiological process. Here, we use published single-cell gene expression data to map the prolongevity roles of two evolutionarily conserved Drosophila transcription factors, FKH and FOXO, onto either neuronal or glial cells. We then demonstrate that neuronal FKH preserves healthy function even under stress. Finally, we identify an autophagy-related gene as one of FKH’s downstream prolongevity effectors. Our results exemplify tapping into publicly available gene expression datasets to extract physiological insights, and highlight the need to shift away from organism-wide approaches and toward cell type-specific strategies to obtain meaningful insights in aging research., Reduced activity of insulin/insulin-like growth factor signaling (IIS) increases healthy lifespan among diverse animal species. Downstream of IIS, multiple evolutionarily conserved transcription factors (TFs) are required; however, distinct TFs are likely responsible for these effects in different tissues. Here we have asked which TFs can extend healthy lifespan within distinct cell types of the adult nervous system in Drosophila. Starting from published single-cell transcriptomic data, we report that forkhead (FKH) is endogenously expressed in neurons, whereas forkhead-box-O (FOXO) is expressed in glial cells. Accordingly, we find that neuronal FKH and glial FOXO exert independent prolongevity effects. We have further explored the role of neuronal FKH in a model of Alzheimer’s disease-associated neuronal dysfunction, where we find that increased neuronal FKH preserves behavioral function and reduces ubiquitinated protein aggregation. Finally, using transcriptomic profiling, we identify Atg17, a member of the Atg1 autophagy initiation family, as one FKH-dependent target whose neuronal overexpression is sufficient to extend healthy lifespan. Taken together, our results underscore the importance of cell type-specific mapping of TF activity to preserve healthy function with age.

Transposable elements (TEs) inflict numerous negative effects on health and fitness as they replicate by integrating into new regions of the host genome. Even though organisms employ powerful mechanisms to demobilize TEs, transposons gradually lose repression during aging. The rising TE activity causes genomic instability and was implicated in age-dependent neurodegenerative diseases, inflammation and the determination of lifespan. It is therefore conceivable that long-lived individuals have improved TE silencing mechanisms resulting in reduced TE expression relative to their shorter-lived counterparts and fewer genomic insertions. Here, we test this hypothesis by performing the first genome-wide analysis of TE insertions and expression in populations of Drosophila melanogaster selected for longevity through late-life reproduction for 50-170 generations from four independent studies. Contrary to our expectation, TE families were generally more abundant in long-lived populations compared to non-selected controls. Although simulations showed that this was not expected under neutrality, we found little evidence for selection driving TE abundance differences. Additional RNA-seq analysis revealed a tendency for reducing TE expression in selected populations, which might be more important for lifespan than regulating genomic insertions. We further find limited evidence of parallel selection on genes related to TE regulation and transposition. However, telomeric TEs were genomically and transcriptionally more abundant in long-lived flies, suggesting improved telomere maintenance as a promising TE-mediated mechanism for prolonging lifespan. Our results provide a novel viewpoint indicating that reproduction at old age increases the opportunity of TEs to be passed on to the next generation with little impact on longevity.

Increased cellular degradation by autophagy is a feature of many interventions that delay ageing. We report here that increased autophagy is necessary for reduced insulin-like signalling (IIS) to extend lifespan in Drosophila and is sufficient on its own to increase lifespan. We first established that the well-characterised lifespan extension associated with deletion of the insulin receptor substrate chico was completely abrogated by downregulation of the essential autophagy gene Atg5. We next directly induced autophagy by over-expressing the major autophagy kinase Atg1 and found that a mild increase in autophagy extended lifespan. Interestingly, strong Atg1 up-regulation was detrimental to lifespan. Transcriptomic and metabolomic approaches identified specific signatures mediated by varying levels of autophagy in flies. Transcriptional upregulation of mitochondrial-related genes was the signature most specifically associated with mild Atg1 upregulation and extended lifespan, whereas short-lived flies, possessing strong Atg1 overexpression, showed reduced mitochondrial metabolism and up-regulated immune system pathways. Increased proteasomal activity and reduced triacylglycerol levels were features shared by both moderate and high Atg1 overexpression conditions. These contrasting effects of autophagy on ageing and differential metabolic profiles highlight the importance of fine-tuning autophagy levels to achieve optimal healthspan and disease prevention., Author summary The increasing number of people living with age-related diseases underscores the importance of ageing research to improve healthspan. Two well-studied evolutionary conserved interventions that extend lifespan and improve health are dietary restriction and down-regulation of nutrient sensing pathways, such as glucose sensing by insulin and amino acid sensing by the target-of-rapamycin signalling pathway. One common characteristic of these anti-ageing interventions is an increase in autophagy, a cellular pathway that degrades damaged proteins and organelles to supply essential building blocks and energy. To help provide a more direct link between autophagy and healthy ageing, we fine-tuned overexpression of Atg1 kinase, which is critical for autophagy induction, and measured its effect on longevity in the fruit fly Drosophila. Interestingly, we observed that a moderate increase in autophagy is beneficial in extending healthy lifespan, whereas strong autophagy up-regulation is detrimental and leads to progressive lipid loss and decreased lifespan. Moderate and stronger Atg1 overexpression displayed opposing transcriptional profiles of mitochondrial genes, being upregulated in long-lived and down-regulated in short-lived Atg1 over-expressing animals. Overall, we provide a detailed description of the phenotypes associated with varying degrees of autophagy up-regulation in vivo, demonstrating that autophagy enhancement delays ageing only when applied in moderation.

Age is a common risk factor in many diseases, but the molecular basis for this relationship is elusive. In this study we identified 4 disease clusters from 116 diseases in the UK Biobank data, defined by their age-of-onset profiles, and found that diseases with the same onset profile are genetically more similar, suggesting a common etiology. This similarity was not explained by disease categories, co-occurrences or disease cause-effect relationships. Two of the four disease clusters had an increased risk of occurrence from age 20 and 40 years respectively. They both showed an association with known aging-related genes, yet differed in functional enrichment and evolutionary profiles. We tested mutation accumulation and antagonistic pleiotropy theories of aging and found support for both. We also identified drug candidates for repurposing to target multiple age-dependent diseases with the potential to improve healthspan and alleviate multimorbidity and polypharmacy in the elderly.

