Predicting Mouse Liver Microsomal Stability with “Pruned” Machine Learning Models and Public Data

PubMed Central

Perryman, Alexander L.; Stratton, Thomas P.; Ekins, Sean; Freundlich, Joel S.

2015-01-01

Purpose Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Methods Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). Results “Pruning” out the moderately unstable/moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 hour. Conclusions Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources. PMID:26415647

Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data.

PubMed

Perryman, Alexander L; Stratton, Thomas P; Ekins, Sean; Freundlich, Joel S

2016-02-01

Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). "Pruning" out the moderately unstable / moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 h. Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources.

Predictive Structure-Based Toxicology Approaches To Assess the Androgenic Potential of Chemicals.

PubMed

Trisciuzzi, Daniela; Alberga, Domenico; Mansouri, Kamel; Judson, Richard; Novellino, Ettore; Mangiatordi, Giuseppe Felice; Nicolotti, Orazio

2017-11-27

We present a practical and easy-to-run in silico workflow exploiting a structure-based strategy making use of docking simulations to derive highly predictive classification models of the androgenic potential of chemicals. Models were trained on a high-quality chemical collection comprising 1689 curated compounds made available within the CoMPARA consortium from the US Environmental Protection Agency and were integrated with a two-step applicability domain whose implementation had the effect of improving both the confidence in prediction and statistics by reducing the number of false negatives. Among the nine androgen receptor X-ray solved structures, the crystal 2PNU (entry code from the Protein Data Bank) was associated with the best performing structure-based classification model. Three validation sets comprising each 2590 compounds extracted by the DUD-E collection were used to challenge model performance and the effectiveness of Applicability Domain implementation. Next, the 2PNU model was applied to screen and prioritize two collections of chemicals. The first is a small pool of 12 representative androgenic compounds that were accurately classified based on outstanding rationale at the molecular level. The second is a large external blind set of 55450 chemicals with potential for human exposure. We show how the use of molecular docking provides highly interpretable models and can represent a real-life option as an alternative nontesting method for predictive toxicology.

De Novo Design of Bioactive Small Molecules by Artificial Intelligence.

PubMed

Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca; Schneider, Gisbert

2018-01-01

Generative artificial intelligence offers a fresh view on molecular design. We present the first-time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine-tuned on recognizing retinoid X and peroxisome proliferator-activated receptor agonists. We synthesized five top-ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low-micromolar receptor modulatory activity in cell-based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

TREATMENT OF VOLATILE ORGANIC COMPOUNDS IN WASTE GASES USING A TRICKLING BIOFILTER SYSTEM: A MODELING APPROACH

EPA Science Inventory

Biofiltration represents a novel strategy for controlling VOC emissions from a variety of industrial processes. As commercial applications of these systems increase, sophisticated theoretical models will be useful in establishing design criteria for providing insights into impor...

Discriminating model for diagnosis of basal cell carcinoma and melanoma in vitro based on the Raman spectra of selected biochemicals

NASA Astrophysics Data System (ADS)

Silveira, Landulfo; Silveira, Fabrício Luiz; Bodanese, Benito; Zângaro, Renato Amaro; Pacheco, Marcos Tadeu T.

2012-07-01

Raman spectroscopy has been employed to identify differences in the biochemical constitution of malignant [basal cell carcinoma (BCC) and melanoma (MEL)] cells compared to normal skin tissues, with the goal of skin cancer diagnosis. We collected Raman spectra from compounds such as proteins, lipids, and nucleic acids, which are expected to be represented in human skin spectra, and developed a linear least-squares fitting model to estimate the contributions of these compounds to the tissue spectra. We used a set of 145 spectra from biopsy fragments of normal (30 spectra), BCC (96 spectra), and MEL (19 spectra) skin tissues, collected using a near-infrared Raman spectrometer (830 nm, 50 to 200 mW, and 20 s exposure time) coupled to a Raman probe. We applied the best-fitting model to the spectra of biochemicals and tissues, hypothesizing that the relative spectral contribution of each compound to the tissue Raman spectrum changes according to the disease. We verified that actin, collagen, elastin, and triolein were the most important biochemicals representing the spectral features of skin tissues. A classification model applied to the relative contribution of collagen III, elastin, and melanin using Euclidean distance as a discriminator could differentiate normal from BCC and MEL.

Development of Anti-Virulence Approaches for Candidiasis via a Novel Series of Small-Molecule Inhibitors of Candida albicans Filamentation

PubMed Central

Romo, Jesus A.; Pierce, Christopher G.; Chaturvedi, Ashok K.; Lazzell, Anna L.; McHardy, Stanton F.

2017-01-01

ABSTRACT Candida albicans remains the main etiologic agent of candidiasis, the most common fungal infection and now the third most frequent infection in U.S. hospitals. The scarcity of antifungal agents and their limited efficacy contribute to the unacceptably high morbidity and mortality rates associated with these infections. The yeast-to-hypha transition represents the main virulence factor associated with the pathogenesis of C. albicans infections. In addition, filamentation is pivotal for robust biofilm development, which represents another major virulence factor for candidiasis and further complicates treatment. Targeting pathogenic mechanisms rather than growth represents an attractive yet clinically unexploited approach in the development of novel antifungal agents. Here, we performed large-scale phenotypic screening assays with 30,000 drug-like small-molecule compounds within ChemBridge’s DIVERSet chemical library in order to identify small-molecule inhibitors of C. albicans filamentation, and our efforts led to the identification of a novel series of bioactive compounds with a common biaryl amide core structure. The leading compound of this series, N-[3-(allyloxy)-phenyl]-4-methoxybenzamide, was able to prevent filamentation under all liquid and solid medium conditions tested, suggesting that it impacts a common core component of the cellular machinery that mediates hypha formation under different environmental conditions. In addition to filamentation, this compound also inhibited C. albicans biofilm formation. This leading compound also demonstrated in vivo activity in clinically relevant murine models of invasive and oral candidiasis. Overall, our results indicate that compounds within this series represent promising candidates for the development of novel anti-virulence approaches to combat C. albicans infections. PMID:29208749

Pharmacology and toxicology of pahayokolide A, a bioactive metabolite from a freshwater species of Lyngbya isolated from the Florida Everglades

PubMed Central

Berry, John P.; Gantar, Miroslav; Gawley, Robert E.; Wang, Minglei; Rein, Kathleen S.

2008-01-01

The genus of filamentous cyanobacteria, Lyngbya, has been found to be a rich source of bioactive metabolites. However, identification of such compounds from Lyngbya has largely focused on a few marine representatives. Here, we report on the pharmacology and toxicology of pahayokolide A from a freshwater isolate, Lyngbya sp. strain 15−2, from the Florida Everglades. Specifically, we investigated inhibition of microbial representatives and mammalian cell lines, as well as toxicity of the compound to both invertebrate and vertebrate models. Pahayokolide A inhibited representatives of Bacillus, as well as the yeast, Saccharomyces cerevisiae. Interestingly, the compound also inhibited several representatives of green algae that were also isolated from the Everglades. Pahayokolide A was shown to inhibit a number of cancer cell lines over a range of concentrations (IC50 varied from 2.13 to 44.57 μM) depending on the cell-type. When tested against brine shrimp, pahayokolide was only marginally toxic at the highest concentrations tested (1 mg/mL). The compound was, however, acutely toxic to zebrafish embryos (LC50=2.15 μM). Possible biomedical and environmental health aspects of the pahayokolides remain to be investigated; however, the identification of bioactive metabolites such as these demonstrates the potential of the Florida Everglades as source of new toxins and drugs. PMID:15683832

Materials cohesion and interaction forces.

PubMed

Rosenholm, Jarl B; Peiponen, Kai-Erik; Gornov, Evgeny

2008-09-01

The most important methods to determine the cohesive interactions of materials and adhesive interactions between different substances are reviewed. The term cohesion is generalized as representing the unifying interaction forces of a single material and adhesion forces between different substances due to attraction. The aim is to interlink a number of frequently used interaction parameters in order to promote the understanding of materials research executed within different scientific (Material, Colloid, Sol-Gel and Nano) communities. The modern interdisciplinary research requires a removal of the historical obstacles represented by widely differing nomenclature used for the same material properties. The interaction parameters of different models are reviewed and representative numerical values computed from tabulated thermodynamic and spectroscopic material constants. The results are compared with published values. The models are grouped to represent single and two component systems, respectively. The latter group includes models for films on substrates and work of adhesion between liquids and solids. In most cases rather rough approximations have been employed, mostly relating to van der Waals substances for which the gas state is common reference state. In order to improve the predictability of the key Hamaker constant, a novel model for interpreting the dielectric spectrum is presented. The interrelation between thermodynamic, electronic, spectroscopic and dielectric parameters is illustrated by model calculations on typical inorganic materials of current interest as model compounds. The ionic solids are represented by NaCl and KCl, while ZnO, FeO, Fe(2)O(3), Fe(3)O(4), Al(2)O(3), SiO(2), TiO(2), ZrO(2), SnO, SnO(2) represent ceramic oxides and semiconductors. The model compounds thus illustrate the effect of bond type (covalent or ionic) and valence (charge number and sign) of the constituent elements. However, since the focus is placed on a phenomenological analysis, the number of examples remains self-evidently incomplete.

Discovery and Optimization of Indolyl-Containing 4-Hydroxy-2-Pyridone Type II DNA Topoisomerase Inhibitors Active against Multidrug Resistant Gram-negative Bacteria.

PubMed

Gerasyuto, Aleksey I; Arnold, Michael A; Wang, Jiashi; Chen, Guangming; Zhang, Xiaoyan; Smith, Sean; Woll, Matthew G; Baird, John; Zhang, Nanjing; Almstead, Neil G; Narasimhan, Jana; Peddi, Srinivasa; Dumble, Melissa; Sheedy, Josephine; Weetall, Marla; Branstrom, Arthur A; Prasad, J V N; Karp, Gary M

2018-05-14

There exists an urgent medical need to identify new chemical entities (NCEs) targeting multidrug resistant (MDR) bacterial infections, particularly those caused by Gram-negative pathogens. 4-Hydroxy-2-pyridones represent a novel class of nonfluoroquinolone inhibitors of bacterial type II topoisomerases active against MDR Gram-negative bacteria. Herein, we report on the discovery and structure-activity relationships of a series of fused indolyl-containing 4-hydroxy-2-pyridones with improved in vitro antibacterial activity against fluoroquinolone resistant strains. Compounds 6o and 6v are representative of this class, targeting both bacterial DNA gyrase and topoisomerase IV (Topo IV). In an abbreviated susceptibility screen, compounds 6o and 6v showed improved MIC 90 values against Escherichia coli (0.5-1 μg/mL) and Acinetobacter baumannii (8-16 μg/mL) compared to the precursor compounds. In a murine septicemia model, both compounds showed complete protection in mice infected with a lethal dose of E. coli.

Concentration Effects of Polymer Electrolyte Membrane Degradation Products on Oxygen Reduction Activity for Three Platinum Catalysts

DOE PAGES

Christ, J. M.; Neyerlin, K. C.; Richards, R.; ...

2014-10-04

A rotating disk electrode (RDE) along with cyclic voltammetry (CV) and linear sweep voltammetry (LSV), were used to investigate the impact of two model compounds representing degradation products of Nafion and 3M perfluorinated sulfonic acid membranes on the electrochemical surface area (ECA) and oxygen reduction reaction (ORR) activity of polycrystalline Pt, nano-structured thin film (NSTF) Pt (3M), and Pt/Vulcan carbon (Pt/Vu) (TKK) electrodes. ORR kinetic currents (measured at 0.9 V and transport corrected) were found to decrease linearly with the log of concentration for both model compounds on all Pt surfaces studied. Ultimately, model compound adsorption effects on ECA weremore » more abstruse due to competitive organic anion adsorption on Pt surfaces superimposing with the hydrogen underpotential deposition (HUPD) region.« less

Concentration-dependent polyparameter linear free energy relationships to predict organic compound sorption on carbon nanotubes

PubMed Central

Zhao, Qing; Yang, Kun; Li, Wei; Xing, Baoshan

2014-01-01

Adsorption of organic compounds on carbon nanotubes (CNTs), governed by interactions between molecules and CNTs surfaces, is critical for their fate, transport, bioavailability and toxicity in the environment. Here, we report a promising concentration-dependent polyparameter linear free energy relationships (pp-LFERs) model to describe the compound-CNTs interactions and to predict sorption behavior of chemicals on CNTs in a wide range of concentrations (over five orders of magnitude). The developed pp-LFERs are able to capture the dependence of the ki on equilibrium concentration. The pp-LFERs indexes [r, p, a, b, v] representing different interactions are found to have a good relationship with the aqueous equilibrium concentrations of compounds. This modified model can successfully interpret the relative contribution of each interaction at a given concentration and reliably predict sorption of various chemicals on CNTs. This approach is expected to help develop a better environmental fate and risk assessment model. PMID:24463462

Adsorption of selected pharmaceuticals and an endocrine disrupting compound by granular activated carbon. 2. Model prediction.

PubMed

Yu, Zirui; Peldszus, Sigrid; Huck, Peter M

2009-03-01

The adsorption of two representative pharmaceutically active compounds (PhACs)-naproxen and carbamazepine and one endocrine disrupting compound (EDC)-nonylphenol was studied in pilot-scale granular activated carbon (GAC) adsorbers using post-sedimentation (PS) water from a full-scale drinking water treatment plant. Acidic naproxen broke through fastest while nonylphenol was removed best, which was consistent with the degree to which fouling affected compound removals. Model predictions and experimental data were generally in good agreement for all three compounds, which demonstrated the effectiveness and robustness of the pore and surface diffusion model (PSDM) used in combination with the time-variable parameter approach for predicting removals at environmentally relevant concentrations (i.e., ng/L range). Sensitivity analyses suggested that accurate determination of film diffusion coefficients was critical for predicting breakthrough for naproxen and carbamazepine, in particular when high removals are targeted. Model simulations demonstrated that GAC carbon usage rates (CURs) for naproxen were substantially influenced by the empty bed contact time (EBCT) at the investigated conditions. Model-based comparisons between GAC CURs and minimum CURs for powdered activated carbon (PAC) applications suggested that PAC would be most appropriate for achieving 90% removal of naproxen, whereas GAC would be more suitable for nonylphenol.

QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.

PubMed

Votano, Joseph R; Parham, Marc; Hall, L Mark; Hall, Lowell H; Kier, Lemont B; Oloff, Scott; Tropsha, Alexander

2006-11-30

Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR modeling. The data was partitioned into a training set of 808 compounds and an external validation test set of 200 compounds. Partitioning was accomplished by clustering the compounds in a structure descriptor space so that random sampling of 20% of the whole data set produced an external test set that is a good representative of the training set with respect to both structure and protein binding values. The four modeling techniques include multiple linear regression (MLR), artificial neural networks (ANN), k-nearest neighbors (kNN), and support vector machines (SVM). With the exception of the MLR model, the ANN, kNN, and SVM QSARs were ensemble models. Training set correlation coefficients and mean absolute error ranged from r2=0.90 and MAE=7.6 for ANN to r2=0.61 and MAE=16.2 for MLR. Prediction results from the validation set yielded correlation coefficients and mean absolute errors which ranged from r2=0.70 and MAE=14.1 for ANN to a low of r2=0.59 and MAE=18.3 for the SVM model. Structure descriptors that contribute significantly to the models are discussed and compared with those found in other published models. For the ANN model, structure descriptor trends with respect to their affects on predicted protein binding can assist the chemist in structure modification during the drug design process.

Design, synthesis, and biological evaluation of 3,4-dihydroquinolin-2(1H)-one and 1,2,3,4-tetrahydroquinoline-based selective human neuronal nitric oxide synthase (nNOS) inhibitors.

PubMed

Ramnauth, Jailall; Speed, Joanne; Maddaford, Shawn P; Dove, Peter; Annedi, Subhash C; Renton, Paul; Rakhit, Suman; Andrews, John; Silverman, Sarah; Mladenova, Gabriela; Zinghini, Salvatore; Nair, Sheela; Catalano, Concettina; Lee, David K H; De Felice, Milena; Porreca, Frank

2011-08-11

Neuronal nitric oxide synthase (nNOS) inhibitors are effective in preclinical models of many neurological disorders. In this study, two related series of compounds, 3,4-dihydroquinolin-2(1H)-one and 1,2,3,4-tetrahydroquinoline, containing a 6-substituted thiophene amidine group were synthesized and evaluated as inhibitors of human nitric oxide synthase (NOS). A structure-activity relationship (SAR) study led to the identification of a number of potent and selective nNOS inhibitors. Furthermore, a few representative compounds were shown to possess druglike properties, features that are often difficult to achieve when designing nNOS inhibitors. Compound (S)-35, with excellent potency and selectivity for nNOS, was shown to fully reverse thermal hyperalgesia when given to rats at a dose of 30 mg/kg intraperitonieally (ip) in the L5/L6 spinal nerve ligation model of neuropathic pain (Chung model). In addition, this compound reduced tactile hyperesthesia (allodynia) after oral administration (30 mg/kg) in a rat model of dural inflammation relevant to migraine pain.

Direct Phenotypic Screening in Mice: Identification of Individual, Novel Antinociceptive Compounds from a Library of 734,821 Pyrrolidine Bis-piperazines.

PubMed

Houghten, Richard A; Ganno, Michelle L; McLaughlin, Jay P; Dooley, Colette T; Eans, Shainnel O; Santos, Radleigh G; LaVoi, Travis; Nefzi, Adel; Welmaker, Greg; Giulianotti, Marc A; Toll, Lawrence

2016-01-11

The hypothesis in the current study is that the simultaneous direct in vivo testing of thousands to millions of systematically arranged mixture-based libraries will facilitate the identification of enhanced individual compounds. Individual compounds identified from such libraries may have increased specificity and decreased side effects early in the discovery phase. Testing began by screening ten diverse scaffolds as single mixtures (ranging from 17,340 to 4,879,681 compounds) for analgesia directly in the mouse tail withdrawal model. The "all X" mixture representing the library TPI-1954 was found to produce significant antinociception and lacked respiratory depression and hyperlocomotor effects using the Comprehensive Laboratory Animal Monitoring System (CLAMS). The TPI-1954 library is a pyrrolidine bis-piperazine and totals 738,192 compounds. This library has 26 functionalities at the first three positions of diversity made up of 28,392 compounds each (26 × 26 × 42) and 42 functionalities at the fourth made up of 19,915 compounds each (26 × 26 × 26). The 120 resulting mixtures representing each of the variable four positions were screened directly in vivo in the mouse 55 °C warm-water tail-withdrawal assay (ip administration). The 120 samples were then ranked in terms of their antinociceptive activity. The synthesis of 54 individual compounds was then carried out. Nine of the individual compounds produced dose-dependent antinociception equivalent to morphine. In practical terms what this means is that one would not expect multiexponential increases in activity as we move from the all-X mixture, to the positional scanning libraries, to the individual compounds. Actually because of the systematic formatting one would typically anticipate steady increases in activity as the complexity of the mixtures is reduced. This is in fact what we see in the current study. One of the final individual compounds identified, TPI 2213-17, lacked significant respiratory depression, locomotor impairment, or sedation. Our results represent an example of this unique approach for screening large mixture-based libraries directly in vivo to rapidly identify individual compounds.

Discovery of a Potent, Dual Serotonin and Norepinephrine Reuptake Inhibitor

PubMed Central

2013-01-01

The objective of the described research effort was to identify a novel serotonin and norepinephrine reuptake inhibitor (SNRI) with improved norepinephrine transporter activity and acceptable metabolic stability and exhibiting minimal drug–drug interaction. We describe herein the discovery of a series of 3-substituted pyrrolidines, exemplified by compound 1. Compound 1 is a selective SNRI in vitro and in vivo, has favorable ADME properties, and retains inhibitory activity in the formalin model of pain behavior. Compound 1 thus represents a potential new probe to explore utility of SNRIs in central nervous system disorders, including chronic pain conditions. PMID:24900709

Chapter 8: Pyrolysis Mechanisms of Lignin Model Compounds Using a Heated Micro-Reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robichaud, David J.; Nimlos, Mark R.; Ellison, G. Barney

2015-10-03

Lignin is an important component of biomass, and the decomposition of its thermal deconstruction products is important in pyrolysis and gasification. In this chapter, we investigate the unimolecular pyrolysis chemistry through the use of singly and doubly substituted benzene molecules that are model compounds representative of lignin and its primary pyrolysis products. These model compounds are decomposed in a heated micro-reactor, and the products, including radicals and unstable intermediates, are measured using photoionization mass spectrometry and matrix isolation infrared spectroscopy. We show that the unimolecular chemistry can yield insight into the initial decomposition of these species. At pyrolysis and gasificationmore » severities, singly substituted benzenes typically undergo bond scission and elimination reactions to form radicals. Some require radical-driven chain reactions. For doubly substituted benzenes, proximity effects of the substituents can change the reaction pathways.« less

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models.

PubMed

Boppana, Kiran; Dubey, P K; Jagarlapudi, Sarma A R P; Vadivelan, S; Rambabu, G

2009-09-01

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

Catalytic Upgrading of Biomass Pyrolysis Oxygenates with Vacuum Gas Oil Using a Davison Circulating Riser Reactor

DOE PAGES

Jarvis, Mark W.; Olstad, Jessica; Parent, Yves; ...

2018-01-02

We investigate and quantitate the changes in hydrocarbon product composition while evaluating the performance and operability of the National Renewable Energy Laboratory's Davison Circulating Riser (DCR) reactor system when biomass model compounds are cofed with traditional fluid catalyst cracking (FCC) feeds and catalyst: vacuum gas oil (VGO) and equilibrium zeolite catalyst (E-Cat). Three compounds (acetic acid, guaiacol, and sorbitan monooleate) were selected to represent the major classes of oxygenates present in biomass pyrolysis vapors. These vapors can contain 30-50% oxygen as oxygenates, which create conversion complications (increased reactivity and coking) when integrating biomass vapors and liquids into fuel and chemicalmore » processes long dominated by petroleum feedstocks. We used these model compounds to determine the appropriate conditions for coprocessing with petroleum and ultimately pure pyrolysis vapors only as compared with standard baseline conditions obtained with VGO and E-Cat only in the DCR. Model compound addition decreased the DCR catalyst circulation rate, which controls reactor temperature and measures reaction heat demand, while increasing catalyst coking rates. Liquid product analyses included 2-dimensional gas chromatography time-of-flight mass spectroscopy (2D GCxGC TOFS), simulated distillation (SIM DIST), 13C NMR, and carbonyl content. Aggregated results indicated that the model compounds were converted during reaction, and despite functional group differences, product distributions for each model compound were very similar. In addition, we determined that adding model compounds to the VGO feed did not significantly affect the DCR's operability or performance. Future work will assess catalytic upgrading of biomass pyrolysis vapor to fungible hydrocarbon products using upgrading catalysts currently being developed at NREL and at Johnson Matthey.« less

Catalytic Upgrading of Biomass Pyrolysis Oxygenates with Vacuum Gas Oil Using a Davison Circulating Riser Reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jarvis, Mark W.; Olstad, Jessica; Parent, Yves

We investigate and quantitate the changes in hydrocarbon product composition while evaluating the performance and operability of the National Renewable Energy Laboratory's Davison Circulating Riser (DCR) reactor system when biomass model compounds are cofed with traditional fluid catalyst cracking (FCC) feeds and catalyst: vacuum gas oil (VGO) and equilibrium zeolite catalyst (E-Cat). Three compounds (acetic acid, guaiacol, and sorbitan monooleate) were selected to represent the major classes of oxygenates present in biomass pyrolysis vapors. These vapors can contain 30-50% oxygen as oxygenates, which create conversion complications (increased reactivity and coking) when integrating biomass vapors and liquids into fuel and chemicalmore » processes long dominated by petroleum feedstocks. We used these model compounds to determine the appropriate conditions for coprocessing with petroleum and ultimately pure pyrolysis vapors only as compared with standard baseline conditions obtained with VGO and E-Cat only in the DCR. Model compound addition decreased the DCR catalyst circulation rate, which controls reactor temperature and measures reaction heat demand, while increasing catalyst coking rates. Liquid product analyses included 2-dimensional gas chromatography time-of-flight mass spectroscopy (2D GCxGC TOFS), simulated distillation (SIM DIST), 13C NMR, and carbonyl content. Aggregated results indicated that the model compounds were converted during reaction, and despite functional group differences, product distributions for each model compound were very similar. In addition, we determined that adding model compounds to the VGO feed did not significantly affect the DCR's operability or performance. Future work will assess catalytic upgrading of biomass pyrolysis vapor to fungible hydrocarbon products using upgrading catalysts currently being developed at NREL and at Johnson Matthey.« less

The Coulombic Lattice Potential of Ionic Compounds: The Cubic Perovskites.

ERIC Educational Resources Information Center

Francisco, E.; And Others

1988-01-01

Presents coulombic models representing the particles of a system by point charges interacting through Coulomb's law to explain coulombic lattice potential. Uses rubidium manganese trifluoride as an example of cubic perovskite structure. Discusses the effects on cluster properties. (CW)

Adsorption of selected pharmaceuticals and an endocrine disrupting compound by granular activated carbon. 2. Model prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Z.; Peldszus, S.; Huck, P.M.

The adsorption of two representative pharmaceutically active compounds (PhACs) naproxen and carbamazepine and one endocrine disrupting compound (EDC) nonylphenol was studied in pilot-scale granular activated carbon (GAC) adsorbers using post-sedimentation (PS) water from a full-scale drinking water treatment plant. The GAC adsorbents were coal-based Calgon Filtrasorb 400 and coconut shell-based PICA CTIF TE. Acidic naproxen broke through fastest while nonylphenol was removed best, which was consistent with the degree to which fouling affected compound removals. Model predictions and experimental data were generally in good agreement for all three compounds, which demonstrated the effectiveness and robustness of the pore and surfacemore » diffusion model (PSDM) used in combination with the time-variable parameter approach for predicting removals at environmentally relevant concentrations (i.e., ng/L range). Sensitivity analyses suggested that accurate determination of film diffusion coefficients was critical for predicting breakthrough for naproxen and carbamazepine, in particular when high removals are targeted. Model simulations demonstrated that GAC carbon usage rates (CURs) for naproxen were substantially influenced by the empty bed contact time (EBCT) at the investigated conditions. Model-based comparisons between GAC CURs and minimum CURs for powdered activated carbon (PAC) applications suggested that PAC would be most appropriate for achieving 90% removal of naproxen, whereas GAC would be more suitable for nonylphenol. 25 refs., 4 figs., 1 tab.« less

Merging the Structural Motifs of Functionalized Amino Acids and α-Aminoamides: Compounds with Significant Anticonvulsant Activities

PubMed Central

Salomé, Christophe; Salomé-Grosjean, Elise; Stables, James P.; Kohn, Harold

2010-01-01

Functional amino acids (FAAs) and α-aminoamides (AAAs) are two classes of antiepileptic drugs (AEDs) that exhibit pronounced anticonvulsant activities. We combined key structural pharmacophores present in FAAs and AAAs to generate a new series of compounds and document that select compounds exhibit activity superior to either the prototypical FAA (lacosamide) or the prototypical AAA (safinamide) in the maximal electroshock (MES) seizure model in rats. A representative compound, (R)-N-4′-((3″-fluoro)benzyloxy)benzyl 2-acetamido-3-methoxypropionamide ((R)-10), was tested in the MES (mice, ip), MES (rat, po), psychomotor 6 Hz (32 mA) (mice, ip), and hippocampal kindled (rat, ip) seizure tests providing excellent protection with ED50 values of 13, 14, ~10 mg/kg, and 12 mg/kg, respectively. In the rat sciatic nerve ligation model (ip), (R)-10 (12 mg/kg) provided an 11.2-fold attenuation of mechanical allodynia. In the mouse biphasic formalin pain model (ip), (R)-10 (15 mg/kg) reduced pain responses in the acute and the chronic inflammatory phases. PMID:20394379

Merging the structural motifs of functionalized amino acids and alpha-aminoamides: compounds with significant anticonvulsant activities.

PubMed

Salomé, Christophe; Salomé-Grosjean, Elise; Stables, James P; Kohn, Harold

2010-05-13

Functional amino acids (FAAs) and alpha-aminoamides (AAAs) are two classes of antiepileptic drugs (AEDs) that exhibit pronounced anticonvulsant activities. We combined key structural pharmacophores present in FAAs and AAAs to generate a new series of compounds and document that select compounds exhibit activity superior to either the prototypical FAA (lacosamide) or the prototypical AAA (safinamide) in the maximal electroshock (MES) seizure model in rats. A representative compound, (R)-N-4'-((3''-fluoro)benzyloxy)benzyl 2-acetamido-3-methoxypropionamide ((R)-10), was tested in the MES (mice, ip), MES (rat, po), psychomotor 6 Hz (32 mA) (mice, ip), and hippocampal kindled (rat, ip) seizure tests providing excellent protection with ED(50) values of 13, 14, approximately 10 mg/kg, and 12 mg/kg, respectively. In the rat sciatic nerve ligation model (ip), (R)-10 (12 mg/kg) provided an 11.2-fold attenuation of mechanical allodynia. In the mouse biphasic formalin pain model (ip), (R)-10 (15 mg/kg) reduced pain responses in the acute and the chronic inflammatory phases.

Predictive models in hazard assessment of Great Lakes contaminants for fish

USGS Publications Warehouse

Passino, Dora R. May

1986-01-01

A hazard assessment scheme was developed and applied to predict potential harm to aquatic biota of nearly 500 organic compounds detected by gas chromatography/mass spectrometry (GC/MS) in Great Lakes fish. The frequency of occurrence and estimated concentrations of compounds found in lake trout (Salvelinus namaycush) and walleyes (Stizostedion vitreum vitreum) were compared with available manufacturing and discharge information. Bioconcentration potential of the compounds was estimated from available data or from calculations of quantitative structure-activity relationships (QSAR). Investigators at the National Fisheries Research Center-Great Lakes also measured the acute toxicity (48-h EC50's) of 35 representative compounds to Daphnia pulex and compared the results with acute toxicity values generated by QSAR. The QSAR-derived toxicities for several chemicals underestimated the actual acute toxicity by one or more orders of magnitude. A multiple regression of log EC50 on log water solubility and molecular volume proved to be a useful predictive model. Additional models providing insight into toxicity incorporate solvatochromic parameters that measure dipolarity/polarizability, hydrogen bond acceptor basicity, and hydrogen bond donor acidity of the solute (toxicant).

Impact of Polymer Electrolyte Membrane Degradation Products on Oxygen Reduction Reaction Activity for Platinum Electrocatalysts

DOE PAGES

Christ, J. M.; Neyerlin, K. C.; Wang, H.; ...

2014-10-30

The impact of model membrane degradation compounds on the relevant electrochemical parameters for the oxygen reduction reaction (i.e. electrochemical surface area and catalytic activity), was studied for both polycrystalline Pt and carbon supported Pt electrocatalysts. Model compounds, representing previously published, experimentally determined polymer electrolyte membrane degradation products, were in the form of perfluorinated organic acids that contained combinations of carboxylic and/or sulfonic acid functionality. Perfluorinated carboxylic acids of carbon chain length C1 – C6 were found to have an impact on electrochemical surface area (ECA). The longest chain length acid also hindered the observed oxygen reduction reaction (ORR) performance, resultingmore » in a 17% loss in kinetic current (determined at 0.9 V). Model compounds containing sulfonic acid functional groups alone did not show an effect on Pt ECA or ORR activity. Lastly, greater than a 44% loss in ORR activity at 0.9V was observed for diacid model compounds DA-Naf (perfluoro(2-methyl-3-oxa-5-sulfonic pentanoic) acid) and DA-3M (perfluoro(4-sulfonic butanoic) acid), which contained both sulfonic and carboxylic acid functionalities.« less

Pharmacophore modeling, molecular docking and molecular dynamics studies on natural products database to discover novel skeleton as non-purine xanthine oxidase inhibitors.

PubMed

Peng, Jiale; Li, Yaping; Zhou, Yeheng; Zhang, Li; Liu, Xingyong; Zuo, Zhili

2018-05-29

Gout is a common inflammatory arthritis caused by the deposition of urate crystals within joints. It is increasingly in prevalence during the past few decades as shown by the epidemiological survey results. Xanthine oxidase (XO) is a key enzyme to transfer hypoxanthine and xanthine to uric acid, whose overproduction leads to gout. Therefore, inhibiting the activity of xanthine oxidase is an important way to reduce the production of urate. In the study, in order to identify the potential natural products targeting XO, pharmacophore modeling was employed to filter databases. Here, two methods, pharmacophore based on ligand and pharmacophore based on receptor-ligand, were constructed by Discovery Studio. Then GOLD was used to refine the potential compounds with higher fitness scores. Finally, molecular docking and dynamics simulations were employed to analyze the interactions between compounds and protein. The best hypothesis was set as a 3D query to screen database, returning 785 and 297 compounds respectively. A merged set of the above 1082 molecules was subjected to molecular docking, which returned 144 hits with high-fitness scores. These molecules were clustered in four main kinds depending on different backbones. What is more, molecular docking showed that the representative compounds established key interactions with the amino acid residues in the protein, and the RMSD and RMSF of molecular dynamics results showed that these compounds can stabilize the protein. The information represented in the study confirmed previous reports. And it may assist to discover and design new backbones as potential XO inhibitors based on natural products.

Evaluation of Substituted 1,2,3-Dithiazoles as Inhibitors of the Feline Immunodeficiency Virus (FIV) Nucleocapsid Protein via a Proposed Zinc Ejection Mechanism.

PubMed

Asquith, Christopher R M; Konstantinova, Lidia S; Laitinen, Tuomo; Meli, Marina L; Poso, Antti; Rakitin, Oleg A; Hofmann-Lehmann, Regina; Hilton, Stephen T

2016-10-06

A diverse library of 5-thieno-, 5-oxo-, and 5-imino-1,2,3-dithiazole derivatives was synthesized and evaluated for efficacy against the feline immunodeficiency virus (FIV) as a model for HIV in cells. Several diverse compounds from this series displayed nanomolar activity and low toxicity, representing a potential new class of compounds for the treatment of FIV and HIV. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Toxicity to Daphnia pulex and QSAR predictions for polycyclic hydrocarbons representative of Great Lakes contaminants

USGS Publications Warehouse

Passino-Reader, D.R.; Hickey, J.P.; Ogilvie, L.M.

1997-01-01

The objectives of this study were (1) to determine the toxicity of several types of polycyclic hydrocarbons characteristic of Great Lakes samples to Daphnia pulex, a Great Lakes zooplankter, (2) to investigate the influence of different structural characteristics on toxicity, and (3) to determine the linear solvation energy relationship (LSER) parameters and model that describe these compounds. These results will be related to comparative toxicity of other Great Lakes environmental compounds and to their application in site specific risk assessment.

Predicting concentrations of trace organic compounds in municipal wastewater treatment plant sludge and biosolids using the PhATE™ model.

PubMed

Cunningham, Virginia L; D'Aco, Vincent J; Pfeiffer, Danielle; Anderson, Paul D; Buzby, Mary E; Hannah, Robert E; Jahnke, James; Parke, Neil J

2012-07-01

This article presents the capability expansion of the PhATE™ (pharmaceutical assessment and transport evaluation) model to predict concentrations of trace organics in sludges and biosolids from municipal wastewater treatment plants (WWTPs). PhATE was originally developed as an empirical model to estimate potential concentrations of active pharmaceutical ingredients (APIs) in US surface and drinking waters that could result from patient use of medicines. However, many compounds, including pharmaceuticals, are not completely transformed in WWTPs and remain in biosolids that may be applied to land as a soil amendment. This practice leads to concerns about potential exposures of people who may come into contact with amended soils and also about potential effects to plants and animals living in or contacting such soils. The model estimates the mass of API in WWTP influent based on the population served, the API per capita use, and the potential loss of the compound associated with human use (e.g., metabolism). The mass of API on the treated biosolids is then estimated based on partitioning to primary and secondary solids, potential loss due to biodegradation in secondary treatment (e.g., activated sludge), and potential loss during sludge treatment (e.g., aerobic digestion, anaerobic digestion, composting). Simulations using 2 surrogate compounds show that predicted environmental concentrations (PECs) generated by PhATE are in very good agreement with measured concentrations, i.e., well within 1 order of magnitude. Model simulations were then carried out for 18 APIs representing a broad range of chemical and use characteristics. These simulations yielded 4 categories of results: 1) PECs are in good agreement with measured data for 9 compounds with high analytical detection frequencies, 2) PECs are greater than measured data for 3 compounds with high analytical detection frequencies, possibly as a result of as yet unidentified depletion mechanisms, 3) PECs are less than analytical reporting limits for 5 compounds with low analytical detection frequencies, and 4) the PEC is greater than the analytical method reporting limit for 1 compound with a low analytical detection frequency, possibly again as a result of insufficient depletion data. Overall, these results demonstrate that PhATE has the potential to be a very useful tool in the evaluation of APIs in biosolids. Possible applications include: prioritizing APIs for assessment even in the absence of analytical methods; evaluating sludge processing scenarios to explore potential mitigation approaches; using in risk assessments; and developing realistic nationwide concentrations, because PECs can be represented as a cumulative probability distribution. Finally, comparison of PECs to measured concentrations can also be used to identify the need for fate studies of compounds of interest in biosolids. Copyright © 2011 SETAC.

Combined pharmacophore and structure-guided studies to identify diverse HSP90 inhibitors.

PubMed

Sanam, Ramadevi; Tajne, Sunita; Gundla, Rambabu; Vadivelan, S; Machiraju, Pavan Kumar; Dayam, Raveendra; Narasu, Lakshmi; Jagarlapudi, Sarma; Neamati, Nouri

2010-02-26

Heat Shock Protein 90 (HSP90), an ATP-dependent molecular chaperone, has emerged as a promising target in the treatment of cancer. Inhibition of HSP90 represents a new target of antitumor therapy, since it may influence many specific signaling pathways. Many HSP90 inhibitors bind to the ATP-binding pocket, inhibit chaperone function, resulting in cell death. Recent clinical trials for treatment of cancer have put HSP90's importance into focus and have highlighted the need for full scale research into HSP90 related pathways. Here we report five novel HSP90 inhibitors which were identified by using pharmacophore models and docking studies. We used highly discriminative pharmacophore model as a 3D query to search against database of approximately 1 M compounds and cluster analysis results yielded 455 compounds which were further subjected for docking. Glide docking studies suggested 122 compounds as in silico hits and these compounds were further selected for the cytotoxicity assay in the HSP90-over expressing SKBr3 cell line. Of the 122 compounds tested, 5 compounds inhibited cell growth with an IC(50) value less than 50 microM. Copyright 2009 Elsevier Inc. All rights reserved.

A generic biokinetic model for carbon-14 labelled compounds

NASA Astrophysics Data System (ADS)

Manger, Ryan Paul

Carbon-14, a radioactive nuclide, is used in many industrial applications. Due to its wide range of uses in industry, many workers are at risk of accidental internal exposure to 14C. Being a low energy beta emitter, 14C is not a significant external radiation hazard, but the internal consequences posed by 14C are important, especially because of its long half life of 5730 years [46]. The current biokinetic model recommended by the International Commission on Radiological Protection (ICRP) is a conservative estimate of how radiocarbon is treated by the human body. The ICRP generic radiocarbon model consists of a single compartment representing the entire human body. This compartment has a biological half life of 40 days yielding an effective dose coefficient of 5.8x10-10 Sv B q-1 [44, 45, 49, 53, 54]. This overestimates the dose of all radiocarbon compounds that have been studied [96]. An improved model has been developed that includes and alimentary tract, a urinary bladder, CO2 model, and an "Other" compartment used to model systemic tissues. The model can be adapted to replicate any excretion curve and excretion pattern. In addition, the effective dose coefficient produced by the updated model is near the mean effective dose coefficient of carbon compounds that have been considered in this research. The major areas of improvement are: more anatomically significant, a less conservative dose coefficient, and the ability to manipulate the model for known excretion data. Due to the wide variety of carbon compounds, it is suggested that specific biokinetic models be implemented for known radiocarbon substances. If the source of radiocarbon is dietary, then the physiologically based model proposed by Whillans [102] that splits all ingested radiocarbon compounds into carbohydrates, fats, and proteins should be used.

Oxidative cleavage of non-phenolic β-O-4 lignin model dimers by an extracellular aromatic peroxygenase

Treesearch

Matthias Kinne; Marzena Poraj-Kobielska; Rene Ullrich; Paula Nousiainen; Jussi Sipilä; Katrin Scheibner; Kenneth E. Hammel; Martin Hofrichter

2011-01-01

The extracellular aromatic peroxygenase of the agaric fungus Agrocybe aegerita catalyzed the H2O2-dependent cleavage of non-phenolic arylgiycerol-ß-aryl ethers (ß-O-4 ethers). For instance 1-(3,4-dimethoxyphenyl)-2-(2-methoxy-phenoxy)propane-1,3-diol, a recalcitrant dimeric lignin model compound that represents the major...

Fire emissions constrained by the synergistic use of formaldehyde and glyoxal SCIAMACHY columns in a two-compound inverse modelling framework

NASA Astrophysics Data System (ADS)

Stavrakou, T.; Muller, J.; de Smedt, I.; van Roozendael, M.; Vrekoussis, M.; Wittrock, F.; Richter, A.; Burrows, J.

2008-12-01

Formaldehyde (HCHO) and glyoxal (CHOCHO) are carbonyls formed in the oxidation of volatile organic compounds (VOCs) emitted by plants, anthropogenic activities, and biomass burning. They are also directly emitted by fires. Although this primary production represents only a small part of the global source for both species, yet it can be locally important during intense fire events. Simultaneous observations of formaldehyde and glyoxal retrieved from the SCIAMACHY satellite instrument in 2005 and provided by the BIRA/IASB and the Bremen group, respectively, are compared with the corresponding columns simulated with the IMAGESv2 global CTM. The chemical mechanism has been optimized with respect to HCHO and CHOCHO production from pyrogenically emitted NMVOCs, based on the Master Chemical Mechanism (MCM) and on an explicit profile for biomass burning emissions. Gas-to-particle conversion of glyoxal in clouds and in aqueous aerosols is considered in the model. In this study we provide top-down estimates for fire emissions of HCHO and CHOCHO precursors by performing a two- compound inversion of emissions using the adjoint of the IMAGES model. The pyrogenic fluxes are optimized at the model resolution. The two-compound inversion offers the advantage that the information gained from measurements of one species constrains the sources of both compounds, due to the existence of common precursors. In a first inversion, only the burnt biomass amounts are optimized. In subsequent simulations, the emission factors for key individual NMVOC compounds are also varied.

Combined effects of pharmaceuticals, personal care products, biocides and organic contaminants on the growth of Skeletonema pseudocostatum.

PubMed

Petersen, Karina; Heiaas, Harald Hasle; Tollefsen, Knut Erik

2014-05-01

Organisms in the environment are exposed to a number of pollutants from different compound groups. In addition to the classic pollutants like the polychlorinated biphenyls, polyaromatic hydrocarbons (PAHs), alkylphenols, biocides, etc. other compound groups of concern are constantly emerging. Pharmaceuticals and personal care products (PPCPs) can be expected to co-occur with other organic contaminants like biocides, PAHs and alkylphenols in areas affected by wastewater, industrial effluents and intensive recreational activity. In this study, representatives from these four different compound groups were tested individually and in mixtures in a growth inhibition assay with the marine algae Skeletonema pseudocostatum (formerly Skeletonema costatum) to determine whether the combined effects could be predicted by models for additive effects; the concentration addition (CA) and independent action (IA) prediction model. The eleven tested compounds reduced the growth of S. pseudocostatum in the microplate test in a concentration-dependent manner. The order of toxicity of these chemicals were irgarol>fluoxetine>diuron>benzo(a)pyrene>thioguanine>triclosan>propranolol>benzophenone 3>cetrimonium bromide>4-tert-octylphenol>endosulfan. Several binary mixtures and a mixture of eight compounds from the four different compound groups were tested. All tested mixtures were additive as model deviation ratios, the deviation between experimental and predicted effect concentrations, were within a factor of 2 from one or both prediction models (e.g. CA and IA). Interestingly, a concentration dependent shift from IA to CA, potentially due to activation of similar toxicity pathways at higher concentrations, was observed for the mixture of eight compounds. The combined effects of the multi-compound mixture were clearly additive and it should therefore be expected that PPCPs, biocides, PAHs and alkylphenols will collectively contribute to the risk in areas contaminated by such complex mixtures. Copyright © 2014 Elsevier B.V. All rights reserved.

Molecular docking and dynamics simulation analyses unraveling the differential enzymatic catalysis by plant and fungal laccases with respect to lignin biosynthesis and degradation.

PubMed

Awasthi, Manika; Jaiswal, Nivedita; Singh, Swati; Pandey, Veda P; Dwivedi, Upendra N

2015-09-01

Laccase, widely distributed in bacteria, fungi, and plants, catalyzes the oxidation of wide range of compounds. With regards to one of the important physiological functions, plant laccases are considered to catalyze lignin biosynthesis while fungal laccases are considered for lignin degradation. The present study was undertaken to explain this dual function of laccases using in-silico molecular docking and dynamics simulation approaches. Modeling and superimposition analyses of one each representative of plant and fungal laccases, namely, Populus trichocarpa and Trametes versicolor, respectively, revealed low level of similarity in the folding of two laccases at 3D levels. Docking analyses revealed significantly higher binding efficiency for lignin model compounds, in proportion to their size, for fungal laccase as compared to that of plant laccase. Residues interacting with the model compounds at the respective enzyme active sites were found to be in conformity with their role in lignin biosynthesis and degradation. Molecular dynamics simulation analyses for the stability of docked complexes of plant and fungal laccases with lignin model compounds revealed that tetrameric lignin model compound remains attached to the active site of fungal laccase throughout the simulation period, while it protrudes outwards from the active site of plant laccase. Stability of these complexes was further analyzed on the basis of binding energy which revealed significantly higher stability of fungal laccase with tetrameric compound than that of plant. The overall data suggested a situation favorable for the degradation of lignin polymer by fungal laccase while its synthesis by plant laccase.

Transformations of Model Organic Compounds on Snow Grains at Summit, Greenland

NASA Astrophysics Data System (ADS)

Galbavy, E. S.; Ram, K.; Anastasio, C.

2005-12-01

Photochemical reactions in snowpacks produce a number of chemicals species that can significantly impact the overlying atmosphere and transform many organic pollutants. During this past summer's field season at Summit we examined the kinetics for the disappearance of a suite of model organic compounds in surface snowpack. Our compounds (2-nitrobenzaldehyde, sodium benzoate, syringol, 4-chlorophenol, 2-oxo-butanoic acid, and phenanthrene) were chosen because they represent markers from several different emission sources and because they have a range of expected fates, i.e., their lifetimes will be determined by different processes. These processes include direct photolysis and reactions with oxidants such as hydroxyl radical (OH) and singlet molecular oxygen (1O2*) In addition to measuring the rates of loss of the model organics, we also measured concentrations of OH and 1O2* in the snow samples, as well as rates of direct photolysis of the organics in frozen, purified water. Our goal was to compare the measured lifetimes of the organic compounds with calculated lifetimes based on reactions with OH and 1O2* and direct photolysis. While certain compounds behaved as expected, others decayed more slowly, or more rapidly, than expected, indicating that other, unidentified, snow grain reactions and/or mechanisms are significant. The rates of organic compound loss, the potential reasons for the observed differences, and the implications for lifetimes of trace organic pollutants in polar regions will be discussed.

