Food Polyphenols Fail to Cause a Biologically Relevant Reduction of COX-2 Activity.
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ABSTRACT:
SUBMITTER: Willenberg I
PROVIDER: S-EPMC4594923 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Oxidative DNA-protein cross-links have received less attention than other types of DNA damage and remain as one of the least understood types of oxidative lesion. A model system using ribonuclease A and a 27-nucleotide DNA was used to determine the propensity of oxidative cross-linking to occur in the presence of oxidants. Cross-link formation was examined using four different oxidation systems that generate singlet oxygen, superoxide, and metal-based Fenton reactions. It is shown that oxidative cross-linking occurs in yields ranging from 14% to a maximal yield of 61% in all oxidative systems when equivalent concentrations of DNA and protein are present. Because singlet oxygen is the most efficient oxidation system in generating DNA-protein cross-links, it was chosen for further analyses. Cross-linking occurred with single-stranded DNA binding protein and not with bovine serum albumin. Addition of salt lowered nonspecific binding affinity and lowered cross-link yield by up to 59%. The yield of cross-linking increased with increased ratios of protein compared with DNA. Cross-linking was highly dependent on the number of guanines in a DNA sequence. Loss of guanine content on the 27-nucleotide DNA led to nearly complete loss in cross-linking, while primer extension studies showed cross-links to predominantly occur at guanine base on a 100-nucleotide DNA. The chemical species generated were examined using two peptides derived from the ribonuclease A sequence, N-acetyl-AAAKF and N-acetyl-AYKTT, which were cross-linked to 2'-deoxyguanosine. The cross-link products were spiroiminodihydantoin, guanidinohydantoin, and tyrosyl-based adducts. Formation of tyrosine-based adducts may be competitive with the more well-studied lysine-based cross-links. We conclude that oxidative cross-links may be present at high levels in cells since the propensity to oxidatively cross-link is high and so much of the genomic DNA is coated with protein.
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Project description:Metalloenzymes that normally perform catalytic antioxidant or radical-degrading functions, as well as small-molecule complexes that mimic them, can also exert pro-oxidant or radical-forming effects depending on the identity of the terminal reductant. Because nitroxyl radicals function as redox active cocatalysts in the aerobic oxidation of alcohols, we hypothesized that catalytic radical reduction could be achieved via the oxidation of biologically-relevant alcohols. Herein we report an organoruthenium complex (Ru1) that catalyzed reduction of 2,2'-azino-bis(3-ethylbenzo-thiazoline-6-sulfonate) radical monoanion (ABTS˙-) to ABTS2- in phosphate buffered saline (pH 7.4) using MeOH, EtOH, i-PrOH, serine, threonine, glucose, arabinose, methyl lactate or dimethyl malate as the terminal reductant. Replacing either the C-H or O-H groups of a -CHOH- moiety resulted in the loss of ABTS˙- reducing ability. Moreover, in conjunction with an alcohol terminal reductant, Ru1 was able to inhibit the oxidation of ABTS2- by H2O2 and horseradish peroxidase, even after multiple successive challenges with excess H2O2 or ABTS˙-. Collectively, these results demonstrate that Ru1 inhibits the oxidative formation of and catalyzes the reduction of radicals in aqueous solution via oxidation of biologically-relevant alcohols.
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Project description:Frailty is a late-life syndrome of vulnerability to adverse health outcomes characterized by a phenotype that includes muscle weakness, fatigue, and inflammatory pathway activation. The identification of biologically relevant pathways that influence frailty is challenged by its biological complexity and the necessity in separating disease states from the syndrome of frailty. As with longevity research, genetic analyses may help to provide insights into biologically relevant pathways that contribute to frailty.Based on current understanding of the physiological basis of frailty, we hypothesize that variation in genes related to inflammation and muscle maintenance would associate with frailty. One thousand three hundred and fifty-four single-nucleotide polymorphisms were genotyped across 134 candidate genes using the Illumina Genotyping platform, and the rank order by strength of association between frailty and genotype was determined in a cross-sectional study.Although no single-nucleotide polymorphism reached study-wide significance after controlling family-wise false-discovery rate at 0.05, single-nucleotide polymorphisms within the 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), Caspase 8 (CASP8), CREB-binding protein (CREBBP), lysine acetyltransferase 2B (KAT2B), and beta-transducin repeat containing (BTRC) loci were among those strongly associated with frailty.The apoptosis- and transcription regulation-related pathways highlighted by this preliminary analysis were consistent with prior gene expression studies in a frail mouse model and provide useful etiological insights for future biological studies of frailty.