Background Cys‐loop receptors control neuronal excitability in the brain and their dysfunction results in numerous neurological disorders. Recently, six missense variants in GABRA2, a member of this family, have been associated with early infantile epileptic encephalopathy (EIEE). We identified a novel de novo missense variant in GABRA2 in a patient with EIEE and performed protein structural analysis of the seven variants. Methods The novel variant was identified by trio whole‐genome sequencing. We performed protein structural analysis of the seven variants, and compared them to previously reported pathogenic mutations at equivalent positions in other Cys‐loop receptors. Additionally, we studied the distribution of disease‐associated variants in the transmembrane helices of these proteins. Results The seven variants are in the transmembrane domain, either close to the desensitization gate, the activation gate, or in inter‐subunit interfaces. Six of them have pathogenic mutations at equivalent positions in other Cys‐loop receptors, emphasizing the importance of these residues. Also, pathogenic mutations are more common in the pore‐lining helix, consistent with this region being highly constrained for variation in control populations. Conclusion Our study reports a novel pathogenic variant in GABRA2, characterizes the regions where pathogenic mutations are in the transmembrane helices, and underscores the value of considering sequence, evolutionary, and structural information as a strategy for variant interpretation of novel missense mutations., This study reports a novel pathogenic variant in GABRA2, characterizes the regions where pathogenic mutations are in the transmembrane helices, and underscores the value of considering sequence, evolutionary, and structural information as a strategy for variant interpretation of novel missense mutations.

DNA methylation is an important epigenetic modification in many species that is critical for development, and implicated in ageing and many complex diseases, such as cancer. Many cost-effective genome-wide analyses of DNA modifications rely on restriction enzymes capable of digesting genomic DNA at defined sequence motifs. There are hundreds of restriction enzyme families but few are used to date, because no tool is available for the systematic evaluation of restriction enzyme combinations that can enrich for certain sites of interest in a genome. Herein, we present customised Reduced Representation Bisulfite Sequencing (cuRRBS), a novel and easy-to-use computational method that solves this problem. By computing the optimal enzymatic digestions and size selection steps required, cuRRBS generalises the traditional MspI-based Reduced Representation Bisulfite Sequencing (RRBS) protocol to all restriction enzyme combinations. In addition, cuRRBS estimates the fold-reduction in sequencing costs and provides a robustness value for the personalised RRBS protocol, allowing users to tailor the protocol to their experimental needs. Moreover, we show in silico that cuRRBS-defined restriction enzymes consistently out-perform MspI digestion in many biological systems, considering both CpG and CHG contexts. Finally, we have validated the accuracy of cuRRBS predictions for single and double enzyme digestions using two independent experimental datasets.

Background Epigenetic clocks are mathematical models that predict the biological age of an individual using DNA methylation data and have emerged in the last few years as the most accurate biomarkers of the aging process. However, little is known about the molecular mechanisms that control the rate of such clocks. Here, we have examined the human epigenetic clock in patients with a variety of developmental disorders, harboring mutations in proteins of the epigenetic machinery. Results Using the Horvath epigenetic clock, we perform an unbiased screen for epigenetic age acceleration in the blood of these patients. We demonstrate that loss-of-function mutations in the H3K36 histone methyltransferase NSD1, which cause Sotos syndrome, substantially accelerate epigenetic aging. Furthermore, we show that the normal aging process and Sotos syndrome share methylation changes and the genomic context in which they occur. Finally, we found that the Horvath clock CpG sites are characterized by a higher Shannon methylation entropy when compared with the rest of the genome, which is dramatically decreased in Sotos syndrome patients. Conclusions These results suggest that the H3K36 methylation machinery is a key component of the epigenetic maintenance system in humans, which controls the rate of epigenetic aging, and this role seems to be conserved in model organisms. Our observations provide novel insights into the mechanisms behind the epigenetic aging clock and we expect will shed light on the different processes that erode the human epigenetic landscape during aging. Electronic supplementary material The online version of this article (10.1186/s13059-019-1753-9) contains supplementary material, which is available to authorized users.

Cys-loop receptors are vital for controlling neuronal excitability in the brain and their dysfunction results in numerous neurological disorders. Recently, six de novo missense variants in GABRA2 gene, a member of this family, have been associated with early infantile epileptic encephalopathy (EIEE) and intellectual disability with seizures. Here, using whole-genome sequencing we identified a de novo missense variant in GABRA2 gene in a patient with EIEE and developmental delay. We perform protein structural analysis of the seven variants and show that all the mutations are in the transmembrane domain, either close to the desensitization gate, the activation gate or in inter-subunit interfaces. Further investigations demonstrated that the majority of pathogenic variants reported are at equivalent positions in other Cys-loop receptors, emphasizing the importance of these residues for the adequate function of the receptor. Also, a comparison of the distribution of the mutations in all the Cys-loop receptors showed that pathogenic variants are more common in the transmembrane helices, more specifically in the M2 helix, highlighting the importance of this segment. Our study expands the clinical spectrum of individuals with pathogenic missense mutations in GABRA2, defines the regions where pathogenic mutations are in the protein structure, and highlights the value of considering sequence, evolutionary, and structural information from other Cys-loop receptors as a strategy for variant interpretation of novel missense mutations in GABRA2.

BackgroundEpigenetic clocks are mathematical models that predict the biological age of an individual using DNA methylation data, and which have emerged in the last few years as the most accurate biomarkers of the ageing process. However, little is known about the molecular mechanisms that control the rate of such clocks. Here, we have examined the human epigenetic clock in patients with a variety of developmental disorders, harbouring mutations in proteins of the epigenetic machinery.ResultsUsing the Horvath epigenetic clock, we performed an unbiased screen for epigenetic age acceleration (EAA) in the blood of these patients. We demonstrate that loss-of-function mutations in the H3K36 histone methyltransferase NSD1, which cause Sotos syndrome, substantially accelerate epigenetic ageing. Furthermore, we show that the normal ageing process and Sotos syndrome share methylation changes and the genomic context in which they occur. Finally, we found that the Horvath clock CpG sites are characterised by a higher Shannon methylation entropy when compared with the rest of the genome, which is dramatically decreased in Sotos syndrome patients.ConclusionsThese results suggest that the H3K36 methylation machinery is a key component of theepigenetic maintenance systemin humans, which controls the rate of epigenetic ageing, and this role seems to be conserved in model organisms. Our observations provide novel insights into the mechanisms behind the epigenetic ageing clock and we expect will shed light on the different processes that erode the human epigenetic landscape during ageing.

