Protein function prediction using domain families

Here we assessed the use of domain families for predicting the functions of whole proteins. These 'functional families' (FunFams) were derived using a protocol that combines sequence clustering with supervised cluster evaluation, relying on available high-quality Gene Ontology (GO) annotation data in the latter step. In essence, the protocol groups domain sequences belonging to the same superfamily into families based on the GO annotations of their parent proteins. An initial test based on enzyme sequences confirmed that the FunFams resemble enzyme (domain) families much better than do families produced by sequence clustering alone. For the CAFA 2011 experiment, we further associated the FunFams with GO terms probabilistically. All target proteins were first submitted to domain superfamily assignment, followed by FunFam assignment and, eventually, function assignment. The latter included an integration step for multi-domain target proteins. The CAFA results put our domain-based approach among the top ten of 31 competing groups and 56 prediction methods, confirming that it outperforms simple pairwise whole-protein sequence comparisons

Phase 1 dose escalation study of the allosteric AKT inhibitor BAY 1125976 in advanced solid cancer-Lack of association between activating AKT mutation and AKT inhibition-derived efficacy

This open-label, phase I first-in-human study (NCT01915576) of BAY 1125976, a highly specific and potent allosteric inhibitor of AKT1/2, aimed to evaluate the safety, pharmacokinetics, and maximum tolerated dose of BAY 1125976 in patients with advanced solid tumors. Oral dose escalation was investigated with a continuous once daily (QD) treatment (21 days/cycle) and a twice daily (BID) schedule. A dose expansion in 28 patients with hormone receptor-positive metastatic breast cancer, including nine patients harboring th

Promoter DNA methylation regulates progranulin expression and is altered in FTLD

BACKGROUND: Frontotemporal lobar degeneration (FTLD) is a heterogeneous group of neurodegenerative diseases associated with personality changes and progressive dementia. Loss-of-function mutations in the growth factor progranulin (GRN) cause autosomal dominant FTLD, but so far the pathomechanism of sporadic FTLD is unclear. RESULTS: We analyzed whether DNA methylation in the GRN core promoter restricts GRN expression and, thus, might promote FTLD in the absence of GRN mutations. GRN expression in human lymphoblast cell lines is negatively correlated with methylation at several CpG units within the GRN promoter. Chronic treatment with the DNA methyltransferase inhibitor 5-aza-2(′)-deoxycytidine (DAC) strongly induces GRN mRNA and protein levels. In a reporter assay, CpG methylation blocks transcriptional activity of the GRN core promoter. In brains of FTLD patients several CpG units in the GRN promoter are significantly hypermethylated compared to age-matched healthy controls, Alzheimer and Parkinson patients. These CpG motifs are critical for GRN promoter activity in reporter assays. Furthermore, DNA methyltransferase 3a (DNMT3a) is upregulated in FTLD patients and overexpression of DNMT3a reduces GRN promoter activity and expression. CONCLUSION: These data suggest that altered DNA methylation is a novel pathomechanism for FTLD that is potentially amenable to targeted pharmacotherapy

GeMMA: functional subfamily classification within superfamilies of predicted protein structural domains

GeMMA (Genome Modelling and Model Annotation) is a new approach to automatic functional subfamily classification within families and superfamilies of protein sequences. A major advantage of GeMMA is its ability to subclassify very large and diverse superfamilies with tens of thousands of members, without the need for an initial multiple sequence alignment. Its performance is shown to be comparable to the established high-performance method SCI-PHY. GeMMA follows an agglomerative clustering protocol that uses existing software for sensitive and accurate multiple sequence alignment and profile–profile comparison. The produced subfamilies are shown to be equivalent in quality whether whole protein sequences are used or just the sequences of component predicted structural domains. A faster, heuristic version of GeMMA that also uses distributed computing is shown to maintain the performance levels of the original implementation. The use of GeMMA to increase the functional annotation coverage of functionally diverse Pfam families is demonstrated. It is further shown how GeMMA clusters can help to predict the impact of experimentally determining a protein domain structure on comparative protein modelling coverage, in the context of structural genomics

New functional families (FunFams) in CATH to improve the mapping of conserved functional sites to 3D structures.

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

The genetic basis for PRC1 complex diversity emerged early in animal evolution

Polycomb group proteins are essential regulators of developmental processes across animals. Despite their importance, studies on Polycomb are often restricted to classical model systems and, as such, little is known about the evolution of these important chromatin regulators. Here we focus on Polycomb Repressive Complex 1 (PRC1) and trace the evolution of core components of canonical and non-canonical PRC1 complexes in animals. Previous work suggested that a major expansion in the number of PRC1 complexes occurred in the vertebrate lineage. We show that the expansion of the Polycomb Group RING Finger (PCGF) protein family, an essential step for the establishment of the large diversity of PRC1 complexes found in vertebrates, predates the bilaterian–cnidarian ancestor. This means that the genetic repertoire necessary to form all major vertebrate PRC1 complexes emerged early in animal evolution, over 550 million years ago. We further show that PCGF5, a gene conserved in cnidarians and vertebrates but lost in all other studied groups, is expressed in the nervous system in the sea anemone Nematostella vectensis, similar to its mammalian counterpart. Together this work provides a framework for understanding the evolution of PRC1 complex diversity and it establishes Nematostella as a promising model system in which the functional ramifications of this diversification can be further explored