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Project description:BackgroundThe use of 3-D similarity techniques in the analysis of biological data and virtual screening is pervasive, but what is a biologically meaningful 3-D similarity value? Can one find statistically significant separation between "active/active" and "active/inactive" spaces? These questions are explored using 734,486 biologically tested chemical structures, 1,389 biological assay data sets, and six different 3-D similarity types utilized by PubChem analysis tools.ResultsThe similarity value distributions of 269.7 billion unique conformer pairs from 734,486 biologically tested compounds (all-against-all) from PubChem were utilized to help work towards an answer to the question: what is a biologically meaningful 3-D similarity score? The average and standard deviation for the six similarity measures STST-opt, CTST-opt, ComboTST-opt, STCT-opt, CTCT-opt, and ComboTCT-opt were 0.54 ± 0.10, 0.07 ± 0.05, 0.62 ± 0.13, 0.41 ± 0.11, 0.18 ± 0.06, and 0.59 ± 0.14, respectively. Considering that this random distribution of biologically tested compounds was constructed using a single theoretical conformer per compound (the "default" conformer provided by PubChem), further study may be necessary using multiple diverse conformers per compound; however, given the breadth of the compound set, the single conformer per compound results may still apply to the case of multi-conformer per compound 3-D similarity value distributions. As such, this work is a critical step, covering a very wide corpus of chemical structures and biological assays, creating a statistical framework to build upon.The second part of this study explored the question of whether it was possible to realize a statistically meaningful 3-D similarity value separation between reputed biological assay "inactives" and "actives". Using the terminology of noninactive-noninactive (NN) pairs and the noninactive-inactive (NI) pairs to represent comparison of the "active/active" and "active/inactive" spaces, respectively, each of the 1,389 biological assays was examined by their 3-D similarity score differences between the NN and NI pairs and analyzed across all assays and by assay category types. While a consistent trend of separation was observed, this result was not statistically unambiguous after considering the respective standard deviations. While not all "actives" in a biological assay are amenable to this type of analysis, e.g., due to different mechanisms of action or binding configurations, the ambiguous separation may also be due to employing a single conformer per compound in this study. With that said, there were a subset of biological assays where a clear separation between the NN and NI pairs found. In addition, use of combo Tanimoto (ComboT) alone, independent of superposition optimization type, appears to be the most efficient 3-D score type in identifying these cases.ConclusionThis study provides a statistical guideline for analyzing biological assay data in terms of 3-D similarity and PubChem structure-activity analysis tools. When using a single conformer per compound, a relatively small number of assays appear to be able to separate "active/active" space from "active/inactive" space.
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Project description:Innovations in LED lighting technology have led to tremendous adoption rates and vastly improved the metrics by which they are traditionally evaluated-including color quality, longevity, and energy efficiency to name a few. Additionally, scientific insight has broadened with respect to the biological impact of light, specifically our circadian rhythm. Indoor electric lighting, despite its many attributes, fails to specifically address the biological responses to light. Traditional electric lighting environments are biologically too dim during the day, too bright at night, and with many people spending much of their lives in these environments, it can lead to circadian dysfunction. The lighting industry's biological solution has been to create bluer days and yellower nights, but the technology created to do so caters primarily to the cones. A better call to action is to provide biologically brighter days and biologically darker nights within the built environment. However, current lighting design practices have specified the comfort and utility of electric light. Brighter intensity during the day can often be uncomfortable or glary, and reduced light intensity at night may compromise visual comfort and safety, both of which will affect user compliance. No single lighting solution will effectively create biologically brighter days and biologically darker nights, but rather a variety of parameters need to be considered. This paper discusses the contributions of spectral power distribution, hue or color temperature, spatial distribution, as well as architectural geometry and surface reflectivity, to achieve biologically relevant lighting.
