Amino acid sequence of β-galactoside-binding bovine heart lectin Member of a novel class of vertebrate proteins

AbstractA variety of animal tissues contain β-galactoside-binding lectins with molecular masses in the range 13–17 kDa. There is evidence that these lectins may constitute a new protein family although their function in vivo is not yet clear. In this work the major part of the amino acid sequence of the 13 kDa lectin from bovine heart muscle has been determined. Comparison of this sequence with the cDNA-deduced sequence published for the chick embryo skin lectin showed 58% homology. Comparison of the bovine lectin sequence with partial sequences from two cDNA clones from a human hepatoma library and partial amino acid sequences of human lung lectin showed 70, 40 and 85% homology, respectively. The sequences of these vertebrate lectins are thus clearly related, supporting earlier results of immunological cross-reactivity within this group of proteins. Computer searching of protein sequence databases did not detect significant homologies between the bovine lectin sequence and other known proteins

Hydrolases in GtoPdb v.2023.1

Listed in this section are hydrolases not accumulated in other parts of the Concise Guide, such as monoacylglycerol lipase and acetylcholinesterase. Pancreatic lipase is the predominant mechanism of fat digestion in the alimentary system; its inhibition is associated with decreased fat absorption. CES1 is present at lower levels in the gut than CES2 (P23141), but predominates in the liver, where it is responsible for the hydrolysis of many aliphatic, aromatic and steroid esters. Hormone-sensitive lipase is also a relatively non-selective esterase associated with steroid ester hydrolysis and triglyceride metabolism, particularly in adipose tissue. Endothelial lipase is secreted from endothelial cells and regulates circulating cholesterol in high density lipoproteins

Hydrolases (version 2019.4) in the IUPHAR/BPS Guide to Pharmacology Database

Listed in this section are hydrolases not accumulated in other parts of the Concise Guide, such as monoacylglycerol lipase and acetylcholinesterase. Pancreatic lipase is the predominant mechanism of fat digestion in the alimentary system; its inhibition is associated with decreased fat absorption. CES1 is present at lower levels in the gut than CES2 (P23141), but predominates in the liver, where it is responsible for the hydrolysis of many aliphatic, aromatic and steroid esters. Hormone-sensitive lipase is also a relatively non-selective esterase associated with steroid ester hydrolysis and triglyceride metabolism, particularly in adipose tissue. Endothelial lipase is secreted from endothelial cells and regulates circulating cholesterol in high density lipoproteins

An open and transparent process to select ELIXIR Node Services as implemented by ELIXIR-UK

ELIXIR is the European infrastructure established specifically for the sharing and sustainability of life science data. To provide up-to-date resources and services, ELIXIR needs to undergo a continuous process of refreshing the services provided by its national Nodes. Here we present the approach taken by ELIXIR-UK to address the advice by the ELIXIR Scientific Advisory Board that Nodes need to develop “mechanisms to ensure that each Node continues to be representative of the Bioinformatics efforts within the country”. ELIXIR-UK put in place an open and transparent process to identify potential ELIXIR resources within the UK during late 2015 and early to mid-2016. Areas of strategic strength were identified and Expressions of Interest in these priority areas were requested from the UK community. A set of criteria were established, in discussion with the ELIXIR Hub, and prospective ELIXIR-UK resources were assessed by an independent committee set up by the Node for this purpose. Of 19 resources considered, 14 were judged to be immediately ready to be included in the UK ELIXIR Node’s portfolio. A further five were placed on the Node’s roadmap for future consideration for inclusion. ELIXIR-UK expects to repeat this process regularly to ensure its portfolio continues to reflect its community’s strengths

Endothelin.

The endothelins comprise three structurally similar 21-amino acid peptides. Endothelin-1 and -2 activate two G-protein coupled receptors, ETA and ETB, with equal affinity, whereas endothelin-3 has a lower affinity for the ETA subtype. Genes encoding the peptides are present only among vertebrates. The ligand-receptor signaling pathway is a vertebrate innovation and may reflect the evolution of endothelin-1 as the most potent vasoconstrictor in the human cardiovascular system with remarkably long lasting action. Highly selective peptide ETA and ETB antagonists and ETB agonists together with radiolabeled analogs have accurately delineated endothelin pharmacology in humans and animal models, although surprisingly no ETA agonist has been discovered. ET antagonists (bosentan, ambrisentan) have revolutionized the treatment of pulmonary arterial hypertension, with the next generation of antagonists exhibiting improved efficacy (macitentan). Clinical trials continue to explore new applications, particularly in renal failure and for reducing proteinuria in diabetic nephropathy. Translational studies suggest a potential benefit of ETB agonists in chemotherapy and neuroprotection. However, demonstrating clinical efficacy of combined inhibitors of the endothelin converting enzyme and neutral endopeptidase has proved elusive. Over 28 genetic modifications have been made to the ET system in mice through global or cell-specific knockouts, knock ins, or alterations in gene expression of endothelin ligands or their target receptors. These studies have identified key roles for the endothelin isoforms and new therapeutic targets in development, fluid-electrolyte homeostasis, and cardiovascular and neuronal function. For the future, novel pharmacological strategies are emerging via small molecule epigenetic modulators, biologicals such as ETB monoclonal antibodies and the potential of signaling pathway biased agonists and antagonists.We (APD, JJM) thank the British Heart Foundation (PS/02/001, PG/05/127/19872, FS/12/64/130001), Wellcome Trust Programme in Metabolic and Cardiovascular Disease 096822/Z/11/Z NIHR Cambridge Biomedical Research Centre and the Pulmonary Hypertension Association UK; Wellcome Biomedical Resources Grant 099156/Z/12/Z for support for IUPHAR/BPS Guide to PHARMACOLOGY (CS). We acknowledge National Heart, Lung, and Blood Institute Grants P01 HL95499 (D.E.K., K.A.H., D.M.P., J.S.P.), P01 HL69999 (D.M.P., J.S.P.), U01HL117684 (D.M.P.).This is the final version of the article. It first appeared from the American Society for Pharmacology and Experimental Therapeutics via https://doi.org/10.1124/pr.115.01183

