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This article provides an update of the latest data and developments within the CATH protein structure classification database (http://www.cathdb.info). The resource provides two levels of release: CATH-B, a daily snapshot of the latest structural domain boundaries and superfamily assignments, and CATH+, which adds layers of derived data, such as predicted sequence domains, functional annotations and functional clustering (known as Functional Families or FunFams). The most recent CATH+ release (version 4.2) provides a huge update in the coverage of structural data. This release increases the number of fully- classified domains by over 40% (from 308 999 to 434 857 structural domains), corresponding to an almost two- fold increase in sequence data (from 53 million to over 95 million predicted domains) organised into 6119 superfamilies. The coverage of high-resolution, protein PDB chains that contain at least one assigned CATH domain is now 90.2% (increased from 82.3% in the previous release). A number of highly requested features have also been implemented in our web pages: allowing the user to view an alignment between their query sequence and a representative FunFam structure and providing tools that make it easier to view the full structural context (multi-domain architecture) of domains and chains.
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Bases de Datos de Proteínas , Genoma , Secuencia de Aminoácidos , Animales , Secuencia Conservada , Ontología de Genes , Humanos , Modelos Moleculares , Anotación de Secuencia Molecular , Familia de Multigenes/genética , Conformación Proteica , Dominios Proteicos/genética , Alineación de Secuencia , Homología de Secuencia de Aminoácido , Relación Estructura-ActividadRESUMEN
An important area of modern biology consists of understanding the relationship between genotype and phenotype. However, to understand this relationship it is essential to investigate one of the principal links between them: the proteome. With the development of recent mass-spectrometry approaches, it is now possible to quantify entire proteomes and thus relate them to different phenotypes. Here, we present a comparison of the proteome of two extreme developmental states in the well-established model organism Drosophila melanogaster: adult and embryo. Protein modules such as ribosome, proteasome, tricarboxylic acid cycle, glycolysis, or oxidative phosphorylation were found differentially expressed between the two developmental stages. Analysis of post-translation modifications of the proteins identified in this study indicates that they generally follow the same trend as their corresponding protein. Comparison between changes in the proteome and the transcriptome highlighted patterns of post-transcriptional regulation for the subunits of protein complexes such as the ribosome and the proteasome, whereas protein from modules such as TCA cycle, glycolysis, and oxidative phosphorylation seem to be coregulated at the transcriptional level. Finally, the impact of the endosymbiont Wolbachia pipientis on the proteome of both developmental states was also investigated.
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Drosophila melanogaster/genética , Biosíntesis de Proteínas/genética , Proteoma/genética , Transcriptoma/genética , Animales , Drosophila melanogaster/crecimiento & desarrollo , Drosophila melanogaster/metabolismo , Drosophila melanogaster/microbiología , Embrión no Mamífero/metabolismo , Embrión no Mamífero/microbiología , Regulación del Desarrollo de la Expresión Génica/genética , Proteolisis , Proteoma/metabolismo , Proteómica/métodos , Wolbachia/patogenicidadRESUMEN
The latest version of the CATH-Gene3D protein structure classification database has recently been released (version 4.1, http://www.cathdb.info). The resource comprises over 300 000 domain structures and over 53 million protein domains classified into 2737 homologous superfamilies, doubling the number of predicted protein domains in the previous version. The daily-updated CATH-B, which contains our very latest domain assignment data, provides putative classifications for over 100 000 additional protein domains. This article describes developments to the CATH-Gene3D resource over the last two years since the publication in 2015, including: significant increases to our structural and sequence coverage; expansion of the functional families in CATH; building a support vector machine (SVM) to automatically assign domains to superfamilies; improved search facilities to return alignments of query sequences against multiple sequence alignments; the redesign of the web pages and download site.
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Biología Computacional/métodos , Bases de Datos de Proteínas , Modelos Moleculares , Proteínas/química , Proteínas/metabolismo , Programas Informáticos , Relación Estructura-Actividad , Navegador WebRESUMEN
Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.