We present a generic, multidisciplinary approach for improving our understanding of novel missense variants in recently discovered disease genes exhibiting genetic heterogeneity, by combining clinical and population genetics with protein structural analysis. Using six new de novo missense diagnoses in TBL1XR1 from the Deciphering Developmental Disorders study, together with population variation data, we show that the β-propeller structure of the ubiquitous WD40 domain provides a convincing way to discriminate between pathogenic and benign variation. Children with likely pathogenic mutations in this gene have severely delayed language development, often accompanied by intellectual disability, autism, dysmorphology and gastrointestinal problems. Amino acids affected by likely pathogenic missense mutations are either crucial for the stability of the fold, forming part of a highly conserved symmetrically repeating hydrogen-bonded tetrad, or located at the top face of the β-propeller, where 'hotspot' residues affect the binding of β-catenin to the TBLR1 protein. In contrast, those altered by population variation are significantly less likely to be spatially clustered towards the top face or to be at buried or highly conserved residues. This result is useful not only for interpreting benign and pathogenic missense variants in this gene, but also in other WD40 domains, many of which are associated with disease.

Many research teams perform numerous genetic, transcriptomic, proteomic and other types of omic experiments to understand molecular, cellular and physiological mechanisms of disease and health. Often (but not always), the results of these experiments are deposited in publicly available repository databases. These data records often include phenotypic characteristics following genetic and environmental perturbations, with the aim of discovering underlying molecular mechanisms leading to the phenotypic responses. A constrained set of phenotypic characteristics is usually recorded and these are mostly hypothesis driven of possible to record within financial or practical constraints. We present a novel proof-of-principal computational approach for combining publicly available gene-expression data from control/mutant animal experiments that exhibit a particular phenotype, and we use this approach to predict unobserved phenotypic characteristics in new experiments (data derived from EBI’s ArrayExpress and ExpressionAtlas respectively). We utilised available microarray gene-expression data for two phenotypes (starvation-sensitive and sterile) in Drosophila. The data were combined using a linear-mixed effects model with the inclusion of consecutive principal components to account for variability between experiments in conjunction with Gene Ontology enrichment analysis. We present how available data can be ranked in accordance to a phenotypic likelihood of exhibiting these two phenotypes using random forest. The results from our study show that it is possible to integrate seemingly different gene-expression microarray data and predict a potential phenotypic manifestation with a relatively high degree of confidence (>80% AUC). This provides thus far unexplored opportunities for inferring unknown and unbiased phenotypic characteristics from already performed experiments, in order to identify studies for future analyses. Molecular mechanisms associated with gene and environment perturbations are intrinsically linked and give rise to a variety of phenotypic manifestations. Therefore, unravelling the phenotypic spectrum can help to gain insights into disease mechanisms associated with gene and environmental perturbations. Our approach uses public data that are set to increase in volume, thus providing value for money.

Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established their association with ageing at multiple levels of biological action including pathways, functions and protein interactions. Finally, combining all the data, we calculated a ranked list of drugs that identified tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans., Author summary Human life expectancy is continuing to increase worldwide, as a result of successive improvements in living conditions and medical care. Although this trend is to be celebrated, advancing age is the major risk factor for multiple impairments and chronic diseases. As a result, the later years of life are often spent in poor health and lowered quality of life. However, these effects of ageing are not inevitable, because very long-lived people often suffer rather little ill-health at the end of their lives. Furthermore, laboratory experiments have shown that animals fed with specific drugs can live longer and with fewer age-related diseases than their untreated companions. We therefore need to identify drugs with anti-ageing properties for humans. We have used publically available data and a computer-based approach to search for drugs that affect components and processes known to be important in human ageing. This approach worked, because it was able to re-discover several drugs known to increase lifespan in animal models, plus some new ones, including one that we tested experimentally and validated in this study. These drugs are now a high priority for animal testing and for exploring effects on human ageing.

M-CSA (Mechanism and Catalytic Site Atlas) is a database of enzyme active sites and reaction mechanisms that can be accessed at www.ebi.ac.uk/thornton-srv/m-csa. Our objectives with M-CSA are to provide an open data resource for the community to browse known enzyme reaction mechanisms and catalytic sites, and to use the dataset to understand enzyme function and evolution. M-CSA results from the merging of two existing databases, MACiE (Mechanism, Annotation and Classification in Enzymes), a database of enzyme mechanisms, and CSA (Catalytic Site Atlas), a database of catalytic sites of enzymes. We are releasing M-CSA as a new website and underlying database architecture. At the moment, M-CSA contains 961 entries, 423 of these with detailed mechanism information, and 538 with information on the catalytic site residues only. In total, these cover 81% (195/241) of third level EC numbers with a PDB structure, and 30% (840/2793) of fourth level EC numbers with a PDB structure, out of 6028 in total. By searching for close homologues, we are able to extend M-CSA coverage of PDB and UniProtKB to 51 993 structures and to over five million sequences, respectively, of which about 40% and 30% have a conserved active site.

Background Syntaxin-binding protein 1, encoded by STXBP1, is highly expressed in the brain and involved in fusing synaptic vesicles with the plasma membrane. Studies have shown that pathogenic loss-of-function variants in this gene result in various types of epilepsies, mostly beginning early in life. We were interested to model pathogenic missense variants on the protein structure to investigate the mechanism of pathogenicity and genotype–phenotype correlations. Methods We report 11 patients with pathogenic de novo mutations in STXBP1 identified in the first 4293 trios of the Deciphering Developmental Disorder (DDD) study, including six missense variants. We analyzed the structural locations of the pathogenic missense variants from this study and the literature, as well as population missense variants extracted from Exome Aggregation Consortium (ExAC). Results Pathogenic variants are significantly more likely to occur at highly conserved locations than population variants, and be buried inside the protein domain. Pathogenic mutations are also more likely to destabilize the domain structure compared with population variants, increasing the proportion of (partially) unfolded domains that are prone to aggregation or degradation. We were unable to detect any genotype–phenotype correlation, but unlike previously reported cases, most of the DDD patients with STXBP1 pathogenic variants did not present with very early-onset or severe epilepsy and encephalopathy, though all have developmental delay with intellectual disability and most display behavioral problems and suffered seizures in later childhood. Conclusion Variants across STXBP1 that cause loss of function can result in severe intellectual disability with or without seizures, consistent with a haploinsufficiency mechanism. Pathogenic missense mutations act through destabilization of the protein domain, making it prone to aggregation or degradation. The presence or absence of early seizures may reflect ascertainment bias in the literature as well as the broad recruitment strategy of the DDD study.

