Mining protein loops using a structural alphabet and statistical exceptionality

<p>Abstract</p> <p>Background</p> <p>Protein loops encompass 50% of protein residues in available three-dimensional structures. These regions are often involved in protein functions, e.g. binding site, catalytic pocket... However, the description of protein loops with conventional tools is an uneasy task. Regular secondary structures, helices and strands, have been widely studied whereas loops, because they are highly variable in terms of sequence and structure, are difficult to analyze. Due to data sparsity, long loops have rarely been systematically studied.</p> <p>Results</p> <p>We developed a simple and accurate method that allows the description and analysis of the structures of short and long loops using structural motifs without restriction on loop length. This method is based on the structural alphabet HMM-SA. HMM-SA allows the simplification of a three-dimensional protein structure into a one-dimensional string of states, where each state is a four-residue prototype fragment, called structural letter. The difficult task of the structural grouping of huge data sets is thus easily accomplished by handling structural letter strings as in conventional protein sequence analysis. We systematically extracted all seven-residue fragments in a bank of 93000 protein loops and grouped them according to the structural-letter sequence, named structural word. This approach permits a systematic analysis of loops of all sizes since we consider the structural motifs of seven residues rather than complete loops. We focused the analysis on highly recurrent words of loops (observed more than 30 times). Our study reveals that 73% of loop-lengths are covered by only 3310 highly recurrent structural words out of 28274 observed words). These structural words have low structural variability (mean RMSd of 0.85 Å). As expected, half of these motifs display a flanking-region preference but interestingly, two thirds are shared by short (less than 12 residues) and long loops. Moreover, half of recurrent motifs exhibit a significant level of amino-acid conservation with at least four significant positions and 87% of long loops contain at least one such word. We complement our analysis with the detection of statistically over-represented patterns of structural letters as in conventional DNA sequence analysis. About 30% (930) of structural words are over-represented, and cover about 40% of loop lengths. Interestingly, these words exhibit lower structural variability and higher sequential specificity, suggesting structural or functional constraints.</p> <p>Conclusions</p> <p>We developed a method to systematically decompose and study protein loops using recurrent structural motifs. This method is based on the structural alphabet HMM-SA and not on structural alignment and geometrical parameters. We extracted meaningful structural motifs that are found in both short and long loops. To our knowledge, it is the first time that pattern mining helps to increase the signal-to-noise ratio in protein loops. This finding helps to better describe protein loops and might permit to decrease the complexity of long-loop analysis. Detailed results are available at <url>http://www.mti.univ-paris-diderot.fr/publication/supplementary/2009/ACCLoop/</url>.</p

Identification of a Kinase Profile that Predicts Chromosome Damage Induced by Small Molecule Kinase Inhibitors

Kinases are heavily pursued pharmaceutical targets because of their mechanistic role in many diseases. Small molecule kinase inhibitors (SMKIs) are a compound class that includes marketed drugs and compounds in various stages of drug development. While effective, many SMKIs have been associated with toxicity including chromosomal damage. Screening for kinase-mediated toxicity as early as possible is crucial, as is a better understanding of how off-target kinase inhibition may give rise to chromosomal damage. To that end, we employed a competitive binding assay and an analytical method to predict the toxicity of SMKIs. Specifically, we developed a model based on the binding affinity of SMKIs to a panel of kinases to predict whether a compound tests positive for chromosome damage. As training data, we used the binding affinity of 113 SMKIs against a representative subset of all kinases (290 kinases), yielding a 113×290 data matrix. Additionally, these 113 SMKIs were tested for genotoxicity in an in vitro micronucleus test (MNT). Among a variety of models from our analytical toolbox, we selected using cross-validation a combination of feature selection and pattern recognition techniques: Kolmogorov-Smirnov/T-test hybrid as a univariate filter, followed by Random Forests for feature selection and Support Vector Machines (SVM) for pattern recognition. Feature selection identified 21 kinases predictive of MNT. Using the corresponding binding affinities, the SVM could accurately predict MNT results with 85% accuracy (68% sensitivity, 91% specificity). This indicates that kinase inhibition profiles are predictive of SMKI genotoxicity. While in vitro testing is required for regulatory review, our analysis identified a fast and cost-efficient method for screening out compounds earlier in drug development. Equally important, by identifying a panel of kinases predictive of genotoxicity, we provide medicinal chemists a set of kinases to avoid when designing compounds, thereby providing a basis for rational drug design away from genotoxicity

The ubiquitin proteasome system in neuropathology

The ubiquitin proteasome system (UPS) orchestrates the turnover of innumerable cellular proteins. In the process of ubiquitination the small protein ubiquitin is attached to a target protein by a peptide bond. The ubiquitinated target protein is subsequently shuttled to a protease complex known as the 26S proteasome and subjected to degradative proteolysis. The UPS facilitates the turnover of proteins in several settings. It targets oxidized, mutant or misfolded proteins for general proteolytic destruction, and allows for the tightly controlled and specific destruction of proteins involved in development and differentiation, cell cycle progression, circadian rhythms, apoptosis, and other biological processes. In neuropathology, alteration of the UPS, or mutations in UPS target proteins may result in signaling abnormalities leading to the initiation or progression of tumors such as astrocytomas, hemangioblastomas, craniopharyngiomas, pituitary adenomas, and medulloblastomas. Dysregulation of the UPS may also contribute to tumor progression by perturbation of DNA replication and mitotic control mechanisms, leading to genomic instability. In neurodegenerative diseases caused by the expression of mutant proteins, the cellular accumulation of these proteins may overload the UPS, indirectly contributing to the disease process, e.g., sporadic Parkinsonism and prion diseases. In other cases, mutation of UPS components may directly cause pathological accumulation of proteins, e.g., autosomal recessive Parkinsonism and spinocerebellar ataxias. Defects or dysfunction of the UPS may also underlie cognitive disorders such as Angelman syndrome, Rett syndrome and autism, and muscle and nerve diseases, e.g., inclusion body myopathy and giant axon neuropathy. This paper describes the basic biochemical mechanisms comprising the UPS and reviews both its theoretical and proven involvement in neuropathological diseases. The potential for the UPS as a target of pharmacological therapy is also discussed

