Identifying and characterising key alternative splicing events in Drosophila development

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

Tracing Evolution Through Protein Structures: Nature Captured in a Few Thousand Folds

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

Turning Back the Clock in Parkinson's Disease: Practical Recommendations for Managing Diurnal Symptom Worsening

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Functional classification of CATH superfamilies: a domain-based approach for protein function annotation

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 characterised. We present a domain-based method for protein function classification and prediction of functional sites that exploits functional subclassification of CATH superfamilies. The superfamilies are subclassified into functional families (FunFams) using a hierarchical clustering algorithm supervised by a new classification method, FunFHMMer

CATH FunFHMMer web server: protein functional annotations using functional family assignments

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

Active immunization with myelin-derived altered peptide ligand reduces mechanical pain hypersensitivity following peripheral nerve injury

BACKGROUND: T cells have been implicated in neuropathic pain that is caused by peripheral nerve injury. Immunogenic myelin basic protein (MBP) peptides have been shown to initiate mechanical allodynia in a T cell-dependent manner. Antagonistic altered peptide ligands (APLs) are peptides with substitutions in amino acid residues at T cell receptor contact sites and can inhibit T cell function and modulate inflammatory responses. In the present study, we studied the effects of immunization with MBP-derived APL on pain behavior and neuroinflammation in an animal model of peripheral nerve injury. METHODS: Lewis rats were immunized subcutaneously at the base of the tail with either a weakly encephalitogenic peptide of MBP (cyclo-MBP(87-99)) or APL (cyclo-(87-99)[A(91),A(96)]MBP(87-99)) in complete Freund’s adjuvant (CFA) or CFA only (control), following chronic constriction injury (CCI) of the left sciatic nerve. Pain hypersensitivity was tested by measurements of paw withdrawal threshold to mechanical stimuli, regulatory T cells in spleen and lymph nodes were analyzed by flow cytometry, and immune cell infiltration into the nervous system was assessed by immunohistochemistry (days 10 and 30 post-CCI). Cytokines were measured in serum and nervous tissue of nerve-injured rats (day 10 post-CCI). RESULTS: Rats immunized with the APL cyclo-(87-99)[A(91),A(96)]MBP(87-99) had significantly reduced mechanical pain hypersensitivity in the ipsilateral hindpaw compared to cyclo-MBP(87-99)-treated and control rats. This was associated with significantly decreased infiltration of T cells and ED1+ macrophages in the injured nerve of APL-treated animals. The percentage of anti-inflammatory (M2) macrophages was significantly upregulated in the APL-treated rats on day 30 post-CCI. Compared to the control rats, microglial activation in the ipsilateral lumbar spinal cord was significantly increased in the MBP-treated rats, but was not altered in the rats immunized with the MBP-derived APL. In addition, immunization with the APL significantly increased splenic regulatory T cells. Several cytokines were significantly altered after CCI, but no significant difference was observed between the APL-treated and control rats. CONCLUSIONS: These results suggest that immune deviation by active immunization with a non-encephalitogenic MBP-derived APL mediates an analgesic effect in animals with peripheral nerve injury. Thus, T cell immunomodulation warrants further investigation as a possible therapeutic strategy for the treatment of peripheral neuropathic pain

CATH: an expanded resource to predict protein function through structure and sequence

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

Finding the "Dark Matter'' in Human and Yeast Protein Network Prediction and Modelling

Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or "dark matter'' of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case, these predictions provide a valuable guide to these experimentally elusive regions

Functional innovation from changes in protein domains and their combinations

Domains are the functional building blocks of proteins. In this work we discuss how domains can contribute to the evolution of new functions. Domains themselves can evolve through various mechanisms, altering their intrinsic function. Domains can also facilitate functional innovations by combining with other domains to make novel proteins. We discuss the mechanisms by which domain and domain combinations support functional innovations. We highlight interesting examples where changes in domain combination promote changes at the domain level

Gene3D: expanding the utility of domain assignments

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 ∼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