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Project description:Previously, SAR models for carcinogenesis used descriptors that are essentially chemical descriptors. Herein we report the development of models with the cat-SAR expert system using biological descriptors (i.e., ligand-receptor interactions) rat mammary carcinogens. These new descriptors are derived from the virtual screening for ligand-receptor interactions of carcinogens, non-carcinogens, and mammary carcinogens to a set of 5494 target proteins. Leave-one-out validations of the ligand mammary carcinogen-non-carcinogen model had a concordance between experimental and predicted results of 71%, and the mammary carcinogen-non-mammary carcinogen model was 72% concordant. The development of a hybrid fragment-ligand model improved the concordances to 85 and 83%, respectively. In a separate external validation exercise, hybrid fragment-ligand models had concordances of 81 and 76%. Analyses of example rat mammary carcinogens including the food mutagen and oestrogenic compound PhIP, the herbicide atrazine, and the drug indomethacin; the ligand model identified a number of proteins associated with each compound that had previously been referenced in Medline in conjunction with the test chemical and separately with association to breast cancer. This new modelling approach can enhance model predictivity and help bridge the gap between chemical structure and carcinogenic activity by descriptors that are related to biological targets.
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Project description:We present plasmonic optical trapping of micron-sized particles in biologically relevant buffer media with varying ionic strength. The media consist of 3 cell-growth solutions and 2 buffers and are specifically chosen due to their widespread use and applicability to breast-cancer and angiogenesis studies. High-precision rheological measurements on the buffer media reveal that, in all cases excluding the 8.0 pH Stain medium, the fluids exhibit Newtonian behavior, thereby enabling straightforward measurements of optical trap stiffness from power-spectral particle displacement data. Using stiffness as a trapping performance metric, we find that for all media under consideration the plasmonic nanotweezers generate optical forces 3-4x a conventional optical trap. Further, plasmonic trap stiffness values are comparable to those of an identical water-only system, indicating that the performance of a plasmonic nanotweezer is not degraded by the biological media. These results pave the way for future biological applications utilizing plasmonic optical traps.
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Project description:Synthetic approaches toward multigram preparation of spirocyclic α,α-disubstituted pyrrolidines from readily available starting materials are discussed. It was shown that although a number of synthetic methodologies have been known to date, many of the title compounds remain hardly accessible. The most appropriate literature method (which relied on reaction of imines and allyl magnesium halide, followed by bromocyclization) was identified and optimized. It was found that the method is most fruitful for simple non-functionalized substrates. Two novel approaches based on the Sakurai or Petasis reactions of cyclic ketones, followed by hydroboration-oxidation at the allyl moiety thus introduced, were elaborated. The latter method had the largest scope and was beneficial for the substrates containing organosulfur or protected amino functions. For the synthesis of 4-azaspiro[2.4]heptane, an alternative synthetic scheme commencing from tert-butyl cyclopropanecarboxylate (instead of the corresponding ketone) was developed. It was shown that the whole set of the methodologies developed can be used for the synthesis of various spirocyclic α,α-disubstituted pyrrolidines-advanced building blocks of potential importance to medicinal and agrochemistry-at up to a 100 g scale.
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Project description:BACKGROUND:Protein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations. RESULTS:In this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking using PEBP (Phosphatidylethanolamine binding protein), a kinase inhibitor with multiple partners. CONCLUSIONS:An approach using arbitrary docking, and based solely on physical properties, can successfully identify biologically pertinent protein interfaces.
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Project description:A new methodology for classifying fragment combinations and characterizing pseudonatural products (PNPs) is described. The source code is based on open-source tools and is organized as a Python package. Tasks can be executed individually or within the context of scalable, robust workflows. First, structures are standardized and duplicate entries are filtered out. Then, molecules are probed for the presence of predefined fragments. For molecules with more than one match, fragment combinations are classified. The algorithm considers the pairwise relative position of fragments within the molecule (fused atoms, linkers, intermediary rings), resulting in 18 different possible fragment combination categories. Finally, all combinations for a given molecule are assembled into a fragment combination graph, with fragments as nodes and combination types as edges. This workflow was applied to characterize PNPs in the ChEMBL database via comparison of fragment combination graphs with natural product (NP) references, represented by the Dictionary of Natural Products. The Murcko fragments extracted from 2000 structures previously described were used to define NP fragments. The results indicate that ca. 23% of the biologically relevant compounds listed in ChEMBL comply to the PNP definition and that, therefore, PNPs occur frequently among known biologically relevant small molecules. The majority (>95%) of PNPs contain two to four fragments, mainly (>95%) distributed in five different combination types. These findings may provide guidance for the design of new PNPs.
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