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Biología Computacional/métodos , Proteínas de Drosophila/genética , Drosophila melanogaster/crecimiento & desarrollo , Perfilación de la Expresión Génica/métodos , Transcriptoma/genética , Animales , Análisis por Conglomerados , Simulación por Computador , Proteínas de Drosophila/análisis , Proteínas de Drosophila/metabolismo , Drosophila melanogaster/genética , Drosophila melanogaster/metabolismo , Modelos Estadísticos , Fenotipo , Transcriptoma/fisiologíaRESUMEN
Gene3D http://gene3d.biochem.ucl.ac.uk is a database of domain annotations of Ensembl and UniProtKB protein sequences. Domains are predicted using a library of profile HMMs representing 2737 CATH superfamilies. Gene3D has previously featured in the Database issue of NAR and here we report updates to the website and database. The current Gene3D (v14) release has expanded its domain assignments to â¼ 20,000 cellular genomes and over 43 million unique protein sequences, more than doubling the number of protein sequences since our last publication. Amongst other updates, we have improved our Functional Family annotation method. We have also improved the quality and coverage of our 3D homology modelling pipeline of predicted CATH domains. Additionally, the structural models have been expanded to include an extra model organism (Drosophila melanogaster). We also document a number of additional visualization tools in the Gene3D website.
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Bases de Datos de Proteínas , Estructura Terciaria de Proteína , Humanos , Internet , Modelos Moleculares , Anotación de Secuencia Molecular , Dominios y Motivos de Interacción de Proteínas , Estructura Terciaria de Proteína/genéticaRESUMEN
The widening function annotation gap in protein databases and the increasing number and diversity of the proteins being sequenced presents new challenges to protein function prediction methods. Multidomain proteins complicate the protein sequence-structure-function relationship further as new combinations of domains can expand the functional repertoire, creating new proteins and functions. Here, we present the FunFHMMer web server, which provides Gene Ontology (GO) annotations for query protein sequences based on the functional classification of the domain-based CATH-Gene3D resource. Our server also provides valuable information for the prediction of functional sites. The predictive power of FunFHMMer has been validated on a set of 95 proteins where FunFHMMer performs better than BLAST, Pfam and CDD. Recent validation by an independent international competition ranks FunFHMMer as one of the top function prediction methods in predicting GO annotations for both the Biological Process and Molecular Function Ontology. The FunFHMMer web server is available at http://www.cathdb.info/search/by_funfhmmer.
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Anotación de Secuencia Molecular , Estructura Terciaria de Proteína , Programas Informáticos , Ontología de Genes , Internet , Proteínas/clasificación , Proteínas/genética , Proteínas/fisiologíaRESUMEN
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.
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Bases de Datos de Proteínas , Anotación de Secuencia Molecular , Estructura Terciaria de Proteína , Genómica , Internet , Estructura Terciaria de Proteína/genética , Proteínas/clasificaciónRESUMEN
MOTIVATION: Computational approaches that can predict protein functions are essential to bridge the widening function annotation gap especially since <1.0% of all proteins in UniProtKB have been experimentally characterized. We present a domain-based method for protein function classification and prediction of functional sites that exploits functional sub-classification of CATH superfamilies. The superfamilies are sub-classified into functional families (FunFams) using a hierarchical clustering algorithm supervised by a new classification method, FunFHMMer. RESULTS: FunFHMMer generates more functionally coherent groupings of protein sequences than other domain-based protein classifications. This has been validated using known functional information. The conserved positions predicted by the FunFams are also found to be enriched in known functional residues. Moreover, the functional annotations provided by the FunFams are found to be more precise than other domain-based resources. FunFHMMer currently identifies 110,439 FunFams in 2735 superfamilies which can be used to functionally annotate>16 million domain sequences. AVAILABILITY AND IMPLEMENTATION: All FunFam annotation data are made available through the CATH webpages (http://www.cathdb.info). The FunFHMMer webserver (http://www.cathdb.info/search/by_funfhmmer) allows users to submit query sequences for assignment to a CATH FunFam. CONTACT: sayoni.das.12@ucl.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Algoritmos , Bases de Datos de Proteínas , Anotación de Secuencia Molecular , Estructura Terciaria de Proteína , Proteínas/química , Proteínas/clasificación , Secuencia de Aminoácidos , Humanos , Datos de Secuencia Molecular , Proteínas/genética , Proteínas/metabolismo , Análisis de Secuencia de Proteína , Homología de Secuencia de Aminoácido , Homología Estructural de ProteínaRESUMEN