Understanding which are the catalytic residues in an enzyme and what function they perform is crucial to many biology studies, particularly those leading to new therapeutics and enzyme design. The original version of the Catalytic Site Atlas (CSA) (http://www.ebi.ac.uk/thornton-srv/databases/CSA) published in 2004, which catalogs the residues involved in enzyme catalysis in experimentally determined protein structures, had only 177 curated entries and employed a simplistic approach to expanding these annotations to homologous enzyme structures. Here we present a new version of the CSA (CSA 2.0), which greatly expands the number of both curated (968) and automatically annotated catalytic sites in enzyme structures, utilizing a new method for annotation transfer. The curated entries are used, along with the variation in residue type from the sequence comparison, to generate 3D templates of the catalytic sites, which in turn can be used to find catalytic sites in new structures. To ease the transfer of CSA annotations to other resources a new ontology has been developed: the Enzyme Mechanism Ontology, which has permitted the transfer of annotations to Mechanism, Annotation and Classification in Enzymes (MACiE) and UniProt Knowledge Base (UniProtKB) resources. The CSA database schema has been re-designed and both the CSA data and search capabilities are presented in a new modern web interface.

Survival records of longevity experiments are a key component in research on aging. However, surprisingly there have been very few cross-study analyses, besides comparisons of median lifespans or similar summary information. Here, we use a large set of full survival data from various studies to address questions in aging, which are beyond the scope of individual studies. We characterize survival differences between female and male flies of different genetic Drosophila strains, showing significant differences between strains. We further analyse the variation in survival of control cohorts recorded under highly similar conditions within different Drosophila strains. We found that overall transgenic constructs of the UAS/GAL4 expression system which should have no effect (e.g. a GAL4 construct alone) extend lifespan significantly in the w1118 strain. Using a large data set comprised of various studies, we found no evidence for larger lifespan extensions being associated with shorter lifespans of the control in Drosophila. This demonstrates that lifespan extending treatments are not purely rescuing weak backgrounds.

Intracellular communication from the mitochondria to the nucleus is achieved via the retrograde response. In budding yeast, the retrograde response, also known as the RTG pathway, is regulated positively by Rtg1, Rtg2, Rtg3 and Grr1 and negatively by Mks1, Lst8 and two 14-3-3 proteins, Bmh1/2. Activation of retrograde signaling leads to activation of Rtg1/3, two basic helix-loop-helix leucine zipper transcription factors. Rtg1/3 activation requires Rtg2, a cytoplasmic protein with an N-terminal adenosine triphosphate (ATP) binding domain belonging to the actin/Hsp70/sugar kinase superfamily. The critical regulatory step of the retrograde response is the interaction between Rtg2 and Mks1. Rtg2 binds to and inactivates Mks1, allowing for activation of Rtg1/3 and the RTG pathway. When the pathway is inactive, Mks1 has dissociated from Rtg2 and bound to Bmh1/2, preventing activation of Rtg1/3. What signals association or disassociation of Mks1 and Rtg2 is unknown. Here, we show that ATP at physiological concentrations dissociates Mks1 from Rtg2 in a highly cooperative fashion. We report that ATP-mediated dissociation of Mks1 from Rtg2 is conserved in two other fungal species, K. lactis and K. waltii. Activation of Rtg1/3 upregulates expression of genes encoding enzymes catalyzing the first three reactions of the Krebs cycle, which is coupled to ATP synthesis through oxidative phosphorylation. Therefore, we propose that the retrograde response is an ATP homeostasis pathway coupling ATP production with ATP-mediated repression of the retrograde response by releasing Mks1 from Rtg2.

The availability of comprehensive information about enzymes plays an important role in answering questions relevant to interdisciplinary fields such as biochemistry, enzymology, biofuels, bioengineering and drug discovery. At the EMBL European Bioinformatics Institute, we have developed an enzyme portal (http://www.ebi.ac.uk/enzymeportal) to provide this wealth of information on enzymes from multiple in-house resources addressing particular data classes: protein sequence and structure, reactions, pathways and small molecules. The fact that these data reside in separate databases makes information discovery cumbersome. The main goal of the portal is to simplify this process for end users.

High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions.

CATH version 3.3 (class, architecture, topology, homology) contains 128,688 domains, 2386 homologous superfamilies and 1233 fold groups, and reflects a major focus on classifying structural genomics (SG) structures and transmembrane proteins, both of which are likely to add structural novelty to the database and therefore increase the coverage of protein fold space within CATH. For CATH version 3.4 we have significantly improved the presentation of sequence information and associated functional information for CATH superfamilies. The CATH superfamily pages now reflect both the functional and structural diversity within the superfamily and include structural alignments of close and distant relatives within the superfamily, annotated with functional information and details of conserved residues. A significantly more efficient search function for CATH has been established by implementing the search server Solr (http://lucene.apache.org/solr/). The CATH v3.4 webpages have been built using the Catalyst web framework.

The wide uptake of next-generation sequencing and other ultra-high throughput technologies by life scientists with a diverse range of interests, spanning fundamental biological research, medicine, agriculture and environmental science, has led to unprecedented growth in the amount of data generated. It has also put the need for unrestricted access to biological data at the centre of biology. The European Bioinformatics Institute (EMBL-EBI) is unique in Europe and is one of only two organisations worldwide providing access to a comprehensive, integrated set of these collections. Here, we describe how the EMBL-EBI's biomolecular databases are evolving to cope with increasing levels of submission, a growing and diversifying user base, and the demand for new types of data. All of the resources described here can be accessed from the EMBL-EBI website: http://www.ebi.ac.uk.

