The antioxidant activity of some curcuminoids and chalcones

The antioxidant properties of the synthetic compound (C1)–(C8), which comprised 7 curcuminoids and a chalcone, were evaluated by two complementary assays, DPPH and β-carotene/linoleic acid. It was found that, in general, the free radical scavenging ability of (C1)–(C8) was concentration-dependent. Compounds (C1) and (C4), which contained (4-OH) phenolic groups, were found to be highly potent antioxidants with higher antioxidant values than BHT suggesting that synthetic curcuminoids are more potent antioxidants than standard antioxidants like BHT. Using β-carotene-linoleic acid assay, only the water-soluble 2, 4,6-trihydroxyphenolic chalcone (C5) showed 85.2 % inhibition of the formation of conjugated dienes reflecting on its potent antioxidant activity

PCDB: a database of protein conformational diversity

PCDB (http://www.pcdb.unq.edu.ar) is a database of protein conformational diversity. For each protein, the database contains the redundant compilation of all the corresponding crystallographic structures obtained under different conditions. These structures could be considered as different instances of protein dynamism. As a measure of the conformational diversity we use the maximum RMSD obtained comparing the structures deposited for each domain. The redundant structures were extracted following CATH structural classification and cross linked with additional information. In this way it is possible to relate a given amount of conformational diversity with different levels of information, such as protein function, presence of ligands and mutations, structural classification, active site information and organism taxonomy among others. Currently the database contains 7989 domains with a total of 36581 structures from 4171 different proteins. The maximum RMSD registered is 26.7 Å and the average of different structures per domain is 4.5

Combined inhibition of MEK and Plk1 has synergistic anti-tumor activity in NRAS mutant melanoma

About one third of cancers harbor activating mutations in rat sarcoma viral oncogene homolog (RAS) oncogenes. In melanoma, aberrant neuroblastoma-RAS (NRAS) signaling fuels tumor progression in about 20% of patients. Current therapeutics for NRAS driven malignancies barely impact overall survival. To date, pathway interference downstream of mutant NRAS seems to be the most promising approach. In this study, data revealed that mutant NRAS induced Plk1 expression, and pharmacologic inhibition of Plk1 stabilized the size of NRAS mutant melanoma xenografts. The combination of MEK and Plk1 inhibitors resulted in a significant growth reduction of NRAS mutant melanoma cells in vitro, and regression of xenografted NRAS mutant melanoma in vivo. Independent cell cycle arrest and increased induction of apoptosis underlies the synergistic effect of this combination. Data further suggest that the p53 signaling pathway is of key importance to the observed therapeutic efficacy. This study provides in vitro, in vivo and first mechanistic data, that a MEK/Plk1 inhibitor combination might be a promising treatment approach for patients with NRAS driven melanoma. Since mutant NRAS signaling is similar across different malignancies, this inhibitor combination could also offer a previously unreported treatment modality for NRAS mutant tumors of other cell origins

Subtype-Selective Small Molecule Inhibitors Reveal a Fundamental Role for Nav1.7 in Nociceptor Electrogenesis, Axonal Conduction and Presynaptic Release.

Human genetic studies show that the voltage gated sodium channel 1.7 (Nav1.7) is a key molecular determinant of pain sensation. However, defining the Nav1.7 contribution to nociceptive signalling has been hampered by a lack of selective inhibitors. Here we report two potent and selective arylsulfonamide Nav1.7 inhibitors; PF-05198007 and PF-05089771, which we have used to directly interrogate Nav1.7's role in nociceptor physiology. We report that Nav1.7 is the predominant functional TTX-sensitive Nav in mouse and human nociceptors and contributes to the initiation and the upstroke phase of the nociceptor action potential. Moreover, we confirm a role for Nav1.7 in influencing synaptic transmission in the dorsal horn of the spinal cord as well as peripheral neuropeptide release in the skin. These findings demonstrate multiple contributions of Nav1.7 to nociceptor signalling and shed new light on the relative functional contribution of this channel to peripheral and central noxious signal transmission.The funder provided support in the form of salaries for authors [AA, AB, MC, JT, MM, AW, EP, AG, PJC, RD, DP, ZL, BM, CW, NS, RS, PS, NC, DK, RB, ES], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section

Recruitment of rare 3-grams at functional sites: Is this a mechanism for increasing enzyme specificity?