MOTIVATION: Most biological processes remain only partially characterized with many components still to be identified. Given that a whole genome can usually not be tested in a functional assay, identifying the genes most likely to be of interest is of critical importance to avoid wasting resources. RESULTS: Given a set of known functionally related genes and using a state-of-the-art approach to data integration and mining, our Functional Lists (FUN-L) method provides a ranked list of candidate genes for testing. Validation of predictions from FUN-L with independent RNAi screens confirms that FUN-L-produced lists are enriched in genes with the expected phenotypes. In this article, we describe a website front end to FUN-L. AVAILABILITY AND IMPLEMENTATION: The website is freely available to use at http://funl.org
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Algoritmos , Biología Computacional/métodos , Minería de Datos/métodos , Redes Reguladoras de Genes , Interferencia de ARN , Programas Informáticos , Humanos , FenotipoRESUMEN
Gene3D (http://gene3d.biochem.ucl.ac.uk) is a database of protein domain structure annotations for protein sequences. Domains are predicted using a library of profile HMMs from 2738 CATH superfamilies. Gene3D assigns domain annotations to Ensembl and UniProt sequence sets including >6000 cellular genomes and >20 million unique protein sequences. This represents an increase of 45% in the number of protein sequences since our last publication. Thanks to improvements in the underlying data and pipeline, we see large increases in the domain coverage of sequences. We have expanded this coverage by integrating Pfam and SUPERFAMILY domain annotations, and we now resolve domain overlaps to provide highly comprehensive composite multi-domain architectures. To make these data more accessible for comparative genome analyses, we have developed novel search algorithms for searching genomes to identify related multi-domain architectures. In addition to providing domain family annotations, we have now developed a pipeline for 3D homology modelling of domains in Gene3D. This has been applied to the human genome and will be rolled out to other major organisms over the next year.
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Bases de Datos de Proteínas , Anotación de Secuencia Molecular , Estructura Terciaria de Proteína , Genoma , Genómica , Internet , Modelos Moleculares , Estructura Terciaria de Proteína/genética , Análisis de Secuencia de ProteínaRESUMEN
BACKGROUND: In complex Metazoans a given gene frequently codes for multiple protein isoforms, through processes such as alternative splicing. Large scale functional annotation of these isoforms is a key challenge for functional genomics. This annotation gap is increasing with the large numbers of multi transcript genes being identified by technologies such as RNASeq. Furthermore attempts to characterise the functions of splicing in an organism are complicated by the difficulty in distinguishing functional isoforms from those produced by splicing errors or transcription noise. Tools to help prioritise candidate isoforms for testing are largely absent. RESULTS: In this study we implement a Time-course Switch (TS) score for ranking isoforms by their likelihood of producing additional functions based on their developmental expression profiles, as reported by modENCODE. The TS score allows us to better investigate functional roles of different isoforms expressed in multi transcript genes. From this analysis, we find that isoforms with high TS scores have sequence feature changes consistent with more deterministic splicing and functional changes and tend to gain domains or whole exons which could carry additional functions. Furthermore these functions appear to be particularly important for essential regulatory roles, establishing functional isoform switching as key for regulatory processes. Based on the TS score we develop a Transcript Annotations Pipeline for Alternative Splicing (TAPAS) that identifies functional neighbourhoods of potentially interesting isoforms. CONCLUSIONS: We have identified a subset of protein isoforms which appear to have high functional significance, particularly in regulation. This has been made possible through the development of novel methods that make use of transcript expression profiles. The methods and analyses we present here represent important first steps in the development of tools to address the near complete lack of isoform specific function annotation. In turn the tools allow us to better characterise the regulatory functions of alternative splicing in more detail.