The process of natural selection acts both on individual organisms within a population and on individual cells within an organism as they develop into cancer. In this work, we have taken a first step toward understanding the differences in selection pressures exerted on the human genome under these disparate circumstances. Focusing on single amino acid substitutions, we have found that cancer-related mutations (CRMs) are frequent in evolutionarily conserved sites, whereas single amino acid polymorphisms (SAPs) tend to appear in sites having a more relaxed evolutionary pressure. Those CRMs classed as cancer driver mutations show greater enrichment for conserved sites than passenger mutations. Consistent with this, driver mutations are enriched for sites annotated as key functional residues and their neighbors, and are more likely to be located on the surface of proteins than expected by chance. Overall the pattern of CRM and polymorphism is remarkably similar, but we do see a clear signal indicative of diversifying selection for disruptive amino acid substitutions in the cancer driver mutations. The ultimate consequence of the appearance of those mutations must be advantageous for the tumor cell, leading to cell population-growth and migration events similar to those seen in natural ecosystems. Proteins 2010. © 2009 Wiley-Liss, Inc.

Recent evidence suggests that alterations in insulin/insulin-like growth factor 1 (IGF1) signaling (IIS) can increase mammalian life span. For example, in several mouse mutants, impairment of the growth hormone (GH)/IGF1 axis increases life span and also insulin sensitivity. However, the intracellular signaling route to altered mammalian aging remains unclear. We therefore measured the life span of mice lacking either insulin receptor substrate (IRS) 1 or 2, the major intracellular effectors of the IIS receptors. Our provisional results indicate that female Irs1-/- mice are long-lived. Furthermore, they displayed resistance to a range of age-sensitive markers of aging including skin, bone, immune, and motor dysfunction. These improvements in health were seen despite mild, lifelong insulin resistance. Thus, enhanced insulin sensitivity is not a prerequisite for IIS mutant longevity. Irs1-/- female mice also displayed normal anterior pituitary function, distinguishing them from long-lived somatotrophic axis mutants. In contrast, Irs2-/- mice were short-lived, whereas Irs1+/- and Irs2+/- mice of both sexes showed normal life spans. Our results therefore suggest that IRS1 signaling is an evolutionarily conserved pathway regulating mammalian life span and may be a point of intervention for therapies with the potential to delay age-related processes.

Allergic reactions can be considered as maladaptive IgE immune responses towards environmental antigens. Intriguingly, these mechanisms are observed to be very similar to those implicated in the acquisition of an important degree of immunity against metazoan parasites (helminths and arthropods) in mammalian hosts. Based on the hypothesis that IgE-mediated immune responses evolved in mammals to provide extra protection against metazoan parasites rather than to cause allergy, we predict that the environmental allergens will share key properties with the metazoan parasite antigens that are specifically targeted by IgE in infected human populations. We seek to test this prediction by examining if significant similarity exists between molecular features of allergens and helminth proteins that induce an IgE response in the human host. By employing various computational approaches, 2712 unique protein molecules that are known IgE antigens were searched against a dataset of proteins from helminths and parasitic arthropods, resulting in a comprehensive list of 2445 parasite proteins that show significant similarity through sequence and structure with allergenic proteins. Nearly half of these parasite proteins from 31 species fall within the 10 most abundant allergenic protein domain families (EF-hand, Tropomyosin, CAP, Profilin, Lipocalin, Trypsin-like serine protease, Cupin, BetV1, Expansin and Prolamin). We identified epitopic-like regions in 206 parasite proteins and present the first example of a plant protein (BetV1) that is the commonest allergen in pollen in a worm, and confirming it as the target of IgE in schistosomiasis infected humans. The identification of significant similarity, inclusive of the epitopic regions, between allergens and helminth proteins against which IgE is an observed marker of protective immunity explains the ‘off-target’ effects of the IgE-mediated immune system in allergy. All these findings can impact the discovery and design of molecules used in immunotherapy of allergic conditions., Author Summary Allergy is an increasingly widespread clinical problem that leads to various conditions such as allergic asthma and susceptibility to anaphylactic shock. These conditions arise from exposure to a range of environmental and food proteins (‘allergens’) that are recognised by a form of immune system antibody called IgE. This part of the immune system is thought to have evolved to provide mammals with additional rapid response mechanisms to combat metazoan parasites. Here, we address the pertinent question, ‘what makes an Allergen an Allergen’ as, although they constitute a very small percentage of known proteins, they appear to be diverse and unrelated. Using computational studies, we have established molecular similarity between parasite proteins and allergens that affect the nature of immune response and are able to predict the regions of parasite proteins that potentially share similarity with the IgE-binding region(s) of the allergens. Our experimental studies support the computational predictions, and we can present the first confirmed example of a plant pollen-like protein in a worm that is targeted by IgE. The results of this study will enable us to predict likely allergens in food and environmental organisms and to help design protein molecules to treat allergy in the future.

Enzyme activity is essential for almost all aspects of life. With completely sequenced genomes, the full complement of enzymes in an organism can be defined, and 3D structures have been determined for many enzyme families. Traditionally each enzyme has been studied individually, but as more enzymes are characterised it is now timely to revisit the molecular basis of catalysis, by comparing different enzymes and their mechanisms, and to consider how complex pathways and networks may have evolved. New approaches to understanding enzymes mechanisms and how enzyme families evolve functional diversity will be described. References

Caloric restriction (CR) increases healthy life span in a range of organisms. The underlying mechanisms are not understood but appear to include changes in gene expression, protein function, and metabolism. Recent studies demonstrate that acute CR alters mortality rates within days in flies. Multitissue transcriptional changes and concomitant metabolic responses to acute CR have not been described. We generated whole genome RNA transcript profiles in liver, skeletal muscle, colon, and hypothalamus and simultaneously measured plasma metabolites using proton nuclear magnetic resonance in mice subjected to acute CR. Liver and muscle showed increased gene expressions associated with fatty acid metabolism and a reduction in those involved in hepatic lipid biosynthesis. Glucogenic amino acids increased in plasma, and gene expression for hepatic gluconeogenesis was enhanced. Increased expression of genes for hormone-mediated signaling and decreased expression of genes involved in protein binding and development occurred in hypothalamus. Cell proliferation genes were decreased and cellular transport genes increased in colon. Acute CR captured many, but not all, hepatic transcriptional changes of long-term CR. Our findings demonstrate a clear transcriptional response across multiple tissues during acute CR, with congruent plasma metabolite changes. Liver and muscle switched gene expression away from energetically expensive biosynthetic processes toward energy conservation and utilization processes, including fatty acid metabolism and gluconeogenesis. Both muscle and colon switched gene expression away from cellular proliferation. Mice undergoing acute CR rapidly adopt many transcriptional and metabolic changes of long-term CR, suggesting that the beneficial effects of CR may require only a short-term reduction in caloric intake.