Selection of representative emerging micropollutants for drinking water treatment studies: a systematic approach.

PubMed

Jin, Xiaohui; Peldszus, Sigrid

2012-01-01

Micropollutants remain of concern in drinking water, and there is a broad interest in the ability of different treatment processes to remove these compounds. To gain a better understanding of treatment effectiveness for structurally diverse compounds and to be cost effective, it is necessary to select a small set of representative micropollutants for experimental studies. Unlike other approaches to-date, in this research micropollutants were systematically selected based solely on their physico-chemical and structural properties that are important in individual water treatment processes. This was accomplished by linking underlying principles of treatment processes such as coagulation/flocculation, oxidation, activated carbon adsorption, and membrane filtration to compound characteristics and corresponding molecular descriptors. A systematic statistical approach not commonly used in water treatment was then applied to a compound pool of 182 micropollutants (identified from the literature) and their relevant calculated molecular descriptors. Principal component analysis (PCA) was used to summarize the information residing in this large dataset. D-optimal onion design was then applied to the PCA results to select structurally representative compounds that could be used in experimental treatment studies. To demonstrate the applicability and flexibility of this selection approach, two sets of 22 representative micropollutants are presented. Compounds in the first set are representative when studying a range of water treatment processes (coagulation/flocculation, oxidation, activated carbon adsorption, and membrane filtration), whereas the second set shows representative compounds for ozonation and advanced oxidation studies. Overall, selected micropollutants in both lists are structurally diverse, have wide-ranging physico-chemical properties and cover a large spectrum of applications. The systematic compound selection approach presented here can also be adjusted to fit individual research needs with respect to type of micropollutants, treatment processes and number of compounds selected. Copyright © 2011 Elsevier B.V. All rights reserved.

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium tuberculosis Drug Discovery

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Hobrath, Judith V.; White, E. Lucile; Reynolds, Robert C

2013-01-01

Purpose Tuberculosis treatments need to be shorter and overcome drug resistance. Our previous large scale phenotypic high-throughput screening against Mycobacterium tuberculosis (Mtb) has identified 737 active compounds and thousands that are inactive. We have used this data for building computational models as an approach to minimize the number of compounds tested. Methods A cheminformatics clustering approach followed by Bayesian machine learning models (based on publicly available Mtb screening data) was used to illustrate that application of these models for screening set selections can enrich the hit rate. Results In order to explore chemical diversity around active cluster scaffolds of the dose-response hits obtained from our previous Mtb screens a set of 1924 commercially available molecules have been selected and evaluated for antitubercular activity and cytotoxicity using Vero, THP-1 and HepG2 cell lines with 4.3%, 4.2% and 2.7% hit rates, respectively. We demonstrate that models incorporating antitubercular and cytotoxicity data in Vero cells can significantly enrich the selection of non-toxic actives compared to random selection. Across all cell lines, the Molecular Libraries Small Molecule Repository (MLSMR) and cytotoxicity model identified ~10% of the hits in the top 1% screened (>10 fold enrichment). We also showed that seven out of nine Mtb active compounds from different academic published studies and eight out of eleven Mtb active compounds from a pharmaceutical screen (GSK) would have been identified by these Bayesian models. Conclusion Combining clustering and Bayesian models represents a useful strategy for compound prioritization and hit-to lead optimization of antitubercular agents. PMID:24132686

Thermoelectric transport in Cu7PSe6 with high copper ionic mobility.

PubMed

Weldert, Kai S; Zeier, Wolfgang G; Day, Tristan W; Panthöfer, Martin; Snyder, G Jeffrey; Tremel, Wolfgang

2014-08-27

Building on the good thermoelectric performances of binary superionic compounds like Cu2Se, Ag2Se and Cu2S, a better and more detailed understanding of phonon-liquid electron-crystal (PLEC) thermoelectric materials is desirable. In this work we present the thermoelectric transport properties of the compound Cu7PSe6 as the first representative of the class of argyrodite-type ion conducting thermoelectrics. With a huge variety of possible compositions and high ionic conductivity even at room temperature, the argyrodites represent a very good model system to study structure-property relationships for PLEC thermoelectric materials. We particularly highlight the extraordinary low thermal conductivity of Cu7PSe6 below the glass limit, which can be associated with the molten copper sublattice leading to a softening of phonon modes.

DEVELOPMENT AND VALIDATION OF AN AIR-TO-BEEF ...

EPA Pesticide Factsheets

A model for predicting concentrations of dioxin-like compounds in beef is developed and tested. The key premise of the model is that concentrations of these compounds in air are the source term, or starting point, for estimating beef concentrations. Vapor-phase concentrations transfer to vegetations cattle consume, and particle-bound concentrations deposit onto soils and these vegetations as well. Congener-specific bioconcentration parameters, coupled with assumptions on cattle diet, transform soil and vegetative concentrations into beef fat concentrations. The premise of the validation exercise is that a profile of typical air concentrations of dioxin-like compounds in a United States rural environment is an appropriate observed independent data set, and that a representative profile of United States beef concentrations of dioxin-like compounds is an appropriate observed dependent result. These data were developed for the validation exercise. An observed concentration of dioxin toxic equivalents in whole beef of 0.48 ng/kg is compared with a predicted 0.36 ng/kg. Principal uncertainties in the approach are identified and discussed. A major finding of this exercise was that vapor phase transfers of dioxin-like compounds to vegetations that cattle consume dominate the estimation of final beef concentrations: over 80% of the modeled beef concentration was attributed to such transfers. journal article

Advanced Characterization of Semivolatile Organic Compounds Emitted from Biomass Burning

NASA Astrophysics Data System (ADS)

Hatch, L. E.; Liu, Y.; Rivas-Ubach, A.; Shaw, J. B.; Lipton, M. S.; Barsanti, K. C.

2016-12-01

Biomass burning (BB) emits large amounts of non-methane organic gases (NMOGs) and primary (directly emitted) particulate matter (PM). NMOGs also react in plume to form secondary PM (i.e., SOA) and ozone. BB-PM has been difficult to represent accurately in models used for chemistry and climate predictions, including for air quality and fire management purposes. Much recent research supports that many previously unconsidered SOA precursors exist, including oxidation of semivolatile compounds (SVOCs). Although many recent studies have characterized relatively volatile BB-derived NMOGs and relatively non-volatile particle-phase organic species, comparatively few studies have performed detailed characterization of SVOCs emitted from BB. Here we present efforts to expand the volatility and compositional ranges of compounds measured in BB smoke. In this work, samples of SVOCs in gas and particle phases were collected from 18 fires representing a range of fuel types during the 2016 FIREX fire laboratory campaign; samples were analyzed by two-dimensional gas chromatography with time-of-flight mass spectrometry (GCxGC-TOFMS) and Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS). Hundreds of compounds were detectable in both gas and particle phases by GCxGC-TOFMS whereas thousands of peaks were present in the FTICR mass spectra. Data from both approaches highlight that chemical fingerprints of smoke are fuel/burn-dependent. These efforts support our continued research in building the understanding and model representation of BB emissions and BB-derived SOA.

Advanced Characterization of Semivolatile Organic Compounds Emitted from Biomass Burning

NASA Astrophysics Data System (ADS)

Hatch, L. E.; Liu, Y.; Rivas-Ubach, A.; Shaw, J. B.; Lipton, M. S.; Barsanti, K. C.

2017-12-01

Biomass burning (BB) emits large amounts of non-methane organic gases (NMOGs) and primary (directly emitted) particulate matter (PM). NMOGs also react in plume to form secondary PM (i.e., SOA) and ozone. BB-PM has been difficult to represent accurately in models used for chemistry and climate predictions, including for air quality and fire management purposes. Much recent research supports that many previously unconsidered SOA precursors exist, including oxidation of semivolatile compounds (SVOCs). Although many recent studies have characterized relatively volatile BB-derived NMOGs and relatively non-volatile particle-phase organic species, comparatively few studies have performed detailed characterization of SVOCs emitted from BB. Here we present efforts to expand the volatility and compositional ranges of compounds measured in BB smoke. In this work, samples of SVOCs in gas and particle phases were collected from 18 fires representing a range of fuel types during the 2016 FIREX fire laboratory campaign; samples were analyzed by two-dimensional gas chromatography with time-of-flight mass spectrometry (GCxGC-TOFMS) and Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS). Hundreds of compounds were detectable in both gas and particle phases by GCxGC-TOFMS whereas thousands of peaks were present in the FTICR mass spectra. Data from both approaches highlight that chemical fingerprints of smoke are fuel/burn-dependent. These efforts support our continued research in building the understanding and model representation of BB emissions and BB-derived SOA.

Antimicrobial activity of N-alkoxycarbonylmethyl-N-alkyl-piperidinium chlorides.

PubMed

Woźniak, Edyta; Mozrzymas, Anna; Czarny, Anna; Kocieba, Maja; Rózycka-Roszak, Bozenna; Dega-Szafran, Zofia; Dulewicz, Ewa; Petryna, Magdalena

2004-01-01

The aim of the study was to assay antibacterial and antifungal activity of newly synthesised N-alkoxycarbonylmethyl-N-alkyl-piperidinium chlorides. The compounds tested were found to inhibit the growth of some Gram-negative bacteria, Gram-positive strains and some representatives of yeast-type Candida. From microbiological experiments two of the compounds tested, N-dodecyloxycarbonylmethyl-N-methyl-piperidinium chloride (3) and N-dodecyl-N-ethoxycarbonylmethyl-piperidinium chloride (6), emerged as more active than the other compounds. Since the resistance of biofilms to biocides should be noted during the design and testing of new antimicrobial agents therefore, we have analysed antibacterial properties of the most active compounds towards biofilms. Our study focused on strains of Pseudomonas aeruginosa and Staphylococcus aureus that served as main model organisms for the biofilm studies.

FINDING A COMMON DATA REPRESENTATION AND INTERCHANGE APPROACH FOR MULTIMEDIA MODELS

EPA Science Inventory

Within many disciplines, multiple approaches are used to represent and access very similar data (e.g., a time series of values), often due to the lack of commonly accepted standards. When projects must use data from multiple disciplines, the problems quickly compound. Often sig...

New Class of Antitrypanosomal Agents Based on Imidazopyridines.

PubMed

Silva, Daniel G; Gillespie, J Robert; Ranade, Ranae M; Herbst, Zackary M; Nguyen, Uyen T T; Buckner, Frederick S; Montanari, Carlos A; Gelb, Michael H

2017-07-13

The present work describes the synthesis of 22 new imidazopyridine analogues arising from medicinal chemistry optimization at different sites on the molecule. Seven and 12 compounds exhibited an in vitro EC 50 ≤ 1 μM against Trypanosoma cruzi ( T. cruzi ) and Trypanosoma brucei ( T. brucei ) parasites, respectively. Based on promising results of in vitro activity (EC 50 < 100 nM), cytotoxicity, metabolic stability, protein binding, and pharmacokinetics (PK) properties, compound 20 was selected as a candidate for in vivo efficacy studies. This compound was screened in an acute mouse model against T.cruzi ( Tulahuen strain). After established infection, mice were dosed twice a day for 5 days, and then monitored for 6 weeks using an in vivo imaging system (IVIS). Compound 20 demonstrated parasite inhibition comparable to the benznidazole treatment group. Compound 20 represents a potential lead for the development of drugs to treat trypanosomiasis.

Tool compounds robustly increase turnover of an artificial substrate by glucocerebrosidase in human brain lysates.

PubMed

Berger, Zdenek; Perkins, Sarah; Ambroise, Claude; Oborski, Christine; Calabrese, Matthew; Noell, Stephen; Riddell, David; Hirst, Warren D

2015-01-01

Mutations in glucocerebrosidase (GBA1) cause Gaucher disease and also represent a common risk factor for Parkinson's disease and Dementia with Lewy bodies. Recently, new tool molecules were described which can increase turnover of an artificial substrate 4MUG when incubated with mutant N370S GBA1 from human spleen. Here we show that these compounds exert a similar effect on the wild-type enzyme in a cell-free system. In addition, these tool compounds robustly increase turnover of 4MUG by GBA1 derived from human cortex, despite substantially lower glycosylation of GBA1 in human brain, suggesting that the degree of glycosylation is not important for compound binding. Surprisingly, these tool compounds failed to robustly alter GBA1 turnover of 4MUG in the mouse brain homogenate. Our data raise the possibility that in vivo models with humanized glucocerebrosidase may be needed for efficacy assessments of such small molecules.

Study of the therapeutic benefit of cationic copolymer administration to vascular endothelium under mechanical stress

PubMed Central

Giantsos-Adams, Kristina; Lopez-Quintero, Veronica; Kopeckova, Pavla; Kopecek, Jindrich; Tarbell, John M.; Dull, Randal

2015-01-01

Pulmonary edema and the associated increases in vascular permeability continue to represent a significant clinical problem in the intensive care setting, with no current treatment modality other than supportive care and mechanical ventilation. Therapeutic compound(s) capable of attenuating changes in vascular barrier function would represent a significant advance in critical care medicine. We have previously reported the development of HPMA-based copolymers, targeted to endothelial glycocalyx that are able to enhance barrier function. In this work, we report the refinement of copolymer design and extend our physiological studies todemonstrate that the polymers: 1) reduce both shear stress and pressure-mediated increase in hydraulic conductivity, 2) reduce nitric oxide production in response to elevated hydrostatic pressure and, 3) reduce the capillary filtration coefficient (Kfc) in an isolated perfused mouse lung model. These copolymers represent an important tool for use in mechanotransduction research and a novel strategy for developing clinically useful copolymers for the treatment of vascular permeability. PMID:20932573

Quantitative structure-retention relationships for gas chromatographic retention indices of alkylbenzenes with molecular graph descriptors.

PubMed

Ivanciuc, O; Ivanciuc, T; Klein, D J; Seitz, W A; Balaban, A T

2001-02-01

Quantitative structure-retention relationships (QSRR) represent statistical models that quantify the connection between the molecular structure and the chromatographic retention indices of organic compounds, allowing the prediction of retention indices of novel, not yet synthesized compounds, solely from their structural descriptors. Using multiple linear regression, QSRR models for the gas chromatographic Kováts retention indices of 129 alkylbenzenes are generated using molecular graph descriptors. The correlational ability of structural descriptors computed from 10 molecular matrices is investigated, showing that the novel reciprocal matrices give numerical indices with improved correlational ability. A QSRR equation with 5 graph descriptors gives the best calibration and prediction results, demonstrating the usefulness of the molecular graph descriptors in modeling chromatographic retention parameters. The sequential orthogonalization of descriptors suggests simpler QSRR models by eliminating redundant structural information.

At the biological modeling and simulation frontier.

PubMed

Hunt, C Anthony; Ropella, Glen E P; Lam, Tai Ning; Tang, Jonathan; Kim, Sean H J; Engelberg, Jesse A; Sheikh-Bahaei, Shahab

2009-11-01

We provide a rationale for and describe examples of synthetic modeling and simulation (M&S) of biological systems. We explain how synthetic methods are distinct from familiar inductive methods. Synthetic M&S is a means to better understand the mechanisms that generate normal and disease-related phenomena observed in research, and how compounds of interest interact with them to alter phenomena. An objective is to build better, working hypotheses of plausible mechanisms. A synthetic model is an extant hypothesis: execution produces an observable mechanism and phenomena. Mobile objects representing compounds carry information enabling components to distinguish between them and react accordingly when different compounds are studied simultaneously. We argue that the familiar inductive approaches contribute to the general inefficiencies being experienced by pharmaceutical R&D, and that use of synthetic approaches accelerates and improves R&D decision-making and thus the drug development process. A reason is that synthetic models encourage and facilitate abductive scientific reasoning, a primary means of knowledge creation and creative cognition. When synthetic models are executed, we observe different aspects of knowledge in action from different perspectives. These models can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete while moving us closer to personalized medicine.

Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling

PubMed Central

Kumar, Raj; Son, Minky; Bavi, Rohit; Lee, Yuno; Park, Chanin; Arulalapperumal, Venkatesh; Cao, Guang Ping; Kim, Hyong-ha; Suh, Jung-keun; Kim, Yong-seong; Kwon, Yong Jung; Lee, Keun Woo

2015-01-01

Aim: Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches. Methods: The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations. Results: The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer's randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10. Conclusion: Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors. PMID:26051108

Drosophila melanogaster as a model system for the evaluation of anti-aging compounds.

PubMed

Jafari, Mahtab

2010-01-01

Understanding the causes of aging is a complex problem due to the multiple factors that influence aging, which include genetics, environment, metabolism and reproduction, among others. These multiple factors create logistical difficulties in the evaluation of anti-aging agents. There is a need for good model systems to evaluate potential anti-aging compounds. The model systems used should represent the complexities of aging in humans, so that the findings may be extrapolated to human studies, but they should also present an opportunity to minimize the variables so that the experimental results can be accurately interpreted. In addition to positively affecting lifespan, the impact of the compound on the physiologic confounders of aging, including fecundity and the health span--the period of life where an organism is generally healthy and free from serious or chronic illness--of the model organism needs to be evaluated. Fecundity is considered a major confounder of aging in fruit flies. It is well established that female flies that are exposed to toxic substances typically reduce their dietary intake and their reproductive output and display an artifactual lifespan extension. As a result, drugs that achieve longevity benefits by reducing fecundity as a result of diminished food intake are probably not useful candidates for eventual treatment of aging in humans and should be eliminated during the screening process. Drosophila melanogaster provides a suitable model system for the screening of anti-aging compounds as D. melanogaster and humans have many conserved physiological and biological pathways. In this paper, I propose an algorithm to screen anti-aging compounds using Drosophila melanogaster as a model system.

Porcine sclera as a model of human sclera for in vitro transport experiments: histology, SEM, and comparative permeability

PubMed Central

Ferrari, G.; Quarta, M.; Macaluso, C.; Govoni, P.; Dallatana, D.; Santi, P.

2009-01-01

Purpose To evaluate porcine sclera as a model of human sclera for in vitro studies of transscleral drug delivery of both low and high molecular weight compounds. Methods Human and porcine scleras were characterized for thickness and water content. The tissue surface was examined by scanning electron microscopy (SEM), and the histology was studied with hematoxylin-eosin staining. Comparative permeation experiments were performed using three model molecules, acetaminophen as the model compound for small molecules; a linear dextran with a molecular weight of 120 kDa as the model compound for high molecular weight drugs; and insulin, which was chosen as the model protein. Permeation parameters such as flux, lag time, and permeability coefficient were determined and compared. Results Human and porcine scleras have a similar histology and collagen bundle organization. The water content is approx 70% for both tissues while a statistically significant difference was found for the thickness, porcine sclera being approximately twofold thicker than human sclera. Differences in thickness produced differences in the permeability coefficient. In fact, human sclera was found to be two to threefold more permeable toward the three molecules studied than porcine sclera. Conclusions The results obtained in the present paper prove that porcine sclera can be considered a good model for human sclera for in vitro permeation experiments of both low and high molecular weight compounds. In fact, if the different tissue thickness is taken into account, comparable permeability was demonstrated. This suggests a possible use of this model in the evaluation of the transscleral permeation of new biotech compounds, which currently represent the most innovative and efficient therapeutic options for the treatment of ocular diseases. PMID:19190734

Porcine sclera as a model of human sclera for in vitro transport experiments: histology, SEM, and comparative permeability.

PubMed

Nicoli, S; Ferrari, G; Quarta, M; Macaluso, C; Govoni, P; Dallatana, D; Santi, P

2009-01-01

To evaluate porcine sclera as a model of human sclera for in vitro studies of transscleral drug delivery of both low and high molecular weight compounds. Human and porcine scleras were characterized for thickness and water content. The tissue surface was examined by scanning electron microscopy (SEM), and the histology was studied with hematoxylin-eosin staining. Comparative permeation experiments were performed using three model molecules, acetaminophen as the model compound for small molecules; a linear dextran with a molecular weight of 120 kDa as the model compound for high molecular weight drugs; and insulin, which was chosen as the model protein. Permeation parameters such as flux, lag time, and permeability coefficient were determined and compared. Human and porcine scleras have a similar histology and collagen bundle organization. The water content is approx 70% for both tissues while a statistically significant difference was found for the thickness, porcine sclera being approximately twofold thicker than human sclera. Differences in thickness produced differences in the permeability coefficient. In fact, human sclera was found to be two to threefold more permeable toward the three molecules studied than porcine sclera. The results obtained in the present paper prove that porcine sclera can be considered a good model for human sclera for in vitro permeation experiments of both low and high molecular weight compounds. In fact, if the different tissue thickness is taken into account, comparable permeability was demonstrated. This suggests a possible use of this model in the evaluation of the transscleral permeation of new biotech compounds, which currently represent the most innovative and efficient therapeutic options for the treatment of ocular diseases.

FY12 ARRA-NRAP Report – Studies to Support Risk Assessment of Geologic Carbon Sequestration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cantrell, Kirk J.; Shao, Hongbo; Thompson, C. J.

2011-09-27

This report summarizes results of research conducted during FY2012 to support the assessment of environmental risks associated with geologic carbon dioxide (CO2) sequestration and storage. Several research focus areas are ongoing as part of this project. This includes the quantification of the leachability of metals and organic compounds from representative CO2 storage reservoir and caprock materials, the fate of metals and organic compounds after release, and the development of a method to measure pH in situ under supercritical CO2 (scCO2) conditions. Metal leachability experiments were completed on 6 different rock samples in brine in equilibrium with scCO2 at representative geologicmore » reservoir conditions. In general, the leaching of RCRA metals and other metals of concern was found to be limited and not likely to be a significant issue (at least, for the rocks tested). Metals leaching experiments were also completed on 1 rock sample with scCO2 containing oxygen at concentrations of 0, 1, 5, and 10% to simulate injection of CO2 originating from the oxy-fuel combustion process. Significant differences in the leaching behavior of certain metals were observed when oxygen is present in the CO2. These differences resulted from oxidation of sulfides, release of sulfate, ferric iron and other metals, and subsequent precipitation of iron oxides and some sulfates such as barite. Experiments to evaluate the potential for mobilization of organic compounds from representative reservoir materials and cap rock and their fate in porous media (quartz sand) have been conducted. Results with Fruitland coal and Gothic shale indicate that lighter organic compounds were more susceptible to mobilization by scCO2 compared to heavier compounds. Alkanes demonstrated very low extractability by scCO2. No significant differences were observed between the extractability of organic compounds by dry or water saturated scCO2. Reaction equilibrium appears to have been reached by 96 hours. When the scCO2 was released from the reactor, less than 60% of the injected lighter compounds (benzene, toluene) were transported through dry sand column by the CO2, while more than 90% of the heavier organics were trapped in the sand column. For wet sand columns, most (80% to 100%) of the organic compounds injected into the sand column passed through, except for naphthalene which was substantial removed from the CO2 within the column. A spectrophotometric method was developed to measure pH in brines in contact with scCO2. This method provides an alternative to fragile glass pH electrodes and thermodynamic modeling approaches for estimating pH. The method was tested in simulated reservoir fluids (CO2–NaCl–H2O) at different temperatures, pressures, and ionic strength, and the results were compared with other experimental studies and geochemical models. Measured pH values were generally in agreement with the models, but inconsistencies were present between some of the models.« less

Effect of climate-driven changes in species composition on regional emission capacities of biogenic compounds

NASA Astrophysics Data System (ADS)

Schurgers, G.; Arneth, A.; Hickler, T.

2011-11-01

Regional or global modeling studies of dynamic vegetation often represent vegetation by large functional units (plant functional types (PFTs)). For simulation of biogenic volatile organic compounds (BVOC) in these models, emission capacities, which give the emission under standardized conditions, are provided as an average value for a PFT. These emission capacities thus hide the known heterogeneity in emission characteristics that are not straightforwardly related to functional characteristics of plants. Here we study the effects of the aggregation of species-level information on emission characteristics at PFT level. The roles of temporal and spatial variability are assessed for Europe by comparing simulations that represent vegetation by dominant tree species on the one hand and by plant functional types on the other. We compare a number of time slices between the Last Glacial Maximum (21,000 years ago) and the present day to quantify the effects of dynamically changing vegetation on BVOC emissions. Spatial heterogeneity of emission factors is studied with present-day simulations. We show that isoprene and monoterpene emissions are of similar magnitude in Europe when the simulation represents dominant European tree species, which indicates that simulations applying typical global-scale emission capacities for PFTs tend to overestimate isoprene and underestimate monoterpene emissions. Moreover, both spatial and temporal variability affect emission capacities considerably, and by aggregating these to PFT level averages, one loses the information on local heterogeneity. Given the reactive nature of these compounds, accounting for spatial and temporal heterogeneity can be important for studies of their fate in the atmosphere.

A Screening Assay Based on Host-Pathogen Interaction Models Identifies a Set of Novel Antifungal Benzimidazole Derivatives▿

PubMed Central

Burger-Kentischer, Anke; Finkelmeier, Doris; Keller, Petra; Bauer, Jörg; Eickhoff, Holger; Kleymann, Gerald; Abu Rayyan, Walid; Singh, Anurag; Schröppel, Klaus; Lemuth, Karin; Wiesmüller, Karl-Heinz; Rupp, Steffen

2011-01-01

Fungal infections are a serious health problem in clinics, especially in the immune-compromised patient. Disease ranges from widespread superficial infections like vulvovaginal infections to life-threatening systemic candidiasis. Especially for systemic mycoses, only a limited arsenal of antifungals is available. The most commonly used classes of antifungal compounds used include azoles, polyenes, and echinocandins. Due to emerging resistance to standard therapy, significant side effects, and high costs for several antifungals, there is a medical need for new antifungals in the clinic and general practice. In order to expand the arsenal of compounds with antifungal activities, we screened a compound library including more than 35,000 individual compounds derived from organic synthesis as well as combinatorial compound collections representing mixtures of compounds for antimycotic activity. In total, more than 100,000 compounds were screened using a new type of activity-selectivity assay, analyzing both the antifungal activity and the compatibility with human cells at the same time. One promising hit, an (S)-2-aminoalkyl benzimidazole derivative, was developed among a series of lead compounds showing potent antifungal activity. (S)-2-(1-Aminoisobutyl)-1-(3-chlorobenzyl) benzimidazole showed the highest antifungal activity and the best compatibility with human cells in several cell culture models and against a number of clinical isolates of several species of pathogenic Candida yeasts. Transcriptional profiling indicates that the newly discovered compound is a potential inhibitor of the ergosterol pathway, in contrast to other benzimidazole derivatives, which target microtubules. PMID:21746957

A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.

PubMed

Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei

2017-12-21

In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.

Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors.

PubMed

Xue, Xin; Wei, Jin-Lian; Xu, Li-Li; Xi, Mei-Yang; Xu, Xiao-Li; Liu, Fang; Guo, Xiao-Ke; Wang, Lei; Zhang, Xiao-Jin; Zhang, Ming-Ye; Lu, Meng-Chen; Sun, Hao-Peng; You, Qi-Dong

2013-10-28

Protein-protein interactions (PPIs) play a crucial role in cellular function and form the backbone of almost all biochemical processes. In recent years, protein-protein interaction inhibitors (PPIIs) have represented a treasure trove of potential new drug targets. Unfortunately, there are few successful drugs of PPIIs on the market. Structure-based pharmacophore (SBP) combined with docking has been demonstrated as a useful Virtual Screening (VS) strategy in drug development projects. However, the combination of target complexity and poor binding affinity prediction has thwarted the application of this strategy in the discovery of PPIIs. Here we report an effective VS strategy on p53-MDM2 PPI. First, we built a SBP model based on p53-MDM2 complex cocrystal structures. The model was then simplified by using a Receptor-Ligand complex-based pharmacophore model considering the critical binding features between MDM2 and its small molecular inhibitors. Cascade docking was subsequently applied to improve the hit rate. Based on this strategy, we performed VS on NCI and SPECS databases and successfully discovered 6 novel compounds from 15 hits with the best, compound 1 (NSC 5359), K(i) = 180 ± 50 nM. These compounds can serve as lead compounds for further optimization.

Ecosystem-scale VOC fluxes during an extreme drought in a broad-leaf temperate forest of the Missouri Ozarks (central USA)

EPA Science Inventory

Considerable amounts and varieties of biogenic volatile organic compounds (BVOCs) are exchanged between vegetation and the surrounding air. These BVOCs play key ecological and atmospheric roles that must be adequately represented for accurately modeling the coupled biosphere-atmo...

Representing high throughput expression profiles via perturbation barcodes reveals compound targets.

PubMed

Filzen, Tracey M; Kutchukian, Peter S; Hermes, Jeffrey D; Li, Jing; Tudor, Matthew

2017-02-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

Furan-based benzene mono- and dicarboxylic acid derivatives as multiple inhibitors of the bacterial Mur ligases (MurC-MurF): experimental and computational characterization.

PubMed

Perdih, Andrej; Hrast, Martina; Pureber, Kaja; Barreteau, Hélène; Grdadolnik, Simona Golič; Kocjan, Darko; Gobec, Stanislav; Solmajer, Tom; Wolber, Gerhard

2015-06-01

Bacterial resistance to the available antibiotic agents underlines an urgent need for the discovery of novel antibacterial agents. Members of the bacterial Mur ligase family MurC-MurF involved in the intracellular stages of the bacterial peptidoglycan biosynthesis have recently emerged as a collection of attractive targets for novel antibacterial drug design. In this study, we have first extended the knowledge of the class of furan-based benzene-1,3-dicarboxylic acid derivatives by first showing a multiple MurC-MurF ligase inhibition for representatives of the extended series of this class. Steady-state kinetics studies on the MurD enzyme were performed for compound 1, suggesting a competitive inhibition with respect to ATP. To the best of our knowledge, compound 1 represents the first ATP-competitive MurD inhibitor reported to date with concurrent multiple inhibition of all four Mur ligases (MurC-MurF). Subsequent molecular dynamic (MD) simulations coupled with interaction energy calculations were performed for two alternative in silico models of compound 1 in the UMA/D-Glu- and ATP-binding sites of MurD, identifying binding in the ATP-binding site as energetically more favorable in comparison to the UMA/D-Glu-binding site, which was in agreement with steady-state kinetic data. In the final stage, based on the obtained MD data novel furan-based benzene monocarboxylic acid derivatives 8-11, exhibiting multiple Mur ligase (MurC-MurF) inhibition with predominantly superior ligase inhibition over the original series, were discovered and for compound 10 it was shown to possess promising antibacterial activity against S. aureus. These compounds represent novel leads that could by further optimization pave the way to novel antibacterial agents.

Furan-based benzene mono- and dicarboxylic acid derivatives as multiple inhibitors of the bacterial Mur ligases (MurC-MurF): experimental and computational characterization

NASA Astrophysics Data System (ADS)

Perdih, Andrej; Hrast, Martina; Pureber, Kaja; Barreteau, Hélène; Grdadolnik, Simona Golič; Kocjan, Darko; Gobec, Stanislav; Solmajer, Tom; Wolber, Gerhard

2015-06-01

Bacterial resistance to the available antibiotic agents underlines an urgent need for the discovery of novel antibacterial agents. Members of the bacterial Mur ligase family MurC-MurF involved in the intracellular stages of the bacterial peptidoglycan biosynthesis have recently emerged as a collection of attractive targets for novel antibacterial drug design. In this study, we have first extended the knowledge of the class of furan-based benzene-1,3-dicarboxylic acid derivatives by first showing a multiple MurC-MurF ligase inhibition for representatives of the extended series of this class. Steady-state kinetics studies on the MurD enzyme were performed for compound 1, suggesting a competitive inhibition with respect to ATP. To the best of our knowledge, compound 1 represents the first ATP-competitive MurD inhibitor reported to date with concurrent multiple inhibition of all four Mur ligases (MurC-MurF). Subsequent molecular dynamic (MD) simulations coupled with interaction energy calculations were performed for two alternative in silico models of compound 1 in the UMA/ d-Glu- and ATP-binding sites of MurD, identifying binding in the ATP-binding site as energetically more favorable in comparison to the UMA/ d-Glu-binding site, which was in agreement with steady-state kinetic data. In the final stage, based on the obtained MD data novel furan-based benzene monocarboxylic acid derivatives 8- 11, exhibiting multiple Mur ligase (MurC-MurF) inhibition with predominantly superior ligase inhibition over the original series, were discovered and for compound 10 it was shown to possess promising antibacterial activity against S. aureus. These compounds represent novel leads that could by further optimization pave the way to novel antibacterial agents.

A strategy to improve the identification reliability of the chemical constituents by high-resolution mass spectrometry-based isomer structure prediction combined with a quantitative structure retention relationship analysis: Phthalide compounds in Chuanxiong as a test case.

PubMed

Zhang, Qingqing; Huo, Mengqi; Zhang, Yanling; Qiao, Yanjiang; Gao, Xiaoyan

2018-06-01

High-resolution mass spectrometry (HRMS) provides a powerful tool for the rapid analysis and identification of compounds in herbs. However, the diversity and large differences in the content of the chemical constituents in herbal medicines, especially isomerisms, are a great challenge for mass spectrometry-based structural identification. In the current study, a new strategy for the structural characterization of potential new phthalide compounds was proposed by isomer structure predictions combined with a quantitative structure-retention relationship (QSRR) analysis using phthalide compounds in Chuanxiong as an example. This strategy consists of three steps. First, the structures of phthalide compounds were reasonably predicted on the basis of the structure features and MS/MS fragmentation patterns: (1) the collected raw HRMS data were preliminarily screened by an in-house database; (2) the MS/MS fragmentation patterns of the analogous compounds were summarized; (3) the reported phthalide compounds were identified, and the structures of the isomers were reasonably predicted. Second, the QSRR model was established and verified using representative phthalide compound standards. Finally, the retention times of the predicted isomers were calculated by the QSRR model, and the structures of these peaks were rationally characterized by matching retention times of the detected chromatographic peaks and the predicted isomers. A multiple linear regression QSRR model in which 6 physicochemical variables were screened was built using 23 phthalide standards. The retention times of the phthalide isomers in Chuanxiong were well predicted by the QSRR model combined with reasonable structure predictions (R 2 =0.955). A total of 81 peaks were detected from Chuanxiong and assigned to reasonable structures, and 26 potential new phthalide compounds were structurally characterized. This strategy can improve the identification efficiency and reliability of homologues in complex materials. Copyright © 2018 Elsevier B.V. All rights reserved.

Protein targets for anticancer gold compounds: mechanistic inferences.

PubMed

Gabbiani, Chiara; Messori, Luigi

2011-12-01

Gold compounds form an interesting class of antiproliferative agents of potential pharmacological use in cancer treatment. Indeed, a number of gold compounds, either gold(III) or gold(I), were recently described and characterised that manifested remarkable cytotoxic properties in vitro against cultured cancer cells; for some of them encouraging in vivo results were also reported toward a few relevant animal models of cancer. The molecular mechanisms through which gold compounds exert their biological effects are still largely unknown and the subject of intense investigations. Recent studies point out that the modes of action of cytotoxic gold compounds are essentially DNA-independent and cisplatin-unrelated, relying -most likely- on gold interactions with a variety of protein targets. Notably, a few cellular proteins playing relevant functional roles were proposed to represent effective targets for cytotoxic gold compounds but these hypotheses need adequate validation. The state of the art of this research area and the perspectives for future studies are herein critically analysed and discussed.

Regional atmospheric emissions determined from measurements at Jeju Island, Korea: Halogenated compounds from China

NASA Astrophysics Data System (ADS)

Kim, Jooil; Li, Shanlan; Kim, Kyung-Ryul; Stohl, Andreas; Mühle, Jens; Kim, Seung-Kyu; Park, Mi-Kyung; Kang, Dong-Jin; Lee, Gangwoong; Harth, Christina M.; Salameh, Peter K.; Weiss, Ray F.

2010-06-01

High-frequency in-situ measurements of a wide range of halogenated compounds including chlorofluorocarbons (CFCs), halons, hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs), perfluorinated compounds (PFCs), sulfur hexafluoride (SF6), and other chlorinated and brominated compounds have been made at Gosan (Jeju Island, Korea). Regional emissions of HCFC-22 (CHClF2) calculated from inverse modeling were combined with interspecies correlation methods to estimate national emissions for China, a major emitter of industrial halogenated gases. Our results confirm the signs of successful phase-out of primary ozone-depleting species such as CFCs, halons and many chlorinated or brominated compounds, along with substantial emissions of replacement HCFCs. Emissions derived for HFCs, PFCs, and SF6 were compared to published estimates and found to be a significant fraction of global totals. Overall, Chinese emissions of the halogenated compounds discussed here represent 19(14-17)% and 20(15-26)% of global emissions when evaluated in terms of their Ozone Depletion Potentials and 100-year Global Warming Potentials, respectively.

New RuII Complex for Dual Activity: Photoinduced Ligand Release and 1O2 Production

PubMed Central

Loftus, Lauren M.; White, Jessica K.; Albani, Bryan A.; Kohler, Lars; Kodanko, Jeremy J.; Thummel, Randolph P.

2016-01-01

The new complex [Ru(pydppn)(biq)(py)]2+ (1) undergoes both py photodissociation in CH3CN with Φ500=0.0070(4) and 1O2 production with ΦΔ=0.75(7) in CH3OH from a long-lived 3ππ* state centered on the pydppn ligand (pydppn=3-(pyrid-2-yl)benzo[i]dipyrido[3,2-a:2′,3′-c]phenazine; biq = 2,2′-biquinoline; py= pyridine). This represents an order of magnitude decrease in the Φ500 compared to the previously reported model compound [Ru(tpy)(biq)(py)]2+ (3) (tpy=2,2′:6′,2″-terpyridine) that undergoes only ligand exchange. The effect on the quantum yields by the addition of a second deactivation pathway through the low-lying 3ππ* state necessary for dual reactivity was investigated using ultrafast and nanosecond transient absorption spectroscopy, revealing a significantly shorter 3MLCT lifetime in 1 relative to that of the model complex 3. Due to the structural similarities between the two compounds, the lower values of Φ500 and ΦΔ compared to that of [Ru(pydppn)(bpy)(py)]2+ (2) (bpy=2,2′-bipyridine) are attributed to a competitive excited state population between the 3LF states involved in ligand dissociation and the long-lived 3ππ* state in 1. Complex 1 represents a model compound for dual activity that may be applied to photochemotherapy. PMID:26715085

QSPR model for bioconcentration factors of nonpolar organic compounds using molecular electronegativity distance vector descriptors.

PubMed

Qin, Li-Tang; Liu, Shu-Shen; Liu, Hai-Ling

2010-02-01

A five-variable model (model M2) was developed for the bioconcentration factors (BCFs) of nonpolar organic compounds (NPOCs) by using molecular electronegativity distance vector (MEDV) to characterize the structures of NPOCs and variable selection and modeling based on prediction (VSMP) to select the optimum descriptors. The estimated correlation coefficient (r (2)) and the leave-one-out cross-validation correlation coefficients (q (2)) of model M2 were 0.9271 and 0.9171, respectively. The model was externally validated by splitting the whole data set into a representative training set of 85 chemicals and a validation set of 29 chemicals. The results show that the main structural factors influencing the BCFs of NPOCs are -cCc, cCcc, -Cl, and -Br (where "-" refers to a single bond and "c" refers to a conjugated bond). The quantitative structure-property relationship (QSPR) model can effectively predict the BCFs of NPOCs, and the predictions of the model can also extend the current BCF database of experimental values.

The Microphysiology Systems Database for Analyzing and Modeling Compound Interactions with Human and Animal Organ Models

PubMed Central

Vernetti, Lawrence; Bergenthal, Luke; Shun, Tong Ying; Taylor, D. Lansing

2016-01-01

Abstract Microfluidic human organ models, microphysiology systems (MPS), are currently being developed as predictive models of drug safety and efficacy in humans. To design and validate MPS as predictive of human safety liabilities requires safety data for a reference set of compounds, combined with in vitro data from the human organ models. To address this need, we have developed an internet database, the MPS database (MPS-Db), as a powerful platform for experimental design, data management, and analysis, and to combine experimental data with reference data, to enable computational modeling. The present study demonstrates the capability of the MPS-Db in early safety testing using a human liver MPS to relate the effects of tolcapone and entacapone in the in vitro model to human in vivo effects. These two compounds were chosen to be evaluated as a representative pair of marketed drugs because they are structurally similar, have the same target, and were found safe or had an acceptable risk in preclinical and clinical trials, yet tolcapone induced unacceptable levels of hepatotoxicity while entacapone was found to be safe. Results demonstrate the utility of the MPS-Db as an essential resource for relating in vitro organ model data to the multiple biochemical, preclinical, and clinical data sources on in vivo drug effects. PMID:28781990

Identification of novel inhibitors of non-replicating Mycobacterium tuberculosis using a carbon starvation model

PubMed Central

Grant, Sarah Schmidt; Kawate, Tomohiko; Nag, Partha P.; Silvis, Melanie R.; Gordon, Katherine; Stanley, Sarah A.; Kazyanskaya, Ed; Nietupski, Ray; Golas, Aaron; Fitzgerald, Michael; Cho, Sanghyun; Franzblau, Scott G.; Hung, Deborah T.

2013-01-01

During Mycobacterium tuberculosis infection, a population of bacteria is thought to exist in a non-replicating state, refractory to antibiotics, which may contribute to the need for prolonged antibiotic therapy. The identification of inhibitors of the non-replicating state provides tools that can be used to probe this hypothesis and the physiology of this state. The development of such inhibitors also has the potential to shorten the duration of antibiotic therapy required. Here we describe the development of a novel non-replicating assay amenable to high-throughput chemical screening coupled with secondary assays that use carbon starvation as the in vitro model. Together these assays identify compounds with activity against replicating and non-replicating M. tuberculosis as well as compounds that inhibit the transition from non-replicating to replicating stages of growth. Using these assays we successfully screened over 300,000 compounds and identified 786 inhibitors of non-replicating M. tuberculosis. In order to understand the relationship among different non-replicating models, we teste 52 of these molecules in a hypoxia model and four different chemical scaffolds in a stochastic persist model and a streptomycin dependent model. We found that compounds display varying levels of activity in different models for the non-replicating state, suggesting important differences in bacterial physiology between models. Therefore, chemical tools identified in this assay may be useful for determining the relevance of different non-replicating in vitro models to in vivo M. tuberculosis infection. Given our current limited understanding, molecules that are active across multiple models may represent more promising candidates for further development. PMID:23898841

Pistachio oil (Pistacia vera L. cv. Uzun): Characterization of key odorants in a representative aromatic extract by GC-MS-olfactometry and phenolic profile by LC-ESI-MS/MS.

PubMed

Sonmezdag, Ahmet Salih; Kelebek, Hasim; Selli, Serkan

2018-02-01

Volatile, aroma-active, and phenolic compounds of pistachio oil obtained from cv. Uzun were investigated in the current study. To obtain a representative aromatic extract, three of the most widely used extraction methods were compared using a representative test; the solvent-assisted flavour extraction (SAFE) aromatic extract from pistachio oil was found to be the most representative. A total of 50 aroma compounds were determined in pistachio oil and it was found that terpenes, aldehydes, and alcohols were the most abundant volatile compounds. Applying GC-MS-olfactometry and aroma extract dilution analysis (AEDA) resulted in a total of 14 aroma-active areas being detected in the extract of pistachio oil. In the phenolic fraction obtained by the LC-ESI-MS/MS method, a total of 12 phenolic compounds was found in the pistachio oil, of which seven compounds were reported for the first time. Eriodictyol-7-O-glucoside and protocatechuic acid were the most dominant phenolic compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Anoxic denitrification of BTEX: Biodegradation kinetics and pollutant interactions.

PubMed

Carvajal, Andrea; Akmirza, Ilker; Navia, Daniel; Pérez, Rebeca; Muñoz, Raúl; Lebrero, Raquel

2018-05-15

Anoxic mineralization of BTEX represents a promising alternative for their abatement from O 2 -deprived emissions. However, the kinetics of anoxic BTEX biodegradation and the interactions underlying the treatment of BTEX mixtures are still unknown. An activated sludge inoculum was used for the anoxic abatement of single, dual and quaternary BTEX mixtures, being acclimated prior performing the biodegradation kinetic tests. The Monod model and a Modified Gompertz model were then used for the estimation of the biodegradation kinetic parameters. Results showed that both toluene and ethylbenzene are readily biodegradable under anoxic conditions, whereas the accumulation of toxic metabolites resulted in partial xylene and benzene degradation when present both as single components or in mixtures. Moreover, the supplementation of an additional pollutant always resulted in an inhibitory competition, with xylene inducing the highest degree of inhibition. The Modified Gompertz model provided an accurate fitting for the experimental data for single and dual substrate experiments, satisfactorily representing the antagonistic pollutant interactions. Finally, microbial analysis suggested that the degradation of the most biodegradable compounds required a lower microbial specialization and diversity, while the presence of the recalcitrant compounds resulted in the selection of a specific group of microorganisms. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm

PubMed Central

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request. PMID:26955638

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm.

PubMed

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request.

Preliminary model and validation of molten carbonate fuel cell kinetics under sulphur poisoning

NASA Astrophysics Data System (ADS)

Audasso, E.; Nam, S.; Arato, E.; Bosio, B.

2017-06-01

MCFC represents an effective technology to deal with CO2 capture and relative applications. If used for these purposes, due to the working conditions and the possible feeding, MCFC must cope with a different number of poisoning gases such as sulphur compounds. In literature, different works deal with the development of kinetic models to describe MCFC performance to help both industrial applications and laboratory simulations. However, in literature attempts to realize a proper model able to consider the effects of poisoning compounds are scarce. The first aim of the present work is to provide a semi-empirical kinetic formulation capable to take into account the effects that sulphur compounds (in particular SO2) have on the MCFC performance. The second aim is to provide a practical example of how to effectively include the poisoning effects in kinetic models to simulate fuel cells performances. To test the reliability of the proposed approach, the obtained formulation is implemented in the kinetic core of the SIMFC (SIMulation of Fuel Cells) code, an MCFC 3D model realized by the Process Engineering Research Team (PERT) of the University of Genova. Validation is performed through data collected at the Korea Institute of Science and Technology in Seoul.

Metastasis: recent discoveries and novel perioperative treatment strategies with particular interest in the hemostatic compound desmopressin.

PubMed

Alonso, D F; Ripoll, G V; Garona, J; Iannucci, N B; Gomez, D E

2011-11-01

Metastatic disease is responsible for most of cancer lethality. A main obstacle for therapy of advanced cancers is that the outcome of metastasis depends on a complex interplay between malignant and host cells. The perioperative period represents an underutilized window of opportunity for cancer treatment where tumor-host interactions can be modulated, reducing the risk of local recurrences and distant metastases. Blood-saving agents are attractive compounds to be administered during tumor surgery. Desmopressin (DDAVP) is a safe and convenient hemostatic peptide with proved antimetastastic properties in experimental models and veterinary clinical trials. The compound seems to induce a dual angiostatic and antimetastatic effect, breaking the cooperative function of cancer cells and endothelial cells during residual tumor progression. DDAVP is therefore an interesting lead compound to develop novel synthetic peptide analogs with enhanced antitumor properties.