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Empalme Alternativo , Drosophila melanogaster/crecimiento & desarrollo , Isoformas de Proteínas/metabolismo , Algoritmos , Animales , Biología Computacional/métodos , Bases de Datos Genéticas , Drosophila melanogaster/genética , Regulación del Desarrollo de la Expresión Génica , ARN Mensajero/metabolismoRESUMEN
CATH version 3.5 (Class, Architecture, Topology, Homology, available at http://www.cathdb.info/) contains 173 536 domains, 2626 homologous superfamilies and 1313 fold groups. When focusing on structural genomics (SG) structures, we observe that the number of new folds for CATH v3.5 is slightly less than for previous releases, and this observation suggests that we may now know the majority of folds that are easily accessible to structure determination. We have improved the accuracy of our functional family (FunFams) sub-classification method and the CATH sequence domain search facility has been extended to provide FunFam annotations for each domain. The CATH website has been redesigned. We have improved the display of functional data and of conserved sequence features associated with FunFams within each CATH superfamily.
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Bases de Datos de Proteínas , Estructura Terciaria de Proteína , Genómica , Internet , Anotación de Secuencia Molecular , Pliegue de Proteína , Proteínas/química , Proteínas/clasificación , Proteínas/genética , Alineación de Secuencia , Análisis de Secuencia de Proteína , Homología Estructural de ProteínaRESUMEN
This article is dedicated to the memory of Cyrus Chothia, who was a leading light in the world of protein structure evolution. His elegant analyses of protein families and their mechanisms of structural and functional evolution provided important evolutionary and biological insights and firmly established the value of structural perspectives. He was a mentor and supervisor to many other leading scientists who continued his quest to characterise structure and function space. He was also a generous and supportive colleague to those applying different approaches. In this article we review some of his accomplishments and the history of protein structure classifications, particularly SCOP and CATH. We also highlight some of the evolutionary insights these two classifications have brought. Finally, we discuss how the expansion and integration of protein sequence data into these structural families helps reveal the dark matter of function space and can inform the emergence of novel functions in Metazoa. Since we cover 25 years of structural classification, it has not been feasible to review all structure based evolutionary studies and hence we focus mainly on those undertaken by the SCOP and CATH groups and their collaborators.
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Alzheimer's disease (AD), the most prevalent form of dementia, is a progressive and devastating neurodegenerative condition for which there are no effective treatments. Understanding the molecular pathology of AD during disease progression may identify new ways to reduce neuronal damage. Here, we present a longitudinal study tracking dynamic proteomic alterations in the brains of an inducible Drosophila melanogaster model of AD expressing the Arctic mutant Aß42 gene. We identified 3093 proteins from flies that were induced to express Aß42 and age-matched healthy controls using label-free quantitative ion-mobility data independent analysis mass spectrometry. Of these, 228 proteins were significantly altered by Aß42 accumulation and were enriched for AD-associated processes. Network analyses further revealed that these proteins have distinct hub and bottleneck properties in the brain protein interaction network, suggesting that several may have significant effects on brain function. Our unbiased analysis provides useful insights into the key processes governing the progression of amyloid toxicity and forms a basis for further functional analyses in model organisms and translation to mammalian systems.
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Péptidos beta-Amiloides/metabolismo , Encéfalo/metabolismo , Fragmentos de Péptidos/metabolismo , Mapas de Interacción de Proteínas/fisiología , Enfermedad de Alzheimer/metabolismo , Enfermedad de Alzheimer/fisiopatología , Péptidos beta-Amiloides/fisiología , Animales , Modelos Animales de Enfermedad , Progresión de la Enfermedad , Proteínas de Drosophila/metabolismo , Drosophila melanogaster/metabolismo , Estudios Longitudinales , Neuronas/metabolismo , Fragmentos de Péptidos/fisiología , Proteómica/métodosRESUMEN
The study of superfamilies of protein domains using a combination of structure, sequence and function data provides insights into deep evolutionary history. In the present paper, analyses of functional diversity within such superfamilies as defined in the CATH-Gene3D resource are described. These analyses focus on structure-function relationships in very large and diverse superfamilies, and on the evolution of domain superfamily members in protein-protein complexes.