<p>Abstract</p> <p>Background</p> <p>A wealth of unannotated and functionally unknown protein sequences has accumulated in recent years with rapid progresses in sequence genomics, giving rise to ever increasing demands for developing methods to efficiently assess functional sites. Sequence and structure conservations have traditionally been the major criteria adopted in various algorithms to identify functional sites. Here, we focus on the distributions of the 20³different types of <it>3</it>-grams (or triplets of sequentially contiguous amino acid) in the entire space of sequences accumulated to date in the UniProt database, and focus in particular on the rare <it>3</it>-grams distinguished by their high entropy-based information content.</p> <p>Results</p> <p>Comparison of the UniProt distributions with those observed near/at the active sites on a non-redundant dataset of 59 enzyme/ligand complexes shows that the active sites preferentially recruit <it>3</it>-grams distinguished by their low frequency in the UniProt. Three cases, Src kinase, hemoglobin, and tyrosyl-tRNA synthetase, are discussed in details to illustrate the biological significance of the results.</p> <p>Conclusion</p> <p>The results suggest that recruitment of rare <it>3</it>-grams may be an efficient mechanism for increasing specificity at functional sites. Rareness/scarcity emerges as a feature that may assist in identifying key sites for proteins function, providing information complementary to that derived from sequence alignments. In addition it provides us (for the first time) with a means of identifying potentially functional sites from sequence information alone, when sequence conservation properties are not available.</p

How accurate and statistically robust are catalytic site predictions based on closeness centrality?

<p>Abstract</p> <p>Background</p> <p>We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid α-carbons specify vertices within a graph and edges connect vertices that are proximal in structure. Closeness centrality, which has shown promise in previous investigations, is used to identify important positions within the network. Closeness centrality, a global measure of network centrality, is calculated as the reciprocal of the average distance between vertex <it>i </it>and all other vertices.</p> <p>Results</p> <p>We benchmark the approach against 283 structurally unique proteins within the Catalytic Site Atlas. Our results, which are inline with previous investigations of smaller datasets, indicate closeness centrality predictions are statistically significant. However, unlike previous approaches, we specifically focus on residues with the very best scores. Over the top five closeness centrality scores, we observe an average true to false positive rate ratio of 6.8 to 1. As demonstrated previously, adding a solvent accessibility filter significantly improves predictive power; the average ratio is increased to 15.3 to 1. We also demonstrate (for the first time) that filtering the predictions by residue identity improves the results even more than accessibility filtering. Here, we simply eliminate residues with physiochemical properties unlikely to be compatible with catalytic requirements from consideration. Residue identity filtering improves the average true to false positive rate ratio to 26.3 to 1. Combining the two filters together has little affect on the results. Calculated p-values for the three prediction schemes range from 2.7E-9 to less than 8.8E-134. Finally, the sensitivity of the predictions to structure choice and slight perturbations is examined.</p> <p>Conclusion</p> <p>Our results resolutely confirm that closeness centrality is a viable prediction scheme whose predictions are statistically significant. Simple filtering schemes substantially improve the method's predicted power. Moreover, no clear effect on performance is observed when comparing ligated and unligated structures. Similarly, the CC prediction results are robust to slight structural perturbations from molecular dynamics simulation.</p

Iron homeostasis and oxidative stress in idiopathic pulmonary alveolar proteinosis: a case-control study

<p>Abstract</p> <p>Background</p> <p>Lung injury caused by both inhaled dusts and infectious agents depends on increased availability of iron and metal-catalyzed oxidative stress. Because inhaled particles, such as silica, and certain infections can cause secondary pulmonary alveolar proteinosis (PAP), we tested the hypothesis that idiopathic PAP is associated with an altered iron homeostasis in the human lung.</p> <p>Methods</p> <p>Healthy volunteers (n = 20) and patients with idiopathic PAP (n = 20) underwent bronchoalveolar lavage and measurements were made of total protein, iron, tranferrin, transferrin receptor, lactoferrin, and ferritin. Histochemical staining for iron and ferritin was done in the cell pellets from control subjects and PAP patients, and in lung specimens of patients without cardiopulmonary disease and with PAP. Lavage concentrations of urate, glutathione, and ascorbate were also measured as indices of oxidative stress.</p> <p>Results</p> <p>Lavage concentrations of iron, transferrin, transferrin receptor, lactoferrin, and ferritin were significantly elevated in PAP patients relative to healthy volunteers. The cells of PAP patients had accumulated significant iron and ferritin, as well as considerable amounts of extracellular ferritin. Immunohistochemistry for ferritin in lung tissue revealed comparable amounts of this metal-storage protein in the lower respiratory tract of PAP patients both intracellularly and extracellularly. Lavage concentrations of ascorbate, glutathione, and urate were significantly lower in the lavage fluid of the PAP patients.</p> <p>Conclusion</p> <p>Iron homeostasis is altered in the lungs of patients with idiopathic PAP, as large amounts of catalytically-active iron and low molecular weight anti-oxidant depletion are present. These findings suggest a metal-catalyzed oxidative stress in the maintenance of this disease.</p

Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties

BACKGROUND: The number of protein sequences deriving from genome sequencing projects is outpacing our knowledge about the function of these proteins. With the gap between experimentally characterized and uncharacterized proteins continuing to widen, it is necessary to develop new computational methods and tools for functional prediction. Knowledge of catalytic sites provides a valuable insight into protein function. Although many computational methods have been developed to predict catalytic residues and active sites, their accuracy remains low, with a significant number of false positives. In this paper, we present a novel method for the prediction of catalytic sites, using a carefully selected, supervised machine learning algorithm coupled with an optimal discriminative set of protein sequence conservation and structural properties. RESULTS: To determine the best machine learning algorithm, 26 classifiers in the WEKA software package were compared using a benchmarking dataset of 79 enzymes with 254 catalytic residues in a 10-fold cross-validation analysis. Each residue of the dataset was represented by a set of 24 residue properties previously shown to be of functional relevance, as well as a label {+1/-1} to indicate catalytic/non-catalytic residue. The best-performing algorithm was the Sequential Minimal Optimization (SMO) algorithm, which is a Support Vector Machine (SVM). The Wrapper Subset Selection algorithm further selected seven of the 24 attributes as an optimal subset of residue properties, with sequence conservation, catalytic propensities of amino acids, and relative position on protein surface being the most important features. CONCLUSION: The SMO algorithm with 7 selected attributes correctly predicted 228 of the 254 catalytic residues, with an overall predictive accuracy of more than 86%. Missing only 10.2% of the catalytic residues, the method captures the fundamental features of catalytic residues and can be used as a "catalytic residue filter" to facilitate experimental identification of catalytic residues for proteins with known structure but unknown function

Understanding network concepts in modules

<p>Abstract</p> <p>Background</p> <p>Network concepts are increasingly used in biology and genetics. For example, the clustering coefficient has been used to understand network architecture; the connectivity (also known as degree) has been used to screen for cancer targets; and the topological overlap matrix has been used to define modules and to annotate genes. Dozens of potentially useful network concepts are known from graph theory.</p> <p>Results</p> <p>Here we study network concepts in special types of networks, which we refer to as approximately factorizable networks. In these networks, the pairwise connection strength (adjacency) between 2 network nodes can be factored into node specific contributions, named node 'conformity'. The node conformity turns out to be highly related to the connectivity. To provide a formalism for relating network concepts to each other, we define three types of network concepts: fundamental-, conformity-based-, and approximate conformity-based concepts. Fundamental concepts include the standard definitions of connectivity, density, centralization, heterogeneity, clustering coefficient, and topological overlap. The approximate conformity-based analogs of fundamental network concepts have several theoretical advantages. First, they allow one to derive simple relationships between seemingly disparate networks concepts. For example, we derive simple relationships between the clustering coefficient, the heterogeneity, the density, the centralization, and the topological overlap. The second advantage of approximate conformity-based network concepts is that they allow one to show that fundamental network concepts can be approximated by simple functions of the connectivity in module networks.</p> <p>Conclusion</p> <p>Using protein-protein interaction, gene co-expression, and simulated data, we show that a) many networks comprised of module nodes are approximately factorizable and b) in these types of networks, simple relationships exist between seemingly disparate network concepts. Our results are implemented in freely available R software code, which can be downloaded from the following webpage: <url>http://www.genetics.ucla.edu/labs/horvath/ModuleConformity/ModuleNetworks</url></p

Fetus-derived DLK1 is required for maternal metabolic adaptations to pregnancy and is associated with fetal growth restriction.

Pregnancy is a state of high metabolic demand. Fasting diverts metabolism to fatty acid oxidation, and the fasted response occurs much more rapidly in pregnant women than in non-pregnant women. The product of the imprinted DLK1 gene (delta-like homolog 1) is an endocrine signaling molecule that reaches a high concentration in the maternal circulation during late pregnancy. By using mouse models with deleted Dlk1, we show that the fetus is the source of maternal circulating DLK1. In the absence of fetally derived DLK1, the maternal fasting response is impaired. Furthermore, we found that maternal circulating DLK1 levels predict embryonic mass in mice and can differentiate healthy small-for-gestational-age (SGA) infants from pathologically small infants in a human cohort. Therefore, measurement of DLK1 concentration in maternal blood may be a valuable method for diagnosing human disorders associated with impaired DLK1 expression and to predict poor intrauterine growth and complications of pregnancy.M.A.M.C. was supported by a PhD studentship from the Cambridge Centre for Trophoblast Research. Research was supported by grants from the MRC (MR/J001597/1 and MR/L002345/1), the Medical College of Saint Bartholomew's Hospital Trust, a Wellcome Trust Investigator Award, EpigeneSys (FP7 Health-257082), EpiHealth (FP7 Health-278414), a Herchel Smith Fellowship (N.T.) and NIH grant RO1 DK89989. The contents are the authors' sole responsibility and do not necessarily represent official NIH views. We thank G. Burton for invaluable support, and M. Constância and I. Sandovici (University of Cambridge) for the Meox2-cre mice. We are extremely grateful to all of the participants in the Pregnancy Outcome Prediction study. This work was supported by the NIHR Cambridge Comprehensive Biomedical Research Centre (Women's Health theme) and project grants from the MRC (G1100221) and Sands (Stillbirth and Neonatal Death Charity). The study was also supported by GE Healthcare (donation of two Voluson i ultrasound systems for this study) and by the NIHR Cambridge Clinical Research Facility, where all research visits took place.This is the author accepted manuscript. The final version is available from Nature Publishing Group via https://doi.org/10.1038/ng.369