Prediction of the effect of formulation on the toxicity of chemicals.

PubMed

Mistry, Pritesh; Neagu, Daniel; Sanchez-Ruiz, Antonio; Trundle, Paul R; Vessey, Jonathan D; Gosling, John Paul

2017-01-01

Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds.

Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

NASA Astrophysics Data System (ADS)

Miller, Shelly L.; Anderson, Melissa J.; Daly, Eileen P.; Milford, Jana B.

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.

Predictions of BuChE inhibitors using support vector machine and naive Bayesian classification techniques in drug discovery.

PubMed

Fang, Jiansong; Yang, Ranyao; Gao, Li; Zhou, Dan; Yang, Shengqian; Liu, Ai-Lin; Du, Guan-hua

2013-11-25

Butyrylcholinesterase (BuChE, EC 3.1.1.8) is an important pharmacological target for Alzheimer's disease (AD) treatment. However, the currently available BuChE inhibitor screening assays are expensive, labor-intensive, and compound-dependent. It is necessary to develop robust in silico methods to predict the activities of BuChE inhibitors for the lead identification. In this investigation, support vector machine (SVM) models and naive Bayesian models were built to discriminate BuChE inhibitors (BuChEIs) from the noninhibitors. Each molecule was initially represented in 1870 structural descriptors (1235 from ADRIANA.Code, 334 from MOE, and 301 from Discovery studio). Correlation analysis and stepwise variable selection method were applied to figure out activity-related descriptors for prediction models. Additionally, structural fingerprint descriptors were added to improve the predictive ability of models, which were measured by cross-validation, a test set validation with 1001 compounds and an external test set validation with 317 diverse chemicals. The best two models gave Matthews correlation coefficient of 0.9551 and 0.9550 for the test set and 0.9132 and 0.9221 for the external test set. To demonstrate the practical applicability of the models in virtual screening, we screened an in-house data set with 3601 compounds, and 30 compounds were selected for further bioactivity assay. The assay results showed that 10 out of 30 compounds exerted significant BuChE inhibitory activities with IC50 values ranging from 0.32 to 22.22 μM, at which three new scaffolds as BuChE inhibitors were identified for the first time. To our best knowledge, this is the first report on BuChE inhibitors using machine learning approaches. The models generated from SVM and naive Bayesian approaches successfully predicted BuChE inhibitors. The study proved the feasibility of a new method for predicting bioactivities of ligands and discovering novel lead compounds.

Structure-based design, synthesis, and biological evaluation of novel pyrrolyl aryl sulfones: HIV-1 non-nucleoside reverse transcriptase inhibitors active at nanomolar concentrations.

PubMed

Artico, M; Silvestri, R; Pagnozzi, E; Bruno, B; Novellino, E; Greco, G; Massa, S; Ettorre, A; Loi, A G; Scintu, F; La Colla, P

2000-05-04

Pyrrolyl aryl sulfones (PASs) have been recently reported as a new class of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) inhibitors acting at the non-nucleoside binding site of this enzyme (Artico, M.; et al. J. Med. Chem. 1996, 39, 522-530). Compound 3, the most potent inhibitor within the series (EC(50) = 0.14 microM, IC(50) = 0.4 microM, and SI > 1429), was then selected as a lead compound for a synthetic project based on molecular modeling studies. Using the three-dimensional structure of RT cocrystallized with the alpha-APA derivative R95845, we derived a model of the RT/3 complex by taking into account previously developed structure-activity relationships. Inspection of this model and docking calculations on virtual compounds prompted the design of novel PAS derivatives and related analogues. Our computational approach proved to be effective in making qualitative predictions, that is in discriminating active versus inactive compounds. Among the compounds synthesized and tested, 20 was the most active one, with EC(50) = 0.045 microM, IC(50) = 0.05 microM, and SI = 5333. Compared with the lead 3, these values represent a 3- and 8-fold improvement in the cell-based and enzyme assays, respectively, together with the highest selectivity achieved so far in the PAS series.

Chlorination and cleavage of lignin structures by fungal chloroperoxidases

Treesearch

Patricia Ortiz-Bermudez; Ewald Srebotnik; Kenneth E. Hammel

2003-01-01

Two fungal chloroperoxidases (CPOs), the heme enzyme from Caldariomyces fumago and the vanadium enzyme from Curvularia inaequalis, chlorinated 1-(4-ethoxy-3-methoxyphenyl)-2-(2-methoxyphenoxy)-1,3-dihydroxypropane, a dimeric model compound that represents the major nonphenolic structure in lignin. Both enzymes also cleaved this dimer to give 1-chloro-4-ethoxy-3-...

Effect of biochar particle size on hydrophobic organic compound sorption kinetics: Applicability of using representative size.

PubMed

Kang, Seju; Jung, Jihyeun; Choe, Jong Kwon; Ok, Yong Sik; Choi, Yongju

2018-04-01

Particle size of biochar may strongly affect the kinetics of hydrophobic organic compound (HOC) sorption. However, challenges exist in characterizing the effect of biochar particle size on the sorption kinetics because of the wide size range of biochar. The present study suggests a novel method to determine a representative value that can be used to show the dependence of HOC sorption kinetics to biochar particle size on the basis of an intra-particle diffusion model. Biochars derived from three different feedstocks are ground and sieved to obtain three daughter products each having different size distributions. Phenanthrene sorption kinetics to the biochars are well described by the intra-particle diffusion model with significantly greater sorption rates observed for finer grained biochars. The time to reach 95% of equilibrium for phenanthrene sorption to biochar is reduced from 4.6-17.9days for the original biochars to <1-4.6days for the powdered biochars with <125μm in size. A moderate linear correlation is found between the inverse square of the representative biochar particle radius obtained using particle size distribution analysis and the apparent phenanthrene sorption rates determined by the sorption kinetics experiments and normalized to account for the variation of the sorption rate-determining factors other than the biochar particle radius. The results suggest that the representative biochar particle radius reasonably describes the dependence of HOC sorption rates on biochar particle size. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic Structure-Based Pharmacophore Model Development: A New and Effective Addition in the Histone Deacetylase 8 (HDAC8) Inhibitor Discovery

PubMed Central

Thangapandian, Sundarapandian; John, Shalini; Lee, Yuno; Kim, Songmi; Lee, Keun Woo

2011-01-01

Histone deacetylase 8 (HDAC8) is an enzyme involved in deacetylating the amino groups of terminal lysine residues, thereby repressing the transcription of various genes including tumor suppressor gene. The over expression of HDAC8 was observed in many cancers and thus inhibition of this enzyme has emerged as an efficient cancer therapeutic strategy. In an effort to facilitate the future discovery of HDAC8 inhibitors, we developed two pharmacophore models containing six and five pharmacophoric features, respectively, using the representative structures from two molecular dynamic (MD) simulations performed in Gromacs 4.0.5 package. Various analyses of trajectories obtained from MD simulations have displayed the changes upon inhibitor binding. Thus utilization of the dynamically-responded protein structures in pharmacophore development has the added advantage of considering the conformational flexibility of protein. The MD trajectories were clustered based on single-linkage method and representative structures were taken to be used in the pharmacophore model development. Active site complimenting structure-based pharmacophore models were developed using Discovery Studio 2.5 program and validated using a dataset of known HDAC8 inhibitors. Virtual screening of chemical database coupled with drug-like filter has identified drug-like hit compounds that match the pharmacophore models. Molecular docking of these hits reduced the false positives and identified two potential compounds to be used in future HDAC8 inhibitor design. PMID:22272142

Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

PubMed

Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena

2013-01-01

The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Research in drug development against viral diseases of military importance (biological testing). Volume 1. Final report, 15 November 1985-31 January 1991

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shannon, W.M.; Arnett, G.; Brazier, A.D.

1991-03-01

The purpose of this program is to evaluate the efficacy of candidate antiviral compounds against a spectrum of viruses of military importance. This program involves (a) primary testing of chemical compounds and natural products for antiviral efficacy in vitro using standard CPE-inhibition assays, (b) primary testing of compounds for antiviral efficacy in vivo in animal model systems, and (c) secondary evaluation of the active candidate antiviral compounds. The target viruses for in vitro testing are Vaccinia Virus (VV), Adenovirus (AD2), Vesicular Stomatitis Virus (VSV), Punta Toro Virus (PT), Sandfly Fever Virus (SF), Yellow Fever Virus (YF), Venezuelan Equine Encephalomyelitis Virusmore » (VE), Japanese Encephalitis Virus and Vaccinia Virus infections of mice. Approximately 10,000 compounds have been received for in vitro evaluation and over 66,000 assays have been performed on this contract. Compounds have been identified in nearly all virus systems that have confirmed antiviral activity equal or exceeding that of the various positive control compounds (Ribavirin, Selenazofurin, Carbocyclic-3-deaza-adenosine, Adenosine dialdehyde, Ara-A, ddC and AZT). Many of these compounds represent potent and selective new antiviral agents.« less

Plasmachemical synthesis and evaluation of the thermal conductivity of metal-oxide compounds "Molybdenum-uranium dioxide"

NASA Astrophysics Data System (ADS)

Kotelnikova, Alexandra A.; Karengin, Alexander G.; Mendoza, Orlando

2018-03-01

The article represents possibility to apply oxidative and reducing plasma for plasma-chemical synthesis of metal-oxide compounds «Mo‒UO2» from water-salt mixtures «molybdic acid‒uranyl nitrate» and «molybdic acid‒ uranyl acetate». The composition of water-salt mixture was calculated and the conditions ensuring plasma-chemical synthesis of «Mo‒UO2» compounds were determined. Calculations were carried out at atmospheric pressure over a wide range of temperatures (300-4000 K), with the use of various plasma coolants (air, hydrogen). The heat conductivity coefficients of metal-oxide compounds «Mo‒UO2» consisting of continuous component (molybdenum matrix) are calculated. Inclusions from ceramics in the form of uranium dioxide were ordered in the matrix. Particular attention is paid to methods for calculating the coefficients of thermal conductivity of these compounds with the use of different models. Calculated results were compared with the experimental data.

Interactions of flavoured oil in-water emulsions with polylactide.

PubMed

Salazar, Rómulo; Domenek, Sandra; Ducruet, Violette

2014-04-01

Polylactide (PLA), a biobased polymer, might prove suitable as eco-friendly packaging, if it proves efficient at maintaining food quality. To assess interactions between PLA and food, an oïl in-water model emulsion was formulated containing aroma compounds representing different chemical structure classes (ethyl esters, 2-nonanone, benzaldehyde) at a concentration typically found in foodstuff (100 ppm). To study non-equilibrium effects during food shelf life, the emulsions were stored in a PLA pack (tray and lid). To assess equilibrium effects, PLA was conditioned in vapour contact with the aroma compounds at concentrations comparable to headspace conditions of real foods. PLA/emulsion interactions showed minor oil and aroma compound sorption in the packaging. Among tested aroma compounds, benzaldehyde and ethyl acetate were most sorbed and preferentially into the lid through the emulsion headspace. Equilibrium effects showed synergy of ethyl acetate and benzaldehyde, favouring sorption of additional aroma compounds in PLA. This should be anticipated during the formulation of food products. Copyright © 2013 Elsevier Ltd. All rights reserved.

Docking and Hydropathic Scoring of Polysubstituted Pyrrole Compounds with Anti-Tubulin Activity

PubMed Central

Tripathi, Ashutosh; Fornabaio, Micaela; Kellogg, Glen E.; Gupton, John T.; Gewirtz, David A.; Yeudall, W. Andrew; Vega, Nina E.; Mooberry, Susan L.

2008-01-01

Compounds that bind at the colchicine site of tubulin have drawn considerable attention with studies indicating that these agents suppress microtubule dynamics and inhibit tubulin polymerization. Data for eighteen polysubstituted pyrrole compounds are reported, including antiproliferative activity against human MDA-MB-435 cells and calculated free energies of binding following docking the compounds into models of αβ-tubulin. These docking calculations coupled with HINT interaction analyses are able to represent the complex structures and the binding modes of inhibitors such that calculated and measured free energies of binding correlate with an r2 of 0.76. Structural analysis of the binding pocket identifies important intermolecular contacts that mediate binding. As seen experimentally, the complex with JG-03-14 (3,5-dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2- carboxylic acid ethyl ester) is the most stable. These results illuminate the binding process and should be valuable in the design of new pyrrole-based colchicine site inhibitors as these compounds have very accessible syntheses. PMID:18083520

Novel series of potent, nonsteroidal, selective androgen receptor modulators based on 7H-[1,4]oxazino[3,2-g]quinolin-7-ones.

PubMed

Higuchi, Robert I; Arienti, Kristen L; López, Francisco J; Mani, Neelakhanda S; Mais, Dale E; Caferro, Thomas R; Long, Yun Oliver; Jones, Todd K; Edwards, James P; Zhi, Lin; Schrader, William T; Negro-Vilar, Andrés; Marschke, Keith B

2007-05-17

Recent interest in orally available androgens has fueled the search for new androgens for use in hormone replacement therapy and as anabolic agents. In pursuit of this, we have discovered a series of novel androgen receptor modulators derived from 7H-[1,4]oxazino[3,2-g]quinolin-7-ones. These compounds were synthesized and evaluated in competitive binding assays and an androgen receptor transcriptional activation assay. A number of compounds from the series demonstrated single-digit nanomolar agonist activity in vitro. In addition, lead compound (R)-16e was orally active in established rodent models that measure androgenic and anabolic properties of these agents. In this assay, (R)-16e demonstrated full efficacy in muscle and only partially stimulated the prostate at 100 mg/kg. These data suggest that these compounds may be utilized as selective androgen receptor modulators or SARMs. This series represents a novel class of compounds for use in androgen replacement therapy.

Synthesis, evaluation and modeling of some triazolothienopyrimidinones as anti-inflammatory and antimicrobial agents.

PubMed

Bekhit, Adnan A; Farghaly, Ahmed M; Shafik, Ragab M; Elsemary, Mona Ma; El-Shoukrofy, Mai S; Bekhit, Alaa El-Din A; Ibrahim, Tamer M

2017-06-01

New triazolotetrahydrobenzothienopyrimidinone derivatives were synthesized. Their structures were confirmed, and their anti-inflammatory, antimicrobial activities and ulcerogenic potentials were evaluated. Compounds 7a, 10a and 11a showed minimal ulcerogenic effect and high selectivity toward human recombinant COX-2 over COX-1 enzyme with IC 50 values of 1.39, 1.22 and 0.56 μM, respectively. Their docking outcome correlated with their biological activity and confirmed the high selectivity binding toward COX-2. Compound 12b displayed antimicrobial activity comparable to that of ampicillin against Escherichia coli while compounds 6 and 11c were similar to ampicillin against Staphylococcus aureus. In addition, compounds 7a, 9a, 10b and 11c showed dual anti-inflammatory/antimicrobial activities. This work represents a promising matrix for developing new potential anti-inflammatory, antimicrobial and dual antimicrobial/anti-inflammatory candidates. [Formula: see text].

Vibrational Markovian modelling of footprints after the interaction of antibiotics with the packaging region of HIV type 1.

PubMed

Díaz, Humberto González; de Armas, Ronal Ramos; Molina, Reinaldo

2003-11-01

The design of novel anti-HIV compounds has now become a crucial area for scientists working in numerous interrelated fields of science such as molecular biology, medicinal chemistry, mathematical biology, molecular modelling and bioinformatics. In this context, the development of simple but physically meaningful mathematical models to represent the interaction between anti-HIV drugs and their biological targets is of major interest. One such area currently under investigation involves the targets in the HIV-RNA-packaging region. In the work described here, we applied Markov chain theory in an attempt to describe the interaction between the antibiotic paromomycin and the packaging region of the RNA in Type-1 HIV. In this model, a nucleic acid squeezed graph is used. The vertices of the graph represent the nucleotides while the edges are the phosphodiester bonds. A stochastic (Markovian) matrix was subsequently defined on this graph, an operation that codifies the probabilities of interaction between specific nucleotides of HIV-RNA and the antibiotic. The strength of these local interactions can be calculated through an inelastic vibrational model. The successive power of this matrix codifies the probabilities with which the vibrations after drug-RNA interactions vanish along the polynucleotide main chain. The sums of self-return probabilities in the k-vicinity of each nucleotide represent physically meaningful descriptors. A linear discriminant function was developed and gave rise to excellent discrimination in 80.8% of interacting and footprinted nucleotides. The Jackknife method was employed to assess the stability and predictability of the model. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the antibiotic (R(2)=0.91, Q(2)=0.86). These kinds of models could play an important role either in the discovery of new anti-HIV compounds or the study of their mode of action.

Representing high throughput expression profiles via perturbation barcodes reveals compound targets

PubMed Central

Kutchukian, Peter S.; Li, Jing; Tudor, Matthew

2017-01-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound’s high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data. PMID:28182661

Toward prediction of alkane/water partition coefficients.

PubMed

Toulmin, Anita; Wood, J Matthew; Kenny, Peter W

2008-07-10

Partition coefficients were measured for 47 compounds in the hexadecane/water ( P hxd) and 1-octanol/water ( P oct) systems. Some types of hydrogen bond acceptor presented by these compounds to the partitioning systems are not well represented in the literature of alkane/water partitioning. The difference, DeltalogP, between logP oct and logP hxd is a measure of the hydrogen bonding potential of a molecule and is identified as a target for predictive modeling. Minimized molecular electrostatic potential ( V min) was shown to be an effective predictor of the contribution of hydrogen bond acceptors to DeltalogP. Carbonyl oxygen atoms were found to be stronger hydrogen bond acceptors for their electrostatic potential than heteroaromatic nitrogen or oxygen bound to hypervalent sulfur or nitrogen. Values of V min calculated for hydrogen-bonded complexes were used to explore polarization effects. Predicted logP hxd and DeltalogP were shown to be more effective than logP oct for modeling brain penetration for a data set of 18 compounds.

Comparative Environmental Performance of Two-Diesel-Fuel Oxygenates: Dibutyl Maleate (DBM) and Triproplyene Glycol Monomethyl Ether (TGME)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Layton, D.W.; Marchetti, A.A.

2001-10-01

Many studies have shown that the addition of oxygen bearing compounds to diesel fuel can significantly reduce particulate emissions. To assist in the evaluation of the environmental performance of diesel-fuel oxygenates, we have implemented a suite of diagnostic models for simulating the transport of compounds released to air, water, and soils/groundwater as well as regional landscapes. As a means of studying the comparative performance of DBM and TGME, we conducted a series of simulations for selected environmental media. Benzene and methyl tertiary butyl ether (MTBE) were also addressed because they represent benchmark fuel-related compounds that have been the subject ofmore » extensive environmental measurements and modeling. The simulations showed that DBM and TGME are less mobile in soil because of reduced vapor-phase transport and increased retention on soil particles. The key distinction between these two oxygenates is that DBM is predicted to have a greater potential than TGME for aerobic biodegradation, based on chemical structure.« less

Quantifying second generation ethanol inhibition: Design of Experiments approach and kinetic model development.

PubMed

Schneiderman, Steven J; Johnson, Roger W; Menkhaus, Todd J; Gilcrease, Patrick C

2015-03-01

While softwoods represent a potential feedstock for second generation ethanol production, compounds present in their hydrolysates can inhibit fermentation. In this study, a novel Design of Experiments (DoE) approach was used to identify significant inhibitory effects on Saccharomyces cerevisiae D5A for the purpose of guiding kinetic model development. Although acetic acid, furfural and 5-hydroxymethyl furfural (HMF) were present at potentially inhibitory levels, initial factorial experiments only identified ethanol as a significant rate inhibitor. It was hypothesized that high ethanol levels masked the effects of other inhibitors, and a subsequent factorial design without ethanol found significant effects for all other compounds. When these non-ethanol effects were accounted for in the kinetic model, R¯(2) was significantly improved over an ethanol-inhibition only model (R¯(2)=0.80 vs. 0.76). In conclusion, when ethanol masking effects are removed, DoE is a valuable tool to identify significant non-ethanol inhibitors and guide kinetic model development. Copyright © 2014 Elsevier Ltd. All rights reserved.

"Plate cherry picking": a novel semi-sequential screening paradigm for cheaper, faster, information-rich compound selection.

PubMed

Crisman, Thomas J; Jenkins, Jeremy L; Parker, Christian N; Hill, W Adam G; Bender, Andreas; Deng, Zhan; Nettles, James H; Davies, John W; Glick, Meir

2007-04-01

This work describes a novel semi-sequential technique for in silico enhancement of high-throughput screening (HTS) experiments now employed at Novartis. It is used in situations in which the size of the screen is limited by the readout (e.g., high-content screens) or the amount of reagents or tools (proteins or cells) available. By performing computational chemical diversity selection on a per plate basis (instead of a per compound basis), 25% of the 1,000,000-compound screening was optimized for general initial HTS. Statistical models are then generated from target-specific primary results (percentage inhibition data) to drive the cherry picking and testing from the entire collection. Using retrospective analysis of 11 HTS campaigns, the authors show that this method would have captured on average two thirds of the active compounds (IC(50) < 10 microM) and three fourths of the active Murcko scaffolds while decreasing screening expenditure by nearly 75%. This result is true for a wide variety of targets, including G-protein-coupled receptors, chemokine receptors, kinases, metalloproteinases, pathway screens, and protein-protein interactions. Unlike time-consuming "classic" sequential approaches that require multiple iterations of cherry picking, testing, and building statistical models, here individual compounds are cherry picked just once, based directly on primary screening data. Strikingly, the authors demonstrate that models built from primary data are as robust as models built from IC(50) data. This is true for all HTS campaigns analyzed, which represent a wide variety of target classes and assay types.

Bond dissociation enthalpies of a pinoresinol lignin model compound

Treesearch

Thomas Elder

2014-01-01

ABSTRACT: The pinoresinol unit is one of the principal interunit linkages in lignin. As such, its chemistry and properties are of major importance in understanding the behavior or the polymer. This work examines the homolytic cleavage of the pinoresinol system, representing the initial step in thermal degradation. The bond dissociation enthalpy of this reaction has...

Synthesis and mechanisms of action of novel harmine derivatives as potential antitumor agents

PubMed Central

Zhang, Xiao-Fei; Sun, Rong-qin; Jia, Yi-fan; Chen, Qing; Tu, Rong-Fu; Li, Ke-ke; Zhang, Xiao-Dong; Du, Run-Lei; Cao, Ri-hui

2016-01-01

A series of novel harmine derivatives bearing a benzylindine substituent in position-1 of β-carboline ring were synthesized and evaluated as antitumor agents. The N2-benzylated β-carboline derivatives 3a–g represented the most interesting anticancer activities and compound 3c was found to be the most active agent to diverse cancer cell lines such as gastric carcinoma, melanoma and colorectal cancer. Notably, compound 3c showed low toxicity to normal cells. The treatment significantly induced cell apoptosis. Mechanistically, PI3K/AKT signaling pathway mediated compound 3c-induced apoptosis. Compound 3c inhibited phosphorylation of AKT and promoted the production of reactive oxygen species (ROS). The ROS scavenger, LNAC and GSH, could disturb the effect of compound 3c induced apoptosis and PI3K activity inhibitor LY294002 synergistically enhanced compound 3c efficacy. Moreover, the results from nude mice xenograft model showed that compound 3c treatment effectively inhibited tumor growth and decreased tumor weight. Collectively, our results demonstrated that compound 3c exerts apoptotic effect in cancer cells via suppression of phosphorylated AKT and evocation of ROS generation, which suggested that compound 3c might be served as a promising therapeutic agent for cancer treatment. PMID:27625151

Deviations from sorption linearity on soils of polar and nonpolar organic compounds at low relative concentrations

USGS Publications Warehouse

Chiou, C.T.; Kile, D.E.

1998-01-01

A series of single-solute and binary-solute sorption data have been obtained on representative samples of polar compounds (substituted ureas and phenolic compounds) and of nonpolar compounds (e.g., EDB and TCE) on a peat soil and a mineral (Woodburn) soil; the data extend to low relative solute concentrations (C(e)/S(w)). At relatively low C(e)/S(w), both the nonpolar and the polar solutes exhibit nonlinear sorption. The sorption nonlinearity approaches apparent saturation at about C(e)/S(w) = 0.010-0.015 for the nonpolar solutes and at about C(e)/S(w) = 0.10-0.13 for the polar solutes; above these C(e)/S(w) regions, the isotherms are practically linear. The nonlinear sorption capacities are greater for polar solutes than for nonpolar solutes and the peat soil shows a greater effect than the Woodburn soil. The small nonlinear sorption capacity for a nonpolar solute is suppressed indiscriminately by either a nonpolar or a polar cosolute at relatively low C(e)/S(w) of the cosolute. By contrast, the abilities of different cosolutes to suppress the nonlinear capacity of a nominal polar solute differ drastically. For polar solutes, a nonpolar cosolute exhibits a limited suppression even at high cosolute C(e)/S(w); effective suppression occurs when the cosolute is relatively polar and at various C(e)/S(w). These differences suggest that more than a single mechanism is required to account for the nonlinear sorption of both nonpolar and polar compounds at low C(e)/S(w). Mechanistic processes consistent with these observations and with soil surface areas are discussed along with other suggested models. Some important consequences of the nonlinear competitive sorption to the behavior of contaminants in natural systems are discussed.A number of conceptual models was postulated to account for the nonlinear solute sorption on soils of significant soil organic matter. A series of single-solute and binary-route sorption data was obtained representing samples of polar compounds of substituted ureas and phenolic compounds, and of nonpolar compounds of EDB and trichloroethylene on a peat soil and a mineral on a Woodburn soil. The nonlinear sorption capacities are greater for polar solutes than for nonpolar solutes and the peat soil shows a greater effect than the Woodburn soil.

QSAR models for removal rates of organic pollutants adsorbed by in situ formed manganese dioxide under acid condition.

PubMed

Su, Pingru; Zhu, Huicen; Shen, Zhemin

2016-02-01

Manganese dioxide formed in oxidation process by potassium permanganate exhibits promising adsorptive capacity which can be utilized to remove organic pollutants in wastewater. However, the structure variances of organic molecules lead to wide difference of adsorption efficiency. Therefore, it is of great significance to find a general relationship between removal rate of organic compounds and their quantum parameters. This study focused on building up quantitative structure activity relationship (QSAR) models based on experimental removal rate (r(exp)) of 25 organic compounds and 17 quantum parameters of each organic compounds computed by Gaussian 09 and Material Studio 6.1. The recommended model is rpre = -0.502-7.742 f(+)x + 0.107 E HOMO + 0.959 q(H(+)) + 1.388 BOx. Both internal and external validations of the recommended model are satisfied, suggesting optimum stability and predictive ability. The definition of applicability domain and the Y-randomization test indicate all the prediction is reliable and no possibility of chance correlation. The recommended model contains four variables, which are closely related to adsorption mechanism. f(+)x reveals the degree of affinity for nucleophilic attack. E HOMO represents the difficulty of electron loss. q(H(+)) reflect the distribution of partial charge between carbon and hydrogen atom. BO x shows the stability of a molecule.

Modelling of Soluble Iron Formation, Transport and Deposition to the North Pacific Ocean, Role of Anthropogenic Pollutants.

NASA Astrophysics Data System (ADS)

Solmon, F.; Chuang, P.; Meskhidze, N.

2006-12-01

Soluble iron deposited via atmospheric processes represents an important nutrient for open ocean ecosystems, which might influence phytoplancton productivity and atmospheric carbon uptake. Atmospheric deposition of mineral dust is known to be the essential supply of iron to the ocean. However, most of the iron contained in mineral particles is unsoluble, whereas only the soluble fraction of the iron is thought to be effectively bio-available. There is still a great deal of uncertainties in the estimation of this fraction and the representation of iron solubilisation processes in the atmosphere. In this scope, we present a modeling study aiming at better representing such processes. In particular, we focus on the different roles of anthropogenic chemical compounds in the atmospheric iron cycle and deposition. These roles are of two orders : (i) the acidification of mineral particles by anthropogenic compounds influencing the solubilisation of the iron transported and (ii) the direct emission, transport and deposition of iron emitted by anthropogenic activities. For this study, we implement a set of specific mechanisms in the global chemistry transport model GEOS- CHEM. Our study focuses on the East Asia - North pacific outflow, a region where interactions between dust and pollution are particularly likely to occur and where the ocean ecosystem is known to be iron limited.

In silico structure prediction and inhibition mechanism studies of AtHDA14 as revealed by homology modeling, docking, molecular dynamics simulation.

PubMed

Zhao, Ming-Lang; Wang, Wang; Nie, Hu; Cao, Sha-Sha; Du, Lin-Fang

2018-05-06

Histone deacetylases (HDACs) play a significant role in the epigenetic mechanism by catalyzing deacetylation of lysine on histone in both animals and plants. HDACs involved in growth, development and response to stresses in plants. Arabidopsis thaliana histone deacetylase 14 (AtHDA14) is found to localize in the mitochondria and chloroplasts, and it involved in photosynthesis and melatonin biosynthesis. However, its mechanism of action was still unknowns so far. Therefore, in this study, we constructed AtHDA14 protein model using homology modeling method, validated using PROCHECK and presented using Ramachandran plots. We also performed virtual screening of AtHDA14 by docking with small molecule drugs and predicted their ADMET properties to select representative inhibitors. MD simulation for representative AtHDA14-ligand complexes was carried out to further research and reveal their stability and inhibition mechanism. Meanwhile, MM/PBSA method was utilized to obtain more valuable information about the residues energy contribution. Moreover, compared with four candidate inhibitors, we also found that compound 645533 and 6918837 might be a more potent AtHDA14 inhibitor than TSA (444732) and SAHA (5311). Therefore, compound 6445533 and 6918837 was anticipated to be a promising drug candidate for inhibition of AtHDA14. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of a pharmacophore for cruzain using oxadiazoles as virtual molecular probes: quantitative structure-activity relationship studies

NASA Astrophysics Data System (ADS)

de Souza, Anacleto S.; de Oliveira, Marcelo T.; Andricopulo, Adriano D.

2017-09-01

Chagas's is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi. According to the World Health Organization, 7 million people are infected worldwide leading to 7000 deaths per year. Drugs available, nifurtimox and benzimidazole, are limited due to low efficacy and high toxicity. As a validated target, cruzain represents a major front in drug discovery attempts for Chagas disease. Herein, we describe the development of 2D QSAR (r_{{{pred}}}2 = 0.81) and a 3D-QSAR-based pharmacophore (r_{{{pred}}}2 = 0.82) from a series of non-covalent cruzain inhibitors represented mostly by oxadiazoles (lead compound, IC50 = 200 nM). Both models allowed us to map key intermolecular interactions in S1', S2 and S3 cruzain sub-sites (including halogen bond and C‒H/π). To probe the predictive capacity of obtained models, inhibitors available in the literature from different classes displaying a range of scaffolds were evaluate achieving mean absolute deviation of 0.33 and 0.51 for 2D and 3D models, respectively. CoMFA revealed an unexplored region where addition of bulky substituents to produce new compounds in the series could be beneficial to improve biological activity.

Key hydride vibrational modes in [NiFe] hydrogenase model compounds studied by resonance Raman spectroscopy and density functional calculations.

PubMed

Shafaat, Hannah S; Weber, Katharina; Petrenko, Taras; Neese, Frank; Lubitz, Wolfgang

2012-11-05

Hydrogenase proteins catalyze the reversible conversion of molecular hydrogen to protons and electrons. While many enzymatic states of the [NiFe] hydrogenase have been studied extensively, there are multiple catalytically relevant EPR-silent states that remain poorly characterized. Analysis of model compounds using new spectroscopic techniques can provide a framework for the study of these elusive states within the protein. We obtained optical absorption and resonance Raman (RR) spectra of (dppe)Ni(μ-pdt)Fe(CO)(3) and [(dppe)Ni(μ-pdt)(μ-H)Fe(CO)(3)][BF(4)], which are structural and functional model compounds for the EPR-silent Ni-SI and Ni-R states of the [NiFe] hydrogenase active site. The studies presented here use RR spectroscopy to probe vibrational modes of the active site, including metal-hydride stretching vibrations along with bridging ligand-metal and Fe-CO bending vibrations, with isotopic substitution used to identify key metal-hydride modes. The metal-hydride vibrations are essentially uncoupled and represent isolated, localized stretching modes; the iron-hydride vibration occurs at 1530 cm(-1), while the nickel-hydride vibration is observed at 945 cm(-1). The significant discrepancy between the metal-hydride vibrational frequencies reflects the slight asymmetry in the metal-hydride bond lengths. Additionally, time-dependent density functional theory (TD-DFT) calculations were carried out to obtain theoretical RR spectra of these compounds. On the basis of the detailed comparison of theory and experiment, the dominant electronic transitions and significant normal modes probed in the RR experiments were assigned; the primary transitions in the visible wavelengths represent metal-to-metal and metal-to-ligand charge transfer bands. Inherent properties of metal-hydride vibrational modes in resonance Raman spectra and DFT calculations are discussed together with the prospects of observing such vibrational modes in metal-hydride-containing proteins. Such a combined theoretical and experimental approach may be valuable for characterization of analogous redox states in the [NiFe] hydrogenases.

Active machine learning-driven experimentation to determine compound effects on protein patterns.

PubMed

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-02-03

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance.

Functional, thermodynamics, structural and biological studies of in silico-identified inhibitors of Mycobacterium tuberculosis enoyl-ACP(CoA) reductase enzyme

NASA Astrophysics Data System (ADS)

Martinelli, Leonardo K. B.; Rotta, Mariane; Villela, Anne D.; Rodrigues-Junior, Valnês S.; Abbadi, Bruno L.; Trindade, Rogério V.; Petersen, Guilherme O.; Danesi, Giuliano M.; Nery, Laura R.; Pauli, Ivani; Campos, Maria M.; Bonan, Carla D.; de Souza, Osmar Norberto; Basso, Luiz A.; Santos, Diogenes S.

2017-04-01

Novel chemotherapeutics agents are needed to kill Mycobacterium tuberculosis, the main causative agent of tuberculosis (TB). The M. tuberculosis 2-trans-enoyl-ACP(CoA) reductase enzyme (MtInhA) is the druggable bona fide target of isoniazid. New chemotypes were previously identified by two in silico approaches as potential ligands to MtInhA. The inhibition mode was determined by steady-state kinetics for seven compounds that inhibited MtInhA activity. Dissociation constant values at different temperatures were determined by protein fluorescence spectroscopy. van’t Hoff analyses of ligand binding to MtInhA:NADH provided the thermodynamic signatures of non-covalent interactions (ΔH°, ΔS°, ΔG°). Phenotypic screening showed that five compounds inhibited in vitro growth of M. tuberculosis H37Rv strain. Labio_16 and Labio_17 compounds also inhibited the in vitro growth of PE-003 multidrug-resistant strain. Cytotoxic effects on Hacat, Vero and RAW 264.7 cell lines were assessed for the latter two compounds. The Labio_16 was bacteriostatic and Labio_17 bactericidal in an M. tuberculosis-infected macrophage model. In Zebrafish model, Labio_16 showed no cardiotoxicity whereas Labio_17 showed dose-dependent cardiotoxicity. Accordingly, a model was built for the MtInhA:NADH:Labio_16 ternary complex. The results show that the Labio_16 compound is a direct inhibitor of MtInhA, and it may represent a hit for the development of chemotherapeutic agents to treat TB.

Evaluating the mutagenic potential of aerosol organic compounds using informatics-based screening

NASA Astrophysics Data System (ADS)

Decesari, Stefano; Kovarich, Simona; Pavan, Manuela; Bassan, Arianna; Ciacci, Andrea; Topping, David

2018-02-01

Whilst general policy objectives to reduce airborne particulate matter (PM) health effects are to reduce exposure to PM as a whole, emerging evidence suggests that more detailed metrics associating impacts with different aerosol components might be needed. Since it is impossible to conduct toxicological screening on all possible molecular species expected to occur in aerosol, in this study we perform a proof-of-concept evaluation on the information retrieved from in silico toxicological predictions, in which a subset (N = 104) of secondary organic aerosol (SOA) compounds were screened for their mutagenicity potential. An extensive database search showed that experimental data are available for 13 % of the compounds, while reliable predictions were obtained for 82 %. A multivariate statistical analysis of the compounds based on their physico-chemical, structural, and mechanistic properties showed that 80 % of the compounds predicted as mutagenic were grouped into six clusters, three of which (five-membered lactones from monoterpene oxidation, oxygenated multifunctional compounds from substituted benzene oxidation, and hydroperoxides from several precursors) represent new candidate groups of compounds for future toxicological screenings. These results demonstrate that coupling model-generated compositions to in silico toxicological screening might enable more comprehensive exploration of the mutagenic potential of specific SOA components.

Benefits of polidocanol endovenous microfoam (Varithena®) compared with physician-compounded foams

PubMed Central

Carugo, Dario; Ankrett, Dyan N; Zhao, Xuefeng; Zhang, Xunli; Hill, Martyn; O’Byrne, Vincent; Hoad, James; Arif, Mehreen; Wright, David DI

2015-01-01

Objective To compare foam bubble size and bubble size distribution, stability, and degradation rate of commercially available polidocanol endovenous microfoam (Varithena®) and physician-compounded foams using a number of laboratory tests. Methods Foam properties of polidocanol endovenous microfoam and physician-compounded foams were measured and compared using a glass-plate method and a Sympatec QICPIC image analysis method to measure bubble size and bubble size distribution, Turbiscan™ LAB for foam half time and drainage and a novel biomimetic vein model to measure foam stability. Physician-compounded foams composed of polidocanol and room air, CO2, or mixtures of oxygen and carbon dioxide (O2:CO2) were generated by different methods. Results Polidocanol endovenous microfoam was found to have a narrow bubble size distribution with no large (>500 µm) bubbles. Physician-compounded foams made with the Tessari method had broader bubble size distribution and large bubbles, which have an impact on foam stability. Polidocanol endovenous microfoam had a lower degradation rate than any physician-compounded foams, including foams made using room air (p < 0.035). The same result was obtained at different liquid to gas ratios (1:4 and 1:7) for physician-compounded foams. In all tests performed, CO2 foams were the least stable and different O2:CO2 mixtures had intermediate performance. In the biomimetic vein model, polidocanol endovenous microfoam had the slowest degradation rate and longest calculated dwell time, which represents the length of time the foam is in contact with the vein, almost twice that of physician-compounded foams using room air and eight times better than physician-compounded foams prepared using equivalent gas mixes. Conclusion Bubble size, bubble size distribution and stability of various sclerosing foam formulations show that polidocanol endovenous microfoam results in better overall performance compared with physician-compounded foams. Polidocanol endovenous microfoam offers better stability and cohesive properties in a biomimetic vein model compared to physician-compounded foams. Polidocanol endovenous microfoam, which is indicated in the United States for treatment of great saphenous vein system incompetence, provides clinicians with a consistent product with enhanced handling properties. PMID:26036246

Benefits of polidocanol endovenous microfoam (Varithena®) compared with physician-compounded foams.

PubMed

Carugo, Dario; Ankrett, Dyan N; Zhao, Xuefeng; Zhang, Xunli; Hill, Martyn; O'Byrne, Vincent; Hoad, James; Arif, Mehreen; Wright, David D I; Lewis, Andrew L

2016-05-01

To compare foam bubble size and bubble size distribution, stability, and degradation rate of commercially available polidocanol endovenous microfoam (Varithena®) and physician-compounded foams using a number of laboratory tests. Foam properties of polidocanol endovenous microfoam and physician-compounded foams were measured and compared using a glass-plate method and a Sympatec QICPIC image analysis method to measure bubble size and bubble size distribution, Turbiscan™ LAB for foam half time and drainage and a novel biomimetic vein model to measure foam stability. Physician-compounded foams composed of polidocanol and room air, CO2, or mixtures of oxygen and carbon dioxide (O2:CO2) were generated by different methods. Polidocanol endovenous microfoam was found to have a narrow bubble size distribution with no large (>500 µm) bubbles. Physician-compounded foams made with the Tessari method had broader bubble size distribution and large bubbles, which have an impact on foam stability. Polidocanol endovenous microfoam had a lower degradation rate than any physician-compounded foams, including foams made using room air (p < 0.035). The same result was obtained at different liquid to gas ratios (1:4 and 1:7) for physician-compounded foams. In all tests performed, CO2 foams were the least stable and different O2:CO2 mixtures had intermediate performance. In the biomimetic vein model, polidocanol endovenous microfoam had the slowest degradation rate and longest calculated dwell time, which represents the length of time the foam is in contact with the vein, almost twice that of physician-compounded foams using room air and eight times better than physician-compounded foams prepared using equivalent gas mixes. Bubble size, bubble size distribution and stability of various sclerosing foam formulations show that polidocanol endovenous microfoam results in better overall performance compared with physician-compounded foams. Polidocanol endovenous microfoam offers better stability and cohesive properties in a biomimetic vein model compared to physician-compounded foams. Polidocanol endovenous microfoam, which is indicated in the United States for treatment of great saphenous vein system incompetence, provides clinicians with a consistent product with enhanced handling properties. © The Author(s) 2015.

Modeling the SOA Forming Potential of Substituted Dihydrofurans from Alkane + OH Reactions in the Atmosphere

NASA Astrophysics Data System (ADS)

Jordan, C. E.; Griffin, R. J.; Lim, Y. B.; Ziemann, P. J.; Atkinson, R.; Arey, J.

2005-12-01

Recent laboratory studies show that δ-hydroxycarbonyls formed in the atmosphere via OH-initiated reactions with alkanes can cyclize then dehydrate to form substituted dihydrofurans. These dihydrofurans are highly reactive, with lifetimes in the atmosphere of 1.3 h (OH), 24 s (NO3), and 7 min (O3). The ability of the δ-hydroxycarbonyls to cyclize and dehydrate has been shown to increase with increasing carbon number. Recent laboratory results show that the secondary organic aerosol (SOA) yields from alkanes also increase with carbon number reaching ~53% for C15. The reaction mechanism proposed based on the chamber results is the basis of the modeling study presented here. We have incorporated this proposed mechanism into the Caltech Atmospheric Chemistry Mechanism (CACM). For computational reasons, similar compounds are lumped together and represented by a single suitable compound. In the present case, alkanes are lumped into 3 groups: short chains (≤C6), medium chains (C7 - C12), and long chains (≥C13). SOA yields obtained in chamber studies increase dramatically from 0.5% for C8 to 25% for C12. The most dramatic increase is observed from C11 (8%) to C13 (~50%). This is attributed to the low volatility of first generation products contributing to the SOA from longer chain alkanes. Here we have studied OH reactions with the substituted dihydrofurans for medium (represented by C10) and long (represented by C16) chain alkanes using CACM along with the aerosol partitioning module MPMPO (Model to Predict the Multi-phase Partitioning of Organics). We will present the results of this modeling study, characterizing the influence of substituted dihydrofurans on the SOA forming potential of alkanes.

New azole antifungals. 2. Synthesis and antifungal activity of heterocyclecarboxamide derivatives of 3-amino-2-aryl-1-azolyl-2-butanol.

PubMed

Bartroli, J; Turmo, E; Algueró, M; Boncompte, E; Vericat, M L; Conte, L; Ramis, J; Merlos, M; García-Rafanell, J; Forn, J

1998-05-21

A series of 92 azole antifungals containing an amido alcohol unit was synthesized. The nature and substitution of the amide portion was systematically modified in search of improved antifungal activity, especially against filamentous fungi. The compounds were tested in vitro against a variety of clinically important pathogens and in vivo (po) in a murine candidosis model. Thiazole and thiophene carboxamides carrying both a substituted phenyl ring and a small alkyl group were best suited for activity against filamentous fungi. In a subset of these compounds, the amide portion was conformationally locked by means of a pyrimidone ring and it was proven that only an orthogonal orientation of the phenyl ring yields bioactive products. A tendency to display long plasma elimination half-lives was observed in both series. Two compounds, 74 and 107, representative of the open and cyclic amides, respectively, were chosen for further studies, based on their excellent activity in in vivo murine models of candidosis and aspergillosis. This work describes the SARs found within this series. The next paper displays the results obtained in a related series of compounds, the quinazolinones.

Modeling nasopharyngeal carcinoma in three dimensions

PubMed Central

Siva Sankar, Prabu; Che Mat, Mohd Firdaus; Muniandy, Kalaivani; Xiang, Benedict Lian Shi; Ling, Phang Su; Hoe, Susan Ling Ling; Khoo, Alan Soo-Beng; Mohana-Kumaran, Nethia

2017-01-01

Nasopharyngeal carcinoma (NPC) is a type of cancer endemic in Asia, including Malaysia, Southern China, Hong Kong and Taiwan. Treatment resistance, particularly in recurring cases, remains a challenge. Thus, studies to develop novel therapeutic agents are important. Potential therapeutic compounds may be effectively examined using two-dimensional (2D) cell culture models, three-dimensional (3D) spheroid models or in vivo animal models. The majority of drug assessments for cancers, including for NPC, are currently performed with 2D cell culture models. This model offers economical and high-throughput screening advantages. However, 2D cell culture models cannot recapitulate the architecture and the microenvironment of a tumor. In vivo models may recapitulate certain architectural and microenvironmental conditions of a tumor, however, these are not feasible for the screening of large numbers of compounds. By contrast, 3D spheroid models may be able to recapitulate a physiological microenvironment not observed in 2D cell culture models, in addition to avoiding the impediments of in vivo animal models. Thus, the 3D spheroid model offers a more representative model for the study of NPC growth, invasion and drug response, which may be cost-effective without forgoing quality. PMID:28454359

Structure and magnetic properties of oxychalcogenides A2F2Fe2OQ2 (A = Sr, Ba; Q = S, Se) with Fe2O square planar layers representing an antiferromagnetic checkerboard spin lattice.

PubMed

Kabbour, Houria; Janod, Etienne; Corraze, Benoît; Danot, Michel; Lee, Changhoon; Whangbo, Myung-Hwan; Cario, Laurent

2008-07-02

The oxychalcogenides A2F2Fe2OQ2 (A = Sr, Ba; Q = S, Se), which contain Fe2O square planar layers of the anti-CuO2 type, were predicted using a modular assembly of layered secondary building units and subsequently synthesized. The physical properties of these compounds were characterized using magnetic susceptibility, electrical resistivity, specific heat, (57)Fe Mossbauer, and powder neutron diffraction measurements and also by estimating their exchange interactions on the basis of first-principles density functional theory electronic structure calculations. These compounds are magnetic semiconductors that undergo a long-range antiferromagnetic ordering below 83.6-106.2 K, and their magnetic properties are well-described by a two-dimensional Ising model. The dominant antiferromagnetic spin exchange interaction between S = 2 Fe(2+) ions occurs through corner-sharing Fe-O-Fe bridges. Moreover, the calculated spin exchange interactions show that the A2F2Fe2OQ2 (A = Sr, Ba; Q = S, Se) compounds represent a rare example of a frustrated antiferromagnetic checkerboard lattice.

Cluster kinetics model for mixtures of glassformers

NASA Astrophysics Data System (ADS)

Brenskelle, Lisa A.; McCoy, Benjamin J.