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

<div><p>Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn’s disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.</p></div

Long non-coding RNAs and cancer: a new frontier of translational research?

Author manuscriptTiling array and novel sequencing technologies have made available the transcription profile of the entire human genome. However, the extent of transcription and the function of genetic elements that occur outside of protein-coding genes, particularly those involved in disease, are still a matter of debate. In this review, we focus on long non-coding RNAs (lncRNAs) that are involved in cancer. We define lncRNAs and present a cancer-oriented list of lncRNAs, list some tools (for example, public databases) that classify lncRNAs or that scan genome spans of interest to find whether known lncRNAs reside there, and describe some of the functions of lncRNAs and the possible genetic mechanisms that underlie lncRNA expression changes in cancer, as well as current and potential future applications of lncRNA research in the treatment of cancer.RS is supported as a fellow of the TALENTS Programme (7th R&D Framework Programme, Specific Programme: PEOPLE—Marie Curie Actions—COFUND). MIA is supported as a PhD fellow of the FCT (Fundação para a Ciência e Tecnologia), Portugal. GAC is supported as a fellow by The University of Texas MD Anderson Cancer Center Research Trust, as a research scholar by The University of Texas System Regents, and by the Chronic Lymphocytic Leukemia Global Research Foundation. Work in GAC’s laboratory is supported in part by the NIH/ NCI (CA135444); a Department of Defense Breast Cancer Idea Award; Developmental Research Awards from the Breast Cancer, Ovarian Cancer, Brain Cancer, Multiple Myeloma and Leukemia Specialized Programs of Research Excellence (SPORE) grants from the National Institutes of Health; a 2009 Seena Magowitz–Pancreatic Cancer Action Network AACR Pilot Grant; the Laura and John Arnold Foundation and the RGK Foundation

Protein quality control: the who’s who, the where’s and therapeutic escapes

In cells the quality of newly synthesized proteins is monitored in regard to proper folding and correct assembly in the early secretory pathway, the cytosol and the nucleoplasm. Proteins recognized as non-native in the ER will be removed and degraded by a process termed ERAD. ERAD of aberrant proteins is accompanied by various changes of cellular organelles and results in protein folding diseases. This review focuses on how the immunocytochemical labeling and electron microscopic analyses have helped to disclose the in situ subcellular distribution pattern of some of the key machinery proteins of the cellular protein quality control, the organelle changes due to the presence of misfolded proteins, and the efficiency of synthetic chaperones to rescue disease-causing trafficking defects of aberrant proteins

Effects of alfacalcidol on circulating cytokines and growth factors in rat skeletal muscle

Abstract Supra-physiological levels of vitamin D induce skeletal muscle atrophy, which may be particularly detrimental in already sarcopaenic elderly. Neither the cause nor whether the atrophy is fibre type specific are known. To obtain supraphysiological levels of circulating vitamin D (1,25(OH)2D3) 27.5-month-old female Fischer344 9 Brown Norway F1 rats were orally treated for 6 weeks with vehicle or the vitamin D analogue alfacalcidol. Alfacalcidol treatment induced a 22% decrease in body mass and 17% muscle atrophy. Fibre atrophy was restricted to type IIb fibres in the low-oxidative part of the gastrocnemius medialis only (-22%; P\0.05). There was a concomitant 1.6-fold increase in mRNA expression of the ubiquitin ligase MuRF-1 (P\0.001), whereas those of insulin-like growth factor 1 and myostatin were not affected. Circulating IL-6 was unaltered, but leptin and adiponectin were decreased (-39%) and increased (64%), respectively. The treated rats also exhibited a reduced food intake. In conclusion, supraphysiological levels of circulating 1,25(OH)2D3 cause preferential atrophy of type IIb fibres, which is associated with an increased expression of MuRF- 1 without evidence of systemic inflammation. The atrophy and loss of body mass in the presence of supra-physiological levels of vitamin D are primarily due to a reduced food intake

Ultraconserved regions encoding ncRNAs are, altered in human leukemias and carcinomas

Noncoding RNA (ncRNA) transcripts are thought to be involved in human tumorigenesis. WE! report that a large fraction of genomic ultraconserved regions (UCRs) encode a particular set of ncRNAs whose expression is altered in human cancers. Genome-wide profiling revealed that UCRs have distinct signatures in human leukemias and carcinomas. UCRs are frequently located at fragile sites and genomic regions involved in cancers. We identified certain UCRs whose expression may be regulated by microRNAs abnormally expressed in human chronic lymphocytic leukemia, and we proved that the inhibition of an overexpressed UCR induces apoptosis in colon cancer cells. Our findings argue that ncRNAs and interaction between noncoding genes are involved in tumorigenesis to a greater extent than previously thought