This work is funded by the UK EPSRC and BBSRC (grant BB/C51320X/1) MACiE (Mechanism, Annotation and Classification in Enzymes) is a database of enzyme reaction mechanisms, and is publicly available as a web-based data resource. This paper presents the first release of a web-based search tool to explore enzyme reaction mechanisms in MACiE. We also present Version 2 of MACiE, which doubles the dataset available (from Version 1). MACiE can be accessed from http://www.ebi.ac.uk/thornton-srv/databases/MACIE/. Publisher PDF

By exploiting three-dimensional structure comparison, which is more sensitive than conventional sequence-based methods for detecting remote homology, we have identified a set of 140 ancestral protein domains using very restrictive criteria to minimize the potential error introduced by horizontal gene transfer. These domains are highly likely to have been present in the Last Universal Common Ancestor (LUCA) based on their universality in almost all of 114 completed prokaryotic (Bacteria and Archaea) and eukaryotic genomes. Functional analysis of these ancestral domains reveals a genetically complex LUCA with practically all the essential functional systems present in extant organisms, supporting the theory that life achieved its modern cellular status much before the main kingdom separation (Doolittle 2000). In addition, we have calculated different estimations of the genetic and functional versatility of all the superfamilies and functional groups in the prokaryote subsample. These estimations reveal that some ancestral superfamilies have been more versatile than others during evolution allowing more genetic and functional variation. Furthermore, the differences in genetic versatility between protein families are more attributable to their functional nature rather than the time that they have been evolving. These differences in tolerance to mutation suggest that some protein families have eroded their phylogenetic signal faster than others, hiding in many cases, their ancestral origin and suggesting that the calculation of 140 ancestral domains is probably an underestimate. © 2006 Springer Science+Business Media, Inc., This work was supported by grants from the MRC (Christine A. Orengo) and European Union (Juan A. G. Ranea). A.S. was a visiting professor at UCL (from UAM) aided by the Spanish Ministry of Education and Science and supported by grants from Direccion General de Investigacion Cientifica y Tecnica (08/0021.1/2001) and Instituto de Salud Carlos III, RMN (C03/08) Madrid, Spain.

The longevity of the Caenorhabditis elegans diapausal dauer larva greatly exceeds that of the adult. Dauer formation and adult ageing are both regulated by insulin/IGF-1 signaling (IIS). Reduced IIS, e.g. by mutation of the daf-2 insulin/IGF-1 receptor gene, increases adult lifespan. This may reflect mis-expression in the adult of dauer longevity-assurance processes. Since IIS plays a central role in the regulation of metabolism, metabolic alterations shared by dauer larvae and daf-2 adults represent candidate mechanisms for lifespan determination. We have conducted a detailed comparison of transcript profile data from dauers and daf-2 mutant adults, focusing on expression of metabolic pathway genes. Our results imply up-regulation in both dauers and daf-2 mutant adults of gluconeogenesis, glyoxylate pathway activity, and trehalose biosynthesis. Down-regulation of the citric acid cycle and mitochondrial respiratory chain occurs in dauers, but not daf-2 adults. However, the F1 ATPase inhibitor was up-regulated in both, implying enhanced homeostasis in conditions where mitochondria are stressed. Overall, the data implies increased conversion of fat to carbohydrate, and conservation of ATP stocks in daf-2 mutant adults, suggesting a state of increased energy availability. We postulate that this fuels increased somatic maintenance activity, as suggested by the disposable soma theory.

ProFunc (http://www.ebi.ac.uk/thornton-srv/databases/ProFunc) is a web server for predicting the likely function of proteins whose 3D structure is known but whose function is not. Users submit the coordinates of their structure to the server in PDB format. ProFunc makes use of both existing and novel methods to analyse the protein's sequence and structure identifying functional motifs or close relationships to functionally characterized proteins. A summary of the analyses provides an at-a-glance view of what each of the different methods has found. More detailed results are available on separate pages. Often where one method has failed to find anything useful another may be more forthcoming. The server is likely to be of most use in structural genomics where a large proportion of the proteins whose structures are solved are of hypothetical proteins of unknown function. However, it may also find use in a comparative analysis of members of large protein families. It provides a convenient compendium of sequence and structural information that often hold vital functional clues to be followed up experimentally.

We present here a comprehensive analysis of the complement of enzymes in a large variety of species. As enzymes are a relatively conserved group there are several classification systems available that are common to all species and link a protein sequence to an enzymatic function. Enzymes are therefore an ideal functional group to study the relationship between sequence expansion, functional divergence and phenotypic changes. By using information retrieved from the well annotated SWISS-PROT database together with sequence information from a variety of fully sequenced genomes and information from the EC functional scheme we have aimed here to estimate the fraction of enzymes in genomes, to determine the extent of their functional redundancy in different domains of life and to identify functional innovations and lineage specific expansions in the metazoa lineage. We found that prokaryote and eukaryote species differ both in the fraction of enzymes in their genomes and in the pattern of expansion of their enzymatic sets. We observe an increase in functional redundancy accompanying an increase in species complexity. A quantitative assessment was performed in order to determine the degree of functional redundancy in different species. Finally, we report a massive expansion in the number of mammalian enzymes involved in signalling and degradation.