2007-10-01

For glassformers we propose a binary mixture relation for parameters in a cluster kinetics model previously shown to represent pure compound data for viscosity and dielectric relaxation as functions of either temperature or pressure. The model parameters are based on activation energies and activation volumes for cluster association-dissociation processes. With the mixture parameters, we calculated dielectric relaxation times and compared the results to experimental values for binary mixtures. Mixtures of sorbitol and glycerol (seven compositions), sorbitol and xylitol (three compositions), and polychloroepihydrin and polyvinylmethylether (three compositions) were studied.

Predicting reactivity of model DOM compounds towards chlorine with mediated electrochemical oxidation.

PubMed

de Vera, Glen Andrew; Gernjak, Wolfgang; Radjenovic, Jelena

2017-05-01

Chlorine demand of a water sample depends on the characteristics of dissolved organic matter (DOM). It is an important parameter for water utilities used to assess oxidant and/or disinfectant consumption of source waters during treatment and distribution. In this study, model compounds namely resorcinol, tannic acid, vanillin, cysteine, tyrosine, and tryptophan were used to represent the reactive moieties of complex DOM mixtures. The reactivity of these compounds was evaluated in terms of Cl 2 demand and electron donating capacity (EDC). The EDC was determined by mediated electrochemical oxidation (MEO) which involves the use of 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) as an electron shuttle. The Cl 2 demand of readily oxidizable compounds (resorcinol, tannic acid, vanillin, and cysteine) was found to correlate well with EDC (R 2  = 0.98). The EDC values (mol e - /mol C) of the model compounds are as follows: 1.18 (cysteine) > 0.77 (resorcinol) > 0.59 (vanillin) > 0.52 (tannic acid) > 0.36 (tryptophan) > 0.19 (tyrosine). To determine the effect of pre-oxidation on EDC, ozone was added (0.1 mol O 3 /mol C) into each model compound solution. Ozonation caused a general decrease in EDC (10-40%), chlorine demand (10-30%), and UV absorbance (10-40%), except for tyrosine which showed both increased UV 275 and EDC. Before and after ozonation, 24 h disinfection byproduct (DBP) formation potential tests (Cl 2 residual = 1.5 mg/L) were conducted to evaluate the use of EDC for DBP formation prediction. The results indicate that there was no significant correlation between the EDC of the model compounds and the formation potentials of adsorbable organic chlorine, trichloromethane, and trichloroacetic acid. This suggests that while EDC correlates with Cl 2 demand, chlorine consumption may not directly translate to DBP formation because oxidation reactions may dominate over substitution reactions. Overall, this study provides useful insights on the reactions of ABTS + and HOCl with model DOM compounds, and highlights the potential application of MEO for rapid determination of Cl 2 demand of a water sample. Copyright © 2017 Elsevier Ltd. All rights reserved.

Physicochemical properties of selected polybrominated diphenyl ethers and extension of the UNIFAC model to brominated aromatic compounds.

PubMed

Kuramochi, Hidetoshi; Maeda, Kouji; Kawamoto, Katsuya

2007-04-01

The aqueous solubilities (S(w)) at various temperatures from 283 K to 308 K and 1-octanol/water partition coefficients (K(ow)) for four polybrominated diphenyl ethers (PBDEs: 4,4'-dibromodiphenyl ether (BDE-15), 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), 2,2',4,4',5-pentabromodiphenyl ether (BDE-99), and 2,2',4,4',5,5'-hexabromodiphenyl ether (BDE-153)) were measured by the generator column method. The S(w) and K(ow) data revealed the effect of bromine substitution and basic structure on S(w) and K(ow). To estimate the infinite dilution activity coefficients (gamma(i)(w,infinity)) of the PBDEs in water from the S(w) data, enthalpies of fusion and melting points for those compounds were measured with a differential scanning calorimeter. Henry's Law constants (H(w)) of the PBDEs were derived from the determined gamma(i)(w,infinity) and literature vapor pressure data. Some physicochemical characteristics of PBDEs were also suggested by comparing the present property data with that of polychlorinated dibenzo-p-dioxins, brominated phenols and brominated benzenes in past studies. Furthermore, in order to represent different phase equilibria including solubility and partition equilibrium for other brominated aromatic compounds using the UNIFAC model, a pair of UNIFAC group interaction parameters between the bromine and water group were determined from the S(w) and K(ow) data of PBDEs and brominated benzenes. The ability of the determined parameters to represent both properties of brominated aromatics was evaluated.

Azo compounds as a family of organic electrode materials for alkali-ion batteries.

PubMed

Luo, Chao; Borodin, Oleg; Ji, Xiao; Hou, Singyuk; Gaskell, Karen J; Fan, Xiulin; Chen, Ji; Deng, Tao; Wang, Ruixing; Jiang, Jianjun; Wang, Chunsheng

2018-02-27

Organic compounds are desirable for sustainable Li-ion batteries (LIBs), but the poor cycle stability and low power density limit their large-scale application. Here we report a family of organic compounds containing azo group (N=N) for reversible lithiation/delithiation. Azobenzene-4,4'-dicarboxylic acid lithium salt (ADALS) with an azo group in the center of the conjugated structure is used as a model azo compound to investigate the electrochemical behaviors and reaction mechanism of azo compounds. In LIBs, ADALS can provide a capacity of 190 mAh g -1 at 0.5 C (corresponding to current density of 95 mA g -1 ) and still retain 90%, 71%, and 56% of the capacity when the current density is increased to 2 C, 10 C, and 20 C, respectively. Moreover, ADALS retains 89% of initial capacity after 5,000 cycles at 20 C with a slow capacity decay rate of 0.0023% per cycle, representing one of the best performances in all organic compounds. Superior electrochemical behavior of ADALS is also observed in Na-ion batteries, demonstrating that azo compounds are universal electrode materials for alkali-ion batteries. The highly reversible redox chemistry of azo compounds to alkali ions was confirmed by density-functional theory (DFT) calculations. It provides opportunities for developing sustainable batteries.

Compound simulation of fluvial floods and storm surges in a global coupled river-coast flood model: Model development and its application to 2007 Cyclone Sidr in Bangladesh

NASA Astrophysics Data System (ADS)

Ikeuchi, Hiroaki; Hirabayashi, Yukiko; Yamazaki, Dai; Muis, Sanne; Ward, Philip J.; Winsemius, Hessel C.; Verlaan, Martin; Kanae, Shinjiro

2017-08-01

Water-related disasters, such as fluvial floods and cyclonic storm surges, are a major concern in the world's mega-delta regions. Furthermore, the simultaneous occurrence of extreme discharges from rivers and storm surges could exacerbate flood risk, compared to when they occur separately. Hence, it is of great importance to assess the compound risks of fluvial and coastal floods at a large scale, including mega-deltas. However, most studies on compound fluvial and coastal flooding have been limited to relatively small scales, and global-scale or large-scale studies have not yet addressed both of them. The objectives of this study are twofold: to develop a global coupled river-coast flood model; and to conduct a simulation of compound fluvial flooding and storm surges in Asian mega-delta regions. A state-of-the-art global river routing model was modified to represent the influence of dynamic sea surface levels on river discharges and water levels. We conducted the experiments by coupling a river model with a global tide and surge reanalysis data set. Results show that water levels in deltas and estuaries are greatly affected by the interaction between river discharge, ocean tides and storm surges. The effects of storm surges on fluvial flooding are further examined from a regional perspective, focusing on the case of Cyclone Sidr in the Ganges-Brahmaputra-Meghna Delta in 2007. Modeled results demonstrate that a >3 m storm surge propagated more than 200 km inland along rivers. We show that the performance of global river routing models can be improved by including sea level dynamics.

Interacting quasi-band model for electronic states in compound semiconductor alloys: Zincblende structure

NASA Astrophysics Data System (ADS)

Shinozuka, Yuzo; Oda, Masato

2015-09-01

The interacting quasi-band model proposed for electronic states in simple alloys is extended for compound semiconductor alloys with general lattice structures containing several atoms per unit cell. Using a tight-binding model, a variational electronic wave function for quasi-Bloch states yields a non-Hermitian Hamiltonian matrix characterized by matrix elements of constituent crystals and concentration of constituents. Solving secular equations for each k-state yields the alloy’s energy spectrum for any type of randomness and arbitrary concentration. The theory is used to address III-V (II-VI) alloys with a zincblende lattice with crystal band structures well represented by the sp3s* model. Using the resulting 15 × 15 matrix, the concentration dependence of valence and conduction bands is calculated in a unified scheme for typical alloys: Al1-xGaxAs, GaAs1-xPx, and GaSb1-xPx. Results agree well with experiments and are discussed with respect to the concentration dependence, direct-indirect gap transition, and band-gap-bowing origin.

Tautomerism, Hammett σ, and QSAR

NASA Astrophysics Data System (ADS)

Martin, Yvonne Connolly

2010-06-01

A consideration of equilibrium model-based equations suggests that tautomeric equilibria do not markedly affect observed potency if the tautomer bound represents at least 50% of the compound in solution. Tautomeric equilibria can enhance or attenuate the correlation of potency with Hammett σ. Additionally, tautomeric equilibria can lead to a correlation of potency with σ even in the absence of a correlation of binding with σ.

Predicting targets of compounds against neurological diseases using cheminformatic methodology

NASA Astrophysics Data System (ADS)

Nikolic, Katarina; Mavridis, Lazaros; Bautista-Aguilera, Oscar M.; Marco-Contelles, José; Stark, Holger; do Carmo Carreiras, Maria; Rossi, Ilaria; Massarelli, Paola; Agbaba, Danica; Ramsay, Rona R.; Mitchell, John B. O.

2015-02-01

Recently developed multi-targeted ligands are novel drug candidates able to interact with monoamine oxidase A and B; acetylcholinesterase and butyrylcholinesterase; or with histamine N-methyltransferase and histamine H3-receptor (H3R). These proteins are drug targets in the treatment of depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease. A probabilistic method, the Parzen-Rosenblatt window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Molecular structures were represented based on the circular fingerprint methodology. The same approach was used to build a "predictor" model from the DrugBank dataset to determine the main pharmacological groups of the compound. The study of off-target interactions is now recognised as crucial to the understanding of both drug action and toxicology. Primary pharmaceutical targets and off-targets for the novel multi-target ligands were examined by use of the developed cheminformatic method. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. The cheminformatic targets identifications were in agreement with four 3D-QSAR (H3R/D1R/D2R/5-HT2aR) models and by in vitro assays for serotonin 5-HT1a and 5-HT2a receptor binding of the most promising ligand ( 71/MBA-VEG8).

QSAR, docking and ADMET studies of artemisinin derivatives for antimalarial activity targeting plasmepsin II, a hemoglobin-degrading enzyme from P. falciparum.

PubMed

Qidwai, Tabish; Yadav, Dharmendra K; Khan, Feroz; Dhawan, Sangeeta; Bhakuni, R S

2012-01-01

This work presents the development of quantitative structure activity relationship (QSAR) model to predict the antimalarial activity of artemisinin derivatives. The structures of the molecules are represented by chemical descriptors that encode topological, geometric, and electronic structure features. Screening through QSAR model suggested that compounds A24, A24a, A53, A54, A62 and A64 possess significant antimalarial activity. Linear model is developed by the multiple linear regression method to link structures to their reported antimalarial activity. The correlation in terms of regression coefficient (r(2)) was 0.90 and prediction accuracy of model in terms of cross validation regression coefficient (rCV(2)) was 0.82. This study indicates that chemical properties viz., atom count (all atoms), connectivity index (order 1, standard), ring count (all rings), shape index (basic kappa, order 2), and solvent accessibility surface area are well correlated with antimalarial activity. The docking study showed high binding affinity of predicted active compounds against antimalarial target Plasmepsins (Plm-II). Further studies for oral bioavailability, ADMET and toxicity risk assessment suggest that compound A24, A24a, A53, A54, A62 and A64 exhibits marked antimalarial activity comparable to standard antimalarial drugs. Later one of the predicted active compound A64 was chemically synthesized, structure elucidated by NMR and in vivo tested in multidrug resistant strain of Plasmodium yoelii nigeriensis infected mice. The experimental results obtained agreed well with the predicted values.

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

DOE PAGES

Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

2016-01-19

A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Kohler theory to predict themore » effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. Furthermore, the model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.« less

Systematic assessment of scaffold hopping versus activity cliff formation across bioactive compound classes following a molecular hierarchy.

PubMed

Stumpfe, Dagmar; Dimova, Dilyana; Bajorath, Jürgen

2015-07-01

Scaffold hopping and activity cliff formation define opposite ends of the activity landscape feature spectrum. To rationalize these events at the level of scaffolds, active compounds involved in scaffold hopping were required to contain topologically distinct scaffolds but have only limited differences in potency, whereas compounds involved in activity cliffs were required to share the same scaffold but have large differences in potency. A systematic search was carried out for compounds involved in scaffold hopping and/or activity cliff formation. Results obtained for compound data sets covering more than 300 human targets revealed clear trends. If scaffolds represented multiple but fewer than 10 active compounds, nearly 90% of all scaffolds were exclusively involved in hopping events. With increasing compound coverage, the fraction of scaffolds involved in both scaffold hopping and activity cliff formation significantly increased to more than 50%. However, ∼40% of the scaffolds representing large numbers of active compounds continued to be exclusively involved in scaffold hopping. More than 200 scaffolds with broad target coverage were identified that consistently represented potent compounds and yielded an abundance of scaffold hops in the low-nanomolar range. These and other subsets of scaffolds we characterized are of prime interest for structure-activity relationship (SAR) exploration and compound design. Therefore, the complete scaffold classification generated in the course of our analysis is made freely available. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimized structure and thermochemical properties of flavonoids determined by the CHIH(medium) DFT model chemistry versus experimental techniques

NASA Astrophysics Data System (ADS)

Mendoza-Wilson, Ana María.; Lardizabal-Gutiérrez, Daniel; Torres-Moye, Enrique; Fuentes-Cobas, Luis; Balandrán-Quintana, René R.; Camacho-Dávila, Alejandro; Quintero-Ramos, Armando; Glossman-Mitnik, Daniel

2007-12-01

The purpose of this work was to evaluate the accuracy of the CHIH(medium)-DFT model chemistry (PBEg/CBSB2 ∗∗//PBEg/CBSB4) in the determination of the optimized structure and thermochemical properties of heterocyclic systems of medium size such as flavonoids, wherefore were selected three of the most abundant flavonoids in vegetable tissues, and which posses the higher antioxidant activity: quercetin, (+)-catechin and cyanidin. As reference systems were employed three cyclic compounds: phenol, catechol and resorcinol. The thermochemical properties evaluated were enthalpy of formation, bond dissociation enthalpy (BDE) and ionization potential (IP), following the scheme of isodesmic reactions. The theoretical results were compared with experimental data generated by X-ray diffraction and calorimetric techniques realized in part by us, whereas other data were taken from the literature. The results obtained in this work reveal that the CHIH(medium)-DFT model chemistry represents an accurate computational tool to calculate structural and thermochemical properties in the studied flavonoid and reference compounds. The average absolute deviation of enthalpy of formation for reference compounds was 3.0 kcal/mol, 2.64 kcal/mol for BDE, and 2.97 kcal/mol for IP.

Structure-based virtual screening of hypothetical inhibitors of the enzyme longiborneol synthase-a potential target to reduce Fusarium head blight disease.

PubMed

Bresso, E; Leroux, V; Urban, M; Hammond-Kosack, K E; Maigret, B; Martins, N F

2016-07-01

Fusarium head blight (FHB) is one of the most destructive diseases of wheat and other cereals worldwide. During infection, the Fusarium fungi produce mycotoxins that represent a high risk to human and animal health. Developing small-molecule inhibitors to specifically reduce mycotoxin levels would be highly beneficial since current treatments unspecifically target the Fusarium pathogen. Culmorin possesses a well-known important synergistically virulence role among mycotoxins, and longiborneol synthase appears to be a key enzyme for its synthesis, thus making longiborneol synthase a particularly interesting target. This study aims to discover potent and less toxic agrochemicals against FHB. These compounds would hamper culmorin synthesis by inhibiting longiborneol synthase. In order to select starting molecules for further investigation, we have conducted a structure-based virtual screening investigation. A longiborneol synthase structural model is first built using homology modeling, followed by molecular dynamics simulations that provided the required input for a protein-ligand ensemble docking procedure. From this strategy, the three most interesting compounds (hits) were selected among the 25 top-ranked docked compounds from a library of 15,000 drug-like compounds. These putative inhibitors of longiborneol synthase provide a sound starting point for further studies involving molecular modeling coupled to biochemical experiments. This process could eventually lead to the development of novel approaches to reduce mycotoxin contamination in harvested grain.

Plant-Derived Polyphenols in Human Health: Biological Activity, Metabolites and Putative Molecular Targets.

PubMed

Olivares-Vicente, Marilo; Barrajon-Catalan, Enrique; Herranz-Lopez, Maria; Segura-Carretero, Antonio; Joven, Jorge; Encinar, Jose Antonio; Micol, Vicente

2018-01-01

Hibiscus sabdariffa, Lippia citriodora, Rosmarinus officinalis and Olea europaea, are rich in bioactive compounds that represent most of the phenolic compounds' families and have exhibited potential benefits in human health. These plants have been used in folk medicine for their potential therapeutic properties in human chronic diseases. Recent evidence leads to postulate that polyphenols may account for such effects. Nevertheless, the compounds or metabolites that are responsible for reaching the molecular targets are unknown. data based on studies directly using complex extracts on cellular models, without considering metabolic aspects, have limited applicability. In contrast, studies exploring the absorption process, metabolites in the blood circulation and tissues have become essential to identify the intracellular final effectors that are responsible for extracts bioactivity. Once the cellular metabolites are identified using high-resolution mass spectrometry, docking techniques suppose a unique tool for virtually screening a large number of compounds on selected targets in order to elucidate their potential mechanisms. we provide an updated overview of the in vitro and in vivo studies on the toxicity, absorption, permeability, pharmacokinetics and cellular metabolism of bioactive compounds derived from the abovementioned plants to identify the potential compounds that are responsible for the observed health effects. we propose the use of targeted metabolomics followed by in silico studies to virtually screen identified metabolites on selected protein targets, in combination with the use of the candidate metabolites in cellular models, as the methods of choice for elucidating the molecular mechanisms of these compounds. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Bivalent compound 17MN exerts neuroprotection through interaction at multiple sites in a cellular model of Alzheimer’s disease

PubMed Central

Liu, Kai; Chojnacki, Jeremy E.; Wade, Emily E.; Saathoff, John M.; Lesnefsky, Edward J.; Chen, Qun; Zhang, Shijun

2016-01-01

Multiple pathogenic factors have been suggested in playing a role in the development of Alzheimer’s disease (AD). The multifactorial nature of AD also suggests the potential use of compounds with polypharmacology as effective disease-modifying agents. Recently, we have developed a bivalent strategy to include cell membrane anchorage into the molecular design. Our results demonstrated that the bivalent compounds exhibited multifunctional properties and potent neuroprotection in a cellular AD model. Herein, we report the mechanistic exploration of one of the representative bivalent compounds, 17MN, in MC65 cells. Our results established that MC65 cells die through a necroptotic mechanism upon the removal of tetracycline (TC). Furthermore, we have shown that mitochondrial membrane potential (MMP) and cytosolic Ca2+ levels are increased upon removal of TC. Our bivalent compound 17MN can reverse such changes and protect MC65 cells from TC removal induced cytotoxicity. The results also suggest that 17MN may function between the Aβ species and RIPK1 in producing its neuroprotection. Colocalization studies employing a fluorescent analog of 17MN and confocal microscopy demonstrated the interactions of 17MN with both mitochondria and endoplasmic reticulum (ER), thus suggesting that 17MN exerts its neuroprotection via a multiple-site mechanism in MC65 cells. Collectively, these results strongly support our original design rationale of bivalent compounds and encourage further optimization of this bivalent strategy to develop more potent analogs as novel disease-modifying agents for AD. PMID:26401780

Chromatographic test methods for characterizing alkylsiloxane-bonded silica columns for reversed-phase liquid chromatography.

PubMed

Poole, Colin F

2018-06-07

Major obstacles to formulating a simple retention mechanism for reversed-phase liquid chromatography have a direct impact on the development of experimental methods for column characterization as they limit our capability to understand observed differences in retention at a system level. These problems arise from the heterogeneous composition of the stationary phase, the difficulty of providing a working definition for the phase ratio, and uncertainty as to whether the distribution mechanism for varied compounds is a partition, adsorption or mixed (combination) of these models. Retention factor and separation factor measurements offer little guidance as they represent an average of various and variable contributing factors that can only be interpreted by assuming a specific model. Column characterization methods have tended to ignore these difficulties by inventing a series of terms to describe column properties, such as hydrophobicity, hydrophilicity, silanol activity, steric resistance, etc., without proper definition. This has allowed multiple scales to be proposed for the same property which generally are only weakly correlated. Against this background we review the major approaches for the characterization of alkylsiloxane-bonded silica stationary phases employing prototypical compounds, the hydrophobic-subtraction model and the solvation parameter model. Those methods using prototypical compounds are limited by the lack of compounds with a singular dominant interaction. The multivariate approaches that extract column characteristic properties from the retention of varied compounds are more hopeful but it is important to be more precise in defining the characteristic column properties and cognizant that general interpretation of these properties for varied columns cannot escape the problem of a poor understanding of the distribution mechanism. Copyright © 2018 Elsevier B.V. All rights reserved.

Chemical Thermodynamics of Aqueous Atmospheric Aerosols: Modeling and Microfluidic Measurements

NASA Astrophysics Data System (ADS)

Nandy, L.; Dutcher, C. S.

2017-12-01

Accurate predictions of gas-liquid-solid equilibrium phase partitioning of atmospheric aerosols by thermodynamic modeling and measurements is critical for determining particle composition and internal structure at conditions relevant to the atmosphere. Organic acids that originate from biomass burning, and direct biogenic emission make up a significant fraction of the organic mass in atmospheric aerosol particles. In addition, inorganic compounds like ammonium sulfate and sea salt also exist in atmospheric aerosols, that results in a mixture of single, double or triple charged ions, and non-dissociated and partially dissociated organic acids. Statistical mechanics based on a multilayer adsorption isotherm model can be applied to these complex aqueous environments for predictions of thermodynamic properties. In this work, thermodynamic analytic predictive models are developed for multicomponent aqueous solutions (consisting of partially dissociating organic and inorganic acids, fully dissociating symmetric and asymmetric electrolytes, and neutral organic compounds) over the entire relative humidity range, that represent a significant advancement towards a fully predictive model. The model is also developed at varied temperatures for electrolytes and organic compounds the data for which are available at different temperatures. In addition to the modeling approach, water loss of multicomponent aerosol particles is measured by microfluidic experiments to parameterize and validate the model. In the experimental microfluidic measurements, atmospheric aerosol droplet chemical mimics (organic acids and secondary organic aerosol (SOA) samples) are generated in microfluidic channels and stored and imaged in passive traps until dehydration to study the influence of relative humidity and water loss on phase behavior.

Prediction of Multi-Target Networks of Neuroprotective Compounds with Entropy Indices and Synthesis, Assay, and Theoretical Study of New Asymmetric 1,2-Rasagiline Carbamates

PubMed Central

Romero Durán, Francisco J.; Alonso, Nerea; Caamaño, Olga; García-Mera, Xerardo; Yañez, Matilde; Prado-Prado, Francisco J.; González-Díaz, Humberto

2014-01-01

In a multi-target complex network, the links (Lij) represent the interactions between the drug (di) and the target (tj), characterized by different experimental measures (Ki, Km, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (cj). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%–90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally. PMID:25255029

Small molecule correctors of F508del-CFTR discovered by structure-based virtual screening

NASA Astrophysics Data System (ADS)

Kalid, Ori; Mense, Martin; Fischman, Sharon; Shitrit, Alina; Bihler, Hermann; Ben-Zeev, Efrat; Schutz, Nili; Pedemonte, Nicoletta; Thomas, Philip J.; Bridges, Robert J.; Wetmore, Diana R.; Marantz, Yael; Senderowitz, Hanoch

2010-12-01

Folding correctors of F508del-CFTR were discovered by in silico structure-based screening utilizing homology models of CFTR. The intracellular segment of CFTR was modeled and three cavities were identified at inter-domain interfaces: (1) Interface between the two Nucleotide Binding Domains (NBDs); (2) Interface between NBD1 and Intracellular Loop (ICL) 4, in the region of the F508 deletion; (3) multi-domain interface between NBD1:2:ICL1:2:4. We hypothesized that compounds binding at these interfaces may improve the stability of the protein, potentially affecting the folding yield or surface stability. In silico structure-based screening was performed at the putative binding-sites and a total of 496 candidate compounds from all three sites were tested in functional assays. A total of 15 compounds, representing diverse chemotypes, were identified as F508del folding correctors. This corresponds to a 3% hit rate, tenfold higher than hit rates obtained in corresponding high-throughput screening campaigns. The same binding sites also yielded potentiators and, most notably, compounds with a dual corrector-potentiator activity (dual-acting). Compounds harboring both activity types may prove to be better leads for the development of CF therapeutics than either pure correctors or pure potentiators. To the best of our knowledge this is the first report of structure-based discovery of CFTR modulators.

Small molecule dual-inhibitors of TRPV4 and TRPA1 for attenuation of inflammation and pain

PubMed Central

Kanju, Patrick; Chen, Yong; Lee, Whasil; Yeo, Michele; Lee, Suk Hee; Romac, Joelle; Shahid, Rafiq; Fan, Ping; Gooden, David M.; Simon, Sidney A.; Spasojevic, Ivan; Mook, Robert A.; Liddle, Rodger A.; Guilak, Farshid; Liedtke, Wolfgang B.

2016-01-01

TRPV4 ion channels represent osmo-mechano-TRP channels with pleiotropic function and wide-spread expression. One of the critical functions of TRPV4 in this spectrum is its involvement in pain and inflammation. However, few small-molecule inhibitors of TRPV4 are available. Here we developed TRPV4-inhibitory molecules based on modifications of a known TRPV4-selective tool-compound, GSK205. We not only increased TRPV4-inhibitory potency, but surprisingly also generated two compounds that potently co-inhibit TRPA1, known to function as chemical sensor of noxious and irritant signaling. We demonstrate TRPV4 inhibition by these compounds in primary cells with known TRPV4 expression - articular chondrocytes and astrocytes. Importantly, our novel compounds attenuate pain behavior in a trigeminal irritant pain model that is known to rely on TRPV4 and TRPA1. Furthermore, our novel dual-channel blocker inhibited inflammation and pain-associated behavior in a model of acute pancreatitis – known to also rely on TRPV4 and TRPA1. Our results illustrate proof of a novel concept inherent in our prototype compounds of a drug that targets two functionally-related TRP channels, and thus can be used to combat isoforms of pain and inflammation in-vivo that involve more than one TRP channel. This approach could provide a novel paradigm for treating other relevant health conditions. PMID:27247148

Optimization of drying process and pressurized liquid extraction for recovery of bioactive compounds from avocado peel by-product.

PubMed

Figueroa, Jorge G; Borrás-Linares, Isabel; Lozano-Sánchez, Jesús; Quirantes-Piné, Rosa; Segura-Carretero, Antonio

2018-04-16

The aim of the present study was to optimize the extraction of phenolic compounds in avocado peel using pressurized liquid extraction (PLE) with GRAS solvents. Response surface methodology (RSM) based on Central Composite Design 2 2 model was used in order to optimize PLE conditions. Moreover, the effect of air drying temperature on the total polyphenol content (TPC) and individual phenolic compounds concentration were evaluated. The quantification of individual compounds was performed by HPLC-DAD-ESI-TOF-MS. The optimized extraction conditions were 200°C as extraction temperature and 1:1 v/v as ethanol/water ratio. Regarding to the effect of drying, the highest TPC was obtained with a drying temperature of 85°C. Forty seven phenolic compounds were quantified in the obtained extracts, showing that phenolic acids found to be the more stables compounds to drying process, while procyanidins were the more thermolabiles analytes. To our knowledge, this is the first available study in which phenolic compounds extraction was optimized using PLE and such amount of phenolic compounds was quantified in avocado peel. These results confirm that PLE represents a powerful tool to obtain avocado peel extracts with high concentration in bioactive compounds suitable for its use in the food, cosmetic or pharmaceutical sector. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The influence of natural organic matter and cations on the rejection of endocrine disrupting and pharmaceutically active compounds by nanofiltration.

PubMed

Comerton, Anna M; Andrews, Robert C; Bagley, David M

2009-02-01

The impact of natural organic matter (NOM) and cations on the rejection of five endocrine disrupting compounds (EDCs) and pharmaceutically active compounds (PhACs) (acetaminophen, carbamazepine, estrone, gemfibrozil, oxybenzone) by nanofiltration (NF) was examined. The water matrices included membrane bioreactor (MBR) effluent, Lake Ontario water and laboratory-prepared waters modelled to represent the characteristics of the Lake Ontario water. The impact of cations in natural waters on compound rejection was also examined by doubling the natural cation concentration (calcium, magnesium, sodium) in both the Lake Ontario water and the MBR effluent. The presence of Suwannee River NOM spiked into laboratory-grade water was found to cause an increase in compound NF rejection. In addition, the presence of cations alone in laboratory-grade water did not have a significant impact on rejection with the exception of the polar compound gemfibrozil. However, when cation concentration in natural waters was increased, a significant decrease in the rejection of EDCs and PhACs was observed. This suggests that the presence of cations may result in a reduction in the association of EDCs and PhACs with NOM.

Polyvinylpolypyrrolidone reduces cross-reactions between antibodies and phenolic compounds in an enzyme-linked immunosorbent assay for the detection of ochratoxin A.

PubMed

Robinson, Andrew L; Lee, Hyun Jung; Ryu, Dojin

2017-01-01

Ochratoxin A (OTA) is a fungal metabolite and putative carcinogen which can contaminate a variety of foods such as cereals, wine, and nuts. Commercial ELISA kits are known to give false-positive results for OTA concentrations when phenolic compounds are present. Pistachios represent a food matrix rich in phenolic compounds potentially contaminated with OTA, and were used to model OTA cross-reactivity. Polyvinylpolypyrrolidone (PVPP) was incorporated during extraction of OTA using a commercial ELISA protocol. HPLC methods were used to confirm that PVPP does not interact with OTA and levels of gallic acid and catechin remaining in pistachio extracts decreased with increasing PVPP application. Cross-reactivity of extracts also decreased with increasing PVPP application, and color loss was used as an indicator of anthocyanin removal. Incorporating PVPP into ELISA protocols allows for the continued use of rapid immunological methods in food matrices containing phenolic compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

QSAR studies of macrocyclic diterpenes with P-glycoprotein inhibitory activity.

PubMed

Sousa, Inês J; Ferreira, Maria-José U; Molnár, Joseph; Fernandes, Miguel X

2013-02-14

Multidrug resistance (MDR) represents a major limitation for cancer chemotherapy. There are several mechanisms of MDR but the most important is associated with P-glycoprotein (P-gp) overexpression. The development of modulators of P-gp that are able to re-establish drug sensitivity of resistant cells has been considered a promising approach for overcoming MDR. Macrocyclic lathyrane and jatrophane-type diterpenes from Euphorbia species were found to be strong MDR reversing agents. In this study we applied quantitative structure-activity relationship (QSAR) methodology in order to identify the most relevant molecular features of macrocyclic diterpenes with P-gp inhibitory activity and to determine which structural modifications can be performed to improve their activity. Using experimental biological data at two concentrations (4 and 40 μg/ml), we developed a QSAR model for a set of 51 bioactive diterpenic compounds which includes lathyrane and jatrophane-type diterpenes and another model just for jatrophanes. The cross-validation correlation values for all diterpenes QSAR models developed for biological activities at compound concentrations of 4 and 40 μg/ml were 0.758 and 0.729, respectively. Regarding the prediction ability, we get R²(pred) values of 0.765 and 0.534 for biological activities at compound concentrations of 4 and 40 μg/ml, respectively. Applying the cross-validation test to jatrophanes QSAR models, we obtained 0.680 and 0.787 for biological activities at compound concentrations of 4 and 40 μg/ml concentrations, respectively. For the same concentrations, the obtained R²(pred) values for jatrophanes models were 0.541 and 0.534, respectively. The obtained models were statistically valid and showed high prediction ability. Copyright © 2012 Elsevier B.V. All rights reserved.

SAGE Analysis of Transcriptome Responses in Arabidopsis Roots Exposed to 2,4,6-Trinitrotoluene1

PubMed Central

Ekman, Drew R.; Lorenz, W. Walter; Przybyla, Alan E.; Wolfe, N. Lee; Dean, Jeffrey F.D.

2003-01-01

Serial analysis of gene expression was used to profile transcript levels in Arabidopsis roots and assess their responses to 2,4,6-trinitrotoluene (TNT) exposure. SAGE libraries representing control and TNT-exposed seedling root transcripts were constructed, and each was sequenced to a depth of roughly 32,000 tags. More than 19,000 unique tags were identified overall. The second most highly induced tag (27-fold increase) represented a glutathione S-transferase. Cytochrome P450 enzymes, as well as an ABC transporter and a probable nitroreductase, were highly induced by TNT exposure. Analyses also revealed an oxidative stress response upon TNT exposure. Although some increases were anticipated in light of current models for xenobiotic metabolism in plants, evidence for unsuspected conjugation pathways was also noted. Identifying transcriptome-level responses to TNT exposure will better define the metabolic pathways plants use to detoxify this xenobiotic compound, which should help improve phytoremediation strategies directed at TNT and other nitroaromatic compounds. PMID:14551330

Non-target time trend screening: a data reduction strategy for detecting emerging contaminants in biological samples.

PubMed

Plassmann, Merle M; Tengstrand, Erik; Åberg, K Magnus; Benskin, Jonathan P

2016-06-01

Non-targeted mass spectrometry-based approaches for detecting novel xenobiotics in biological samples are hampered by the occurrence of naturally fluctuating endogenous substances, which are difficult to distinguish from environmental contaminants. Here, we investigate a data reduction strategy for datasets derived from a biological time series. The objective is to flag reoccurring peaks in the time series based on increasing peak intensities, thereby reducing peak lists to only those which may be associated with emerging bioaccumulative contaminants. As a result, compounds with increasing concentrations are flagged while compounds displaying random, decreasing, or steady-state time trends are removed. As an initial proof of concept, we created artificial time trends by fortifying human whole blood samples with isotopically labelled standards. Different scenarios were investigated: eight model compounds had a continuously increasing trend in the last two to nine time points, and four model compounds had a trend that reached steady state after an initial increase. Each time series was investigated at three fortification levels and one unfortified series. Following extraction, analysis by ultra performance liquid chromatography high-resolution mass spectrometry, and data processing, a total of 21,700 aligned peaks were obtained. Peaks displaying an increasing trend were filtered from randomly fluctuating peaks using time trend ratios and Spearman's rank correlation coefficients. The first approach was successful in flagging model compounds spiked at only two to three time points, while the latter approach resulted in all model compounds ranking in the top 11 % of the peak lists. Compared to initial peak lists, a combination of both approaches reduced the size of datasets by 80-85 %. Overall, non-target time trend screening represents a promising data reduction strategy for identifying emerging bioaccumulative contaminants in biological samples. Graphical abstract Using time trends to filter out emerging contaminants from large peak lists.

Chronic bioassays of rainbow trout fry with compounds representative of contaminants in Great Lakes fish

USGS Publications Warehouse

Passino-Reader, Dora R.; Berlin, William H.; Hickey, James P.

1995-01-01

To evaluate the hazard of organic compounds detected in Great Lakes fish by gas chromatography/mass spectrometry, we tested compounds representative of heterocyclic nitrogen compounds, polycyclic aromatic hydrocarbons, and cyclic alkanes and alkenes. Sixty-day bioassays on the effects of nicotine, phenanthrene, pinane, and pinene on the behavior, growth, and survival of rainbow trout fry, Oncorhynchus mykiss, were conducted in a large, constant-flow, temperature-controlled water system. The following 60-day LCSO's were determined (mg/L): nicotine 5.0, phenanthrene 0.2, pinane 0.8, and pinene 1.2. Values of lowest observed effects level (LOEL) and no observed effects level (NOEL) showed that growth was generally as sensitive an endpoint as behavior and was more sensitive than time of swim-up. The 60-day LC50 values for rainbow trout were compared with earlier acute bioassays with Daphnia pulexand rainbow trout and chronic bioassays with D.pulex conducted at the Great Lakes Science Center. Rainbow trout fry were less sensitive than daphnids in all tests, indicating that toxicity tests with daphnids should be protective of salmonid fry for these types of compounds. The results for representative compounds indicate that these classes of compounds should be included in aquatic risk assessments at sites in the Great Lakes.

7-MEOTA-donepezil like compounds as cholinesterase inhibitors: Synthesis, pharmacological evaluation, molecular modeling and QSAR studies.

PubMed

Korabecny, Jan; Dolezal, Rafael; Cabelova, Pavla; Horova, Anna; Hruba, Eva; Ricny, Jan; Sedlacek, Lukas; Nepovimova, Eugenie; Spilovska, Katarina; Andrs, Martin; Musilek, Kamil; Opletalova, Veronika; Sepsova, Vendula; Ripova, Daniela; Kuca, Kamil

2014-07-23

A novel series of 7-methoxytacrine (7-MEOTA)-donepezil like compounds was synthesized and tested for their ability to inhibit electric eel acetylcholinesterase (EeAChE), human recombinant AChE (hAChE), equine serum butyrylcholinesterase (eqBChE) and human plasmatic BChE (hBChE). New hybrids consist of a 7-MEOTA unit, representing less toxic tacrine (THA) derivative, connected with analogues of N-benzylpiperazine moieties mimicking N-benzylpiperidine fragment from donepezil. 7-MEOTA-donepezil like compounds exerted mostly non-selective profile in inhibiting cholinesterases of different origin with IC50 ranging from micromolar to sub-micromolar concentration scale. Kinetic analysis confirmed mixed-type inhibition presuming that these inhibitors are capable to simultaneously bind peripheral anionic site (PAS) as well as catalytic anionic site (CAS) of AChE. Molecular modeling studies and QSAR studies were performed to rationalize studies from in vitro. Overall, 7-MEOTA-donepezil like derivatives can be considered as interesting candidates for Alzheimer's disease treatment. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Catalytic oxidative desulfurization of liquid hydrocarbon fuels using air

NASA Astrophysics Data System (ADS)

Sundararaman, Ramanathan

Conventional approaches to oxidative desulfurization of liquid hydrocarbons involve use of high-purity, expensive water soluble peroxide for oxidation of sulfur compounds followed by post-treatment for removal of oxidized sulfones by extraction. Both are associated with higher cost due to handling, storage of oxidants and yield loss with extraction and water separation, making the whole process more expensive. This thesis explores an oxidative desulfurization process using air as an oxidant followed by catalytic decomposition of sulfones thereby eliminating the aforementioned issues. Oxidation of sulfur compounds was realized by a two step process in which peroxides were first generated in-situ by catalytic air oxidation, followed by catalytic oxidation of S compounds using the peroxides generated in-situ completing the two step approach. By this technique it was feasible to oxidize over 90% of sulfur compounds present in real jet (520 ppmw S) and diesel (41 ppmw S) fuels. Screening of bulk and supported CuO based catalysts for peroxide generation using model aromatic compound representing diesel fuel showed that bulk CuO catalyst was more effective in producing peroxides with high yield and selectivity. Testing of three real diesel fuels obtained from different sources for air oxidation over bulk CuO catalyst showed different level of effectiveness for generating peroxides in-situ which was consistent with air oxidation of representative model aromatic compounds. Peroxides generated in-situ was then used as an oxidant to oxidize sulfur compounds present in the fuel over MoO3/SiO2 catalyst. 81% selectivity of peroxides for oxidation of sulfur compounds was observed on MoO3/SiO2 catalyst at 40 °C and under similar conditions MoO3/Al2O3 gave only 41% selectivity. This difference in selectivity might be related to the difference in the nature of active sites of MoO3 on SiO2 and Al2O 3 supports as suggested by H2-TPR and XRD analyses. Testing of supported and bulk MgO catalysts for decomposition of sulfones showed that these catalysts are effective in decomposing oxidized sulfur compounds such as dibenzothiophene sulfone and 3-methyl benzothiophene sulfone to biphenyl and isopropyl benzene respectively and SO2. Study of catalyst structure-activity relationship revealed that in the range of 40--140 nm of MgO, crystallite size plays a critical role on activity of the catalyst for sulfone decomposition. In testing other alkali oxides, it was demonstrated that CaO was effective as a reagent in decomposing oxidized sulfur compounds in a crude oil at a much lower temperature than used for MgO based catalyst. Preliminary data on potential regeneration scheme of spent CaO is also discussed.

In Silico Discovery of Novel Potent Antioxidants on the Basis of Pulvinic Acid and Coumarine Derivatives and Their Experimental Evaluation

PubMed Central

Martinčič, Rok; Mravljak, Janez; Švajger, Urban; Perdih, Andrej; Anderluh, Marko; Novič, Marjana

2015-01-01

A pigment from the edible mushroom Xerocomus badius norbadione A, which is a natural derivative of pulvinic acid, was found to possess antioxidant properties. Since the pulvinic acid represents a novel antioxidant scaffold, several other derivatives were recently synthetized and evaluated experimentally, along with some structurally related coumarine derivatives. The obtained data formed the basis for the construction of several quantitative structure-activity and pharmacophore models, which were employed in the virtual screening experiments of compound libraries and for the prediction of their antioxidant activity, with the goal of discovering novel compounds possessing antioxidant properties. A final prioritization list of 21 novel compounds alongside 8 established antioxidant compounds was created for their experimental evaluation, consisting of the DPPH assay, 2-deoxyribose assay, β-carotene bleaching assay and the cellular antioxidant activity assay. Ten novel compounds from the tetronic acid and barbituric acid chemical classes displayed promising antioxidant activity in at least one of the used assays, that is comparable to or even better than some standard antioxidants. Compounds 5, 7 and 9 displayed good activity in all the assays, and were furthermore effective preventers of oxidative stress in human peripheral blood mononuclear cells, which are promising features for the potential therapeutic use of such compounds. PMID:26474393

A QSAR study of integrase strand transfer inhibitors based on a large set of pyrimidine, pyrimidone, and pyridopyrazine carboxamide derivatives

NASA Astrophysics Data System (ADS)

de Campos, Luana Janaína; de Melo, Eduardo Borges

2017-08-01

In the present study, 199 compounds derived from pyrimidine, pyrimidone and pyridopyrazine carboxamides with inhibitory activity against HIV-1 integrase were modeled. Subsequently, a multivariate QSAR study was conducted with 54 molecules employed by Ordered Predictors Selection (OPS) and Partial Least Squares (PLS) for the selection of variables and model construction, respectively. Topological, electrotopological, geometric, and molecular descriptors were used. The selected real model was robust and free from chance correlation; in addition, it demonstrated favorable internal and external statistical quality. Once statistically validated, the training model was used to predict the activity of a second data set (n = 145). The root mean square deviation (RMSD) between observed and predicted values was 0.698. Although it is a value outside of the standards, only 15 (10.34%) of the samples exhibited higher residual values than 1 log unit, a result considered acceptable. Results of Williams and Euclidean applicability domains relative to the prediction showed that the predictions did not occur by extrapolation and that the model is representative of the chemical space of test compounds.

A site-specific screening comparison of modeled and monitored air dispersion and deposition for perfluorooctanoate.

PubMed

Barton, Catherine A; Zarzecki, Charles J; Russell, Mark H

2010-04-01

This work assessed the usefulness of a current air quality model (American Meteorological Society/Environmental Protection Agency Regulatory Model [AERMOD]) for predicting air concentrations and deposition of perfluorooctanoate (PFO) near a manufacturing facility. Air quality models play an important role in providing information for verifying permitting conditions and for exposure assessment purposes. It is important to ensure traditional modeling approaches are applicable to perfluorinated compounds, which are known to have unusual properties. Measured field data were compared with modeling predictions to show that AERMOD adequately located the maximum air concentration in the study area, provided representative or conservative air concentration estimates, and demonstrated bias and scatter not significantly different than that reported for other compounds. Surface soil/grass concentrations resulting from modeled deposition flux also showed acceptable bias and scatter compared with measured concentrations of PFO in soil/grass samples. Errors in predictions of air concentrations or deposition may be best explained by meteorological input uncertainty and conservatism in the PRIME algorithm used to account for building downwash. In general, AERMOD was found to be a useful screening tool for modeling the dispersion and deposition of PFO in air near a manufacturing facility.

The discovery of new and more potent chloropyramine (C4) analogues for the potential treatment of invasive breast cancer.

PubMed

Kandil, Sahar; Prencipe, Filippo; Jones, Samuel; Hiscox, Stephen; Westwell, Andrew D

2018-01-01

Breast cancer is the second most common cancer worldwide, accounting for 25% of all female cancers. Although the survival rate has increased significantly in the past few decades, patients who develop secondary site metastasis as well as those diagnosed with triple negative breast cancer still represent a real unmet medical challenge. Previous studies have shown that chloropyramine (C4) inhibits FAK-VEGFR3 signalling. More recently, C4 is reported to have SASH1 inducing properties. However, C4 exerts its antitumour and antiangiogenic effects at high micromolar concentrations (>100 μm) that would not be compatible with further drug development against invasive breast cancer driven by FAK signalling. In this study, molecular modelling guided structural modifications have been introduced to the chloropyramine C4 scaffold to improve its activity in breast cancer cell lines. Seventeen compounds were designed and synthesized, and their antiproliferative activity was evaluated against three human breast cancer lines (MDA-MB-231, BT474 and T47D). Compound 5c was identified to display an average activity of IC 50  = 23.5-31.3 μm, which represents a significant improvement of C4 activity in the same assay model. Molecular modelling and pharmacokinetic studies provided more promising insights into the mechanistic features of this new series. © 2017 John Wiley & Sons A/S.

Analysis and hit filtering of a very large library of compounds screened against Mycobacterium tuberculosis.

PubMed

Ekins, Sean; Kaneko, Takushi; Lipinski, Christopher A; Bradford, Justin; Dole, Krishna; Spektor, Anna; Gregory, Kellan; Blondeau, David; Ernst, Sylvia; Yang, Jeremy; Goncharoff, Nicko; Hohman, Moses M; Bunin, Barry A

2010-11-01

There is an urgent need for new drugs against tuberculosis which annually claims 1.7-1.8 million lives. One approach to identify potential leads is to screen in vitro small molecules against Mycobacterium tuberculosis (Mtb). Until recently there was no central repository to collect information on compounds screened. Consequently, it has been difficult to analyze molecular properties of compounds that inhibit the growth of Mtb in vitro. We have collected data from publically available sources on over 300 000 small molecules deposited in the Collaborative Drug Discovery TB Database. A cheminformatics analysis on these compounds indicates that inhibitors of the growth of Mtb have statistically higher mean logP, rule of 5 alerts, while also having lower HBD count, atom count and lower PSA (ChemAxon descriptors), compared to compounds that are classed as inactive. Additionally, Bayesian models for selecting Mtb active compounds were evaluated with over 100 000 compounds and, they demonstrated 10 fold enrichment over random for the top ranked 600 compounds. This represents a promising approach for finding compounds active against Mtb in whole cells screened under the same in vitro conditions. Various sets of Mtb hit molecules were also examined by various filtering rules used widely in the pharmaceutical industry to identify compounds with potentially reactive moieties. We found differences between the number of compounds flagged by these rules in Mtb datasets, malaria hits, FDA approved drugs and antibiotics. Combining these approaches may enable selection of compounds with increased probability of inhibition of whole cell Mtb activity.