Quantitative assessment of the expanding complementarity between public and commercial databases of bioactive compounds

<p>Abstract</p> <p>Background</p> <p>Since 2004 public cheminformatic databases and their collective functionality for exploring relationships between compounds, protein sequences, literature and assay data have advanced dramatically. In parallel, commercial sources that extract and curate such relationships from journals and patents have also been expanding. This work updates a previous comparative study of databases chosen because of their bioactive content, availability of downloads and facility to select informative subsets.</p> <p>Results</p> <p>Where they could be calculated, extracted compounds-per-journal article were in the range of 12 to 19 but compound-per-protein counts increased with document numbers. Chemical structure filtration to facilitate standardised comparisons typically reduced source counts by between 5% and 30%. The pair-wise overlaps between 23 databases and subsets were determined, as well as changes between 2006 and 2008. While all compound sets have increased, PubChem has doubled to 14.2 million. The 2008 comparison matrix shows not only overlap but also unique content across all sources. Many of the detailed differences could be attributed to individual strategies for data selection and extraction. While there was a big increase in patent-derived structures entering PubChem since 2006, GVKBIO contains over 0.8 million unique structures from this source. Venn diagrams showed extensive overlap between compounds extracted by independent expert curation from journals by GVKBIO, WOMBAT (both commercial) and BindingDB (public) but each included unique content. In contrast, the approved drug collections from GVKBIO, MDDR (commercial) and DrugBank (public) showed surprisingly low overlap. Aggregating all commercial sources established that while 1 million compounds overlapped with PubChem 1.2 million did not.</p> <p>Conclusion</p> <p>On the basis of chemical structure content <it>per se </it>public sources have covered an increasing proportion of commercial databases over the last two years. However, commercial products included in this study provide links between compounds and information from patents and journals at a larger scale than current public efforts. They also continue to capture a significant proportion of unique content. Our results thus demonstrate not only an encouraging overall expansion of data-supported bioactive chemical space but also that both commercial and public sources are complementary for its exploration.</p

The IUPHAR Guide to Immunopharmacology: connecting immunology and pharmacology

Given the critical role that the immune system plays in a multitude of diseases, having a clear understanding of the pharmacology of the immune system is crucial to new drug discovery and development. Here we describe the International Union of Basic and Clinical Pharmacology (IUPHAR) Guide to Immunopharmacology (GtoImmuPdb), which connects expert-curated pharmacology with key immunological concepts and aims to put pharmacological data into the hands of immunologists. In the pursuit of new therapeutics, pharmacological databases are a vital resource to researchers through providing accurate information on the fundamental science underlying drug action. This extension to the existing IUPHAR/British Pharmacological Society Guide to Pharmacology supports research into the development of drugs targeted at modulating immune, inflammatory or infectious components of disease. To provide a deeper context for how the resource can support research we show data in GtoImmuPdb relating to a case study on the targeting of vascular inflammation

Electrophysiological Properties of Embryonic Stem Cell-Derived Neurons

In vitro generation of functional neurons from embryonic stem (ES) cells and induced pluripotent stem cells offers exciting opportunities for dissecting gene function, disease modelling, and therapeutic drug screening. To realize the potential of stem cells in these biomedical applications, a complete understanding of the cell models of interest is required. While rapid advances have been made in developing the technologies for directed induction of defined neuronal subtypes, most published works focus on the molecular characterization of the derived neural cultures. To characterize the functional properties of these neural cultures, we utilized an ES cell model that gave rise to neurons expressing the green fluorescent protein (GFP) and conducted targeted whole-cell electrophysiological recordings from ES cell-derived neurons. Current-clamp recordings revealed that most neurons could fire single overshooting action potentials; in some cases multiple action potentials could be evoked by depolarization, or occurred spontaneously. Voltage-clamp recordings revealed that neurons exhibited neuronal-like currents, including an outward current typical of a delayed rectifier potassium conductance and a fast-activating, fast-inactivating inward current, typical of a sodium conductance. Taken together, these results indicate that ES cell-derived GFP+ neurons in culture display functional neuronal properties even at early stages of differentiation

Penalized likelihood for sparse contingency tables with an application to full-length cDNA libraries

<p>Abstract</p> <p>Background</p> <p>The joint analysis of several categorical variables is a common task in many areas of biology, and is becoming central to systems biology investigations whose goal is to identify potentially complex interaction among variables belonging to a network. Interactions of arbitrary complexity are traditionally modeled in statistics by log-linear models. It is challenging to extend these to the high dimensional and potentially sparse data arising in computational biology. An important example, which provides the motivation for this article, is the analysis of so-called full-length cDNA libraries of alternatively spliced genes, where we investigate relationships among the presence of various exons in transcript species.</p> <p>Results</p> <p>We develop methods to perform model selection and parameter estimation in log-linear models for the analysis of sparse contingency tables, to study the interaction of two or more factors. Maximum Likelihood estimation of log-linear model coefficients might not be appropriate because of the presence of zeros in the table's cells, and new methods are required. We propose a computationally efficient ℓ₁-penalization approach extending the Lasso algorithm to this context, and compare it to other procedures in a simulation study. We then illustrate these algorithms on contingency tables arising from full-length cDNA libraries.</p> <p>Conclusion</p> <p>We propose regularization methods that can be used successfully to detect complex interaction patterns among categorical variables in a broad range of biological problems involving categorical variables.</p