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Evolución Molecular , Proteínas/química , Proteínas/metabolismo , Animales , Bases de Datos de Proteínas , Humanos , Estructura Secundaria de Proteína , Estructura Terciaria de Proteína , Proteínas/clasificación , Relación Estructura-ActividadRESUMEN
BACKGROUND: A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available. RESULTS: In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements. CONCLUSION: Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.
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Algoritmos , Dicroismo Circular/métodos , Modelos Químicos , Mapeo Peptídico/métodos , Proteínas/química , Análisis de Secuencia de Proteína/métodos , Espectrofotometría Infrarroja/métodos , Secuencia de Aminoácidos , Simulación por Computador , Modelos Moleculares , Datos de Secuencia Molecular , Estructura Secundaria de Proteína , Proteínas/ultraestructura , Integración de SistemasRESUMEN
MOTIVATION: Circular Dichroism (CD) spectroscopy is a long-established technique for studying protein secondary structures in solution. Empirical analyses of CD data rely on the availability of reference datasets comprised of far-UV CD spectra of proteins whose crystal structures have been determined. This article reports on the creation of a new reference dataset which effectively covers both secondary structure and fold space, and uses the higher information content available in synchrotron radiation circular dichroism (SRCD) spectra to more accurately predict secondary structure than has been possible with existing reference datasets. It also examines the effects of wavelength range, structural redundancy and different means of categorizing secondary structures on the accuracy of the analyses. In addition, it describes a novel use of hierarchical cluster analyses to identify protein relatedness based on spectral properties alone. The databases are shown to be applicable in both conventional CD and SRCD spectroscopic analyses of proteins. Hence, by combining new bioinformatics and biophysical methods, a database has been produced that should have wide applicability as a tool for structural molecular biology.
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Dicroismo Circular/métodos , Bases de Datos de Proteínas , Algoritmos , Biofisica/métodos , Calibración , Análisis por Conglomerados , Biología Computacional/métodos , Bases de Datos Genéticas , Pliegue de Proteína , Estructura Secundaria de Proteína , Rayos UltravioletaRESUMEN
This chapter describes the generation of the data in the CATH-Gene3D online resource and how it can be used to study protein domains and their evolutionary relationships. Methods will be presented for: comparing protein structures, recognizing homologs, predicting domain structures within protein sequences, and subclassifying superfamilies into functionally pure families, together with a guide on using the webpages.
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Biología Computacional/métodos , Bases de Datos Genéticas , Proteínas/genética , Proteínas/metabolismo , Programas Informáticos , Algoritmos , Modelos Moleculares , Anotación de Secuencia Molecular , Unión Proteica , Conformación Proteica , Dominios y Motivos de Interacción de Proteínas , Proteínas/química , Proteínas/clasificación , Relación Estructura-Actividad , Navegador Web , Flujo de TrabajoRESUMEN
BACKGROUND: Circular Dichroism (CD) spectroscopy is a widely used method for studying protein structures in solution. Modern synchrotron radiation CD (SRCD) instruments have considerably higher photon fluxes than do conventional lab-based CD instruments, and hence have the ability to routinely measure CD data to much lower wavelengths. Recently a new reference dataset of SRCD spectra of proteins of known structure, designed to cover secondary structure and fold space, has been produced which includes low wavelength (vacuum ultraviolet - VUV) data. However, the existing algorithms used to calculate protein secondary structures from CD data have not been designed to take optimal advantage of the additional information in these low wavelength data. RESULTS: In this study, we have optimised secondary structure calculation methods based on the low wavelength CD data by examining existing algorithms and secondary structure assignment schemes, and then developing new methods which have produced clear improvements in prediction accuracy, especially for beta-sheet components. We have further shown that if precise measurements of protein concentrations, and therefore spectral magnitudes, are not available, the inclusion of the low wavelength data will significantly improve the analyses. However, we have also demonstrated that the new reference dataset, methods, and assignments can also improve the analyses of conventional circular dichroism data, even if the low wavelength data is not available. CONCLUSION: VUV CD data include important information on protein structure which can be exploited with the algorithms and methodologies described.