In Silico Mining for Antimalarial Structure-Activity Knowledge and Discovery of Novel Antimalarial Curcuminoids.

PubMed

Viira, Birgit; Gendron, Thibault; Lanfranchi, Don Antoine; Cojean, Sandrine; Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre; Maes, Louis; Maran, Uko; Loiseau, Philippe M; Davioud-Charvet, Elisabeth

2016-06-29

Malaria is a parasitic tropical disease that kills around 600,000 patients every year. The emergence of resistant Plasmodium falciparum parasites to artemisinin-based combination therapies (ACTs) represents a significant public health threat, indicating the urgent need for new effective compounds to reverse ACT resistance and cure the disease. For this, extensive curation and homogenization of experimental anti-Plasmodium screening data from both in-house and ChEMBL sources were conducted. As a result, a coherent strategy was established that allowed compiling coherent training sets that associate compound structures to the respective antimalarial activity measurements. Seventeen of these training sets led to the successful generation of classification models discriminating whether a compound has a significant probability to be active under the specific conditions of the antimalarial test associated with each set. These models were used in consensus prediction of the most likely active from a series of curcuminoids available in-house. Positive predictions together with a few predicted as inactive were then submitted to experimental in vitro antimalarial testing. A large majority from predicted compounds showed antimalarial activity, but not those predicted as inactive, thus experimentally validating the in silico screening approach. The herein proposed consensus machine learning approach showed its potential to reduce the cost and duration of antimalarial drug discovery.

Volatile profile analysis and quality prediction of Longjing tea (Camellia sinensis) by HS-SPME/GC-MS

PubMed Central

Lin, Jie; Dai, Yi; Guo, Ya-nan; Xu, Hai-rong; Wang, Xiao-chang

2012-01-01

This study aimed to analyze the volatile chemical profile of Longjing tea, and further develop a prediction model for aroma quality of Longjing tea based on potent odorants. A total of 21 Longjing samples were analyzed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Pearson’s linear correlation analysis and partial least square (PLS) regression were applied to investigate the relationship between sensory aroma scores and the volatile compounds. Results showed that 60 volatile compounds could be commonly detected in this famous green tea. Terpenes and esters were two major groups characterized, representing 33.89% and 15.53% of the total peak area respectively. Ten compounds were determined to contribute significantly to the perceived aroma quality of Longjing tea, especially linalool (0.701), nonanal (0.738), (Z)-3-hexenyl hexanoate (−0.785), and β-ionone (−0.763). On the basis of these 10 compounds, a model (correlation coefficient of 89.4% and cross-validated correlation coefficient of 80.4%) was constructed to predict the aroma quality of Longjing tea. Summarily, this study has provided a novel option for quality prediction of green tea based on HS-SPME/GC-MS technique. PMID:23225852

Relation between chemical composition or antioxidant activity and antihypertensive activity for six essential oils.

PubMed

Yvon, Yan; Raoelison, Emmanuel Guy; Razafindrazaka, René; Randriantsoa, Adolphe; Romdhane, Mehrez; Chabir, Naziha; Mkaddem, Mounira Guedri; Bouajila, Jalloul

2012-08-01

Six essential oils (EOs), Juniperus phoenicea (leaves and berries), Thymus capitatus, Lauris nobilis, Melaleuca armillaris, and Eucalyptus gracilis, were screened for their antioxidant and antihypertensive activity as well as their chemical compositions. We identified and quantified 24 compounds (representing 99.8% of total oil) for J. phoenicea leaves, 14 compounds (representing 98.8% of total oil) for J. phoenicea berries, 11 compounds (representing 99.6% of total oil) for T. capitatus, 32 compounds (representing 98.9% of total oil) for L. nobilis, 32 compounds (representing 98.7% of total oil) for M. armillaris, and 26 compounds (representing 99.3% of total oil) for E. gracilis. In the 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay, the antioxidant activity was in the range of 0.59 to 2183.6 mg/L, whereas T. capitatus (1.24 ± 0.05 mg/L) gave the best activity in the 2,2'-azinobis-3-ethylbenzothiazoline-6-sulfonate assay. Antihypertensive activity was evaluated by testing the vasorelaxing capacity of EOs on rat aorta precontracted by phenylephrine (10(-6) M). T. capitatus and L. nobilis were most active for an antihypertensive activity (29 ± 3 and 59 ± 2 mg/L, respectively). Correlations between chemical composition or antioxidant activity and/or antihypertensive activity were studied. Significant correlation has been found for antihypertensive activity and p-cymene (R(2) = 0.86), β-elemene (R(2) = 0.90), and β-myrcene (R(2) = 0.76). A good correlation has been found between antihypertensive activity and antioxidant activity by DPPH assay (R(2) = 0.98). Antioxidant activity can contribute to the prevention of the increase of the blood pressure. According to the literature, no study has been reported until now of correlation between antihypertensive activity and antioxidant activity. Natural EOs can find its interest and application in a medicinal area. © 2012 Institute of Food Technologists®

Predicting novel substrates for enzymes with minimal experimental effort with active learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pertusi, Dante A.; Moura, Matthew E.; Jeffryes, James G.

Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of enzyme promiscuity. Enzyme promiscuity is currently characterized with a limited number of human-selected compounds that may not be representative of the enzyme's versatility. While testing large numbers of compounds may be impractical, computational approaches can exploit existing data to determine the most informative substrates to test next, thereby more thoroughly exploring an enzyme's versatility. To demonstrate this, we used existing studies and tested compounds for four different enzymes,more » developed support vector machine (SVM) models using these datasets, and selected additional compounds for experiments using an active learning approach. SVMs trained on a chemically diverse set of compounds were discovered to achieve maximum accuracies of similar to 80% using similar to 33% fewer compounds than datasets based on all compounds tested in existing studies. Active learning-selected compounds for testing resolved apparent conflicts in the existing training data, while adding diversity to the dataset. The application of these algorithms to wide arrays of metabolic enzymes would result in a library of SVMs that can predict high-probability promiscuous enzymatic reactions and could prove a valuable resource for the design of novel metabolic pathways.« less

Research in drug development against viral diseases of military importance (biological testing). Volume 2. Final report, 15 November 1985-31 January 1991

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shannon, W.M.; Arnett, G.; Brazier, A.D.

1991-03-01

The purpose of this program is to evaluate the efficacy of candidate antiviral compounds against a spectrum of viruses of military importance. This program involves (a) primary testing of chemical compounds and natural products for antiviral efficacy in vitro using standard CPE-inhibition assays, (b) primary testing of compounds for antiviral efficacy in vivo in animal model systems, and (c) secondary evaluation of the active candidate antiviral compounds. The target viruses for in vitro testing are Vaccinia Virus (VV), Adenovirus (AD2), Vesicular Stomatitis Virus (VSV), Punta Toro Virus (PT), Sandfly fever Virus (SF), Yellow Fever Virus (YF), Venezuelan Equine Encephalomyelitis Virusmore » (VE), Japanese Encephalitis Virus, Pichinde Virus (PIC), Hantaan Virus (HTN), and Human Immunodeficiency Virus (HIV). The in vivo systems are Pichinde Virus infection of hamsters, Venezuelan Equine Encephalomyelitis Virus, Japanese Encephalitis Virus and Vaccinia virus infections of mice. Approximately 10,000 compounds have been received for in vitro evaluation and over 66,000 assays have been performed on this contract. Compounds have been identified in nearly all virus systems that have confirmed antiviral activity equal or exceeding that of the various positive control compounds (ribavirin, selenazofurin, carbocyclic-3-aza-adenosine, adenosine dialdehyde, Ara-A, ddC and AZT). Many of these compounds represent potent and selective new antiviral agents.« less

Predicting novel substrates for enzymes with minimal experimental effort with active learning.

PubMed

Pertusi, Dante A; Moura, Matthew E; Jeffryes, James G; Prabhu, Siddhant; Walters Biggs, Bradley; Tyo, Keith E J

2017-11-01

Enzymatic substrate promiscuity is more ubiquitous than previously thought, with significant consequences for understanding metabolism and its application to biocatalysis. This realization has given rise to the need for efficient characterization of enzyme promiscuity. Enzyme promiscuity is currently characterized with a limited number of human-selected compounds that may not be representative of the enzyme's versatility. While testing large numbers of compounds may be impractical, computational approaches can exploit existing data to determine the most informative substrates to test next, thereby more thoroughly exploring an enzyme's versatility. To demonstrate this, we used existing studies and tested compounds for four different enzymes, developed support vector machine (SVM) models using these datasets, and selected additional compounds for experiments using an active learning approach. SVMs trained on a chemically diverse set of compounds were discovered to achieve maximum accuracies of ~80% using ~33% fewer compounds than datasets based on all compounds tested in existing studies. Active learning-selected compounds for testing resolved apparent conflicts in the existing training data, while adding diversity to the dataset. The application of these algorithms to wide arrays of metabolic enzymes would result in a library of SVMs that can predict high-probability promiscuous enzymatic reactions and could prove a valuable resource for the design of novel metabolic pathways. Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

ProTox: a web server for the in silico prediction of rodent oral toxicity

PubMed Central

Drwal, Malgorzata N.; Banerjee, Priyanka; Dunkel, Mathias; Wettig, Martin R.; Preissner, Robert

2014-01-01

Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein–ligand-based pharmacophore models (‘toxicophores’) for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes. PMID:24838562

Natural products from filamentous fungi and production by heterologous expression.

PubMed

Alberti, Fabrizio; Foster, Gary D; Bailey, Andy M

2017-01-01

Filamentous fungi represent an incredibly rich and rather overlooked reservoir of natural products, which often show potent bioactivity and find applications in different fields. Increasing the naturally low yields of bioactive metabolites within their host producers can be problematic, and yield improvement is further hampered by such fungi often being genetic intractable or having demanding culturing conditions. Additionally, total synthesis does not always represent a cost-effective approach for producing bioactive fungal-inspired metabolites, especially when pursuing assembly of compounds with complex chemistry. This review aims at providing insights into heterologous production of secondary metabolites from filamentous fungi, which has been established as a potent system for the biosynthesis of bioactive compounds. Numerous advantages are associated with this technique, such as the availability of tools that allow enhanced production yields and directing biosynthesis towards analogues of the naturally occurring metabolite. Furthermore, a choice of hosts is available for heterologous expression, going from model unicellular organisms to well-characterised filamentous fungi, which has also been shown to allow the study of biosynthesis of complex secondary metabolites. Looking to the future, fungi are likely to continue to play a substantial role as sources of new pharmaceuticals and agrochemicals-either as producers of novel natural products or indeed as platforms to generate new compounds through synthetic biology.

Chitosan derivatives targeting lipid bilayers: Synthesis, biological activity and interaction with model membranes.

PubMed

Martins, Danubia Batista; Nasário, Fábio Domingues; Silva-Gonçalves, Laiz Costa; de Oliveira Tiera, Vera Aparecida; Arcisio-Miranda, Manoel; Tiera, Marcio José; Dos Santos Cabrera, Marcia Perez

2018-02-01

The antimicrobial activity of chitosan and derivatives to human and plant pathogens represents a high-valued prospective market. Presently, two low molecular weight derivatives, endowed with hydrophobic and cationic character at different ratios were synthesized and characterized. They exhibit antimicrobial activity and increased performance in relation to the intermediate and starting compounds. However, just the derivative with higher cationic character showed cytotoxicity towards human cervical carcinoma cells. Considering cell membranes as targets, the mode of action was investigated through the interaction with model lipid vesicles mimicking bacterial, tumoral and erythrocyte membranes. Intense lytic activity and binding are demonstrated for both derivatives in anionic bilayers. The less charged compound exhibits slightly improved selectivity towards bacterial model membranes, suggesting that balancing its hydrophobic/hydrophilic character may improve efficiency. Observing the aggregation of vesicles, we hypothesize that the "charge cluster mechanism", ascribed to some antimicrobial peptides, could be applied to these chitosan derivatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Active machine learning-driven experimentation to determine compound effects on protein patterns

PubMed Central

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-01-01

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance. DOI: http://dx.doi.org/10.7554/eLife.10047.001 PMID:26840049

Machine learning of atmospheric chemistry. Applications to a global chemistry transport model.

NASA Astrophysics Data System (ADS)

Evans, M. J.; Keller, C. A.

2017-12-01

Atmospheric chemistry is central to many environmental issues such as air pollution, climate change, and stratospheric ozone loss. Chemistry Transport Models (CTM) are a central tool for understanding these issues, whether for research or for forecasting. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (mili-seconds for O(1D) to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a CTM.We have investigated a machine learning approach to solving the differential equations instead of solving them numerically. From an annual simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (random regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry.This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, centennial scale climate simulations etc. We discuss our approches' speed and accuracy, and highlight some potential future directions for improving this approach.

In Vitro Evaluation of Antileishmanial Activity of Computationally Screened Compounds against Ascorbate Peroxidase To Combat Amphotericin B Drug Resistance

PubMed Central

Mansuri, Rani; Kumar, Ashish; Rana, Sindhuprava; Panthi, Bhavana; Ansari, M. Yousuf; Das, Sushmita; Dikhit, Manas Ranjan

2017-01-01

ABSTRACT In visceral leishmaniasis (VL), the host macrophages generate oxidative stress to destroy the pathogen, while Leishmania combats the harmful effect of radicals by redox homeostasis through its unique trypanothione cascade. Leishmania donovani ascorbate peroxidase (LdAPx) is a redox enzyme that regulates the trypanothione cascade and detoxifies the effect of H2O2. The absence of an LdAPx homologue in humans makes it an excellent drug target. In this study, the homology model of LdAPx was built, including heme, and diverse compounds were prefiltered (PAINS, ADMET, and Lipinski's rule of five) and thereafter screened against the LdAPx model. Compounds having good affinity in terms of the Glide XP (extra precision) score were clustered to select diverse compounds for experimental validation. A total of 26 cluster representatives were procured and tested on promastigote culture, yielding 12 compounds with good antileishmanial activity. Out of them, six compounds were safer on the BALB/c peritoneal macrophages and were also effective against disease-causing intracellular amastigotes. Three out of six compounds inhibited recombinant LdAPx in a noncompetitive manner and also demonstrated partial reversion of the resistance property in an amphotericin B (AmB)-resistant strain, which may be due to an increased level of reactive oxygen species (ROS) and decrease of glutathione (GSH) content. However, inhibition of LdAPx in resistant parasites enhanced annexin V staining and activation of metacaspase-like protease activity, which may help in DNA fragmentation and apoptosis-like cell death. Thus, the present study will help in the search for specific hits and templates of potential therapeutic interest and therefore may facilitate the development of new drugs for combination therapy against VL. PMID:28461317

MATRIX-VBS Condensing Organic Aerosols in an Aerosol Microphysics Model

NASA Technical Reports Server (NTRS)

Gao, Chloe Y.; Tsigaridis, Konstas; Bauer, Susanne E.

2015-01-01

The condensation of organic aerosols is represented in a newly developed box-model scheme, where its effect on the growth and composition of particles are examined. We implemented the volatility-basis set (VBS) framework into the aerosol mixing state resolving microphysical scheme Multiconfiguration Aerosol TRacker of mIXing state (MATRIX). This new scheme is unique and advances the representation of organic aerosols in models in that, contrary to the traditional treatment of organic aerosols as non-volatile in most climate models and in the original version of MATRIX, this new scheme treats them as semi-volatile. Such treatment is important because low-volatility organics contribute significantly to the growth of particles. The new scheme includes several classes of semi-volatile organic compounds from the VBS framework that can partition among aerosol populations in MATRIX, thus representing the growth of particles via condensation of low volatility organic vapors. Results from test cases representing Mexico City and a Finish forrest condistions show good representation of the time evolutions of concentration for VBS species in the gas phase and in the condensed particulate phase. Emitted semi-volatile primary organic aerosols evaporate almost completely in the high volatile range, and they condense more efficiently in the low volatility range.

Design of a fragment library that maximally represents available chemical space.

PubMed

Schulz, M N; Landström, J; Bright, K; Hubbard, R E

2011-07-01

Cheminformatics protocols have been developed and assessed that identify a small set of fragments which can represent the compounds in a chemical library for use in fragment-based ligand discovery. Six different methods have been implemented and tested on Input Libraries of compounds from three suppliers. The resulting Fragment Sets have been characterised on the basis of computed physico-chemical properties and their similarity to the Input Libraries. A method that iteratively identifies fragments with the maximum number of similar compounds in the Input Library (Nearest Neighbours) produces the most diverse library. This approach could increase the success of experimental ligand discovery projects, by providing fragments that can be progressed rapidly to larger compounds through access to available similar compounds (known as SAR by Catalog).

ACUTE TOXICITY OF SELECTED ORGANIC COMPOUNDS TO FATHEAD MINNOWS

EPA Science Inventory

Static nonrenewal laboratory bioassays were conducted with 26 organic compounds commonly used by industry. The selected compounds represented the five following chemical classes: acids, alcohols, hydrocarbons, ketones and aldehydes, and phenols. Juvenile fathead minnows (Pimephal...

Novel inhibitor against Malassezia globosa LIP1 (SMG1), a potential anti-dandruff target.

PubMed

Guo, Shaohua; Huang, Wenkang; Zhang, Jian; Wang, Yonghua

2015-09-01

Compelling evidence have demonstrated the role of lipase activity in the pathogenicity of Malassezia globosa toward dandruff and seborrheic dermatitis (D/SD). As a representative secreted lipase from M. globosa CBS 7966, Malassezia globosa LIP1 (SMG1) is considered a potential anti-dandruff target. In this study, homology modeling, docking-based virtual screening and in vitro lipase-based assay were integrated to identify the first hit compound against SMG1, with an IC50 of 20 μM against synthetic lipase substrate, and of 0.19 μM when using natural lipase substrate. Evaluation of similar compounds, along with docking, offered information on the binding patterns of the hit compound. This work is expected to serve as a starting point for the rational design of more potent inhibitors against SMG1. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bromomethylthioindole Inspired Carbazole Hybrids as Promising Class of Anti-MRSA Agents.

PubMed

Cheng, Chia-Yi; Chang, Chun-Ping; Lauderdale, Tsai-Ling Yang; Yu, Guann-Yi; Lee, Jinq-Chyi; Jhang, Yi-Wun; Wu, Chien-Huang; Ke, Yi-Yu; Sadani, Amit A; Yeh, Ching-Fang; Huang, I-Wen; Kuo, Yi-Ping; Tsai, De-Jiun; Yeh, Teng-Kuang; Tseng, Chen-Tso; Song, Jen-Shin; Liu, Yu-Wei; Tsou, Lun K; Shia, Kak-Shan

2016-12-08

Series of N -substituted carbazole analogues bearing an indole ring were synthesized as anti-methicillin-resistant Staphylococcus aureus (MRSA) agents from a molecular hybridization approach. The representative compound 19 showed an MIC = 1 μg/mL against a panel of MRSA clinical isolates as it possessed comparable in vitro activities to that of vancomycin. Moreover, compound 19 also exhibited MIC = 1 μg/mL activities against a recent identified Z172 MRSA strain (vancomycin-intermediate and daptomycin-nonsusceptible phenotype) and the vancomycin-resistant Enterococcus faecalis (VRE) strain. In a mouse model with lethal infection of MRSA (4N216), a 75% survival rate was observed after a single dose of compound 19 was intravenously administered at 20 mg/kg. In light of their equipotent activities against different MRSA isolates and VRE strain, the data underscore the importance of designed hybrid series for the development of new N -substituted carbazoles as potential anti-MRSA agents.

The Apollo program and amino acids. [precursors significance in molecular evolution

NASA Technical Reports Server (NTRS)

Fox, S. W.

1973-01-01

Apollo lunar sample analyses designed to detect the presence of organic compounds are reviewed, and the results are discussed from the viewpoint of relevance to laboratory experiments on the synthesis of amino acids and to theoretical models of cosmochemical processes resulting in the formation of organic compounds. Glycine, alanine, glutamic acid, aspartic acid, serine, and threonine have been found repeatedly in the hydrolyzates of hot aqueous extracts of lunar dust. These compounds represent an early step in the sequence of events leading to the rise of living material and were probably deposited by the solar wind. The results of the Apollo program so far suggest that the pathway from cosmic organic matter to life as it evolved on earth could have been pursued on the moon to the stage of amino acid precursors and then may have been terminated for lack of sufficient water.

New tacrine-dihydropyridine hybrids that inhibit acetylcholinesterase, calcium entry, and exhibit neuroprotection properties.

PubMed

León, Rafael; de los Ríos, Cristóbal; Marco-Contelles, José; Huertas, Oscar; Barril, Xavier; Luque, F Javier; López, Manuela G; García, Antonio G; Villarroya, Mercedes

2008-08-15

In this communication, we describe the synthesis and biological evaluation of tacripyrimedones 1-5, a series of new tacrine-1,4-dihydropyridine hybrids bearing the general structure of 11-amino-12-aryl-3,3-dimethyl-3,4,5,7,8,9,10,12-octahydrodibenzo[b,g][1,8]naphthyridine-1(2H)-one. These multifunctional compounds are moderately potent and selective AChEIs, with no activity toward BuChE. Kinetic analysis and molecular modeling studies point out that the new compounds preferentially bind the peripheral anionic site of AChE. In addition, compounds 1-5 show an excellent neuroprotective profile, and a moderate blocking effect of L-type voltage-dependent calcium channels due to the mitigation of [Ca(2+)] elevation elicited by K(+) depolarization. Therefore, they represent a new family of molecules with potential therapeutic application for the treatment of Alzheimer's disease.

Physiologically based pharmacokinetic model for quinocetone in pigs and extrapolation to mequindox.

PubMed

Zhu, Xudong; Huang, Lingli; Xu, Yamei; Xie, Shuyu; Pan, Yuanhu; Chen, Dongmei; Liu, Zhenli; Yuan, Zonghui

2017-02-01

Physiologically based pharmacokinetic (PBPK) models are scientific methods used to predict veterinary drug residues that may occur in food-producing animals, and which have powerful extrapolation ability. Quinocetone (QCT) and mequindox (MEQ) are widely used in China for the prevention of bacterial infections and promoting animal growth, but their abuse causes a potential threat to human health. In this study, a flow-limited PBPK model was developed to simulate simultaneously residue depletion of QCT and its marker residue dideoxyquinocetone (DQCT) in pigs. The model included compartments for blood, liver, kidney, muscle and fat and an extra compartment representing the other tissues. Physiological parameters were obtained from the literature. Plasma protein binding rates, renal clearances and tissue/plasma partition coefficients were determined by in vitro and in vivo experiments. The model was calibrated and validated with several pharmacokinetic and residue-depletion datasets from the literature. Sensitivity analysis and Monte Carlo simulations were incorporated into the PBPK model to estimate individual variation of residual concentrations. The PBPK model for MEQ, the congener compound of QCT, was built through cross-compound extrapolation based on the model for QCT. The QCT model accurately predicted the concentrations of QCT and DQCT in various tissues at most time points, especially the later time points. Correlation coefficients between predicted and measured values for all tissues were greater than 0.9. Monte Carlo simulations showed excellent consistency between estimated concentration distributions and measured data points. The extrapolation model also showed good predictive power. The present models contribute to improve the residue monitoring systems of QCT and MEQ, and provide evidence of the usefulness of PBPK model extrapolation for the same kinds of compounds.

Synthesis and exploration of QSAR model of 2-methyl-3-[2-(2-methylprop-1-en-1-yl)-1H-benzimidazol-1-yl]pyrimido[1,2-a]benzimidazol-4(3H)-one as potential antibacterial agents.

PubMed

Sharma, Pratibha; Kumar, Ashok; Sharma, Manisha; Singh, Jitendra; Bandyopadhyay, Prabal; Sathe, Manisha; Kaushik, M P

2012-04-01

Present communication deals with the synthesis of novel 2-methyl-3-[2-(2-methylprop-1-en-1-yl)-1H-benzimidazol-1-yl]pyrimido[1,2-a]benzimidazol-4(3H)-one derivatives under phase transfer catalysis (PTC) conditions using benzyl triethyl ammonium chloride (BTEAC) as PTC. It also elicits the studies on in vitro antimicrobial evaluation of synthesized compounds against a representative genera of gram-negative and gram-positive bacteria i.e., Bacillus subtilis, Staphylococcus aureus, Pseudomonas diminuta and Escherichia coli. All the compounds have been found to manifest profound antimicrobial activity. Moreover, extensive quantitative structure-activity relationship (QSAR) studies have been performed to deduce a correlation between molecular descriptors under consideration and the elicited biological activity. A tri-parametric QSAR model has been generated upon rigorous statistical treatment.

Preventing the return of smallpox: molecular modeling studies on thymidylate kinase from Variola virus.

PubMed

Guimarães, Ana Paula; Ramalho, Teodorico Castro; França, Tanos Celmar Costa

2014-01-01

Smallpox was one of the most devastating diseases in the human history and still represents a serious menace today due to its potential use by bioterrorists. Considering this threat and the non-existence of effective chemotherapy, we propose the enzyme thymidylate kinase from Variola virus (VarTMPK) as a potential target to the drug design against smallpox. We first built a homology model for VarTMPK and performed molecular docking studies on it in order to investigate the interactions with inhibitors of Vaccinia virus TMPK (VacTMPK). Subsequently, molecular dynamics (MD) simulations of these compounds inside VarTMPK and human TMPK (HssTMPK) were carried out in order to select the most promising and selective compounds as leads for the design of potential VarTMPK inhibitors. Results of the docking and MD simulations corroborated to each other, suggesting selectivity towards VarTMPK and, also, a good correlation with the experimental data.

Integrated ecological and chemical food web accumulation modeling explains PAH temporal trends during regime shifts in a shallow lake.

PubMed

Kong, Xiangzhen; He, Wei; Qin, Ning; Liu, Wenxiu; Yang, Bin; Yang, Chen; Xu, Fuliu; Mooij, Wolf M; Koelmans, Albert A

2017-08-01

Shallow lakes can switch suddenly from a turbid situation with high concentrations of phytoplankton and other suspended solids to a vegetated state with clear water, and vice versa. These alternative stable states may have a substantial impact on the fate of hydrophobic organic compounds (HOCs). Models that are fit to simulate impacts from these complex interactions are scarce. We developed a contaminant fate model which is linked to an ecosystem model (PCLake) for shallow lakes. This integrated model was successful in simulating long-term dynamics (1953-2012) of representative polycyclic aromatic hydrocarbons (PAHs) in the main biotic and abiotic components in a large shallow lake (Chaohu in China), which has undergone regime shifts in this period. Historical records from sediment cores were used to evaluate the model. The model revealed that regime shifts in shallow lakes had a strong impact on the fate of less hydrophobic compounds due to the large storage capacity of macrophytes, which accumulated up to 55.6% of phenanthrene in the clear state. The abrupt disappearance of macrophytes after the regime shift resulted in a sudden change in phenanthrene distribution, as the sediment became the major sink. For more hydrophobic compounds such as benzo(a)pyrene, the modeled impact of the regime shift was negligible for the whole environment, yet large for biotic compartments. This study is the first to provide a full mechanistic analysis of the impact of regime shifts on the fate of PAHs in a real lake ecosystem. Copyright © 2017 Elsevier Ltd. All rights reserved.

Organic Compounds Complexify Transport in the Amargosa Desert—The Case for Phytotritiation

NASA Astrophysics Data System (ADS)

Stonestrom, D. A.; Luo, W.; Andraski, B. J.; Baker, R. J.; Maples, S.; Mayers, C. J.; Young, M. B.

2014-12-01

Civilian low-level radioactive waste containing organic compounds was disposed in 2- to 15-m deep unlined trenches in a 110-m deep unsaturated zone at the present-day USGS Amargosa Desert Research Site. Tritium represents the plurality of disposed activity. A plume of gas-phase contaminants surrounds the disposal area, with 60 distinct volatile organic compounds (VOCs) identified to date. The distribution of tritiated water in the unsaturated zone surrounding the disposal area is highly enigmatic, with orders of magnitude separating observed levels from those predicted by multiphase models of mass and energy transport. Peaks of tritium and VOCs are coincidently located in sediments tens of meters below the root zone, suggesting abiotic stratigraphic control on lateral transport at depth. Surprisingly, the highest observed levels of tritium occur at a depth of about 1.5 m, the base of the creosote-bush plant-community root zone, where levels of waste-derived VOCs are low (approaching atmospheric levels). Bulk water-vapor samples from shallow and deep unsaturated-zone profile hot spots were trapped as water ice in cold fingers immersed in dry ice-isopropyl alcohol filled Dewar flasks, then melted and sequentially extracted by purge-and-trap VOC degassing followed by elution through activated carbon solid-phase extraction (SPE) cartridges. Analysis of tritium activities and mass spectrometer results indicate that over 98% of tritium activity at depth is present as water, whereas about 15% of basal root zone tritium activity is present as organic compounds trapped with the water. Of these, the less-volatile compound group removed by SPE accounted for about 85% of the organic tritium activity, with mass spectrometry identifying 2-ethyl-1-hexanol as the principal compound removed. This plant-produced fatty alcohol is ubiquitous in the root zone of creosote-bush communities and represents a family of hydroxyl-containing plant produced compounds that give the plants their pungency. These findings suggest that tritiated hydroxyl groups on plant-produced organic compounds provide an important reservoir and pathway for tritium transport.

Mimicking the Impact of Infant Tongue Peristalsis on Behavior of Solid Oral Dosage Forms Administered During Breastfeeding.

PubMed

Scheuerle, Rebekah L; Kendall, Richard A; Tuleu, Catherine; Slater, Nigel K H; Gerrard, Stephen E

2017-01-01

An in vitro simulation system was developed to study the effect of an infant's peristaltic tongue motion during breastfeeding on oral rapidly disintegrating tablets in the mouth, for use in rapid product candidate screening. These tablets are being designed for use inside a modified nipple shield worn by a mother during breastfeeding, a proposed novel platform technology to administer drugs and nutrients to breastfeeding infants. In this study, the release of a model compound, sulforhodamine B, from tablet formulations was studied under physiologically relevant forces induced by compression and rotation of a tongue mimic. The release profiles of the sulforhodamine B in flowing deionized water were found to be statistically different using 2-way ANOVA with matching, when tongue mimic rotation was introduced for 2 compression levels representing 2 tongue strengths (p = 0.0013 and p < 0.0001 for the lower and higher compression settings, respectively). Compression level was found to be a significant factor for increasing model compound release at rotational rates representing nonnutritive breastfeeding (p = 0.0162). This novel apparatus is the first to simulate the motion and pressures applied by the tongue and could be used in future infant oral product development. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Best of both worlds: combining pharma data and state of the art modeling technology to improve in Silico pKa prediction.

PubMed

Fraczkiewicz, Robert; Lobell, Mario; Göller, Andreas H; Krenz, Ursula; Schoenneis, Rolf; Clark, Robert D; Hillisch, Alexander

2015-02-23

In a unique collaboration between a software company and a pharmaceutical company, we were able to develop a new in silico pKa prediction tool with outstanding prediction quality. An existing pKa prediction method from Simulations Plus based on artificial neural network ensembles (ANNE), microstates analysis, and literature data was retrained with a large homogeneous data set of drug-like molecules from Bayer. The new model was thus built with curated sets of ∼14,000 literature pKa values (∼11,000 compounds, representing literature chemical space) and ∼19,500 pKa values experimentally determined at Bayer Pharma (∼16,000 compounds, representing industry chemical space). Model validation was performed with several test sets consisting of a total of ∼31,000 new pKa values measured at Bayer. For the largest and most difficult test set with >16,000 pKa values that were not used for training, the original model achieved a mean absolute error (MAE) of 0.72, root-mean-square error (RMSE) of 0.94, and squared correlation coefficient (R(2)) of 0.87. The new model achieves significantly improved prediction statistics, with MAE = 0.50, RMSE = 0.67, and R(2) = 0.93. It is commercially available as part of the Simulations Plus ADMET Predictor release 7.0. Good predictions are only of value when delivered effectively to those who can use them. The new pKa prediction model has been integrated into Pipeline Pilot and the PharmacophorInformatics (PIx) platform used by scientists at Bayer Pharma. Different output formats allow customized application by medicinal chemists, physical chemists, and computational chemists.

Production of fermentation aroma compounds by Saccharomyces cerevisiae wine yeasts: effects of yeast assimilable nitrogen on two model strains.

PubMed

Carrau, Francisco M; Medina, Karina; Farina, Laura; Boido, Eduardo; Henschke, Paul A; Dellacassa, Eduardo

2008-11-01

The contribution of yeast fermentation metabolites to the aromatic profile of wine is well documented; however, the biotechnological application of this knowledge, apart from strain selection, is still rather limited and often contradictory. Understanding and modeling the relationship between nutrient availability and the production of desirable aroma compounds by different strains must be one of the main objectives in the selection of industrial yeasts for the beverage and food industry. In order to overcome the variability in the composition of grape juices, we have used a chemically defined model medium for studying yeast physiological behavior and metabolite production in response to nitrogen supplementation so as to identify an appropriate yeast assimilable nitrogen level for strain differentiation. At low initial nitrogen concentrations, strain KU1 produced higher quantities of esters and fatty acids whereas M522 produced higher concentrations of isoacids, gamma-butyrolactone, higher alcohols and 3-methylthio-1-propanol. We propose that although strains KU1 and M522 have a similar nitrogen consumption profile, they represent useful models for the chemical characterization of wine strains in relation to wine quality. The differential production of aroma compounds by the two strains is discussed in relation to their capacity for nitrogen usage and their impact on winemaking. The results obtained here will help to develop targeted metabolic footprinting methods for the discrimination of industrial yeasts.

Prediction of multi-target networks of neuroprotective compounds with entropy indices and synthesis, assay, and theoretical study of new asymmetric 1,2-rasagiline carbamates.

PubMed

Romero Durán, Francisco J; Alonso, Nerea; Caamaño, Olga; García-Mera, Xerardo; Yañez, Matilde; Prado-Prado, Francisco J; González-Díaz, Humberto

2014-09-24

In a multi-target complex network, the links (L(ij)) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K(i), K(m), IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity.

PubMed

Vyas, V K; Qureshi, G; Ghate, M; Patel, H; Dalai, S

2016-06-01

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC50 values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere-Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a QFIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

[The use of complex interval models for predicting activity of non-nucleoside reverse transcriptase activity].

PubMed

Burliaeva, E V; Tarkhov, A E; Burliaev, V V; Iurkevich, A M; Shvets, V I

2002-01-01

Searching of new anti-HIV agents is still crucial now. In general, researches are looking for inhibitors of certain HIV's vital enzymes, especially for reverse transcriptase (RT) inhibitors. Modern generation of anti-HIV agents represents non-nucleoside reverse transcriptase inhibitors (NNRTIs). They are much less toxic than nucleoside analogues and more chemically stable, thus being slower metabolized and emitted from the human body. Thus, search of new NNRTIs is actual today. Synthesis and study of new anti-HIV drugs is very expensive. So employment of the activity prediction techniques for such a search is very beneficial. This technique allows predicting the activities for newly proposed structures. It is based on the property model built by investigation of a series of known compounds with measured activity. This paper presents an approach of activity prediction based on "structure-activity" models designed to form a hypothesis about probably activity interval estimate. This hypothesis formed is based on structure descriptor domains, calculated for all energetically allowed conformers for each compound in the studied sef. Tetrahydroimidazobenzodiazipenone (TIBO) derivatives and phenylethyltiazolyltiourea (PETT) derivatives illustrated the predictive power of this method. The results are consistent with experimental data and allow to predict inhibitory activity of compounds, which were not included into the training set.

Quantitative structure-retention relationship models for the prediction of the reversed-phase HPLC gradient retention based on the heuristic method and support vector machine.

PubMed

Du, Hongying; Wang, Jie; Yao, Xiaojun; Hu, Zhide

2009-01-01

The heuristic method (HM) and support vector machine (SVM) were used to construct quantitative structure-retention relationship models by a series of compounds to predict the gradient retention times of reversed-phase high-performance liquid chromatography (HPLC) in three different columns. The aims of this investigation were to predict the retention times of multifarious compounds, to find the main properties of the three columns, and to indicate the theory of separation procedures. In our method, we correlated the retention times of many diverse structural analytes in three columns (Symmetry C18, Chromolith, and SG-MIX) with their representative molecular descriptors, calculated from the molecular structures alone. HM was used to select the most important molecular descriptors and build linear regression models. Furthermore, non-linear regression models were built using the SVM method; the performance of the SVM models were better than that of the HM models, and the prediction results were in good agreement with the experimental values. This paper could give some insights into the factors that were likely to govern the gradient retention process of the three investigated HPLC columns, which could theoretically supervise the practical experiment.

Synthesis and bioactivities of halogen bearing phenolic chalcones and their corresponding bis Mannich bases.

PubMed

Yamali, Cem; Gul, Halise Inci; Sakagami, Hiroshi; Supuran, Claudiu T

2016-01-01

Phenolic bis Mannich bases having the chemical structure of 1-[3,5-bis-aminomethyl-4-hydroxyphenyl]-3-(4-halogenophenyl)-2-propen-1-ones (1a-c, 2a-c, 3a-c) were synthesized (Numbers 1, 2, and 3 represent fluorine, chlorine, and bromine bearing compounds, respectively, while a, b, and c letters represent the compounds having piperidine, morpholine, and N-methyl piperazine) and their cytotoxic and carbonic anhydrase (CA, EC 4.2.1.1) enzyme inhibitory effects were evaluated. Lead compounds should possess both marked cytotoxic potencies and selective toxicity for tumors. To reflect this potency, PSE values of the compounds were calculated. According to PSE values, the compounds 2b and 3b may serve as lead molecules for further anticancer drug candidate developments. Although the compounds showed a low inhibition potency toward hCA I (25-43%) and hCA II (6-25%) isoforms at 10 μM concentration of inhibitor, the compounds were more selective (1.5-5.2 times) toward hCA I isoenzyme. It seems that the compounds need molecular modifications for the development of better CA inhibitors.

Mixing of sulfur between pyritic and organic phases during coal conversion processes: Annual final report, March 1, 1986-February 28, 1987

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunkerton, L.V.; Nigam, A.; Mitra, S.

1987-05-01

In preparation for using /sup 33/S NMR for characterization of organic sulfur types in coal, previously prepared substituted dibenzothiophene model compounds were converted to their corresponding sulfones and their sulfur-33 nmr recorded. The sulfur-33 NMR spectra of dibenzothiophene-5,5-dioxide (2), 2-(p-methylphenylsulfonyl) dibenzothiophene-5,5-dioxide (4), and 2-(methylsulfonyl) dibenzothiophene-5,5-dioxide (6) are reported. The chemical shifts were in the +2 to -21 ppM range. The line widths ranged 70 to 200 Hz. The changes in /sup 13/C chemical shift experienced by aromatic carbons upon oxidizing the sulfide to its sulfone were also studied and the data used to identify which sulfone was formed in multiplemore » thioether-containing aromatics after partial oxidation. Continuing results on the use of the substituted dibenzothiophenes to monitor mixing of sulfur between pyritic and organic phases are also reported. Non-isothermal hydrodesulfurization of model organic sulfur compounds was carried out in a cola-like environment. The model sulfur compounds represented different types of carbon-sulfur bonds commonly encountered in coal. Similar experiments were carried out in the presence of troilite (iron sulfide) to investigate the possibility of sulfur migration from the organic compound to the iron sulfide. Next, iron pyrite was hydrodesulfurized in the presence of some organic molecules to see if sulfur could be incorporated into the organic molecules during the process. Results show that sulfur from organic compounds can be absorbed by troilite, and, similarly, sulfur from pyrite can form new carbon-sulfur bonds during hydrodesulfurization. Based on these observations, it is suggested that during coal conversion reactions it is possible to have intermigration of sulfur between the organic and the inorganic phases.« less

Assessment on personal exposure to particulate compounds using an empirical exposure model in an elderly community in Tianjin, China.

PubMed

Xu, Jia; Zhang, Nan; Han, Bin; You, Yan; Zhou, Jian; Zhang, Jiefeng; Niu, Can; Liu, Yating; He, Fei; Ding, Xiao; Bai, Zhipeng

2016-12-01

Using central site measurement data to predict personal exposure to particulate matter (PM) is challenging, because people spend most of their time indoors and ambient contribution to personal exposure is subject to infiltration conditions affected by many factors. Efforts in assessing and predicting exposure on the basis of associated indoor/outdoor and central site monitoring were limited in China. This study collected daily personal exposure, residential indoor/outdoor and community central site PM filter samples in an elderly community during the non-heating and heating periods in 2009 in Tianjin, China. Based on the chemical analysis results of particulate species, mass concentrations of the particulate compounds were estimated and used to reconstruct the PM mass for mass balance analysis. The infiltration factors (F inf ) of particulate compounds were estimated using both robust regression and mixed effect regression methods, and further estimated the exposure factor (F pex ) according to participants' time-activity patterns. Then an empirical exposure model was developed to predict personal exposure to PM and particulate compounds as the sum of ambient and non-ambient contributions. Results showed that PM mass observed during the heating period could be well represented through chemical mass reconstruction, because unidentified mass was minimal. Excluding the high observations (>300μg/m 3 ), this empirical exposure model performed well for PM and elemental carbon (EC) that had few indoor sources. These results support the use of F pex as an indicator for ambient contribution predictions, and the use of empirical non-ambient contribution to assess exposure to particulate compounds. Copyright © 2016 Elsevier B.V. All rights reserved.

Ultra‐high performance supercritical fluid chromatography of lignin‐derived phenols from alkaline cupric oxide oxidation

PubMed Central

Sun, Mingzhe; Lidén, Gunnar; Sandahl, Margareta

2016-01-01

Traditional chromatographic methods for the analysis of lignin‐derived phenolic compounds in environmental samples are generally time consuming. In this work, an ultra‐high performance supercritical fluid chromatography method with a diode array detector for the analysis of major lignin‐derived phenolic compounds produced by alkaline cupric oxide oxidation was developed. In an analysis of a collection of 11 representative monomeric lignin phenolic compounds, all compounds were clearly separated within 6 min with excellent peak shapes, with a limit of detection of 0.5–2.5 μM, a limit of quantification of 2.5–5.0 μM, and a dynamic range of 5.0–2.0 mM (R 2 > 0.997). The new ultra‐high performance supercritical fluid chromatography method was also applied for the qualitative and quantitative analysis of lignin‐derived phenolic compounds obtained upon alkaline cupric oxide oxidation of a commercial humic acid. Ten out of the previous eleven model compounds could be quantified in the oxidized humic acid sample. The high separation power and short analysis time obtained demonstrate for the first time that supercritical fluid chromatography is a fast and reliable technique for the analysis of lignin‐derived phenols in complex environmental samples. PMID:27452148

The incorporation of butyrophenones and related compounds into a pharmacophore for dopamine D2 antagonists.

PubMed

Froimowitz, M; Cody, V

1997-08-01

This study is an attempt to incorporate the butyrophenones, an important class of nontricyclic antipsychotic drugs, into a previously proposed pharmacophore model of tricyclic dopamine D2 receptor antagonist ligands. Conformational energy calculations were performed using the MM3-92 program on spiperone, as a representative butyrophenone, and milenperone and R48455, as related compounds with more limited conformational freedom. Twenty seven conformers were evaluated for spiperone with MM3-92 calculations and nine of these were within 1.1 kcal/mole of the global minima indicating the flexibility of the compound. A conformational analysis of twenty crystal structures of butyrophenones was also performed and six distinct conformers were represented. All of the energy minimized conformers of spiperone were superimposed in a least squares sense onto loxapine as a relatively rigid, typical D2 antagonist and a pair of mirror image conformers, which are observed in one crystal structure of spiperone, were found to be the best fit. However, it was not possible to discriminate between these two conformers since they fit the pharmacophore model equally well. The para-fluoro and carbonyl group of the butyrophenones were found to correspond best to the oxygen and chlorine atoms of loxapine, respectively. The conformations of milenperone and R48455 were also consistent with the two putative biologically active forms of spiperone and the pharmacophore model. Conformational energy calculations were also performed on molindone, an antipsychotic drug in clinical use, which can be related to the butyrophenones since both have a carbonyl group adjacent to an aromatic ring. A putative biologically active form was proposed for molindone and this was related to the structure of piquindone, a rigid analog of molindone. All of the compounds were found to be entirely consistent with the pharmacophore model. However, as previously found, there is great variability in the distance between the ammonium nitrogen and the center of the relevant aromatic ring with the most extreme case in the present study being R48455 where the distance is 7.2 A. The results of the present study should also be relevant to the structures of novel, atypical antipsychotic drugs such as risperidone which appear to be analogs of the butyrophenones.

Surgical Management of Compound Odontoma Associated with Unerupted Tooth

PubMed Central

Marini, Roberta; Pacifici, Luciano

2015-01-01

Odontomas represent the most common type of odontogenic benign jaws tumors among patients younger than 20 years of age. These tumors are composed of enamel, dentine, cementum, and pulp tissue. According to the World Health Organization classification, two distinct types of odontomas are acknowledged: complex and compound odontoma. In complex odontomas, all dental tissues are formed, but appeared without an organized structure. In compound odontomas, all dental tissues are arranged in numerous tooth-like structures known as denticles. Compound odontomas are often associated with impacted adjacent permanent teeth and their surgical removal represents the best therapeutic option. A case of a 20-year-old male patient with a compound odontoma-associated of impacted maxillary canine is presented. A minimally invasive surgical technique is adopted to remove the least amount of bone tissue as far as possible. PMID:26199762

An urban photochemistry study in Santiago de Chile

NASA Astrophysics Data System (ADS)

Rappenglück, B.; Schmitz, R.; Bauerfeind, M.; Cereceda-Balic, F.; von Baer, D.; Jorquera, H.; Silva, Y.; Oyola, P.

During spring time 2002 a field experiment was carried out in the Metropolitan Area of Santiago de Chile at three monitoring sites located along a SW-NE transect that represents upwind, downtown and downwind conditions, respectively. Three consecutive days (30 October-01 November 2002) reflecting different photochemical and meteorological conditions were selected. These days included two workdays and one holiday and thus the effect of different primary emissions could be investigated. A variety of trace gas measurements (O 3, NO x, CO, volatile organic compounds (VOC)) were obtained at these sites. Alkanes represent the largest VOC fraction at all sites, followed by aromatics and alkenes, the smallest fractions are represented by the alkynes or isoprene. Regarding reactivity ranking propene equivalent values show that during morning hours, alkenes are the most reactive compounds, at noon, aromatics are dominant, and in the afternoon isoprene becomes important. Alkanes do not contribute more than 20% to the total air mass reactivity despite being present at the higher concentration levels. Regarding liquefied petroleum gas (LPG) impacts, we find a threefold decrease of concentrations at the eastern side of the city—and no significant trend at Downtown Santiago—which we ascribe to a switch to natural gas in the higher income eastern side of town. The generation of ozone impacts above 50 ppbv is mainly due to anthropogenic traffic-related hydrocarbons. In addition, traffic emissions are contributing most to the formation of secondary organic aerosols (SOA). A model study was carried out, applying a Lagrange trajectory model coupled with photochemical and aerosol modules. The model results are in good agreement with the observations. Additionally, the relative contribution of the respective hydrocarbons to the ozone production in an air parcel along the trajectory was computed. The model also indicates SOA formation by means of oxidation of higher alkanes, alkenes, and aromatics, the latter being the major contributors to those secondary pollutants.