The explosion in gene sequence data and technological breakthroughs in protein structure determination inspired the launch of structural genomics (SG) initiatives. An often stated goal of structural genomics is the high-throughput structural characterisation of all protein sequence families, with the long-term hope of significantly impacting on the life sciences, biotechnology and drug discovery. Here, we present a comprehensive analysis of solved SG targets to assess progress of these initiatives. Eleven consortia have contributed 316 non-redundant entries and 323 protein chains to the Protein Data Bank (PDB), and 459 and 393 domains to the CATH and SCOP structure classifications, respectively. The quality and size of these proteins are comparable to those solved in traditional structural biology and, despite huge scope for duplicated efforts, only 14% of targets have a close homologue (>/=30% sequence identity) solved by another consortium. Analysis of CATH and SCOP revealed the significant contribution that structural genomics is making to the coverage of superfamilies and folds. A total of 67% of SG domains in CATH are unique, lacking an already characterised close homologue in the PDB, whereas only 21% of non-SG domains are unique. For 29% of domains, structure determination revealed a remote evolutionary relationship not apparent from sequence, and 19% and 11% contributed new superfamilies and folds. The secondary structure class, fold and superfamily distributions of this dataset reflect those of the genomes. The domains fall into 172 different folds and 259 superfamilies in CATH but the distribution is highly skewed. The most populous of these are those that recur most frequently in the genomes. Whilst 11% of superfamilies are bacteria-specific, most are common to all three superkingdoms of life and together the 316 PDB entries have provided new and reliable homology models for 9287 non-redundant gene sequences in 206 completely sequenced genomes. From the perspective of this analysis, it appears that structural genomics is on track to be a success, and it is hoped that this work will inform future directions of the field.

We present a method called DAVROS to detect, localize, and validate repeating motifs in protein structure allowing for insertions and deletions. DAVROS uses the score matrix from a structural alignment program (SAP) to search for repeating motifs using an algorithm based on concepts from signal processing and the statistical properties of the alignments. The method was tested against a nonredundant Protein Data Bank, and each chain was assigned a score. For the top 50 chains ranked by score, 70% contain repeating motifs detected without error. These represent 14 types of fold covering α, β, and αβ protein classes. A second data set comprising protein chains in different sequence families for triosephosphate isomerase (TIM) barrel, leucine-rich repeat (LRR), trefoil, and α–α barrel folds was used to assess the ability of DAVROS to detect all motifs within a specific fold. For the second test set, the percentage of motifs detected was highest for the LRR chains (88.7%) and least for the TIM barrels (60%). This variability results from the regularity of the LRR motif compared to the αβ units of the TIM barrel, which generally have many more indels. These reduce the strength of the repeat signal in the SAP matrix, making repeat detection more difficult. Proteins 2004. © 2004 Wiley-Liss, Inc.

The role of conformational change in substrate binding, catalysis and product release is reviewed for 11 enzymes, for which crystal structures are available for the apo, substrate- and product-bound states. The extent of global conformational changes is measured, and the movements of the functional regions involved in catalysis and ligand binding are compared to the rest of the structure. We find that most of these enzymes undergo relatively small amounts of conformational change and particularly small changes in catalytic residue geometry, usually less than 1 Å. In some enzymes there is significant movement of the binding residues, usually on surface loops.

The Catalytic Site Atlas (CSA) provides catalytic residue annotation for enzymes in the Protein Data Bank. It is available online at http://www.ebi.ac.uk/thornton-srv/databases/CSA. The database consists of two types of annotated site: an original hand-annotated set containing information extracted from the primary literature, using defined criteria to assign catalytic residues, and an additional homologous set, containing annotations inferred by PSI-BLAST and sequence alignment to one of the original set. The CSA can be queried via Swiss-Prot identifier and EC number, as well as by PDB code. CSA Version 1.0 contains 177 original hand- annotated entries and 2608 homologous entries, and covers approximately 30% of all EC numbers found in PDB. The CSA will be updated on a monthly basis to include homologous sites found in new PDBs, and new hand-annotated enzymes as and when their annotation is completed.

The solution of the shortest path problem in biochemical systems constitutes an important step for studies of their evolution. In this paper, a linear programming (LP) algorithm for calculating minimal pathway distances in metabolic networks is studied. Minimal pathway distances are identified as the smallest number of metabolic steps separating two enzymes in metabolic pathways. The algorithm deals effectively with circularity and reaction directionality. The applicability of the algorithm is illustrated by calculating the minimal pathway distances for Escherichia coli small molecule metabolism enzymes, and then considering their correlations with genome distance (distance separating two genes on a chromosome) and enzyme function (as characterised by enzyme commission number). The results illustrate the effectiveness of the LP model. In addition, the data confirm that propinquity of genes on the genome implies similarity in function (as determined by co-involvement in the same region of the metabolic network), but suggest that no correlation exists between pathway distance and enzyme function. These findings offer insight into the probable mechanism of pathway evolution.

This work describes a method for predicting DNA binding function from structure using 3-dimensional templates. Proteins that bind DNA using small contiguous helix-turn-helix (HTH) motifs comprise a significant number of all DNA-binding proteins. A structural template library of seven HTH motifs has been created from non-homologous DNA-binding proteins in the Protein Data Bank. The templates were used to scan complete protein structures using an algorithm that calculated the root mean squared deviation (rmsd) for the optimal superposition of each template on each structure, based on C(alpha) backbone coordinates. Distributions of rmsd values for known HTH-containing proteins (true hits) and non-HTH proteins (false hits) were calculated. A threshold value of 1.6 A rmsd was selected that gave a true hit rate of 88.4% and a false positive rate of 0.7%. The false positive rate was further reduced to 0.5% by introducing an accessible surface area threshold value of 990 A2 per HTH motif. The template library and the validated thresholds were used to make predictions for target proteins from a structural genomics project.

The CATH database of protein domain structures (http://www.biochem.ucl.ac.uk/bsm/cath_new) currently contains 34 287 domain structures classified into 1383 superfamilies and 3285 sequence families. Each structural family is expanded with domain sequence relatives recruited from GenBank using a variety of efficient sequence search protocols and reliable thresholds. This extended resource, known as the CATH-protein family database (CATH-PFDB) contains a total of 310 000 domain sequences classified into 26 812 sequence families. New sequence search protocols have been designed, based on these intermediate sequence libraries, to allow more regular updating of the classification. Further developments include the adaptation of a recently developed method for rapid structure comparison, based on secondary structure matching, for domain boundary assignment. The philosophy behind CATHEDRAL is the recognition of recurrent folds already classified in CATH. Benchmarking of CATHEDRAL, using manually validated domain assignments, demonstrated that 43% of domains boundaries could be completely automatically assigned. This is an improvement on a previous consensus approach for which only 10-20% of domains could be reliably processed in a completely automated fashion. Since domain boundary assignment is a significant bottleneck in the classification of new structures, CATHEDRAL will also help to increase the frequency of CATH updates.