An amphiphilic graft copolymer-based nanoparticle platform for reduction-responsive anticancer and antimalarial drug delivery

NASA Astrophysics Data System (ADS)

Najer, Adrian; Wu, Dalin; Nussbaumer, Martin G.; Schwertz, Geoffrey; Schwab, Anatol; Witschel, Matthias C.; Schäfer, Anja; Diederich, François; Rottmann, Matthias; Palivan, Cornelia G.; Beck, Hans-Peter; Meier, Wolfgang

2016-08-01

Medical applications of anticancer and antimalarial drugs often suffer from low aqueous solubility, high systemic toxicity, and metabolic instability. Smart nanocarrier-based drug delivery systems provide means of solving these problems at once. Herein, we present such a smart nanoparticle platform based on self-assembled, reduction-responsive amphiphilic graft copolymers, which were successfully synthesized through thiol-disulfide exchange reaction between thiolated hydrophilic block and pyridyl disulfide functionalized hydrophobic block. These amphiphilic graft copolymers self-assembled into nanoparticles with mean diameters of about 30-50 nm and readily incorporated hydrophobic guest molecules. Fluorescence correlation spectroscopy (FCS) was used to study nanoparticle stability and triggered release of a model compound in detail. Long-term colloidal stability and model compound retention within the nanoparticles was found when analyzed in cell media at body temperature. In contrast, rapid, complete reduction-triggered disassembly and model compound release was achieved within a physiological reducing environment. The synthesized copolymers revealed no intrinsic cellular toxicity up to 1 mg mL-1. Drug-loaded reduction-sensitive nanoparticles delivered a hydrophobic model anticancer drug (doxorubicin, DOX) to cancer cells (HeLa cells) and an experimental, metabolically unstable antimalarial drug (the serine hydroxymethyltransferase (SHMT) inhibitor (+/-)-1) to Plasmodium falciparum-infected red blood cells (iRBCs), with higher efficacy compared to similar, non-sensitive drug-loaded nanoparticles. These responsive copolymer-based nanoparticles represent a promising candidate as smart nanocarrier platform for various drugs to be applied to different diseases, due to the biocompatibility and biodegradability of the hydrophobic block, and the protein-repellent hydrophilic block.Medical applications of anticancer and antimalarial drugs often suffer from low aqueous solubility, high systemic toxicity, and metabolic instability. Smart nanocarrier-based drug delivery systems provide means of solving these problems at once. Herein, we present such a smart nanoparticle platform based on self-assembled, reduction-responsive amphiphilic graft copolymers, which were successfully synthesized through thiol-disulfide exchange reaction between thiolated hydrophilic block and pyridyl disulfide functionalized hydrophobic block. These amphiphilic graft copolymers self-assembled into nanoparticles with mean diameters of about 30-50 nm and readily incorporated hydrophobic guest molecules. Fluorescence correlation spectroscopy (FCS) was used to study nanoparticle stability and triggered release of a model compound in detail. Long-term colloidal stability and model compound retention within the nanoparticles was found when analyzed in cell media at body temperature. In contrast, rapid, complete reduction-triggered disassembly and model compound release was achieved within a physiological reducing environment. The synthesized copolymers revealed no intrinsic cellular toxicity up to 1 mg mL-1. Drug-loaded reduction-sensitive nanoparticles delivered a hydrophobic model anticancer drug (doxorubicin, DOX) to cancer cells (HeLa cells) and an experimental, metabolically unstable antimalarial drug (the serine hydroxymethyltransferase (SHMT) inhibitor (+/-)-1) to Plasmodium falciparum-infected red blood cells (iRBCs), with higher efficacy compared to similar, non-sensitive drug-loaded nanoparticles. These responsive copolymer-based nanoparticles represent a promising candidate as smart nanocarrier platform for various drugs to be applied to different diseases, due to the biocompatibility and biodegradability of the hydrophobic block, and the protein-repellent hydrophilic block. Electronic supplementary information (ESI) available: Detailed experimental procedures, additional schemes and supplementary data including NMR, FTIR, TEM, DLS, UV-Vis, FCS, and fluorescence microscopy images. See DOI: 10.1039/c6nr04290b

Robust encoding of stimulus identity and concentration in the accessory olfactory system.

PubMed

Arnson, Hannah A; Holy, Timothy E

2013-08-14

Sensory systems represent stimulus identity and intensity, but in the neural periphery these two variables are typically intertwined. Moreover, stable detection may be complicated by environmental uncertainty; stimulus properties can differ over time and circumstance in ways that are not necessarily biologically relevant. We explored these issues in the context of the mouse accessory olfactory system, which specializes in detection of chemical social cues and infers myriad aspects of the identity and physiological state of conspecifics from complex mixtures, such as urine. Using mixtures of sulfated steroids, key constituents of urine, we found that spiking responses of individual vomeronasal sensory neurons encode both individual compounds and mixtures in a manner consistent with a simple model of receptor-ligand interactions. Although typical neurons did not accurately encode concentration over a large dynamic range, from population activity it was possible to reliably estimate the log-concentration of pure compounds over several orders of magnitude. For binary mixtures, simple models failed to accurately segment the individual components, largely because of the prevalence of neurons responsive to both components. By accounting for such overlaps during model tuning, we show that, from neuronal firing, one can accurately estimate log-concentration of both components, even when tested across widely varying concentrations. With this foundation, the difference of logarithms, log A - log B = log A/B, provides a natural mechanism to accurately estimate concentration ratios. Thus, we show that a biophysically plausible circuit model can reconstruct concentration ratios from observed neuronal firing, representing a powerful mechanism to separate stimulus identity from absolute concentration.

Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds.

PubMed

Chen, Lei; Zhang, Yu-Hang; Zheng, Mingyue; Huang, Tao; Cai, Yu-Dong

2016-12-01

Compound-protein interactions play important roles in every cell via the recognition and regulation of specific functional proteins. The correct identification of compound-protein interactions can lead to a good comprehension of this complicated system and provide useful input for the investigation of various attributes of compounds and proteins. In this study, we attempted to understand this system by extracting properties from both proteins and compounds, in which proteins were represented by gene ontology and KEGG pathway enrichment scores and compounds were represented by molecular fragments. Advanced feature selection methods, including minimum redundancy maximum relevance, incremental feature selection, and the basic machine learning algorithm random forest, were used to analyze these properties and extract core factors for the determination of actual compound-protein interactions. Compound-protein interactions reported in The Binding Databases were used as positive samples. To improve the reliability of the results, the analytic procedure was executed five times using different negative samples. Simultaneously, five optimal prediction methods based on a random forest and yielding maximum MCCs of approximately 77.55 % were constructed and may be useful tools for the prediction of compound-protein interactions. This work provides new clues to understanding the system of compound-protein interactions by analyzing extracted core features. Our results indicate that compound-protein interactions are related to biological processes involving immune, developmental and hormone-associated pathways.

Non-invasive identification of organic materials in historical stringed musical instruments by reflection infrared spectroscopy: a methodological approach.

PubMed

Invernizzi, Claudia; Daveri, Alessia; Vagnini, Manuela; Malagodi, Marco

2017-05-01

The analysis of historical musical instruments is becoming more relevant and the interest is increasingly moving toward the non-invasive reflection FTIR spectroscopy, especially for the analysis of varnishes. In this work, a specific infrared reflectance spectral library of organic compounds was created with the aim of identifying musical instrument materials in a totally non-invasive way. The analyses were carried out on pure organic compounds, as bulk samples and laboratory wooden models, to evaluate the diagnostic reflection mid-infrared (MIR) bands of proteins, polysaccharides, lipids, and resins by comparing reflection spectra before and after the KK correction. This methodological approach was applied to real case studies represented by four Stradivari violins and a Neapolitan mandolin.

Modeling and analysis of personal exposures to VOC mixtures using copulas

PubMed Central

Su, Feng-Chiao; Mukherjee, Bhramar; Batterman, Stuart

2014-01-01

Environmental exposures typically involve mixtures of pollutants, which must be understood to evaluate cumulative risks, that is, the likelihood of adverse health effects arising from two or more chemicals. This study uses several powerful techniques to characterize dependency structures of mixture components in personal exposure measurements of volatile organic compounds (VOCs) with aims of advancing the understanding of environmental mixtures, improving the ability to model mixture components in a statistically valid manner, and demonstrating broadly applicable techniques. We first describe characteristics of mixtures and introduce several terms, including the mixture fraction which represents a mixture component's share of the total concentration of the mixture. Next, using VOC exposure data collected in the Relationship of Indoor Outdoor and Personal Air (RIOPA) study, mixtures are identified using positive matrix factorization (PMF) and by toxicological mode of action. Dependency structures of mixture components are examined using mixture fractions and modeled using copulas, which address dependencies of multiple variables across the entire distribution. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) are evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks are calculated for mixtures, and results from copulas and multivariate lognormal models are compared to risks calculated using the observed data. Results obtained using the RIOPA dataset showed four VOC mixtures, representing gasoline vapor, vehicle exhaust, chlorinated solvents and disinfection by-products, and cleaning products and odorants. Often, a single compound dominated the mixture, however, mixture fractions were generally heterogeneous in that the VOC composition of the mixture changed with concentration. Three mixtures were identified by mode of action, representing VOCs associated with hematopoietic, liver and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10−3 for about 10% of RIOPA participants. Factors affecting the likelihood of high concentration mixtures included city, participant ethnicity, and house air exchange rates. The dependency structures of the VOC mixtures fitted Gumbel (two mixtures) and t (four mixtures) copulas, types that emphasize tail dependencies. Significantly, the copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy, and performed better than multivariate lognormal distributions. Copulas may be the method of choice for VOC mixtures, particularly for the highest exposures or extreme events, cases that poorly fit lognormal distributions and that represent the greatest risks. PMID:24333991

Comprehensive investigations of kinetics of alkaline hydrolysis of TNT (2,4,6-trinitrotoluene), DNT (2,4-dinitrotoluene), and DNAN (2,4-dinitroanisole).

PubMed

Sviatenko, Liudmyla; Kinney, Chad; Gorb, Leonid; Hill, Frances C; Bednar, Anthony J; Okovytyy, Sergiy; Leszczynski, Jerzy

2014-09-02

Combined experimental and computational techniques were used to analyze multistep chemical reactions in the alkaline hydrolysis of three nitroaromatic compounds: 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT), and 2,4-dinitroanisole (DNAN). The study reveals common features and differences in the kinetic behavior of these compounds. The analysis of the predicted pathways includes modeling of the reactions, along with simulation of UV-vis spectra, experimental monitoring of reactions using LC/MS techniques, development of the kinetic model by designing and solving the system of differential equations, and obtaining computationally predicted kinetics for decay and accumulation of reactants and products. Obtained results suggest that DNT and DNAN are more resistant to alkaline hydrolysis than TNT. The direct substitution of a nitro group by a hydroxide represents the most favorable pathway for all considered compounds. The formation of Meisenheimer complexes leads to the kinetic first-step intermediates in the hydrolysis of TNT. Janovsky complexes can also be formed during hydrolysis of TNT and DNT but in small quantities. Methyl group abstraction is one of the suggested pathways of DNAN transformation during alkaline hydrolysis.

Beta-cyclodextrin enhanced gastroprotective effect of (-)-linalool, a monoterpene present in rosewood essential oil, in gastric lesion models.

PubMed

da Silva, Francilene Vieira; de Barros Fernandes, Hélio; Oliveira, Irisdalva Sousa; Viana, Ana Flávia Seraine Custódio; da Costa, Douglas Soares; Lopes, Miriam Teresa Paz; de Lira, Kamila Lopes; Quintans-Júnior, Lucindo José; de Sousa, Adriano Antunes; de Cássia Meneses Oliveira, Rita

2016-11-01

(-)-Linalool is a monoterpene constituent of many essential oils. This particular monoterpene has both anti-inflammatory and antimicrobial activity. Moreover, this compound has been shown to be antinociceptive. However, the poor chemical stability and short half-life prevents the clinical application of (-)-linalool and many other essential oils. Important to the topic of this study, β-cyclodextrin (β-CD) has been used to increase the solubility, stability, and pharmacological effects of numerous lipophilic compounds in vivo. In this study, the gastroprotective activities of (-)-linalool (LIN) and linalool incorporated into inclusion complex containing β-cyclodextrin (LIN-βCD) were evaluated using models of acute and chronic gastric ulcers in rodents. LIN and LIN-βCD showed strong gastroprotective activity (p < 0.001). The LIN-βCD complex revealed that the gastroprotective effect was significantly improved compared with LIN uncomplexed, suggesting that this improvement is related to increased solubility and stability. Taking together the potentiation of the antioxidant profile of this monoterpene, our results suggest that β-CD may represent an important tool for improved gastroprotective activity of (-)-linalool and other water-insoluble compounds.

Enthalpy measurement of coal-derived liquids. Technical progress report, November 1982-January 1983

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kidnay, A.J.; Yesavage, V.F.

The objective of this research is to measure the enthalpy for representative coal-derived liquids and model compounds over the pressure and temperature regions most likely to be encountered in both liquefaction and processing systems, and to prepare from the data an enthalpy correlation suitable for process design calculations. The correlational effort this past quarter on the enthalpy of coal-derived syncrudes and model compounds has emphasized the experimental determination of a correlating factor for association in coal liquids. As in previous work, the degree of association is to be related to cryoscopic molecular weight determinations on the coal liquids. To thismore » end, work on and an evaluationof a cryoscopic molecular weight apparatus was completed this quarter. Molecular weights of coal liquids determined by the standard Beckman freezing point depression apparatus were consistently low (5 to 10%). After modifications of the apparatus, it was tested with the following compounds: hexane, dodecane, m-xylene and naphthalene. Benzene was the solvent used. However, the molecular weight measurements were again consistently lower than the true values, and in many cases the experimental error was greater than that of the Beckman apparatus.« less

Autoignition Studies of Diesel Alternative Biofuels

NASA Astrophysics Data System (ADS)

Wang, Weijing

The autoignition of biofuel compounds that offer potential as diesel fuel alternatives was studied under high-pressure engine-like conditions using the shock tube technique. Ignition delay times were determined in reflected shock experiments using measured pressure and electronically-excited OH emission. Measurements were made at conditions ranging from 650 to 1350 K, pressures from 6 to 50 atm, and for fuel/air/diluent mixtures at equivalence ratios from 0.5 to 2. The wide range of temperatures examined provides observation of autoignition in three reactivity regimes, including the negative temperature coefficient (NTC) regime which is characteristic of fuels containing alkyl functionalities. Compounds studied include biodiesel-related compounds and real biodiesel fuels, dimethyl ether, and 3-methylheptane which is representative of compounds found in synthetic diesel fuels produced using the Fischer-Tropsch and hydrotreatment processes. Biodiesel compounds studied include biodiesel surrogates, methyl decanoate, methyl-5-decenoate, and methyl-9-decenoate; compounds found in large quantities in biodiesels, methyl palmitate, methyl stearate, methyl oleate, and methyl linoleate; and soy-based and animal fat based methyl ester biodiesels. Comparison of biodiesel compounds illustrates the influence of molecular structure (e.g., chain length, double bonds, and ester functionality) on reactivity. For methyl decanoate, the effect of high pressure exhaust gas recirculation (EGR) conditions relevant to internal combustion engines was also determined. Results showed that the first-order influence of EGR by displacing fuel and O2 to decrease radical branching. Measurements were compared to kinetic modeling results from models available in the literature providing varying degrees of model validation. Reaction flux analyses were also carried out to further examine the kinetic differences in different temperature regimes for fuel compounds. For example, reaction flux analyses illustrates the importance of the long alkyl chain in controlling the overall reactivity of methyl ester biodiesel compounds and the subtle role the ester group has on inhibiting low-temperature reactivity as well as the influence of branching on reactivity for lightly branched alkanes. This thesis work provides a rich database of kinetic information for biofuel-related compounds at conditions relevant to real engine operations, offering quantitative kinetic targets for the development and evaluation of future kinetic models for important alternative fuel compounds. The results quantify the reactivity variability of biodiesel alternatives and illustrate that at temperature greater than 900 to 1000 K fuel structure has little influence on reactivity, as fuel fragmentation results in an intermediate pool that is largely the same for the fuels studied. On the other hand at temperature lower than 900 K, where fuel-specific low-temperature chemistry plays a role, different fuel structures can result in vast differences in reactivity, up to factors of three or more in ignition delay.

Mixed raster content (MRC) model for compound image compression

NASA Astrophysics Data System (ADS)

de Queiroz, Ricardo L.; Buckley, Robert R.; Xu, Ming

1998-12-01

This paper will describe the Mixed Raster Content (MRC) method for compressing compound images, containing both binary test and continuous-tone images. A single compression algorithm that simultaneously meets the requirements for both text and image compression has been elusive. MRC takes a different approach. Rather than using a single algorithm, MRC uses a multi-layered imaging model for representing the results of multiple compression algorithms, including ones developed specifically for text and for images. As a result, MRC can combine the best of existing or new compression algorithms and offer different quality-compression ratio tradeoffs. The algorithms used by MRC set the lower bound on its compression performance. Compared to existing algorithms, MRC has some image-processing overhead to manage multiple algorithms and the imaging model. This paper will develop the rationale for the MRC approach by describing the multi-layered imaging model in light of a rate-distortion trade-off. Results will be presented comparing images compressed using MRC, JPEG and state-of-the-art wavelet algorithms such as SPIHT. MRC has been approved or proposed as an architectural model for several standards, including ITU Color Fax, IETF Internet Fax, and JPEG 2000.

Acute bioassays and hazard evaluation of representative contaminants detected in Great Lakes fish

USGS Publications Warehouse

Passino, Dora R. May; Smith, Stephen B.

1987-01-01

We have provided a hazard ranking for 19 classes of compounds representing many of the nearly 500 organic compounds identified by gas chromatography-mass spectrometry in lake trout (Salvelinus namaycush) and walleye (Stizostedion vitreum vitreum) from the Great Lakes and Lake St. Clair. We initially made a provisional hazard ranking based on available published and unpublished information on aquatic toxicity, bioaccumulation, occurrence and sources. Acute toxicity tests with Daphnia pulex at 17A°C in reconstituted hard water were performed with 30 compounds representative of the 19 classes that were highest in the provisional ranking. The resulting toxicity data, along with information on the compounds' occurrence in Great Lakes fish and their sources, were ranked and weighted and then used in calculating the revised hazard ranking. The 10 most hazardous classes, in descending order, are as follows (values shown are mean 48-h EC50s, in μ/ml): arene halides (e.g., polychlorinated biphenyls, DDT), 0.0011; phthalate esters, 0.133; chlorinated camphenes (toxaphene), 0.0082; polyaromatic hydrocarbons (PAHs; e.g., dimethylnaphthalene) and reduced derivatives, 1.01; chlorinated fused polycyclics (e.g., trans-nonachlor), 0.022; nitrogen-containing compounds (e.g., O-methylhydroxyl-amine), 1.35; alkyl halides (e.g., (bromomethyl)cyclohexene), 10.1; cyclic alkanes (e.g., cyclododecane), 20.9; silicon-containing compounds (e.g., dimethyldiethoxy silane), 1.25; and heterocyclic nitrogen compounds (e.g., nicotine), 2.48. We recommend that chronic bioassays be conducted with fish and invertebrates to determine the sublethal effects of the following classes of compounds, for which few toxicity data are available: PAHs, heterocyclic nitrogen compounds, other nitrogen-containing compounds, alkyl halides, cyclic alkanes and silicon-containing compounds. Information from these types of studies will aid researchers in determining the possible causal role these contaminants play in the decline and reproductive impairment of Great Lakes fish.

The First Attempt at Non-Linear in Silico Prediction of Sampling Rates for Polar Organic Chemical Integrative Samplers (POCIS)

PubMed Central

2016-01-01

Modeling and prediction of polar organic chemical integrative sampler (POCIS) sampling rates (Rs) for 73 compounds using artificial neural networks (ANNs) is presented for the first time. Two models were constructed: the first was developed ab initio using a genetic algorithm (GSD-model) to shortlist 24 descriptors covering constitutional, topological, geometrical and physicochemical properties and the second model was adapted for Rs prediction from a previous chromatographic retention model (RTD-model). Mechanistic evaluation of descriptors showed that models did not require comprehensive a priori information to predict Rs. Average predicted errors for the verification and blind test sets were 0.03 ± 0.02 L d–1 (RTD-model) and 0.03 ± 0.03 L d–1 (GSD-model) relative to experimentally determined Rs. Prediction variability in replicated models was the same or less than for measured Rs. Networks were externally validated using a measured Rs data set of six benzodiazepines. The RTD-model performed best in comparison to the GSD-model for these compounds (average absolute errors of 0.0145 ± 0.008 L d–1 and 0.0437 ± 0.02 L d–1, respectively). Improvements to generalizability of modeling approaches will be reliant on the need for standardized guidelines for Rs measurement. The use of in silico tools for Rs determination represents a more economical approach than laboratory calibrations. PMID:27363449

Modeling Stochastic Boundary Conditions in a Coastal Catchment using a Bayesian Network: An Application to the Houston Ship Channel, Texas

NASA Astrophysics Data System (ADS)

Couasnon, Anaïs; Sebastian, Antonia; Morales-Nápoles, Oswaldo

2017-04-01

Recent research has highlighted the increased risk of compound flooding in the U.S. In coastal catchments, an elevated downstream water level, resulting from high tide and/or storm surge, impedes drainage creating a backwater effect that may exacerbate flooding in the riverine environment. Catchments exposed to tropical cyclone activity along the Gulf of Mexico and Atlantic coasts are particularly vulnerable. However, conventional flood hazard models focus mainly on precipitation-induced flooding and few studies accurately represent the hazard associated with the interaction between discharge and elevated downstream water levels. This study presents a method to derive stochastic boundary conditions for a coastal watershed. Mean daily discharge and maximum daily residual water levels are used to build a non-parametric Bayesian network (BN) based on copulas. Stochastic boundary conditions for the watershed are extracted from the BN and input into a 1-D process-based hydraulic model to obtain water surface elevations in the main channel of the catchment. The method is applied to a section of the Houston Ship Channel (Buffalo Bayou) in Southeast Texas. Data at six stream gages and two tidal stations are used to build the BN and 100-year joint return period events are modeled. We find that the dependence relationship between the daily residual water level and the mean daily discharge in the catchment can be represented by a Gumbel copula (Spearman's rank correlation coefficient of 0.31) and that they result in higher water levels in the mid- to upstream reaches of the watershed than when modeled independently. This indicates that conventional (deterministic) methods may underestimate the flood hazard associated with compound flooding in the riverine environment and that such interactions should not be neglected in future coastal flood hazard studies.

A Comparison of Parameterizations of Secondary Organic Aerosol Production: Global Budget and Spatiotemporal Variability

NASA Astrophysics Data System (ADS)

Liu, J.; Chen, Z.; Horowitz, L. W.; Carlton, A. M. G.; Fan, S.; Cheng, Y.; Ervens, B.; Fu, T. M.; He, C.; Tao, S.

2014-12-01

Secondary organic aerosols (SOA) have a profound influence on air quality and climate, but large uncertainties exist in modeling SOA on the global scale. In this study, five SOA parameterization schemes, including a two-product model (TPM), volatility basis-set (VBS) and three cloud SOA schemes (Ervens et al. (2008, 2014), Fu et al. (2008) , and He et al. (2013)), are implemented into the global chemical transport model (MOZART-4). For each scheme, model simulations are conducted with identical boundary and initial conditions. The VBS scheme produces the highest global annual SOA production (close to 35 Tg·y-1), followed by three cloud schemes (26-30 Tg·y-1) and TPM (23 Tg·y-1). Though sharing a similar partitioning theory to the TPM scheme, the VBS approach simulates the chemical aging of multiple generations of VOCs oxidation products, resulting in a much larger SOA source, particularly from aromatic species, over Europe, the Middle East and Eastern America. The formation of SOA in VBS, which represents the net partitioning of semi-volatile organic compounds from vapor to condensed phase, is highly sensitivity to the aging and wet removal processes of vapor-phase organic compounds. The production of SOA from cloud processes (SOAcld) is constrained by the coincidence of liquid cloud water and water-soluble organic compounds. Therefore, all cloud schemes resolve a fairly similar spatial pattern over the tropical and the mid-latitude continents. The spatiotemporal diversity among SOA parameterizations is largely driven by differences in precursor inputs. Therefore, a deeper understanding of the evolution, wet removal, and phase partitioning of semi-volatile organic compounds, particularly above remote land and oceanic areas, is critical to better constrain the global-scale distribution and related climate forcing of secondary organic aerosols.

High-Throughput Screening Using iPSC-Derived Neuronal Progenitors to Identify Compounds Counteracting Epigenetic Gene Silencing in Fragile X Syndrome.

PubMed

Kaufmann, Markus; Schuffenhauer, Ansgar; Fruh, Isabelle; Klein, Jessica; Thiemeyer, Anke; Rigo, Pierre; Gomez-Mancilla, Baltazar; Heidinger-Millot, Valerie; Bouwmeester, Tewis; Schopfer, Ulrich; Mueller, Matthias; Fodor, Barna D; Cobos-Correa, Amanda

2015-10-01

Fragile X syndrome (FXS) is the most common form of inherited mental retardation, and it is caused in most of cases by epigenetic silencing of the Fmr1 gene. Today, no specific therapy exists for FXS, and current treatments are only directed to improve behavioral symptoms. Neuronal progenitors derived from FXS patient induced pluripotent stem cells (iPSCs) represent a unique model to study the disease and develop assays for large-scale drug discovery screens since they conserve the Fmr1 gene silenced within the disease context. We have established a high-content imaging assay to run a large-scale phenotypic screen aimed to identify compounds that reactivate the silenced Fmr1 gene. A set of 50,000 compounds was tested, including modulators of several epigenetic targets. We describe an integrated drug discovery model comprising iPSC generation, culture scale-up, and quality control and screening with a very sensitive high-content imaging assay assisted by single-cell image analysis and multiparametric data analysis based on machine learning algorithms. The screening identified several compounds that induced a weak expression of fragile X mental retardation protein (FMRP) and thus sets the basis for further large-scale screens to find candidate drugs or targets tackling the underlying mechanism of FXS with potential for therapeutic intervention. © 2015 Society for Laboratory Automation and Screening.

Experimental basis for a role for sulfhydryls and dopamine in ulcerogenesis: a primer for cytoprotection--organoprotection.

PubMed

Szabo, S

1986-01-01

This brief review presents the evolution of the concept of cytoprotection which was originally described by Robert (1979) to represent prevention of chemically induced hemorrhagic gastric erosions without inhibiting acid secretion. Prostaglandins (PG) and sulfhydryls (SH) protect only against deep hemorrhagic necrosis in the mucosa without altering the initial damage to surface epithelial cells. Organ integrity and function are thus maintained (i.e., organoprotection) despite the loss of several layers of mucosal cells. While both PG and SH are natural products it must be stressed that only SH compounds can enter directly into protective reactions (e.g., free radical scavenging, modification of receptor SH groups, oxidation of certain structural and enzyme proteins). In addition, SH compounds also stimulate PG synthesis. A major target of gastroprotection by either PG or SH is the preservation of mucosal microvasculature to maintain blood flow for rapid restitution and cell proliferation. Dopamine-related compounds are reviewed because of their possible role in duodenal ulceration. Dopamine and dopamine agonists are antiulcerogens in duodenal ulcer models. Dopamine antagonists are proulcerogens and the dopamine neurotoxin MPTP causes duodenal ulcer in experimental animals. The mechanism of duodenal antiulcerogenic effect involves inhibition of gastric acid and pepsin secretion, stimulation of duodenal bicarbonate secretion, correction of duodenal dysmotility, and maybe increased blood flow. Because of their multiple beneficial effects, SH compounds and dopamine drugs are good models for gastroenteroprotection.

Selective complexation of K+ and Na+ in simple polarizable ion-ligating systems.

PubMed

Bostick, David L; Brooks, Charles L

2010-09-29

An influx of experimental and theoretical studies of ion transport protein structure has inspired efforts to understand underlying determinants of ionic selectivity. Design principles for selective ion binding can be effectively isolated and interrogated using simplified models composed of a single ion surrounded by a set of ion-ligating molecular species. While quantum mechanical treatments of such systems naturally incorporate electronic degrees of freedom, their computational overhead typically prohibits thorough dynamic sampling of configurational space and, thus, requires approximations when determining ion-selective free energy. As an alternative, we employ dynamical simulations with a polarizable force field to probe the structure and K(+)/Na(+) selectivity in simple models composed of one central K(+)/Na(+) ion surrounded by 0-8 identical model compounds: N-methylacetamide, formamide, or water. In the absence of external restraints, these models represent gas-phase clusters displaying relaxed coordination structures with low coordination number. Such systems display Na(+) selectivity when composed of more than ∼3 organic carbonyl-containing compounds and always display K(+) selectivity when composed of water molecules. Upon imposing restraints that solely enforce specific coordination numbers, we find all models are K(+)-selective when ∼7-8-fold ion coordination is achieved. However, when models composed of the organic compounds provide ∼4-6-fold coordination, they retain their Na(+) selectivity. From these trends, design principles emerge that are of basic importance in the behavior of K(+) channel selectivity filters and suggest a basis not only for K(+) selectivity but also for modulation of block and closure by smaller ions.

Chemistry of Volatile Organic Compounds in the Los Angeles Basin: Formation of Oxygenated Compounds and Determination of Emission Ratios

NASA Astrophysics Data System (ADS)

de Gouw, J. A.; Gilman, J. B.; Kim, S.-W.; Alvarez, S. L.; Dusanter, S.; Graus, M.; Griffith, S. M.; Isaacman-VanWertz, G.; Kuster, W. C.; Lefer, B. L.; Lerner, B. M.; McDonald, B. C.; Rappenglück, B.; Roberts, J. M.; Stevens, P. S.; Stutz, J.; Thalman, R.; Veres, P. R.; Volkamer, R.; Warneke, C.; Washenfelder, R. A.; Young, C. J.

2018-02-01

We analyze an expanded data set of oxygenated volatile organic compounds (OVOCs) in air measured by several instruments at a surface site in Pasadena near Los Angeles during the National Oceanic and Atmospheric Administration California Nexus study in 2010. The contributions of emissions, chemical formation, and removal are quantified for each OVOC using CO as a tracer of emissions and the OH exposure of the sampled air masses calculated from hydrocarbon ratios. The method for separating emissions from chemical formation is evaluated using output for Pasadena from the Weather Research and Forecasting-Chemistry model. The model is analyzed by the same method as the measurement data, and the emission ratios versus CO calculated from the model output agree for ketones with the inventory used in the model but overestimate aldehydes by 70%. In contrast with the measurements, nighttime formation of OVOCs is significant in the model and is attributed to overestimated precursor emissions and overestimated rate coefficients for the reactions of the precursors with ozone and NO3. Most measured aldehydes correlated strongly with CO at night, suggesting a contribution from motor vehicle emissions. However, the emission ratios of most aldehydes versus CO are higher than those reported in motor vehicle emissions and the aldehyde sources remain unclear. Formation of several OVOCs is investigated in terms of the removal of specific precursors. Direct emissions of alcohols and aldehydes contribute significantly to OH reactivity throughout the day, and these emissions should be accurately represented in models describing ozone formation.

Toxic volatile organic compounds in environmental tobacco smoke: Emission factors for modeling exposures of California populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daisey, J.M.; Mahanama, K.R.R.; Hodgson, A.T.

The primary objective of this study was to measure emission factors for selected toxic air contaminants in environmental tobacco smoke (ETS) using a room-sized environmental chamber. The emissions of 23 volatile organic compounds (VOCs), including, 1,3-butadiene, three aldehydes and two vapor-phase N-nitrosamines were determined for six commercial brands of cigarettes and reference cigarette 1R4F. The commercial brands were selected to represent 62.5% of the cigarettes smoked in California. For each brand, three cigarettes were machine smoked in the chamber. The experiments were conducted over four hours to investigate the effects of aging. Emission factors of the target compounds were alsomore » determined for sidestream smoke (SS). For almost all target compounds, the ETS emission factors were significantly higher than the corresponding SS values probably due to less favorable combustion conditions and wall losses in the SS apparatus. Where valid comparisons could be made, the ETS emission factors were generally in good agreement with the literature. Therefore, the ETS emission factors, rather than the SS values, are recommended for use in models to estimate population exposures from this source. The variabilities in the emission factors ({mu}g/cigarette) of the selected toxic air contaminants among brands, expressed as coefficients of variation, were 16 to 29%. Therefore, emissions among brands were Generally similar. Differences among brands were related to the smoked lengths of the cigarettes and the masses of consumed tobacco. Mentholation and whether a cigarette was classified as light or regular did not significantly affect emissions. Aging was determined not to be a significant factor for the target compounds. There were, however, deposition losses of the less volatile compounds to chamber surfaces.« less

Inhibition of endotoxin-induced airway epithelial cell injury by a novel family of pyrrol derivates.

PubMed

Cabrera-Benítez, Nuria E; Pérez-Roth, Eduardo; Ramos-Nuez, Ángela; Sologuren, Ithaisa; Padrón, José M; Slutsky, Arthur S; Villar, Jesús

2016-06-01

Inflammation and apoptosis are crucial mechanisms for the development of the acute respiratory distress syndrome (ARDS). Currently, there is no specific pharmacological therapy for ARDS. We have evaluated the ability of a new family of 1,2,3,5-tetrasubstituted pyrrol compounds for attenuating lipopolysaccharide (LPS)-induced inflammation and apoptosis in an in vitro LPS-induced airway epithelial cell injury model based on the first steps of the development of sepsis-induced ARDS. Human alveolar A549 and human bronchial BEAS-2B cells were exposed to LPS, either alone or in combination with the pyrrol derivatives. Rhein and emodin, two representative compounds with proven activity against the effects of LPS, were used as reference compounds. The pyrrol compound that was termed DTA0118 had the strongest inhibitory activity and was selected as the lead compound to further explore its properties. Exposure to LPS caused an intense inflammatory response and apoptosis in both A549 and BEAS-2B cells. DTA0118 treatment downregulated Toll-like receptor-4 expression and upregulated nuclear factor-κB inhibitor-α expression in cells exposed to LPS. These anti-inflammatory effects were accompanied by a significantly lower secretion of interleukin-6 (IL-6), IL-8, and IL-1β. The observed antiapoptotic effect of DTA0118 was associated with the upregulation of antiapoptotic Bcl-2 and downregulation of proapoptotic Bax and active caspase-3 protein levels. Our findings demonstrate the potent anti-inflammatory and antiapoptotic properties of the pyrrol DTA0118 compound and suggest that it could be considered as a potential drug therapy for the acute phase of sepsis and septic ARDS. Further investigations are needed to examine and validate these mechanisms and effects in a clinically relevant animal model of sepsis and sepsis-induced ARDS.

Toxic Volatile Organic Compounds in Environmental Tobacco Smoke:Emission Factors for Modeling Exposures of California Populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daisey, J.M.; Mahanama, K.R.R.; Hodgson, A.T.

The primary objective of this study was to measure emission factors for selected toxic air in environmental tobacco smoke (ETS) using a room-sized environmental chamber. The emissions of 23 volatile organic compounds (VOCs), including 1,3-butadiene, three aldehydes and two vapor-phase N-nitrosarnines were determined for six commercial brands of cigarettes and reference cigarette 1R4F. The commercial brands were selected to represent 62.5% of the cigarettes smoked in California. For each brand, three cigarettes were machine smoked in the chamber. The experiments were conducted over four hours to investigate the effects of aging. Emission factors of the target compounds were also determinedmore » for sidestream smoke (SS). For almost all target compounds, the ETS emission factors were significantly higher than the corresponding SS values probably due to less favorable combustion conditions and wall losses in the SS apparatus. Where valid comparisons could be made, the ETS emission factors were generally in good agreement with the literature. Therefore, the ETS emission factors, rather than the SS values, are recommended for use in models to estimate population exposures from this source. The variabilities in the emission factors (pgkigarette) of the selected toxic air contaminants among brands, expressed as coefficients of variation, were 16 to 29%. Therefore, emissions among brands were generally similar. Differences among brands were related to the smoked lengths of the cigarettes and the masses of consumed tobacco. Mentholation and whether a cigarette was classified as light or regular did not significantly affect emissions. Aging was determined not to be a significant factor for the target compounds. There were, however, deposition losses of the less volatile compounds to chamber surfaces.« less

Assessing Hypervalency in Iodanes.

PubMed

Stirling, András

2018-02-01

The so-called hypervalent iodane compounds are very useful and versatile reactants and oxidizing agents in modern organic chemistry. The hypercoordinated central iodine in these compounds hints at a hypervalent state, which is often stressed to justify their reactivity. In this study a theoretical analysis of the electronic structure of a large, representative set of hypercoordinated iodane compounds has been carried out. We observed that the iodonium is not hypervalent in these compounds. In contrast, the analysis reveals a variation of the iodine valence state from a normal octet state to hypovalent depending on the ligands, but irrespective of the coordination number. On the basis of the calculations the reactivity of these compounds can be ascribed to the strong unquenched charge separation present in these molecules which represents a compromise between Coulomb interaction and the resistance of iodonium toward hypervalency. In extreme cases this leads to hypovalency and enhanced reactivity. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

ProTox: a web server for the in silico prediction of rodent oral toxicity.

PubMed

Drwal, Malgorzata N; Banerjee, Priyanka; Dunkel, Mathias; Wettig, Martin R; Preissner, Robert

2014-07-01

Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein-ligand-based pharmacophore models ('toxicophores') for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Multiple-Lemma Representation of Italian Compound Nouns: A Single Case Study of Deep Dyslexia

ERIC Educational Resources Information Center

Marelli, Marco; Aggujaro, Silvia; Molteni, Franco; Luzzatti, Claudio

2012-01-01

It is not clear how compound words are represented within the influential framework of the lemma-lexeme theory. Theoretically, compounds could be structured through a multiple lemma architecture, in which the lemma nodes of both the compound and its constituents are involved in lexical processing. If this were the case, syntactic properties of…

Effect of PTX3 and Voriconazole Combination in a Rat Model of Invasive Pulmonary Aspergillosis

PubMed Central

Lo Giudice, Pietro; Campo, Silvia; De Santis, Rita

2012-01-01

This study evaluated the pharmacological activity of PTX3, administered in combination with voriconazole, in a rat model of pulmonary aspergillosis. The data indicated additive therapeutic activities of these compounds, as demonstrated by the amelioration of respiratory function changes, reduction of lung fungal burden, and increased survival. Overall, we provide clear evidence that the combination of PTX3 with a suboptimal dose of voriconazole might represent a therapeutic option under those clinical conditions where the use of voriconazole alone is not warranted for efficacy and tolerability reasons. PMID:23006752

Solid state electrochemical current source

DOEpatents

Potanin, Alexander Arkadyevich; Vedeneev, Nikolai Ivanovich

2002-04-30

A cathode and a solid state electrochemical cell comprising said cathode, a solid anode and solid fluoride ion conducting electrolyte. The cathode comprises a metal oxide and a compound fluoride containing at least two metals with different valences. Representative compound fluorides include solid solutions of bismuth fluoride and potassium fluoride; and lead fluoride and potassium fluoride. Representative metal oxides include copper oxide, lead oxide, manganese oxide, vanadium oxide and silver oxide.

Extensive Evaluation of the Conductor-like Screening Model for Real Solvents Method in Predicting Liquid-Liquid Equilibria in Ternary Systems of Ionic Liquids with Molecular Compounds.

PubMed

Paduszyński, Kamil

2018-04-12

A conductor-like screening model for real solvents (COSMO-RS) is nowadays one of the most popular and commonly applied tools for the estimation of thermodynamic properties of complex fluids. The goal of this work is to provide a comprehensive review and analysis of the performance of this approach in calculating liquid-liquid equilibrium (LLE) phase diagrams in ternary systems composed of ionic liquid and two molecular compounds belonging to diverse families of chemicals (alkanes, aromatics, S/N-compounds, alcohols, ketones, ethers, carboxylic acid, esters, and water). The predictions are presented for extensive experimental database, including 930 LLE data sets and more than 9000 data points (LLE tie lines) reported for 779 unique ternary mixtures. An impact of the type of molecular binary subsystem on the accuracy of predictions is demonstrated and discussed on the basis of representative examples. The model's capability of capturing qualitative trends in the LLE distribution ratio and selectivity is also checked for a number of structural effects. Comparative analysis of two levels of quantum chemical theory (BP-TZVP-COSMO vs BP-TZVPD-FINE) for the input molecular data for COSMO-RS is presented. Finally, some general recommendations for the applicability of the model are indicated based on the analysis of the global performance as well as on the results obtained for systems relevant from the point of view of important separation problems.

Further evaluation of quantitative structure--activity relationship models for the prediction of the skin sensitization potency of selected fragrance allergens.

PubMed

Patlewicz, Grace Y; Basketter, David A; Pease, Camilla K Smith; Wilson, Karen; Wright, Zoe M; Roberts, David W; Bernard, Guillaume; Arnau, Elena Giménez; Lepoittevin, Jean-Pierre

2004-02-01

Fragrance substances represent a very diverse group of chemicals; a proportion of them are associated with the ability to cause allergic reactions in the skin. Efforts to find substitute materials are hindered by the need to undertake animal testing for determining both skin sensitization hazard and potency. One strategy to avoid such testing is through an understanding of the relationships between chemical structure and skin sensitization, so-called structure-activity relationships. In recent work, we evaluated 2 groups of fragrance chemicals -- saturated aldehydes and alpha,beta-unsaturated aldehydes. Simple quantitative structure-activity relationship (QSAR) models relating the EC3 values [derived from the local lymph node assay (LLNA)] to physicochemical properties were developed for both sets of aldehydes. In the current study, we evaluated an additional group of carbonyl-containing compounds to test the predictive power of the developed QSARs and to extend their scope. The QSAR models were used to predict EC3 values of 10 newly selected compounds. Local lymph node assay data generated for these compounds demonstrated that the original QSARs were fairly accurate, but still required improvement. Development of these QSAR models has provided us with a better understanding of the potential mechanisms of action for aldehydes, and hence how to avoid or limit allergy. Knowledge generated from this work is being incorporated into new/improved rules for sensitization in the expert toxicity prediction system, deductive estimation of risk from existing knowledge (DEREK).

Synthesis and Study of Analgesic and Anti-inflammatory Activities of Amide Derivatives of Ibuprofen.

PubMed

Ahmadi, Abbas; Khalili, Mohsen; Olama, Zahra; Karami, Shirin; Nahri-Niknafs, Babak

2017-01-01

Nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most widely used drugs worldwide and represent a mainstay in the therapy of acute and chronic pain and inflammation. The traditional NSAIDs like ibuprofen (I) contain free carboxylic acid group which can produce gastrointestinal (GI) damage for long-term use. In order to obtain the novel NSAIDs with less side effects; carboxylic acid moiety has been modified into various amide groups which is the most active area of research in this family. In this research, synthesis of various pharmacological heterocyclic amides of ibuprofen is described. All the new compounds were tested for their analgesic and anti-inflammatory activities in mice and compared with standard (Ibuprofen) and control (saline) groups. The results revealed that all the synthesized compounds (III-VI) exhibited more analgesic and anti-inflammatory activities in tail immersion (as a model of acute thermal pain), formalin (as a model of acute chemical and chronic pain) and paw edema (as a model of acute inflammation) tests when compared with standard and control animals. These pharmacological activities were significant for VI compared to other new compounds (III-V) which may be concern to more effective role of morpholin for the reduction of pain and inflammation compared to other used heterocyclic amines. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Application of the target lipid model and passive samplers to characterize the toxicity of bioavailable organics in oil sands process-affected water.

PubMed

Redman, Aaron D; Parkerton, Thomas F; Butler, Josh David; Letinski, Daniel J; Frank, Richard A; Hewitt, L Mark; Bartlett, Adrienne J; Gillis, Patricia Leigh; Marentette, Julie R; Parrott, Joanne L; Hughes, Sarah A; Guest, Rodney; Bekele, Asfaw; Zhang, Kun; Morandi, Garrett; Wiseman, Steve B; Giesy, John P

2018-06-14

Oil sand operations in Alberta, Canada will eventually include returning treated process-affected waters to the environment. Organic constituents in oil sand process-affected water (OSPW) represent complex mixtures of nonionic and ionic (e.g. naphthenic acids) compounds, and compositions can vary spatially and temporally, which has impeded development of water quality benchmarks. To address this challenge, it was hypothesized that solid phase microextraction fibers coated with polydimethylsiloxane (PDMS) could be used as a biomimetic extraction (BE) to measure bioavailable organics in OSPW. Organic constituents of OSPW were assumed to contribute additively to toxicity, and partitioning to PDMS was assumed to be predictive of accumulation in target lipids, which were the presumed site of action. This method was tested using toxicity data for individual model compounds, defined mixtures, and organic mixtures extracted from OSPW. Toxicity was correlated with BE data, which supports the use of this method in hazard assessments of acute lethality to aquatic organisms. A species sensitivity distribution (SSD), based on target lipid model and BE values, was similar to SSDs based on residues in tissues for both nonionic and ionic organics. BE was shown to be an analytical tool that accounts for bioaccumulation of organic compound mixtures from which toxicity can be predicted, with the potential to aid in the development of water quality guidelines.

Measurements of VOC adsorption/desorption characteristics of typical interior building materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

An, Y.; Zhang, J.S.; Shaw, C.Y.

2000-07-01

The adsorption/desorption of volatile organic compounds (VOCs) on interior building material surfaces (i.e., the sink effect) can affect the VOC concentrations in a building, and thus need to be accounted for an indoor air quality (IAQ) prediction model. In this study, the VOC adsorption/desorption characteristics (sink effect) were measured for four typical interior building materials including carpet, vinyl floor tile, painted drywall, and ceiling tile. The VOCs tested were ethylbenzene, cyclohexanone, 1,4-dichlorobenzene, benzaldehyde, and dodecane. These five VOCs were selected because they are representative of hydrocarbons, aromatics, ketones, aldehydes, and chlorine substituted compounds. The first order reversible adsorption/desorption model wasmore » based on the Langmuir isotherm was used to analyze the data and to determine the equilibrium constant of each VOC-material combination. It was found that the adsorption/desorption equilibrium constant, which is a measure of the sink capacity, increased linearly with the inverse of the VOC vapor pressure. For each compound, the adsorption/desorption equilibrium constant, and the adsorption rate constant differed significantly among the four materials tested. A detailed characterization of the material structure in the micro-scale would improve the understanding and modeling of the sink effect in the future. The results of this study can be used to estimate the impact of sink effect on the VOC concentrations in buildings.« less

Ultra-high performance supercritical fluid chromatography of lignin-derived phenols from alkaline cupric oxide oxidation.

PubMed

Sun, Mingzhe; Lidén, Gunnar; Sandahl, Margareta; Turner, Charlotta

2016-08-01

Traditional chromatographic methods for the analysis of lignin-derived phenolic compounds in environmental samples are generally time consuming. In this work, an ultra-high performance supercritical fluid chromatography method with a diode array detector for the analysis of major lignin-derived phenolic compounds produced by alkaline cupric oxide oxidation was developed. In an analysis of a collection of 11 representative monomeric lignin phenolic compounds, all compounds were clearly separated within 6 min with excellent peak shapes, with a limit of detection of 0.5-2.5 μM, a limit of quantification of 2.5-5.0 μM, and a dynamic range of 5.0-2.0 mM (R(2) > 0.997). The new ultra-high performance supercritical fluid chromatography method was also applied for the qualitative and quantitative analysis of lignin-derived phenolic compounds obtained upon alkaline cupric oxide oxidation of a commercial humic acid. Ten out of the previous eleven model compounds could be quantified in the oxidized humic acid sample. The high separation power and short analysis time obtained demonstrate for the first time that supercritical fluid chromatography is a fast and reliable technique for the analysis of lignin-derived phenols in complex environmental samples. © 2016 The Authors, Journal of Separation Science Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Small-molecule inhibitors of FABP4/5 ameliorate dyslipidemia but not insulin resistance in mice with diet-induced obesity

PubMed Central

Lan, Hong; Cheng, Cliff C.; Kowalski, Timothy J.; Pang, Ling; Shan, Lixin; Chuang, Cheng-Chi; Jackson, James; Rojas-Triana, Alberto; Bober, Loretta; Liu, Li; Voigt, Johannes; Orth, Peter; Yang, Xianshu; Shipps, Gerald W.; Hedrick, Joseph A.

2011-01-01

Fatty acid binding protein-4 (FABP4) and FABP5 are two closely related FA binding proteins expressed primarily in adipose tissue and/or macrophages. The small-molecule FABP4 inhibitor BMS309403 was previously reported to improve insulin sensitivity in leptin-deficient Lepob/Lepob (ob/ob) mice. However, this compound was not extensively characterized in the more physiologically relevant animal model of mice with diet-induced obesity (DIO). Here, we report the discovery and characterization of a novel series of FABP4/5 dual inhibitors represented by Compounds 1–3. Compared with BMS309403, the compounds had significant in vitro potency toward both FABP4 and FABP5. In cell-based assays, Compounds 2 and 3 were more potent than BMS309403 to inhibit lipolysis in 3T3-L1 adipocytes and in primary human adipocytes. They also inhibited MCP-1 release from THP-1 macrophages as well as from primary human macrophages. When chronically administered to DIO mice, BMS309403 and Compound 3 reduced plasma triglyceride and free FA levels. Compound 3 reduced plasma free FAs at a lower dose level than BMS309403. However, no significant change was observed in insulin, glucose, or glucose tolerance. Our results indicate that the FABP4/5 inhibitors ameliorate dyslipidemia but not insulin resistance in DIO mice. PMID:21296956

Small-molecule inhibitors of FABP4/5 ameliorate dyslipidemia but not insulin resistance in mice with diet-induced obesity.

PubMed

Lan, Hong; Cheng, Cliff C; Kowalski, Timothy J; Pang, Ling; Shan, Lixin; Chuang, Cheng-Chi; Jackson, James; Rojas-Triana, Alberto; Bober, Loretta; Liu, Li; Voigt, Johannes; Orth, Peter; Yang, Xianshu; Shipps, Gerald W; Hedrick, Joseph A

2011-04-01

Fatty acid binding protein-4 (FABP4) and FABP5 are two closely related FA binding proteins expressed primarily in adipose tissue and/or macrophages. The small-molecule FABP4 inhibitor BMS309403 was previously reported to improve insulin sensitivity in leptin-deficient Lep(ob)/Lep(ob) (ob/ob) mice. However, this compound was not extensively characterized in the more physiologically relevant animal model of mice with diet-induced obesity (DIO). Here, we report the discovery and characterization of a novel series of FABP4/5 dual inhibitors represented by Compounds 1-3. Compared with BMS309403, the compounds had significant in vitro potency toward both FABP4 and FABP5. In cell-based assays, Compounds 2 and 3 were more potent than BMS309403 to inhibit lipolysis in 3T3-L1 adipocytes and in primary human adipocytes. They also inhibited MCP-1 release from THP-1 macrophages as well as from primary human macrophages. When chronically administered to DIO mice, BMS309403 and Compound 3 reduced plasma triglyceride and free FA levels. Compound 3 reduced plasma free FAs at a lower dose level than BMS309403. However, no significant change was observed in insulin, glucose, or glucose tolerance. Our results indicate that the FABP4/5 inhibitors ameliorate dyslipidemia but not insulin resistance in DIO mice.

Balancing Antioxidant, Hypolipidemic and Anti-inflammatory Activity in a Single Agent: The Example of 2-Hydroxy-2-Substituted Morpholine, 1,4-Benzoxazine and 1,4-Benzothiazine Derivatives as a Rational Therapeutic Approach against Atherosclerosis.

PubMed

Matralis, Alexios N; Bavavea, Eugenia-Ismini; Incerpi, Sandra; Pedersen, Jens Z; Kourounakis, Angeliki P

2017-01-01

In line with our previous studies, novel morpholine and benzoxa(or thia)zine lead compounds have been developed through a rational design that modulate a multiplicity of targets against atherosclerosis. We have evaluated the most promising compounds for their efficiency to a) intercept and scavenge free radicals, b) inhibit the metal ion (Cu2+)- induced LDL oxidation c) act intracellularly as antioxidants in THP-1 monocytes from a leukemic patient and d) inhibit the pro-inflammatory enzymes cyclooxygenase-1 (COX-1) and -2 (COX-2) in vitro. Furthermore, two representative compounds were tested for their potential to decrease lipidemic parameters (TC, LDL and TG) in hyperlipidemic mice. Most derivatives indicated a remarkable antioxidant activity, while at the same time exhibited a significant in vitro anti-inflammatory activity, inhibiting COX-1 or/and COX-2 activity at 20 μΜ. In addition, after their long-term administration, compounds 6 and 8 afforded considerable activity in a chronic experimental animal model of hyperlipidemia (after high fat diet administration). The multifunctional pharmacological profile exhibited by the compounds of this study renders them interesting lead compounds for the development of novel agents against atherosclerosis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Novel inhibitor candidates of TRPV2 prevent damage of dystrophic myocytes and ameliorate against dilated cardiomyopathy in a hamster model.

PubMed

Iwata, Yuko; Katayama, Yoshimi; Okuno, Yasushi; Wakabayashi, Shigeo

2018-03-06

Transient receptor potential cation channel, subfamily V, member 2 (TRPV2) is a principal candidate for abnormal Ca 2+ -entry pathways, which is a potential target for therapy of muscular dystrophy and cardiomyopathy. Here, an in silico drug screening and the following cell-based screening to measure the TRPV2 activation were carried out in HEK293 cells expressing TRPV2 using lead compounds (tranilast or SKF96365) and off-patent drug stocks. We identified 4 chemical compounds containing amino-benzoyl groups and 1 compound (lumin) containing an ethylquinolinium group as candidate TRPV2 inhibitors. Three of these compounds inhibited Ca 2+ entry through both mouse and human TRPV2, with IC 50 of less than 10 μM, but had no apparent effect on other members of TRP family such as TRPV1 and TRPC1. Particularly, lumin inhibited agonist-induced TRPV2 channel activity at a low dose. These compounds inhibited abnormally increased Ca 2+ influx and prevented stretch-induced skeletal muscle damage in cultured myocytes from dystrophic hamsters (J2N-k). Further, they ameliorated cardiac dysfunction, and prevented disease progression in vivo in the same J2N-k hamsters developing dilated cardiomyopathy as well as muscular dystrophy. The identified compounds described here are available as experimental tools and represent potential treatments for patients with cardiomyopathy and muscular dystrophy.

Novel inhibitor candidates of TRPV2 prevent damage of dystrophic myocytes and ameliorate against dilated cardiomyopathy in a hamster model

PubMed Central

Iwata, Yuko; Katayama, Yoshimi; Okuno, Yasushi; Wakabayashi, Shigeo

2018-01-01

Transient receptor potential cation channel, subfamily V, member 2 (TRPV2) is a principal candidate for abnormal Ca2+-entry pathways, which is a potential target for therapy of muscular dystrophy and cardiomyopathy. Here, an in silico drug screening and the following cell-based screening to measure the TRPV2 activation were carried out in HEK293 cells expressing TRPV2 using lead compounds (tranilast or SKF96365) and off-patent drug stocks. We identified 4 chemical compounds containing amino-benzoyl groups and 1 compound (lumin) containing an ethylquinolinium group as candidate TRPV2 inhibitors. Three of these compounds inhibited Ca2+ entry through both mouse and human TRPV2, with IC50 of less than 10 μM, but had no apparent effect on other members of TRP family such as TRPV1 and TRPC1. Particularly, lumin inhibited agonist-induced TRPV2 channel activity at a low dose. These compounds inhibited abnormally increased Ca2+ influx and prevented stretch-induced skeletal muscle damage in cultured myocytes from dystrophic hamsters (J2N-k). Further, they ameliorated cardiac dysfunction, and prevented disease progression in vivo in the same J2N-k hamsters developing dilated cardiomyopathy as well as muscular dystrophy. The identified compounds described here are available as experimental tools and represent potential treatments for patients with cardiomyopathy and muscular dystrophy. PMID:29581825

Isolation and structural elucidation of cytotoxic compounds from the root bark of Diospyros quercina (Baill.) endemic to Madagascar

PubMed Central

Ruphin, Fatiany Pierre; Baholy, Robijaona; Emmanuel, Randrianarivo; Amelie, Raharisololalao; Martin, Marie-Therese; Koto–te-Nyiwa, Ngbolua

2014-01-01

Objective To isolate and characterize the cytotoxic compounds from Diospyros quercina (Baill.) G.E. Schatz & Lowry (Ebenaceae). Methods An ethno-botanical survey was conducted in the south of Madagascar from July to August 2010. Bio-guided fractionation assay was carried out on the root bark of Diospyros quercina, using cytotoxicity bioassay on murine P388 leukemia cell lines as model. The structures of the cytotoxic compounds were elucidated by 1D and 2D NMR spectroscopy and mass spectrometry. Results Biological experiments resulted in the isolation of three bioactive pure compounds (named TR-21, TR-22, and TR-23) which exhibited very good in vitro cytotoxic activities with the IC50 values of (0.017 5±0.0060) µg/mL, (0.089±0.005) µg/mL and (1.027±0.070) µg/mL respectively. Thus, they support the claims of traditional healers and suggest the possible correlation between the chemical composition of this plant and its wide use in Malagasy folk medicine to treat cancer. Conclusions The ability of isolated compounds in this study to inhibit cell growth may represent a rational explanation for the use of Diospyros quercina root bark in treating cancer by Malagasy traditional healers. Further studies are, therefore, necessary to evaluate the in vivo anti-neoplastic activity of these cytotoxic compounds as effective anticancer drugs. PMID:25182433

G protein-coupled receptor internalization assays in the high-content screening format.

PubMed

Haasen, Dorothea; Schnapp, Andreas; Valler, Martin J; Heilker, Ralf

2006-01-01

High-content screening (HCS), a combination of fluorescence microscopic imaging and automated image analysis, has become a frequently applied tool to study test compound effects in cellular disease-modeling systems. This chapter describes the measurement of G protein-coupled receptor (GPCR) internalization in the HCS format using a high-throughput, confocal cellular imaging device. GPCRs are the most successful group of therapeutic targets on the pharmaceutical market. Accordingly, the search for compounds that interfere with GPCR function in a specific and selective way is a major focus of the pharmaceutical industry today. This chapter describes methods for the ligand-induced internalization of GPCRs labeled previously with either a fluorophore-conjugated ligand or an antibody directed against an N-terminal tag of the GPCR. Both labeling techniques produce robust assay formats. Complementary to other functional GPCR drug discovery assays, internalization assays enable a pharmacological analysis of test compounds. We conclude that GPCR internalization assays represent a valuable medium/high-throughput screening format to determine the cellular activity of GPCR ligands.

Selective arylsulfonamide inhibitors of ADAM-17: hit optimization and activity in ovarian cancer cell models.

PubMed

Nuti, Elisa; Casalini, Francesca; Santamaria, Salvatore; Fabbi, Marina; Carbotti, Grazia; Ferrini, Silvano; Marinelli, Luciana; La Pietra, Valeria; Novellino, Ettore; Camodeca, Caterina; Orlandini, Elisabetta; Nencetti, Susanna; Rossello, Armando

2013-10-24

Activated leukocyte cell adhesion molecule (ALCAM) is expressed at the surface of epithelial ovarian cancer (EOC) cells and is released in a soluble form (sALCAM) by ADAM-17-mediated shedding. This process is relevant to EOC cell motility and invasiveness, which is reduced by inhibitors of ADAM-17. In addition, ADAM-17 plays a key role in EGFR signaling and thus may represent a useful target in anticancer therapy. Herein we report our hit optimization effort to identify potent and selective ADAM-17 inhibitors, starting with previously identified inhibitor 1. A new series of secondary sulfonamido-based hydroxamates was designed and synthesized. The biological activity of the newly synthesized compounds was tested in vitro on isolated enzymes and human EOC cell lines. The optimization process led to compound 21, which showed an IC50 of 1.9 nM on ADAM-17 with greatly increased selectivity. This compound maintained good inhibitory properties on sALCAM shedding in several in vitro assays.

Bromomethylthioindole Inspired Carbazole Hybrids as Promising Class of Anti-MRSA Agents

PubMed Central

2016-01-01

Series of N-substituted carbazole analogues bearing an indole ring were synthesized as anti-methicillin-resistant Staphylococcus aureus (MRSA) agents from a molecular hybridization approach. The representative compound 19 showed an MIC = 1 μg/mL against a panel of MRSA clinical isolates as it possessed comparable in vitro activities to that of vancomycin. Moreover, compound 19 also exhibited MIC = 1 μg/mL activities against a recent identified Z172 MRSA strain (vancomycin-intermediate and daptomycin-nonsusceptible phenotype) and the vancomycin-resistant Enterococcus faecalis (VRE) strain. In a mouse model with lethal infection of MRSA (4N216), a 75% survival rate was observed after a single dose of compound 19 was intravenously administered at 20 mg/kg. In light of their equipotent activities against different MRSA isolates and VRE strain, the data underscore the importance of designed hybrid series for the development of new N-substituted carbazoles as potential anti-MRSA agents. PMID:27994762

Distribution of apparent activation energy counterparts during thermo - And thermo-oxidative degradation of Aronia melanocarpa (black chokeberry).

PubMed

Janković, Bojan; Marinović-Cincović, Milena; Janković, Marija

2017-09-01

Kinetics of degradation for Aronia melanocarpa fresh fruits in argon and air atmospheres were investigated. The investigation was based on probability distributions of apparent activation energy of counterparts (ε a ). Isoconversional analysis results indicated that the degradation process in an inert atmosphere was governed by decomposition reactions of esterified compounds. Also, based on same kinetics approach, it was assumed that in an air atmosphere, the primary compound in degradation pathways could be anthocyanins, which undergo rapid chemical reactions. A new model of reactivity demonstrated that, under inert atmospheres, expectation values for ε a occured at levels of statistical probability. These values corresponded to decomposition processes in which polyphenolic compounds might be involved. ε a values obeyed laws of binomial distribution. It was established that, for thermo-oxidative degradation, Poisson distribution represented a very successful approximation for ε a values where there was additional mechanistic complexity and the binomial distribution was no longer valid. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multitarget Therapeutic Leads for Alzheimer's Disease: Quinolizidinyl Derivatives of Bi- and Tricyclic Systems as Dual Inhibitors of Cholinesterases and β-Amyloid (Aβ) Aggregation.

PubMed

Tonelli, Michele; Catto, Marco; Tasso, Bruno; Novelli, Federica; Canu, Caterina; Iusco, Giovanna; Pisani, Leonardo; Stradis, Angelo De; Denora, Nunzio; Sparatore, Anna; Boido, Vito; Carotti, Angelo; Sparatore, Fabio

2015-06-01

Multitarget therapeutic leads for Alzheimer's disease were designed on the models of compounds capable of maintaining or restoring cell protein homeostasis and of inhibiting β-amyloid (Aβ) oligomerization. Thirty-seven thioxanthen-9-one, xanthen-9-one, naphto- and anthraquinone derivatives were tested for the direct inhibition of Aβ(1-40) aggregation and for the inhibition of electric eel acetylcholinesterase (eeAChE) and horse serum butyrylcholinesterase (hsBChE). These compounds are characterized by basic side chains, mainly quinolizidinylalkyl moieties, linked to various bi- and tri-cyclic (hetero)aromatic systems. With very few exceptions, these compounds displayed inhibitory activity on both AChE and BChE and on the spontaneous aggregation of β-amyloid. In most cases, IC50 values were in the low micromolar and sub-micromolar range, but some compounds even reached nanomolar potency. The time course of amyloid aggregation in the presence of the most active derivative (IC50 =0.84 μM) revealed that these compounds might act as destabilizers of mature fibrils rather than mere inhibitors of fibrillization. Many compounds inhibited one or both cholinesterases and Aβ aggregation with similar potency, a fundamental requisite for the possible development of therapeutics exhibiting a multitarget mechanism of action. The described compounds thus represent interesting leads for the development of multitarget AD therapeutics. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

PubMed

Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

2012-08-01

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

Binding Mode Analyses and Pharmacophore Model Development for Stilbene Derivatives as a Novel and Competitive Class of α-Glucosidase Inhibitors

PubMed Central

Kim, Jun Young; Arooj, Mahreen; Kim, Siu; Hwang, Swan; Kim, Byeong-Woo; Park, Ki Hun; Lee, Keun Woo

2014-01-01

Stilbene urea derivatives as a novel and competitive class of non-glycosidic α-glucosidase inhibitors are effective for the treatment of type II diabetes and obesity. The main purposes of our molecular modeling study are to explore the most suitable binding poses of stilbene derivatives with analyzing the binding affinity differences and finally to develop a pharmacophore model which would represents critical features responsible for α-glucosidase inhibitory activity. Three-dimensional structure of S. cerevisiae α-glucosidase was built by homology modeling method and the structure was used for the molecular docking study to find out the initial binding mode of compound 12, which is the most highly active one. The initial structure was subjected to molecular dynamics (MD) simulations for protein structure adjustment at compound 12-bound state. Based on the adjusted conformation, the more reasonable binding modes of the stilbene urea derivatives were obtained from molecular docking and MD simulations. The binding mode of the derivatives was validated by correlation analysis between experimental Ki value and interaction energy. Our results revealed that the binding modes of the potent inhibitors were engaged with important hydrogen bond, hydrophobic, and π-interactions. With the validated compound 12-bound structure obtained from combining approach of docking and MD simulation, a proper four featured pharmacophore model was generated. It was also validated by comparison of fit values with the Ki values. Thus, these results will be helpful for understanding the relationship between binding mode and bioactivity and for designing better inhibitors from stilbene derivatives. PMID:24465730

How Displaced Migratory Birds Could Use Volatile Atmospheric Compounds to Find Their Migratory Corridor: A Test Using a Particle Dispersion Model

PubMed Central

Safi, Kamran; Gagliardo, Anna; Wikelski, Martin; Kranstauber, Bart

2016-01-01

Olfaction represents an important sensory modality for navigation of both homing pigeons and wild birds. Experimental evidence in homing pigeons showed that airborne volatile compounds carried by the winds at the home area are learned in association with wind directions. When displaced, pigeons obtain information on the direction of their displacement using local odors at the release site. Recently, the role of olfactory cues in navigation has been reported also for wild birds during migration. However, the question whether wild birds develop an olfactory navigational map similar to that described in homing pigeons or, alternatively, exploit the distribution of volatile compounds in different manner for reaching the goal is still an open question. Using an interdisciplinary approach, we evaluate the possibilities of reconstructing spatio-temporally explicit aerosol dispersion at large spatial scales using the particle dispersion model FLEXPART. By combining atmospheric information with particle dispersion models, atmospheric scientists predict the dispersion of pollutants for example, after nuclear fallouts or volcanic eruptions or wildfires, or in retrospect reconstruct the origin of emissions such as aerosols. Using simple assumptions, we reconstructed the putative origin of aerosols traveling to the location of migrating birds. We use the model to test whether the putative odor plume could have originated from an important stopover site. If the migrating birds knew this site and the associated plume from previous journeys, the odor could contribute to the reorientation towards the migratory corridor, as suggested for the model scenario in displaced Lesser black-backed gulls migrating from Northern Europe into Africa. PMID:27799899

Design, Synthesis and Biological Evaluation of Novel Peptide-Like Analogues as Selective COX-2 Inhibitors

PubMed Central

Ahmaditaba, Mohammad Ali; Houshdar Tehrani, Mohammad Hassan; Zarghi, Afshin; Shahosseini, Sorayya; Daraei, Bahram

2018-01-01

A new series of peptide-like derivatives containing different aromatic amino acids and possessing pharmacophores of COX-2 inhibitors as SO2Me or N3 attached to the para position of an end phenyl ring was synthesized for evaluation as selective cyclooxygenase-2 (COX-2) inhibitors. The synthetic reactions were based on the solid phase peptide synthesis method using Wang resin. One of the analogues, i.e., compound 2d, as the representative of these series was recognized as the most effective and the highest selective COX-2 inhibitor with IC50 value of 0.08 μM and COX-2 selectivity index of 351.2, among the other synthesized compounds. Molecular docking study was operated to determine possible binding models of compound 2d to COX-2 enzyme. The study showed that the p-azido-phenyl fragment of 2d occupied inside the secondary COX-2 binding site (Arg513, and His90). The structure-activity relationships acquired disclosed that compound 2d with 4-(azido phenyl) group as pharmacophore and histidine as amino acid gives the essential geometry to provide inhibition of the COX-2 enzyme with high selectivity. Compound 2d can be a good candidate for the development of new hits of COX-2 inhibitors.

Efficacy of 2'-C-methylcytidine against yellow fever virus in cell culture and in a hamster model.

PubMed

Julander, Justin G; Jha, Ashok K; Choi, Jung-Ae; Jung, Kie-Hoon; Smee, Donald F; Morrey, John D; Chu, Chung K

2010-06-01

Yellow fever virus (YFV) continues to cause outbreaks of disease in endemic areas where vaccine is underutilized. Due to the effectiveness of the vaccine, antiviral development solely for the treatment of YFV is not feasible, but antivirals that are effective in the treatment of related viral diseases may be characterized for potential use against YFV as a secondary indication disease. 2'-C-methylcytidine (2'-C-MeC), a compound active against hepatitis C virus, was found to have activity against the 17D vaccine strain of YFV in cell culture (EC(90)=0.32 microg/ml, SI=141). This compound was effective when added as late as 16 h after virus challenge of Vero cells. When administered to YFV-infected hamsters 4 h prior to virus challenge at a dose as low as 80 mg/kg/d, 2'-C-MeC was effective in significantly improving survival and other disease parameters (weight change, serum ALT, and liver virus titers). Disease was improved when compound was administered beginning as late as 3 d post-virus infection. Broadly active antiviral compounds, such as 2'-C-MeC, represent potential for the development of compounds active against related viruses for the treatment of YFV. Copyright 2010 Elsevier B.V. All rights reserved.

Decaffeinated Coffee and Nicotine-Free Tobacco Provide Neuroprotection in Drosophila Models of Parkinson's Disease through an NRF2-Dependent Mechanism

PubMed Central

Trinh, Kien; Andrews, Laurie; Krause, James; Hanak, Tyler; Lee, Daewoo; Gelb, Michael

2010-01-01

Epidemiological studies have revealed a significantly reduced risk of Parkinson's disease (PD) among coffee and tobacco users, although it is unclear whether these correlations reflect neuroprotective/symptomatic effects of these agents or preexisting differences in the brains of tobacco and coffee users. Here, we report that coffee and tobacco, but not caffeine or nicotine, are neuroprotective in fly PD models. We further report that decaffeinated coffee and nicotine-free tobacco are as neuroprotective as their caffeine and nicotine-containing counterparts and that the neuroprotective effects of decaffeinated coffee and nicotine-free tobacco are also evident in Drosophila models of Alzheimer's disease and polyglutamine disease. Finally, we report that the neuroprotective effects of decaffeinated coffee and nicotine-free tobacco require the cytoprotective transcription factor Nrf2 and that a known Nrf2 activator in coffee, cafestol, is also able to confer neuroprotection in our fly models of PD. Our findings indicate that coffee and tobacco contain Nrf2-activating compounds that may account for the reduced risk of PD among coffee and tobacco users. These compounds represent attractive candidates for therapeutic intervention in PD and perhaps other neurodegenerative diseases. PMID:20410106

The polygonal model: A simple representation of biomolecules as a tool for teaching metabolism.

PubMed

Bonafe, Carlos Francisco Sampaio; Bispo, Jose Ailton Conceição; de Jesus, Marcelo Bispo

2018-01-01

Metabolism involves numerous reactions and organic compounds that the student must master to understand adequately the processes involved. Part of biochemical learning should include some knowledge of the structure of biomolecules, although the acquisition of such knowledge can be time-consuming and may require significant effort from the student. In this report, we describe the "polygonal model" as a new means of graphically representing biomolecules. This model is based on the use of geometric figures such as open triangles, squares, and circles to represent hydroxyl, carbonyl, and carboxyl groups, respectively. The usefulness of the polygonal model was assessed by undergraduate students in a classroom activity that consisted of "transforming" molecules from Fischer models to polygonal models and vice and versa. The survey was applied to 135 undergraduate Biology and Nursing students. Students found the model easy to use and we noted that it allowed identification of students' misconceptions in basic concepts of organic chemistry, such as in stereochemistry and organic groups that could then be corrected. The students considered the polygonal model easier and faster for representing molecules than Fischer representations, without loss of information. These findings indicate that the polygonal model can facilitate the teaching of metabolism when the structures of biomolecules are discussed. Overall, the polygonal model promoted contact with chemical structures, e.g. through drawing activities, and encouraged student-student dialog, thereby facilitating biochemical learning. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):66-75, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

Investigation of the "true" extraction recovery of analytes from multiple types of tissues and its impact on tissue bioanalysis using two model compounds.

PubMed

Yuan, Long; Ma, Li; Dillon, Lisa; Fancher, R Marcus; Sun, Huadong; Zhu, Mingshe; Lehman-McKeeman, Lois; Aubry, Anne-Françoise; Ji, Qin C

2016-11-16

LC-MS/MS has been widely applied to the quantitative analysis of tissue samples. However, one key remaining issue is that the extraction recovery of analyte from spiked tissue calibration standard and quality control samples (QCs) may not accurately represent the "true" recovery of analyte from incurred tissue samples. This may affect the accuracy of LC-MS/MS tissue bioanalysis. Here, we investigated whether the recovery determined using tissue QCs by LC-MS/MS can accurately represent the "true" recovery from incurred tissue samples using two model compounds: BMS-986104, a S1P 1 receptor modulator drug candidate, and its phosphate metabolite, BMS-986104-P. We first developed a novel acid and surfactant assisted protein precipitation method for the extraction of BMS-986104 and BMS-986104-P from rat tissues, and determined their recoveries using tissue QCs by LC-MS/MS. We then used radioactive incurred samples from rats dosed with 3 H-labeled BMS-986104 to determine the absolute total radioactivity recovery in six different tissues. The recoveries determined using tissue QCs and incurred samples matched with each other very well. The results demonstrated that, in this assay, tissue QCs accurately represented the incurred tissue samples to determine the "true" recovery, and LC-MS/MS assay was accurate for tissue bioanalysis. Another aspect we investigated is how the tissue QCs should be prepared to better represent the incurred tissue samples. We compared two different QC preparation methods (analyte spiked in tissue homogenates or in intact tissues) and demonstrated that the two methods had no significant difference when a good sample preparation was in place. The developed assay showed excellent accuracy and precision, and was successfully applied to the quantitative determination of BMS-986104 and BMS-986104-P in tissues in a rat toxicology study. Copyright © 2016 Elsevier B.V. All rights reserved.

Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States

USGS Publications Warehouse

Stackelberg, Paul E.; Barbash, Jack E.; Gilliom, Robert J.; Stone, Wesley W.; Wolock, David M.

2012-01-01

Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro-N-(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate that variability in the concentration of atrazine residues (atrazine plus DEA) in groundwater underlying agricultural areas is more strongly controlled by the history of atrazine use in relation to the timing of recharge (groundwater age) than by processes that control the dispersion, adsorption, or degradation of these compounds in the saturated zone. Current (1990s) atrazine use was found to be a weak explanatory variable, perhaps because it does not represent the use of atrazine at the time of recharge of the sampled groundwater and because the likelihood that these compounds will reach the water table is affected by other factors operating within the unsaturated zone, such as soil characteristics, artificial drainage, and water movement. Results show that only about 5% of agricultural areas have greater than a 10% probability of exceeding the USEPA maximum contaminant level of 3.0 μg L-1. These models are not developed for regulatory purposes but rather can be used to (i) identify areas of potential concern, (ii) provide conservative estimates of the concentrations of atrazine residues in deeper potential drinking water supplies, and (iii) set priorities among areas for future groundwater monitoring.

Metarrestin, a perinucleolar compartment inhibitor, effectively suppresses metastasis.

PubMed

Frankowski, Kevin J; Wang, Chen; Patnaik, Samarjit; Schoenen, Frank J; Southall, Noel; Li, Dandan; Teper, Yaroslav; Sun, Wei; Kandela, Irawati; Hu, Deqing; Dextras, Christopher; Knotts, Zachary; Bian, Yansong; Norton, John; Titus, Steve; Lewandowska, Marzena A; Wen, Yiping; Farley, Katherine I; Griner, Lesley Mathews; Sultan, Jamey; Meng, Zhaojing; Zhou, Ming; Vilimas, Tomas; Powers, Astin S; Kozlov, Serguei; Nagashima, Kunio; Quadri, Humair S; Fang, Min; Long, Charles; Khanolkar, Ojus; Chen, Warren; Kang, Jinsol; Huang, Helen; Chow, Eric; Goldberg, Esthermanya; Feldman, Coral; Xi, Romi; Kim, Hye Rim; Sahagian, Gary; Baserga, Susan J; Mazar, Andrew; Ferrer, Marc; Zheng, Wei; Shilatifard, Ali; Aubé, Jeffrey; Rudloff, Udo; Marugan, Juan Jose; Huang, Sui

2018-05-16

Metastasis remains a leading cause of cancer mortality due to the lack of specific inhibitors against this complex process. To identify compounds selectively targeting the metastatic state, we used the perinucleolar compartment (PNC), a complex nuclear structure associated with metastatic behaviors of cancer cells, as a phenotypic marker for a high-content screen of over 140,000 structurally diverse compounds. Metarrestin, obtained through optimization of a screening hit, disassembles PNCs in multiple cancer cell lines, inhibits invasion in vitro, suppresses metastatic development in three mouse models of human cancer, and extends survival of mice in a metastatic pancreatic cancer xenograft model with no organ toxicity or discernable adverse effects. Metarrestin disrupts the nucleolar structure and inhibits RNA polymerase (Pol) I transcription, at least in part by interacting with the translation elongation factor eEF1A2. Thus, metarrestin represents a potential therapeutic approach for the treatment of metastatic cancer. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Marine guanidine alkaloids crambescidins inhibit tumor growth and activate intrinsic apoptotic signaling inducing tumor regression in a colorectal carcinoma zebrafish xenograft model.

PubMed

Roel, María; Rubiolo, Juan A; Guerra-Varela, Jorge; Silva, Siguara B L; Thomas, Olivier P; Cabezas-Sainz, Pablo; Sánchez, Laura; López, Rafael; Botana, Luis M

2016-12-13

The marine environment constitutes an extraordinary resource for the discovery of new therapeutic agents. In the present manuscript we studied the effect of 3 different sponge derived guanidine alkaloids, crambescidine-816, -830, and -800. We show that these compounds strongly inhibit tumor cell proliferation by down-regulating cyclin-dependent kinases 2/6 and cyclins D/A expression while up-regulating the cell cyclin-dependent kinase inhibitors -2A, -2D and -1A. We also show that these guanidine compounds disrupt tumor cell adhesion and cytoskeletal integrity promoting the activation of the intrinsic apoptotic signaling, resulting in loss of mitochondrial membrane potential and concomitant caspase-3 cleavage and activation. The crambescidin 816 anti-tumor effect was fnally assayed in a zebrafish xenotransplantation model confirming its potent antitumor activity against colorectal carcinoma in vivo.Considering these results crambescidins could represent promising natural anticancer agents and therapeutic tools.

Marine guanidine alkaloids crambescidins inhibit tumor growth and activate intrinsic apoptotic signaling inducing tumor regression in a colorectal carcinoma zebrafish xenograft model

PubMed Central

Roel, María; Rubiolo, Juan A.; Guerra-Varela, Jorge; Silva, Siguara B. L.; Thomas, Olivier P.; Cabezas-Sainz, Pablo; Sánchez, Laura; López, Rafael; Botana, Luis M.

2016-01-01

The marine environment constitutes an extraordinary resource for the discovery of new therapeutic agents. In the present manuscript we studied the effect of 3 different sponge derived guanidine alkaloids, crambescidine-816, -830, and -800. We show that these compounds strongly inhibit tumor cell proliferation by down-regulating cyclin-dependent kinases 2/6 and cyclins D/A expression while up-regulating the cell cyclin-dependent kinase inhibitors -2A, -2D and -1A. We also show that these guanidine compounds disrupt tumor cell adhesion and cytoskeletal integrity promoting the activation of the intrinsic apoptotic signaling, resulting in loss of mitochondrial membrane potential and concomitant caspase-3 cleavage and activation. The crambescidin 816 anti-tumor effect was fnally assayed in a zebrafish xenotransplantation model confirming its potent antitumor activity against colorectal carcinoma in vivo. Considering these results crambescidins could represent promising natural anticancer agents and therapeutic tools. PMID:27825113

Novel substituted (pyridin-3-yl)phenyloxazolidinones: antibacterial agents with reduced activity against monoamine oxidase A and increased solubility.

PubMed

Reck, Folkert; Zhou, Fei; Eyermann, Charles J; Kern, Gunther; Carcanague, Dan; Ioannidis, Georgine; Illingworth, Ruth; Poon, Grace; Gravestock, Michael B

2007-10-04

Oxazolidinones represent a new and promising class of antibacterial agents. Current research in this area is mainly concentrated on improving the safety profile and the antibacterial spectrum. Oxazolidinones bearing a (pyridin-3-yl)phenyl moiety (e.g., 3) generally show improved antibacterial activity compared to linezolid but suffer from potent monoamine oxidase A (MAO-A) inhibition and low solubility. We now disclose the finding that new analogues of 3 with acyclic substituents on the pyridyl moiety exhibit excellent activity against Gram-positive pathogens, including linezolid-resistant Streptococcus pneumoniae. Generally, more bulky substituents yielded significantly reduced MAO-A inhibition relative to the unsubstituted compound 3. The MAO-A SAR can be rationalized on the basis of docking studies using a MAO-A/MAO-B homology model. Solubility was enhanced with incorporation of polar groups. One optimized analogue, compound 13, showed low clearance in the rat and efficacy against S. pneumoniae in a mouse pneumonia model.

Discovery of a Novel Class of Survival Motor Neuron 2 Splicing Modifiers for the Treatment of Spinal Muscular Atrophy.

PubMed

Pinard, Emmanuel; Green, Luke; Reutlinger, Michael; Weetall, Marla; Naryshkin, Nikolai A; Baird, John; Chen, Karen S; Paushkin, Sergey V; Metzger, Friedrich; Ratni, Hasane

2017-05-25

Spinal muscular atrophy (SMA) is caused by mutation or deletion of the survival motor neuron 1 (SMN1) gene, resulting in low levels of functional SMN protein. We have reported recently the identification of small molecules (coumarins, iso-coumarins and pyrido-pyrimidinones) that modify the alternative splicing of SMN2, a paralogous gene to SMN1, restoring the survival motor neuron (SMN) protein level in mouse models of SMA. Herein, we report our efforts to identify a novel chemotype as one strategy to potentially circumvent safety concerns from earlier derivatives such as in vitro phototoxicity and in vitro mutagenicity associated with compounds 1 and 2 or the in vivo retinal findings observed in a long-term chronic tox study with 3 at high exposures only. Optimized representative compounds modify the alternative splicing of SMN2, increase the production of full length SMN2 mRNA, and therefore levels of full length SMN protein upon oral administration in two mouse models of SMA.

Augmented multivariate image analysis applied to quantitative structure-activity relationship modeling of the phytotoxicities of benzoxazinone herbicides and related compounds on problematic weeds.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2013-09-11

Two of major weeds affecting cereal crops worldwide are Avena fatua L. (wild oat) and Lolium rigidum Gaud. (rigid ryegrass). Thus, development of new herbicides against these weeds is required; in line with this, benzoxazinones, their degradation products, and analogues have been shown to be important allelochemicals and natural herbicides. Despite earlier structure-activity studies demonstrating that hydrophobicity (log P) of aminophenoxazines correlates to phytotoxicity, our findings for a series of benzoxazinone derivatives do not show any relationship between phytotoxicity and log P nor with other two usual molecular descriptors. On the other hand, a quantitative structure-activity relationship (QSAR) analysis based on molecular graphs representing structural shape, atomic sizes, and colors to encode other atomic properties performed very accurately for the prediction of phytotoxicities of these compounds against wild oat and rigid ryegrass. Therefore, these QSAR models can be used to estimate the phytotoxicity of new congeners of benzoxazinone herbicides toward A. fatua L. and L. rigidum Gaud.

Effect of historical land-use and climate change on tree-climate relationships in the upper Midwestern United States.

PubMed

Goring, Simon J; Williams, John W

2017-04-01

Contemporary forest inventory data are widely used to understand environmental controls on tree species distributions and to construct models to project forest responses to climate change, but the stability and representativeness of contemporary tree-climate relationships are poorly understood. We show that tree-climate relationships for 15 tree genera in the upper Midwestern US have significantly altered over the last two centuries due to historical land-use and climate change. Realised niches have shifted towards higher minimum temperatures and higher rainfall. A new attribution method implicates both historical climate change and land-use in these shifts, with the relative importance varying among genera and climate variables. Most climate/land-use interactions are compounding, in which historical land-use reinforces shifts in species-climate relationships toward wetter distributions, or confounding, in which land-use complicates shifts towards warmer distributions. Compounding interactions imply that contemporary-based models of species distributions may underestimate species resilience to climate change. © 2017 John Wiley & Sons Ltd/CNRS.

New insights into single-compound and binary adsorption of copper and lead ions on a treated sea mango shell: experimental and theoretical studies.

PubMed

Sellaoui, Lotfi; Edi Soetaredjo, Felycia; Ismadji, Suryadi; Cláudio Lima, Éder; Dotto, Guilherme L; Ben Lamine, Abdelmottaleb; Erto, Alessandro

2017-10-04

Herein, adsorption isotherms of Pb(ii) and Cu(ii) ions on treated sea mango fruit in both single-compound and binary systems were experimentally realized at different temperatures in the range of 30-50 °C. Experimental results show that adsorption of Pb(ii) was more as compared to that of Cu(ii) ions; however, for both ions, a significant reduction in the adsorption capacity was observed in the binary system as compared to that in the single-compound systems. Moreover, under all the investigated conditions, adsorption seems to be promoted by an increase in temperature. To understand and interpret the experimental evidences, the Hill and competitive Hill models developed on the basis of the grand canonical ensemble were applied for the analysis of adsorption equilibrium data. These models contain some physicochemical parameters that allow an exhaustive analysis of the dynamics of single-compound and binary adsorptions. Based on the fitting results, in particular, through the evaluation of the number of ions bonded per site (n and n i ), it was found that lead and copper ions interacted by inclined and horizontal positions on treated sea mango in single-compound and binary systems, respectively. In addition, based on the same parameters, a significant interaction between ions was retrieved. A study focused on the saturation adsorption capacity in single-compound and binary systems affirmed that the adsorbent was more selective for lead than for copper. The reduction of the adsorbed capacity ratio between the binary and single-compound systems (i.e. Q b /Q s ) explained and confirmed that an inhibition effect between copper and lead ions at the same receptor site occurred. Finally, based on the energetic investigations, it was deduced that the adsorption energy represented the dominant factor promoting the greater adsorption of lead than that of copper in both systems.

Identification of novel antitubulin agents by using a virtual screening approach based on a 7-point pharmacophore model of the tubulin colchi-site.

PubMed

Massarotti, Alberto; Theeramunkong, Sewan; Mesenzani, Ornella; Caldarelli, Antonio; Genazzani, Armando A; Tron, Gian Cesare

2011-12-01

Tubulin inhibition represents an established target in the field of anticancer research, and over the last 20 years, an intensive search for new antimicrotubule agents has occurred. Indeed, in silico models have been presented that might aid the discovery of novel agents. Among these, a 7-point pharmacophore model has been recently proposed. As a formal proof of this model, we carried out a ligand-based virtual screening on the colchicine-binding site. In vitro testing demonstrated that two compounds displayed a cytotoxic profile on neuroblastoma cancer cells (SH-SY5H) and one had an antitubulinic profile. © 2011 John Wiley & Sons A/S.

[Prognostic model of the space station contamination stage].

PubMed

Zlotovol'skiĭ, V M; Smolenskaia, G S

1998-01-01

Forty two non-metallic materials, 8 human metabolites and a process liquid (ethylene glycol) were selected for development of a prognostic model of space station contamination by harmful trace admixtures (HTAs). Removal technologies made allowance for absorption by atmospheric condensate (AC) and filter adsorption. Calculations took in 18 HTAs representative of 8 classes of compounds. Simulation modeling allowed to determine HTA migration rates and percent ratio (1), calculate concentrations of contaminants in the atmosphere and atmospheric condensate (2), and to assess filter efficiency by comparison of loads on the filter and a refrigeration/drying set (3). Comparison of empirical and measured data permitted conclusions about adequacy of the model and its potentiality for predicting ramifications of nominal and contingency situations.

The role of the resid solvent in coprocessing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Curtis, C.W.

1995-12-31

The objective of this project is to determine the role of petroleum resid in coprocessing of coal and resid. The question being asked is whether the resid is a reactant in the system or whether the resid is a merely a diluent that is being simultaneously upgraded? To fulfill the objective the hydrogen transfer from model compounds, naphthenes that represent petroleum resids to model acceptors is being determined. The specificity of different catalytic systems for promoting the hydrogen transfer from naphthenes to model acceptors and to coal is also being determined. In addition the efficacy of hydrogen transfer from andmore » solvancy of whole and specific resid fractions under coprocessing conditions is being determined.« less

Combining functional genomics and chemical biology to identify targets of bioactive compounds.

PubMed

Ho, Cheuk Hei; Piotrowski, Jeff; Dixon, Scott J; Baryshnikova, Anastasia; Costanzo, Michael; Boone, Charles

2011-02-01

Genome sequencing projects have revealed thousands of suspected genes, challenging researchers to develop efficient large-scale functional analysis methodologies. Determining the function of a gene product generally requires a means to alter its function. Genetically tractable model organisms have been widely exploited for the isolation and characterization of activating and inactivating mutations in genes encoding proteins of interest. Chemical genetics represents a complementary approach involving the use of small molecules capable of either inactivating or activating their targets. Saccharomyces cerevisiae has been an important test bed for the development and application of chemical genomic assays aimed at identifying targets and modes of action of known and uncharacterized compounds. Here we review yeast chemical genomic assays strategies for drug target identification. Copyright © 2010 Elsevier Ltd. All rights reserved.

Discovery of piperidin-4-yl-aminopyrimidine derivatives as potent non-nucleoside HIV-1 reverse transcriptase inhibitors.

PubMed

Wan, Zheng-Yong; Yao, Jin; Tao, Yuan; Mao, Tian-Qi; Wang, Xin-Long; Lu, Yi-Pei; Wang, Hai-Feng; Yin, Hong; Wu, Yan; Chen, Fen-Er; De Clercq, Erik; Daelemans, Dirk; Pannecouque, Christophe

2015-06-05

A novel series of piperidin-4-yl-aminopyrimidine derivatives were designed fusing the pharmacophore templates of etravirine-VRX-480773 hybrids our group previously described and piperidine-linked aminopyrimidines. Most compounds displayed significantly improved activity against wild-type HIV-1 with EC50 values in single-digit nanomolar concentrations compared to etravirine-VRX-480773 hybrids. Selected compounds were also evaluated for activity against reverse transcriptase, and had lower IC50 values than that of nevirapine. The improved potency observed in this in vitro model of HIV RNA replication partly validates the mechanism by which this class of allosteric pyrimidine derivatives inhibits reverse transcriptase, and represents a remarkable step forward in the development of AIDS therapeutics. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Molecular structures and thermodynamic properties of monohydrated gaseous iodine compounds: Modelling for severe accident simulation

NASA Astrophysics Data System (ADS)

Sudolská, Mária; Cantrel, Laurent; Budzák, Šimon; Černušák, Ivan

2014-03-01

Monohydrated complexes of iodine species (I, I2, HI, and HOI) have been studied by correlated ab initio calculations. The standard enthalpies of formation, Gibbs free energy and the temperature dependence of the heat capacities at constant pressure were calculated. The values obtained have been implemented in ASTEC nuclear accident simulation software to check the thermodynamic stability of hydrated iodine compounds in the reactor coolant system and in the nuclear containment building of a pressurised water reactor during a severe accident. It can be concluded that iodine complexes are thermodynamically unstable by means of positive Gibbs free energies and would be represented by trace level concentrations in severe accident conditions; thus it is well justified to only consider pure iodine species and not hydrated forms.

Prediction of gas chromatographic retention indices by the use of radial basis function neural networks.

PubMed

Yao, Xiaojun; Zhang, Xiaoyun; Zhang, Ruisheng; Liu, Mancang; Hu, Zhide; Fan, Botao

2002-05-16

A new method for the prediction of retention indices for a diverse set of compounds from their physicochemical parameters has been proposed. The two used input parameters for representing molecular properties are boiling point and molar volume. Models relating relationships between physicochemical parameters and retention indices of compounds are constructed by means of radial basis function neural networks. To get the best prediction results, some strategies are also employed to optimize the topology and learning parameters of the RBFNNs. For the test set, a predictive correlation coefficient R=0.9910 and root mean squared error of 14.1 are obtained. Results show that radial basis function networks can give satisfactory prediction ability and its optimization is less-time consuming and easy to implement.