This review describes methods for the prediction of DNA binding function, and specifically summarizes a new method using 3D structural templates. The new method features the HTH motif that is found in approximately one-third of DNAbinding protein families. A library of 3D structural templates of HTH motifs was derived from proteins in the PDB. Templates were scanned against complete protein structures and the optimal superposition of a template on a structure calculated. Significance thresholds in terms of a minimum root mean squared deviation (rmsd) of an optimal superposition, and a minimum motif accessible surface area (ASA), have been calculated. In this way, it is possible to scan the template library against proteins of unknown function to make predictions about DNA-binding functionality.

Here we describe various methods currently under development aimed at identifying a protein’s function from its three-dimensional structure. We are combining a number of these methods to create a pipeline of applications, called ProFunc, which will take a given 3D structure, run all the applications on it and compile and summarise the results obtained. The aim is to provide a best guess as to the protein’s function from the evidence provided by the different methods. Here we present three examples, using structures solved by the Midwest Center for Structural Genomics consortium, illustrating the strengths and weaknesses of current approaches.

We present a novel web-based resource,Gene3D, of precalculated structural assignments to gene sequences and whole genomes. This resource assigns structural domains from the CATH database to whole genes and links these to their curated functional and structural annotations within the CATH domain structure database, the functional Dictionary of Homologous Superfamilies (DHS) and PDBsum. CurrentlyGene3D provides annotation for 36 complete genomes (two eukaryotes, six archaea, and 28 bacteria). On average, between 30% and 40% of the genes of a given genome can be structurally annotated. Matches to structural domains are found using the profile-based method (PSI-BLAST). and a novel protocol, DRange, is used to resolve conflicts in matches involving different homologous superfamilies.

The latest version of the CATH-Gene3D protein structure classification database (4.0, http://www.cathdb.info) provides annotations for over 235,000 protein domain structures and includes 25 million domain predictions. This article provides an update on the major developments in the 2 years since the last publication in this journal including: significant improvements to the predictive power of our functional families (FunFams); the release of our 'current' putative domain assignments (CATH-B); a new, strictly non-redundant data set of CATH domains suitable for homology benchmarking experiments (CATH-40) and a number of improvements to the web pages.

Motivation : A large number of experimental studies on ageing focus on the effects of genetic perturbations of the insulin/insulin-like growth factor signalling pathway (IIS) on lifespan. Short-lived invertebrate laboratory model organisms are extensively used to quickly identify ageing-related genes and pathways. It is important to extrapolate this knowledge to longer lived mammalian organisms, such as mouse and eventually human, where such analyses are difficult or impossible to perform. Computational tools are needed to integrate and manipulate pathway knowledge in different species. Results: We performed a literature review and curation of the IIS and target of rapamycin signalling pathways in Mus Musculus . We compare this pathway model to the equivalent models in Drosophila melanogaster and Caenorhabtitis elegans . Although generally well-conserved, they exhibit important differences. In general, the worm and mouse pathways include a larger number of feedback loops and interactions than the fly. We identify ‘functional orthologues’ that share similar molecular interactions, but have moderate sequence similarity. Finally, we incorporate the mouse model into the web-service NetEffects and perform in silico gene perturbations of IIS components and analyses of experimental results. We identify sub-paths that, given a mutation in an IIS component, could potentially antagonize the primary effects on ageing via FOXO in mouse and via SKN-1 in worm. Finally, we explore the effects of FOXO knockouts in three different mouse tissues. Availability and implementation: http://www.ebi.ac.uk/thornton-srv/software/NetEffects Contact: ip8@sanger.ac.uk or thornton@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Using a novel method to map and cluster chemical reactions, we have re-examined the chemistry of the ligases [Enzyme Commission (EC) Class 6] and their associated protein families in detail. The type of bond formed by the ligase can be automatically extracted from the equation of the reaction, replicating the EC subclass division. However, this subclass division hides considerable complexities, especially for the C–N forming ligases, which fall into at least three distinct types. The lower levels of the EC classification for ligases are somewhat arbitrary in their definition and add little to understanding their chemistry or evolution. By comparing the multi-domain architecture of the enzymes and using sequence similarity networks, we examined the links between overall reaction and evolution of the ligases. These show that, whilst many enzymes that perform the same overall chemistry group together, both convergent (similar function, different ancestral lineage) and divergent (different function, common ancestor) evolution of function are observed. However, a common theme is that a single conserved domain (often the nucleoside triphosphate binding domain) is combined with ancillary domains that provide the variation in substrate binding and function., Graphical abstract, Highlights • The ligases are a small set of enzymes with functions that are critical for life. Their functions include (but are not limited to) the attachment of amino acid residues onto the corresponding tRNA, DNA repair and coenzyme A decorations. • The subclass level of the EC number, namely, the type of bond formed between the two substrates, is the primary discriminator between the overall chemical transformations. Further detailed examination can produce interesting insights but does not offer more in the means of more detailed automatic classification. • Many examples exist of ligases that have evolved both divergently and convergently, with examples of ligases that have evolved to work on different substrates using the same chemistry and occasional examples where there is an apparent change of chemistry in the reaction mechanism itself. We show a single example (the acyl-coenzyme A superfamily) in which divergent evolution has occurred to perform different overall bond formations utilising the same basic mechanistic approach. • Our systematic and automatic approach to comparing and analysing enzyme reactions and the evolution of the associated enzyme sequences provides a robust route to better understand how these ligase enzymes have evolved all the complex chemistries needed for life in diverse environment.

Escherichia coli has been a popular organism for studying metabolic pathways. In an attempt to find out more about how these pathways are constructed, the enzymes were analysed by defining their protein domains. Structural assignments and sequence comparisons were used to show that 213 domain families constitute approximately 90% of the enzymes in the small-molecule metabolic pathways. Catalytic or cofactor-binding properties between family members are often conserved, while recognition of the main substrate with change in catalytic mechanism is only observed in a few cases of consecutive enzymes in a pathway. Recruitment of domains across pathways is very common, but there is little regularity in the pattern of domains in metabolic pathways. This is analogous to a mosaic in which a stone of a certain colour is selected to fill a position in the picture.