Moving beyond the van Krevelen Diagram: A New Stoichiometric Approach for Compound Classification in Organisms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivas-Ubach, Albert; Liu, Yina; Bianchi, Thomas S.

van Krevelen diagrams (O:C vs H:C ratios of elemental formulas) have been widely used in studies to obtain an estimation of the main compound categories present in environmental samples. However, the limits defining a specific compound category based solely on O:C and H:C ratios of elemental formulas have never been accurately listed or proposed to classify metabolites in biological samples. Furthermore, while O:C vs. H:C ratios of elemental formulas can provide an overview of the compound categories, such classification is inefficient because of the large overlap among different compound categories along both axes. We propose a more accurate compound classificationmore » for biological samples analyzed by high-resolution mass spectrometry-based on an assessment of the C:H:O:N:P stoichiometric ratios of over 130,000 elemental formulas of compounds classified in 6 main categories: lipids, peptides, amino-sugars, carbohydrates, nucleotides and phytochemical compounds (oxy-aromatic compounds). Our multidimensional stoichiometric compound classification (MSCC) constraints showed a highly accurate categorization of elemental formulas to the main compound categories in biological samples with over 98% of accuracy representing a substantial improvement over any classification based on the classic van Krevelen diagram. This method represents a significant step forward in environmental research, especially ecological stoichiometry and eco-metabolomics studies, by providing a novel and robust tool to further our understanding the ecosystem structure and function through the chemical characterization of different biological samples.« less

Field guide for collecting samples for analysis of volatile organic compounds in stream water for the National Water-Quality Assessment Program

USGS Publications Warehouse

Shelton, Larry R.

1997-01-01

For many years, stream samples for analysis of volatile organic compounds have been collected without specific guidelines or a sampler designed to avoid analyte loss. In 1996, the U.S. Geological Survey's National Water-Quality Assessment Program began aggressively monitoring urban stream-water for volatile organic compounds. To assure representative samples and consistency in collection procedures, a specific sampler was designed to collect samples for analysis of volatile organic compounds in stream water. This sampler, and the collection procedures, were tested in the laboratory and in the field for compound loss, contamination, sample reproducibility, and functional capabilities. This report describes that sampler and its use, and outlines field procedures specifically designed to provide contaminant-free, reproducible volatile organic compound data from stream-water samples. These guidelines and the equipment described represent a significant change in U.S. Geological Survey instructions for collecting and processing stream-water samples for analysis of volatile organic compounds. They are intended to produce data that are both defensible and interpretable, particularly for concentrations below the microgram-per-liter level. The guidelines also contain detailed recommendations for quality-control samples.

Charge-dependent non-bonded interaction methods for use in quantum mechanical modeling of condensed phase reactions

NASA Astrophysics Data System (ADS)

Kuechler, Erich R.

Molecular modeling and computer simulation techniques can provide detailed insight into biochemical phenomena. This dissertation describes the development, implementation and parameterization of two methods for the accurate modeling of chemical reactions in aqueous environments, with a concerted scientific effort towards the inclusion of charge-dependent non-bonded non-electrostatic interactions into currently used computational frameworks. The first of these models, QXD, modifies interactions in a hybrid quantum mechanical/molecular (QM/MM) mechanical framework to overcome the current limitations of 'atom typing' QM atoms; an inaccurate and non-intuitive practice for chemically active species as these static atom types are dictated by the local bonding and electrostatic environment of the atoms they represent, which will change over the course of the simulation. The efficacy QXD model is demonstrated using a specific reaction parameterization (SRP) of the Austin Model 1 (AM1) Hamiltonian by simultaneously capturing the reaction barrier for chloride ion attack on methylchloride in solution and the solvation free energies of a series of compounds including the reagents of the reaction. The second, VRSCOSMO, is an implicit solvation model for use with the DFTB3/3OB Hamiltonian for biochemical reactions; allowing for accurate modeling of ionic compound solvation properties while overcoming the discontinuous nature of conventional PCM models when chemical reaction coordinates. The VRSCOSMO model is shown to accurately model the solvation properties of over 200 chemical compounds while also providing smooth, continuous reaction surfaces for a series of biologically motivated phosphoryl transesterification reactions. Both of these methods incorporate charge-dependent behavior into the non-bonded interactions variationally, allowing the 'size' of atoms to change in meaningful ways with respect to changes in local charge state, as to provide an accurate, predictive and transferable models for the interactions between the quantum mechanical system and their solvated surroundings.

Influence of rearing conditions on the volatile compounds of cooked fillets of Silurus glanis (European catfish).

PubMed

Hallier, Arnaud; Prost, Carole; Serot, Thierry

2005-09-07

Volatile compounds of cooked fillets of Silurus glanis reared under two conditions occurring in France were studied. They were extracted by dynamic headspace, identified by gas chromatography/mass spectrometry, and quantified by gas chromatography-flame ionization detection. Odor active volatile compounds were characterized by gas chromatography-olfactometry. Sixty volatile compounds were detected in dynamic headspace extracts, among which 33 were odor active. Rearing conditions affected their estimated concentrations and their odor intensities, but very few qualitative differences were exhibited (only seven volatile compounds were concerned). A good correlation between quantitative and olfactometric results is shown. 2-Methylisoborneol and (E)-2-hexenal were less represented in OUTDOOR extracts, while 2-butanone was less represented in INDOOR extracts. In addition, olfactometric results can be closely related to those previously obtained by sensory analysis. Boiled potato sensory odor of the silurus cooked fillets can be related to (Z)-4-heptenal and methional, and buttery odor can be related to 2,3-butanedione, an unknown compound (RI = 1010), and 2,3-pentadione.

Tyrosine Kinase 2-mediated Signal Transduction in T Lymphocytes Is Blocked by Pharmacological Stabilization of Its Pseudokinase Domain*

PubMed Central

Tokarski, John S.; Zupa-Fernandez, Adriana; Tredup, Jeffrey A.; Pike, Kristen; Chang, ChiehYing; Xie, Dianlin; Cheng, Lihong; Pedicord, Donna; Muckelbauer, Jodi; Johnson, Stephen R.; Wu, Sophie; Edavettal, Suzanne C.; Hong, Yang; Witmer, Mark R.; Elkin, Lisa L.; Blat, Yuval; Pitts, William J.; Weinstein, David S.; Burke, James R.

2015-01-01

Inhibition of signal transduction downstream of the IL-23 receptor represents an intriguing approach to the treatment of autoimmunity. Using a chemogenomics approach marrying kinome-wide inhibitory profiles of a compound library with the cellular activity against an IL-23-stimulated transcriptional response in T lymphocytes, a class of inhibitors was identified that bind to and stabilize the pseudokinase domain of the Janus kinase tyrosine kinase 2 (Tyk2), resulting in blockade of receptor-mediated activation of the adjacent catalytic domain. These Tyk2 pseudokinase domain stabilizers were also shown to inhibit Tyk2-dependent signaling through the Type I interferon receptor but not Tyk2-independent signaling and transcriptional cellular assays, including stimulation through the receptors for IL-2 (JAK1- and JAK3-dependent) and thrombopoietin (JAK2-dependent), demonstrating the high functional selectivity of this approach. A crystal structure of the pseudokinase domain liganded with a representative example showed the compound bound to a site analogous to the ATP-binding site in catalytic kinases with features consistent with high ligand selectivity. The results support a model where the pseudokinase domain regulates activation of the catalytic domain by forming receptor-regulated inhibitory interactions. Tyk2 pseudokinase stabilizers, therefore, represent a novel approach to the design of potent and selective agents for the treatment of autoimmunity. PMID:25762719

Emerging Estrogenic Pollutants in the Aquatic Environment and Breast Cancer

PubMed Central

Lecomte, Sylvain; Charlier, Thierry D.; Pakdel, Farzad

2017-01-01

The number and amount of man-made chemicals present in the aquatic environment has increased considerably over the past 50 years. Among these contaminants, endocrine-disrupting chemicals (EDCs) represent a significant proportion. This family of compounds interferes with normal hormonal processes through multiple molecular pathways. They represent a potential risk for human and wildlife as they are suspected to be involved in the development of diseases including, but not limited to, reprotoxicity, metabolic disorders, and cancers. More precisely, several studies have suggested that the increase of breast cancers in industrialized countries is linked to exposure to EDCs, particularly estrogen-like compounds. Estrogen receptors alpha (ERα) and beta (ERβ) are the two main transducers of estrogen action and therefore important targets for these estrogen-like endocrine disrupters. More than 70% of human breast cancers are ERα-positive and estrogen-dependent, and their development and growth are not only influenced by endogenous estrogens but also likely by environmental estrogen-like endocrine disrupters. It is, therefore, of major importance to characterize the potential estrogenic activity from contaminated surface water and identify the molecules responsible for the hormonal effects. This information will help us understand how environmental contaminants can potentially impact the development of breast cancer and allow us to fix a maximal limit to the concentration of estrogen-like compounds that should be found in the environment. The aim of this review is to provide an overview of emerging estrogen-like compounds in the environment, sum up studies demonstrating their direct or indirect interactions with ERs, and link their presence to the development of breast cancer. Finally, we emphasize the use of in vitro and in vivo methods based on the zebrafish model to identify and characterize environmental estrogens. PMID:28914763

Optimal experimental design for assessment of enzyme kinetics in a drug discovery screening environment.

PubMed

Sjögren, Erik; Nyberg, Joakim; Magnusson, Mats O; Lennernäs, Hans; Hooker, Andrew; Bredberg, Ulf

2011-05-01

A penalized expectation of determinant (ED)-optimal design with a discrete parameter distribution was used to find an optimal experimental design for assessment of enzyme kinetics in a screening environment. A data set for enzyme kinetic data (V(max) and K(m)) was collected from previously reported studies, and every V(max)/K(m) pair (n = 76) was taken to represent a unique drug compound. The design was restricted to 15 samples, an incubation time of up to 40 min, and starting concentrations (C(0)) for the incubation between 0.01 and 100 μM. The optimization was performed by finding the sample times and C(0) returning the lowest uncertainty (S.E.) of the model parameter estimates. Individual optimal designs, one general optimal design and one, for laboratory practice suitable, pragmatic optimal design (OD) were obtained. In addition, a standard design (STD-D), representing a commonly applied approach for metabolic stability investigations, was constructed. Simulations were performed for OD and STD-D by using the Michaelis-Menten (MM) equation, and enzyme kinetic parameters were estimated with both MM and a monoexponential decay. OD generated a better result (relative standard error) for 99% of the compounds and an equal or better result [(root mean square error (RMSE)] for 78% of the compounds in estimation of metabolic intrinsic clearance. Furthermore, high-quality estimates (RMSE < 30%) of both V(max) and K(m) could be obtained for a considerable number (26%) of the investigated compounds by using the suggested OD. The results presented in this study demonstrate that the output could generally be improved compared with that obtained from the standard approaches used today.

Volatile Compounds with Characteristic Odor of Essential Oil from Magnolia obovata Leaves by Hydrodistillation and Solvent-assisted Flavor Evaporation.

PubMed

Miyazawa, Mitsuo; Nakashima, Yoshimi; Nakahashi, Hiroshi; Hara, Nobuyuki; Nakagawa, Hiroki; Usami, Atsushi; Chavasiri, Warinthorn

2015-01-01

The present study focuses on the volatile compounds with characteristic odor of essential oil from the leaves of Magnolia obovata by hydrodistillation (HD) and solvent-assisted flavor evaporation (SAFE) method. Eighty-seven compounds, representing 98.0% of the total oil, were identified using HD. The major compounds of HD oil were (E)-β-caryophyllene (23.7%), α-humulene (11.6%), geraniol (9.1%), and borneol (7.0%). In SAFE oil, fifty-eight compounds, representing 99.7% of the total oil, were identified. The main compounds of SAFE oil were (E)-β-caryophyllene (48.9%), α-humulene (15.7%), and bicyclogermacrene (4.2%). In this study, we newly identified eighty-five compounds of the oils from M. obovata leaves. These oils were also subjected to aroma evaluation by gas chromatography-olfactometry (GC-O) and aroma extract dilution analysis (AEDA). As a result, twenty-four (HD) and twenty-five (SAFE) aroma-active compounds were detected. (E)-β-Caryophyllene, α-humulene, linalool, geraniol, 1,8-cineole, and bicyclogermacrene were found to impart the characteristic odor of M. obovata leaves. These results imply that the oils of M. obovata leaves must be investigated further to clarify their potential application in the food and pharmaceutical industries.

Detection of Mutant Huntingtin Aggregation Conformers and Modulation of SDS-Soluble Fibrillar Oligomers by Small Molecules

PubMed Central

Sontag, Emily Mitchell; Lotz, Gregor P.; Yang, Guocheng; Sontag, Christopher J.; Cummings, Brian J.; Glabe, Charles G.; Muchowski, Paul J.; Thompson, Leslie Michels

2012-01-01

The Huntington’s disease (HD) mutation leads to a complex process of Huntingtin (Htt) aggregation into multimeric species that eventually form visible inclusions in cytoplasm, nuclei and neuronal processes. One hypothesis is that smaller, soluble forms of amyloid proteins confer toxic effects and contribute to early cell dysfunction. However, analysis of mutant Htt aggregation intermediates to identify conformers that may represent toxic forms of the protein and represent potential drug targets remains difficult. We performed a detailed analysis of aggregation conformers in multiple in vitro, cell and ex vivo models of HD. Conformation-specific antibodies were used to identify and characterize aggregation species, allowing assessment of multiple conformers present during the aggregation process. Using a series of assays together with these antibodies, several forms could be identified. Fibrillar oligomers, defined as having a β-sheet rich conformation, are observed in vitro using recombinant protein and in protein extracts from cells in culture or mouse brain and shown to be globular, soluble and non-sedimentable structures. Compounds previously described to modulate visible inclusion body formation and reduce toxicity in HD models were also tested and consistently found to alter the formation of fibrillar oligomers. Interestingly, these compounds did not alter the rate of visible inclusion formation, indicating that fibrillar oligomers are not necessarily the rate limiting step of inclusion body formation. Taken together, we provide insights into the structure and formation of mutant Htt fibrillar oligomers that are modulated by small molecules with protective potential in HD models. PMID:24086178

Discovery of a Novel Series of CRTH2 (DP2) Receptor Antagonists Devoid of Carboxylic Acids

PubMed Central

2011-01-01

Antagonism of the CRTH2 receptor represents a very attractive target for a variety of allergic diseases. Most CRTH2 antagonists known to date possess a carboxylic acid moiety, which is essential for binding. However, potential acid metabolites O-acyl glucuronides might be linked to idiosynchratic toxicity in humans. In this communication, we describe a new series of compounds that lack the carboxylic acid moiety. Compounds with high affinity (Ki < 10 nM) for the receptor have been identified. Subsequent optimization succeeded in reducing the high metabolic clearance of the first compounds in human and rat liver microsomes. At the same time, inhibition of the CYP isoforms was optimized, giving rise to stable compounds with an acceptable CYP inhibition profile (IC50 CYP2C9 and 2C19 > 1 μM). Taken together, these data show that compounds devoid of carboxylic acid groups could represent an interesting alternative to current CRTH2 antagonists in development. PMID:24900284

Natural compounds and combination therapy in colorectal cancer treatment.

PubMed

Rejhová, A; Opattová, A; Čumová, A; Slíva, D; Vodička, P

2018-01-20

Colorectal cancer (CRC) therapy using conventional chemotherapeutics represents a considerable burden for the patient's organism because of high toxicity while the response is relatively low. Our review summarizes the findings about natural compounds as chemoprotective agents for decreasing risk of CRC. It also identifies natural compounds which possess anti-tumor effects of various characteristics, mainly in vitro on colorectal cell lines or in vivo studies on experimental models, but also in a few clinical trials. Many of natural compounds suppress proliferation by inducing cell cycle arrest or induce apoptosis of CRC cells resulting in the inhibition of tumor growth. A novel employment of natural substances is a so-called combination therapy - administration of two or more substances - conventional chemotherapeutics and a natural compound or more natural compounds at a time. Some natural compounds may sensitize to conventional cytotoxic therapy, reinforce the drug effective concentration, intensify the combined effect of both administered therapeutics or exert cytotoxic effects specifically on tumor cells. Moreover, combined therapy by targeting multiple signaling pathways, uses various mechanisms to reduce the development of resistance to antitumor drugs. The desired effect could be to diminish burden on the patient's organism by replacing part of the dose of a conventional chemotherapeutic with a natural substance with a defined effect. Many natural compounds are well tolerated by the patients and do not cause toxic effects even at high doses. Interaction of conventional chemotherapeutics with natural compounds introduces a new aspect in the research and therapy of cancer. It could be a promising approach to potentially achieve improvements, while minimizing of adverse effects associated with conventional chemotherapy. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Redox-active compounds with a history of human use: antistaphylococcal action and potential for repurposing as topical antibiofilm agents.

PubMed

Ooi, N; Eady, E A; Cove, J H; O'Neill, A J

2015-02-01

To investigate the antistaphylococcal/antibiofilm activity and mode of action (MOA) of a panel of redox-active (RA) compounds with a history of human use and to provide a preliminary preclinical assessment of their potential for topical treatment of staphylococcal infections, including those involving a biofilm component. Antistaphylococcal activity was evaluated by broth microdilution and by time-kill studies with growing and slow- or non-growing cells. The antibiofilm activity of RA compounds, alone and in combination with established antibacterial agents, was assessed using the Calgary Biofilm Device. Established assays were used to examine the membrane-perturbing effects of RA compounds, to measure penetration into biofilms and physical disruption of biofilms and to assess resistance potential. A living skin equivalent model was used to assess the effects of RA compounds on human skin. All 15 RA compounds tested displayed antistaphylococcal activity against planktonic cultures (MIC 0.25-128 mg/L) and 7 eradicated staphylococcal biofilms (minimum biofilm eradication concentration 4-256 mg/L). The MOA of all compounds involved perturbation of the bacterial membrane, whilst selected compounds with antibiofilm activity caused destructuring of the biofilm matrix. The two most promising agents [celastrol and nordihydroguaiaretic acid (NDGA)] in respect of antibacterial potency and selective toxicity against bacterial membranes acted synergistically with gentamicin against biofilms, did not damage artificial skin following topical application and exhibited low resistance potential. In contrast to established antibacterial drugs, some RA compounds are capable of eradicating staphylococcal biofilms. Of these, celastrol and NDGA represent particularly attractive candidates for development as topical antistaphylococcal biofilm treatments. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.

Synthesis and Biological Evaluation of Apogossypolone Derivatives as Pan-active Inhibitors of Anti-apoptotic B-Cell Lymphoma/Leukemia-2 (Bcl-2) Family Proteins

PubMed Central

Wei, Jun; Kitada, Shinichi; Stebbins, John L.; Placzek, William; Zhai, Dayong; Wu, Bainan; Rega, Michele F.; Zhang, Ziming; Cellitti, Jason; Yang, Li; Dahl, Russell; Reed, John C.; Pellecchia, Maurizio

2010-01-01

Overexpression of anti-apoptotic Bcl-2 family proteins is commonly related with tumor maintenance, progression, and chemoresistance. Inhibition of these anti-apoptotic proteins is an attractive approach for cancer therapy. Guided by nuclear magnetic resonance (NMR) binding assays, a series of 5, 5′ substituted compound 6a (Apogossypolone) derivatives was synthesized and identified pan-active antagonists of anti-apoptotic Bcl-2 family proteins, with binding potency in the low micromolar to nanomolar range. Compound 6f inhibits the binding of BH3 peptides to Bcl-XL, Bcl-2 and Mcl-1 with IC50 values of 3.10, 3.12 and 2.05 μM, respectively. In a cellular assay, 6f potently inhibits cell growth in several human cancer cell lines in a dose-dependent manner. Compound 6f further displays in vivo efficacy in transgenic mice and demonstrated superior single-agent antitumor efficacy in a PPC-1 mouse xenograft model. Together with its negligible toxicity, compound 6f represents a promising drug lead for the development of novel apoptosis-based therapies for cancer. PMID:21033669

Structural design, synthesis and substituent effect of hydrazone-N-acylhydrazones reveal potent immunomodulatory agents.

PubMed

Meira, Cássio S; Dos Santos Filho, José Maurício; Sousa, Caroline C; Anjos, Pâmela S; Cerqueira, Jéssica V; Dias Neto, Humberto A; da Silveira, Rafael G; Russo, Helena M; Wolfender, Jean-Luc; Queiroz, Emerson F; Moreira, Diogo R M; Soares, Milena B P

2018-05-01

4-(Nitrophenyl)hydrazone derivatives of N-acylhydrazone were synthesized and screened for suppress lymphocyte proliferation and nitrite inhibition in macrophages. Compared to an unsubstituted N-acylhydrazone, active compounds were identified within initial series when hydroxyl, chloride and nitro substituents were employed. Structure-activity relationship was further developed by varying the position of these substituents as well as attaching structurally-related substituents. Changing substituent position revealed a more promising compound series of anti-inflammatory agents. In contrast, an N-methyl group appended to the 4-(nitrophenyl)hydrazone moiety reduced activity. Anti-inflammatory activity of compounds is achieved by modulating IL-1β secretion and prostaglandin E2 synthesis in macrophages and by inhibiting calcineurin phosphatase activity in lymphocytes. Compound SintMed65 was advanced into an acute model of peritonitis in mice, where it inhibited the neutrophil infiltration after being orally administered. In summary, we demonstrated in great details the structural requirements and the underlying mechanism for anti-inflammatory activity of a new family of hydrazone-N-acylhydrazone, which may represent a valuable medicinal chemistry direction for the anti-inflammatory drug development in general. Copyright © 2018 Elsevier Ltd. All rights reserved.

Desensitization of B-adrenergic receptors following repeated injections of 2-substituted-4-phenylquinolines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alhaider, A.A.

1986-03-05

In a previous work, they synthesized some new 2-substituted-4-phenylquinoline derivatives which demonstrated potent antidepressant activities as revealed by their antagonism to the uptake of /sup 3/(H)-norepinephrine and /sup 3/(H)-serotonin into brain synaptosomal preparation. Also, these compounds have demonstrated less anticholinergic, antihistamine and cardiovascular effects as compared to imipramine in animal models. In this present work, the chronic effects of some of these compounds on the sensitivity of the noradrenergic cyclic-AMP generating system on rat brain cortex has been conducted by the daily injection of 20 mg/kg i.p. for a period of three weeks. Imipramine and trazodone were utilized as standards,more » representing typical and atypical antidepressants, respectively. Acute treatment (single dose 20 mg/kg) and subchronic treatment (20 mg/kg for 10 days) produced no significant desensitization of the B-adrenoceptors. However, chronic treatment with the compounds significantly decreased isoprenaline-induced increase in c-AMP in the cortex which suggests desensitization of B-adrenoceptors. This effect coupled with the previous findings point to a potential rule of these compounds as suitable antidepressant candidates.« less

Multidrug-Resistant Enterococcal Infections: New Compounds, Novel Antimicrobial Therapies?

PubMed

van Harten, Roel M; Willems, Rob J L; Martin, Nathaniel I; Hendrickx, Antoni P A

2017-06-01

Over the past two decades infections due to antibiotic-resistant bacteria have escalated world-wide, affecting patient morbidity, mortality, and health care costs. Among these bacteria, Enterococcus faecium and Enterococcus faecalis represent opportunistic nosocomial pathogens that cause difficult-to-treat infections because of intrinsic and acquired resistance to a plethora of antibiotics. In recent years, a number of novel antimicrobial compound classes have been discovered and developed that target Gram-positive bacteria, including E. faecium and E. faecalis. These new antibacterial agents include teixobactin (targeting lipid II and lipid III), lipopeptides derived from nisin (targeting lipid II), dimeric vancomycin analogues (targeting lipid II), sortase transpeptidase inhibitors (targeting the sortase enzyme), alanine racemase inhibitors, lipoteichoic acid synthesis inhibitors (targeting LtaS), various oxazolidinones (targeting the bacterial ribosome), and tarocins (interfering with teichoic acid biosynthesis). The targets of these novel compounds and mode of action make them very promising for further antimicrobial drug development and future treatment of Gram-positive bacterial infections. Here we review current knowledge of the most favorable anti-enterococcal compounds along with their implicated modes of action and efficacy in animal models to project their possible future use in the clinical setting. Copyright © 2017 Elsevier Ltd. All rights reserved.

Formation of Hydrogen Sulfide in Wine: Interactions between Copper and Sulfur Dioxide.

PubMed

Bekker, Marlize Z; Smith, Mark E; Smith, Paul A; Wilkes, Eric N

2016-09-10

The combined synergistic effects of copper (Cu(2+)) and sulfur dioxide (SO₂) on the formation of hydrogen sulfide (H₂S) in Verdelho and Shiraz wine samples post-bottling was studied over a 12-month period. The combined treatment of Cu(2+) and SO₂ significantly increased H₂S formation in Verdelho wines samples that were not previously treated with either Cu(2+) or SO₂. The formation of H₂S produced through Cu(2+) mediated reactions was likely either: (a) directly through the interaction of SO₂ with either Cu(2+) or H₂S; or (b) indirectly through the interaction of SO₂ with other wine matrix compounds. To gain better understanding of the mechanisms responsible for the significant increases in H₂S concentration in the Verdelho samples, the interaction between Cu(2+) and SO₂ was studied in a model wine matrix with and without the presence of a representative thiol quenching compound (4-methylbenzoquinone, 4MBQ). In these model studies, the importance of naturally occurring wine compounds and wine additives, such as quinones, SO₂, and metal ions, in modulating the formation of H₂S post-bottling was demonstrated. When present in equimolar concentrations a 1:1 ratio of H₂S- and SO₂-catechol adducts were produced. At wine relevant concentrations, however, only SO₂-adducts were produced, reinforcing that the competition reactions of sulfur nucleophiles, such as H₂S and SO₂, with wine matrix compounds play a critical role in modulating final H₂S concentrations in wines.

Co-culturing of Fungal Strains Against Botrytis cinerea as a Model for the Induction of Chemical Diversity and Therapeutic Agents.

PubMed

Serrano, Rachel; González-Menéndez, Víctor; Rodríguez, Lorena; Martín, Jesús; Tormo, José R; Genilloud, Olga

2017-01-01

New fungal SMs (SMs) have been successfully described to be produced by means of in vitro -simulated microbial community interactions. Co-culturing of fungi has proved to be an efficient way to induce cell-cell interactions that can promote the activation of cryptic pathways, frequently silent when the strains are grown in laboratory conditions. Filamentous fungi represent one of the most diverse microbial groups known to produce bioactive natural products. Triggering the production of novel antifungal compounds in fungi could respond to the current needs to fight health compromising pathogens and provide new therapeutic solutions. In this study, we have selected the fungus Botrytis cinerea as a model to establish microbial interactions with a large set of fungal strains related to ecosystems where they can coexist with this phytopathogen, and to generate a collection of extracts, obtained from their antagonic microbial interactions and potentially containing new bioactive compounds. The antifungal specificity of the extracts containing compounds induced after B. cinerea interaction was determined against two human fungal pathogens ( Candida albicans and Aspergillus fumigatus ) and three phytopathogens ( Colletotrichum acutatum , Fusarium proliferatum , and Magnaporthe grisea ). In addition, their cytotoxicity was also evaluated against the human hepatocellular carcinoma cell line (HepG2). We have identified by LC-MS the production of a wide variety of known compounds induced from these fungal interactions, as well as novel molecules that support the potential of this approach to generate new chemical diversity and possible new therapeutic agents.

Independent valine and leucine isotope labeling in Escherichia coli protein overexpression systems.

PubMed

Lichtenecker, Roman J; Weinhäupl, Katharina; Reuther, Lukas; Schörghuber, Julia; Schmid, Walther; Konrat, Robert

2013-11-01

The addition of labeled α-ketoisovalerate to the growth medium of a protein-expressing host organism has evolved into a versatile tool to achieve concomitant incorporation of specific isotopes into valine- and leucine- residues. The resulting target proteins represent excellent probes for protein NMR analysis. However, as the sidechain resonances of these residues emerge in a narrow spectral range, signal overlap represents a severe limitation in the case of high-molecular-weight NMR probes. We present a protocol to eliminate leucine labeling by supplying the medium with unlabeled α-ketoisocaproate. The resulting spectra of a model protein exclusively feature valine signals of increased intensity, confirming the method to be a first example of independent valine and leucine labeling employing α-ketoacid precursor compounds.

Prevention of chemotherapy-induced alopecia in rats by CDK inhibitors.

PubMed

Davis, S T; Benson, B G; Bramson, H N; Chapman, D E; Dickerson, S H; Dold, K M; Eberwein, D J; Edelstein, M; Frye, S V; Gampe, R T; Griffin, R J; Harris, P A; Hassell, A M; Holmes, W D; Hunter, R N; Knick, V B; Lackey, K; Lovejoy, B; Luzzio, M J; Murray, D; Parker, P; Rocque, W J; Shewchuk, L; Veal, J M; Walker, D H; Kuyper, L F

2001-01-05

Most traditional cytotoxic anticancer agents ablate the rapidly dividing epithelium of the hair follicle and induce alopecia (hair loss). Inhibition of cyclin-dependent kinase 2 (CDK2), a positive regulator of eukaryotic cell cycle progression, may represent a therapeutic strategy for prevention of chemotherapy-induced alopecia (CIA) by arresting the cell cycle and reducing the sensitivity of the epithelium to many cell cycle-active antitumor agents. Potent small-molecule inhibitors of CDK2 were developed using structure-based methods. Topical application of these compounds in a neonatal rat model of CIA reduced hair loss at the site of application in 33 to 50% of the animals. Thus, inhibition of CDK2 represents a potentially useful approach for the prevention of CIA in cancer patients.

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE PAGES

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin; ...

2018-03-15

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Mathematical modelling of the influenced of diffusion rate on macro nutrient availability in paddy field

NASA Astrophysics Data System (ADS)

Renny; Supriyanto

2018-04-01

Nutrition is the chemical compounds that needed by the organism for the growth process. In plants, nutrients are organic or inorganic compounds that are absorbed from the roots of the soil. It consist of macro and micro nutrient. Macro nutrients are nutrition that needed by plants in large quantities, such as, nitrogen, calcium, pottacium, magnesium, and sulfur. The total soil nutrient is the difference between the input nutrient and the output nutrients. Input nutrients are nutrient that derived from the decomposition of organic substances. Meanwhile, the output nutrient consists of the nutrients that absorbed by plant roots (uptake), the evaporated nutrients (volatilized) and leached nutrients. The nutrient transport can be done through diffusion process. The diffusion process is essential in removing the nutrient from one place to the root surface. It will cause the rate of absorption of nutrient by the roots will be greater. Nutrient concept in paddy filed can be represented into a mathematical modelling, by making compartment models. The rate of concentration change in the compartment model forms a system of homogeneous linear differential equations. In this research, we will use Laplaces transformation to solve the compartment model and determined the dynamics of macro nutrition due to diffusion process.

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

HPLC-Based Activity Profiling for GABAA Receptor Modulators in Extracts: Validation of an Approach Utilizing a Larval Zebrafish Locomotor Assay.

PubMed

Moradi-Afrapoli, Fahimeh; Ebrahimi, Samad Nejad; Smiesko, Martin; Hamburger, Matthias

2017-05-26

Gamma-aminobutyric acid type A (GABA A ) receptors are major inhibitory neurotransmitter receptors in the central nervous system and a target for numerous clinically important drugs used to treat anxiety, insomnia, and epilepsy. A series of allosteric GABA A receptor agonists was identified previously with the aid of HPLC-based activity profiling, whereby activity was tracked with an electrophysiological assay in Xenopus laevis oocytes. To accelerate the discovery process, an approach has been established for HPLC-based profiling using a larval zebrafish (Danio rerio) seizure model induced by pentylenetetrazol (PTZ), a pro-convulsant GABA A receptor antagonist. The assay was validated with the aid of representative GABAergic plant compounds and extracts. Various parameters that are relevant for the quality of results obtained, including PTZ concentration, the number of larvae, the incubation time, and the data analysis protocol, were optimized. The assay was then translated into an HPLC profiling protocol, and active compounds were tracked in extracts of Valeriana officinalis and Magnolia officinalis. For selected compounds the effects in the zebrafish larvae model were compared with data from in silico blood-brain barrier (BBB) permeability predictions, to validate the use for discovery of BBB-permeable natural products.

Bioaccumulation and trophic dilution of human pharmaceuticals across trophic positions of an effluent-dependent wadeable stream

PubMed Central

Du, Bowen; Haddad, Samuel P.; Luek, Andreas; Scott, W. Casan; Saari, Gavin N.; Kristofco, Lauren A.; Connors, Kristin A.; Rash, Christopher; Rasmussen, Joseph B.; Chambliss, C. Kevin; Brooks, Bryan W.

2014-01-01

Though pharmaceuticals are increasingly observed in a variety of organisms from coastal and inland aquatic systems, trophic transfer of pharmaceuticals in aquatic food webs have not been reported. In this study, bioaccumulation of select pharmaceuticals was investigated in a lower order effluent-dependent stream in central Texas, USA, using isotope dilution liquid chromatography–tandem mass spectrometry (MS). A fish plasma model, initially developed from laboratory studies, was tested to examine observed versus predicted internal dose of select pharmaceuticals. Pharmaceuticals accumulated to higher concentrations in invertebrates relative to fish; elevated concentrations of the antidepressant sertraline and its primary metabolite desmethylsertraline were observed in the Asian clam, Corbicula fluminea, and two unionid mussel species. Trophic positions were determined from stable isotopes (δ15N and δ13C) collected by isotope ratio-MS; a Bayesian mixing model was then used to estimate diet contributions towards top fish predators. Because diphenhydramine and carbamazepine were the only target compounds detected in all species examined, trophic magnification factors (TMFs) were derived to evaluate potential trophic transfer of both compounds. TMFs for diphenhydramine (0.38) and carbamazepine (1.17) indicated neither compound experienced trophic magnification, which suggests that inhalational and not dietary exposure represented the primary route of uptake by fish in this effluent-dependent stream. PMID:25313153

Efficient electricity production and simultaneously wastewater treatment via a high-performance photocatalytic fuel cell.

PubMed

Liu, Yanbiao; Li, Jinhua; Zhou, Baoxue; Li, Xuejin; Chen, Hongchong; Chen, Quanpeng; Wang, Zhongsheng; Li, Lei; Wang, Jiulin; Cai, Weimin

2011-07-01

A great quantity of wastewater were discharged into water body, causing serious environmental pollution. Meanwhile, the organic compounds in wastewater are important sources of energy. In this work, a high-performance short TiO(2) nanotube array (STNA) electrode was applied as photoanode material in a novel photocatalytic fuel cell (PFC) system for electricity production and simultaneously wastewater treatment. The results of current work demonstrate that various model compounds as well as real wastewater samples can be used as substrates for the PFC system. As a representative of model compounds, the acetic acid solution produces the highest cell performance with short-circuit current density 1.42 mA cm(-2), open-circuit voltage 1.48 V and maximum power density output 0.67 mW cm(-2). The STNA photoanode reveals obviously enhanced cell performance compared with TiO(2) nanoparticulate film electrode or other long nanotubes electrode. Moreover, the photoanode material, electrolyte concentration, pH of the initial solution, and cathode material were found to be important factors influencing the system performance of PFC. Therefore, the proposed fuel cell system provides a novel way of energy conversion and effective disposal mode of organics and serves well as a promising technology for wastewater treatment. Copyright © 2011 Elsevier Ltd. All rights reserved.

The effect of ventilation on indoor exposure to semivolatile organic compounds.

PubMed

Liu, C; Zhang, Y; Benning, J L; Little, J C

2015-06-01

A mechanistic model was developed to examine how natural ventilation influences residential indoor exposure to semivolatile organic compounds (SVOCs) via inhalation, dermal sorption, and dust ingestion. The effect of ventilation on indoor particle mass concentration and mass transfer at source/sink surfaces, and the enhancing effect of particles on mass transfer at source/sink surfaces are included. When air exchange rate increases from 0.6/h to 1.8/h, the steady-state SVOC (gas-phase plus particle phase with log KOA varying from 9 to 13) concentration in the idealized model decreases by about 60%. In contrast, for the same change in ventilation, the simulated indoor formaldehyde (representing volatile organic compounds) gas-phase concentration decreases by about 70%. The effect of ventilation on exposure via each pathway has a relatively insignificant association with the KOA of the SVOCs: a change of KOA from 10(9) to 10(13) results in a change of only 2-30%. Sensitivity analysis identifies the deposition rate of PM2.5 as a primary factor influencing the relationship between ventilation and exposure for SVOCs with log KOA = 13. The relationship between ventilation rate and air speed near surfaces needs to be further substantiated. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Biochemical interpretation of quantitative structure-activity relationships (QSAR) for biodegradation of N-heterocycles: a complementary approach to predict biodegradability.

PubMed

Philipp, Bodo; Hoff, Malte; Germa, Florence; Schink, Bernhard; Beimborn, Dieter; Mersch-Sundermann, Volker

2007-02-15

Prediction of the biodegradability of organic compounds is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. We combined quantitative structure-activity relationships (QSAR) with the systematic collection of biochemical knowledge to establish rules for the prediction of aerobic biodegradation of N-heterocycles. Validated biodegradation data of 194 N-heterocyclic compounds were analyzed using the MULTICASE-method which delivered two QSAR models based on 17 activating (OSAR 1) and on 16 inactivating molecular fragments (GSAR 2), which were statistically significantly linked to efficient or poor biodegradability, respectively. The percentages of correct classifications were over 99% for both models, and cross-validation resulted in 67.9% (GSAR 1) and 70.4% (OSAR 2) correct predictions. Biochemical interpretation of the activating and inactivating characteristics of the molecular fragments delivered plausible mechanistic interpretations and enabled us to establish the following biodegradation rules: (1) Target sites for amidohydrolases and for cytochrome P450 monooxygenases enhance biodegradation of nonaromatic N-heterocycles. (2) Target sites for molybdenum hydroxylases enhance biodegradation of aromatic N-heterocycles. (3) Target sites for hydratation by an urocanase-like mechanism enhance biodegradation of imidazoles. Our complementary approach represents a feasible strategy for generating concrete rules for the prediction of biodegradability of organic compounds.

Synthesis, molecular modeling, and opioid receptor affinity of 9, 10-diazatricyclo[4.2.1.1(2,5)]decanes and 2,7-diazatricyclo[4.4.0. 0(3,8)]decanes structurally related to 3,8-diazabicyclo[3.2. 1]octanes.

PubMed

Vianello, P; Albinati, A; Pinna, G A; Lavecchia, A; Marinelli, L; Borea, P A; Gessi, S; Fadda, P; Tronci, S; Cignarella, G

2000-06-01

Various lines of evidence, including molecular modeling studies, imply that the endoethylenic bridge of 3,8-diazabicyclo[3.2. 1]octanes (DBO, 1) plays an essential role in modulating affinity toward mu opioid receptors. This hypothesis, together with the remarkable analgesic properties observed for N(3) propionyl, N(8) arylpropenyl derivatives (2) and of the reverted isomers (3), has prompted us to insert an additional endoethylenic bridge on the piperazine moiety in order to identify derivatives with increased potency toward this receptor class. In the present report, we describe the synthesis of the novel compounds 9,10-diazatricyclo[4.2. 1.1(2,5)]decane (4) and 2,7-diazatricyclo[4.4.0.0(3,8)]decane (5), as well as the representative derivatives functionalized at the two nitrogen atoms by propionyl and arylpropenyl groups (6a-e, 7a-d). Opioid receptor binding assays revealed that, among the compounds tested, the N-propionyl-N-cinnamyl derivatives 6a and 7a exhibited the highest mu-receptor affinity, and remarkably, compound 7a displayed in vivo (mice) an analgesic potency 6-fold that of morphine.

Petroleum dynamics in the sea and influence of subsea dispersant injection during Deepwater Horizon.

PubMed

Gros, Jonas; Socolofsky, Scott A; Dissanayake, Anusha L; Jun, Inok; Zhao, Lin; Boufadel, Michel C; Reddy, Christopher M; Arey, J Samuel

2017-09-19

During the Deepwater Horizon disaster, a substantial fraction of the 600,000-900,000 tons of released petroleum liquid and natural gas became entrapped below the sea surface, but the quantity entrapped and the sequestration mechanisms have remained unclear. We modeled the buoyant jet of petroleum liquid droplets, gas bubbles, and entrained seawater, using 279 simulated chemical components, for a representative day (June 8, 2010) of the period after the sunken platform's riser pipe was pared at the wellhead (June 4-July 15). The model predicts that 27% of the released mass of petroleum fluids dissolved into the sea during ascent from the pared wellhead (1,505 m depth) to the sea surface, thereby matching observed volatile organic compound (VOC) emissions to the atmosphere. Based on combined results from model simulation and water column measurements, 24% of released petroleum fluid mass became channeled into a stable deep-water intrusion at 900- to 1,300-m depth, as aqueously dissolved compounds (∼23%) and suspended petroleum liquid microdroplets (∼0.8%). Dispersant injection at the wellhead decreased the median initial diameters of simulated petroleum liquid droplets and gas bubbles by 3.2-fold and 3.4-fold, respectively, which increased dissolution of ascending petroleum fluids by 25%. Faster dissolution increased the simulated flows of water-soluble compounds into biologically sparse deep water by 55%, while decreasing the flows of several harmful compounds into biologically rich surface water. Dispersant injection also decreased the simulated emissions of VOCs to the atmosphere by 28%, including a 2,000-fold decrease in emissions of benzene, which lowered health risks for response workers.

ARQiv-HTS, a versatile whole-organism screening platform enabling in vivo drug discovery at high-throughput rates

PubMed Central

White, David T; Eroglu, Arife Unal; Wang, Guohua; Zhang, Liyun; Sengupta, Sumitra; Ding, Ding; Rajpurohit, Surendra K; Walker, Steven L; Ji, Hongkai; Qian, Jiang; Mumm, Jeff S

2017-01-01

The zebrafish has emerged as an important model for whole-organism small-molecule screening. However, most zebrafish-based chemical screens have achieved only mid-throughput rates. Here we describe a versatile whole-organism drug discovery platform that can achieve true high-throughput screening (HTS) capacities. This system combines our automated reporter quantification in vivo (ARQiv) system with customized robotics, and is termed ‘ARQiv-HTS’. We detail the process of establishing and implementing ARQiv-HTS: (i) assay design and optimization, (ii) calculation of sample size and hit criteria, (iii) large-scale egg production, (iv) automated compound titration, (v) dispensing of embryos into microtiter plates, and (vi) reporter quantification. We also outline what we see as best practice strategies for leveraging the power of ARQiv-HTS for zebrafish-based drug discovery, and address technical challenges of applying zebrafish to large-scale chemical screens. Finally, we provide a detailed protocol for a recently completed inaugural ARQiv-HTS effort, which involved the identification of compounds that elevate insulin reporter activity. Compounds that increased the number of insulin-producing pancreatic beta cells represent potential new therapeutics for diabetic patients. For this effort, individual screening sessions took 1 week to conclude, and sessions were performed iteratively approximately every other day to increase throughput. At the conclusion of the screen, more than a half million drug-treated larvae had been evaluated. Beyond this initial example, however, the ARQiv-HTS platform is adaptable to almost any reporter-based assay designed to evaluate the effects of chemical compounds in living small-animal models. ARQiv-HTS thus enables large-scale whole-organism drug discovery for a variety of model species and from numerous disease-oriented perspectives. PMID:27831568

Petroleum dynamics in the sea and influence of subsea dispersant injection during Deepwater Horizon

PubMed Central

Gros, Jonas; Socolofsky, Scott A.; Dissanayake, Anusha L.; Jun, Inok; Zhao, Lin; Boufadel, Michel C.; Reddy, Christopher M.; Arey, J. Samuel

2017-01-01

During the Deepwater Horizon disaster, a substantial fraction of the 600,000–900,000 tons of released petroleum liquid and natural gas became entrapped below the sea surface, but the quantity entrapped and the sequestration mechanisms have remained unclear. We modeled the buoyant jet of petroleum liquid droplets, gas bubbles, and entrained seawater, using 279 simulated chemical components, for a representative day (June 8, 2010) of the period after the sunken platform’s riser pipe was pared at the wellhead (June 4–July 15). The model predicts that 27% of the released mass of petroleum fluids dissolved into the sea during ascent from the pared wellhead (1,505 m depth) to the sea surface, thereby matching observed volatile organic compound (VOC) emissions to the atmosphere. Based on combined results from model simulation and water column measurements, 24% of released petroleum fluid mass became channeled into a stable deep-water intrusion at 900- to 1,300-m depth, as aqueously dissolved compounds (∼23%) and suspended petroleum liquid microdroplets (∼0.8%). Dispersant injection at the wellhead decreased the median initial diameters of simulated petroleum liquid droplets and gas bubbles by 3.2-fold and 3.4-fold, respectively, which increased dissolution of ascending petroleum fluids by 25%. Faster dissolution increased the simulated flows of water-soluble compounds into biologically sparse deep water by 55%, while decreasing the flows of several harmful compounds into biologically rich surface water. Dispersant injection also decreased the simulated emissions of VOCs to the atmosphere by 28%, including a 2,000-fold decrease in emissions of benzene, which lowered health risks for response workers. PMID:28847967

Observation of Vacancies, Faults, and Superstructures in Ln5Mo2O12 (Ln = La, Y, and Lu) Compounds with Direct Mo-Mo Bonding.

PubMed

Colabello, Diane M; Sobalvarro, Elizabeth M; Sheckelton, John P; Neuefeind, Joerg C; McQueen, Tyrel M; Khalifah, Peter G

2017-11-06

Among oxide compounds with direct metal-metal bonding, the Y 5 Mo 2 O 12 (A 5 B 2 O 12 ) structural family of compounds has a particularly intriguing low-dimensional structure due to the presence of bioctahedral B 2 O 10 dimers arranged in one-dimensional edge-sharing chains along the direction of the metal-metal bonds. Furthermore, these compounds can have a local magnetic moment due to the noninteger oxidation state (+4.5) of the transition metal, in contrast to the conspicuous lack of a local moment that is commonly observed when oxide compounds with direct metal-metal bonding have integer oxidation states resulting from the lifting of orbital degeneracy typically induced by the metal-metal bonding. Although a monoclinic C2/m structure has been previously proposed for Ln 5 Mo 2 O 12 (Ln = La-Lu and Y) members of this family based on prior single crystal diffraction data, it is found that this structural model misses many important structural features. On the basis of synchrotron powder diffraction data, it is shown that the C2/m monoclinic unit cell represents a superstructure relative to a previously unrecognized orthorhombic Immm subcell and that the superstructure derives from the ordering of interchangeable Mo 2 O 10 and LaO 6 building blocks. The superstructure for this reason is typically highly faulted, as evidenced by the increased breadth of superstructure diffraction peaks associated with a coherence length of 1-2 nm in the c* direction. Finally, it is shown that oxygen vacancies can occur when Ln = La, producing an oxygen deficient stoichiometry of La 5 Mo 2 O 11.55 and an approximately 10-fold reduction in the number of unpaired electrons due to the reduction of the average Mo valence from +4.5 to +4.05, a result confirmed by magnetic susceptibility measurements. This represents the first observation of oxygen vacancies in this family of compounds and provides an important means of continuously tuning the magnetic interactions within the one-dimensional octahedral chains of this system.

Observation of Vacancies, Faults, and Superstructures in Ln 5Mo 2O 12 (Ln = La, Y, and Lu) Compounds with Direct Mo–Mo Bonding

DOE PAGES

Colabello, Diane M.; Sobalvarro, Elizabeth M.; Sheckelton, John P.; ...

2017-10-26

Among oxide compounds with direct metal–metal bonding, the Y 5Mo 2O 12 (A 5B 2O 12) structural family of compounds has a particularly intriguing low-dimensional structure due to the presence of bioctahedral B 2O 10 dimers arranged in one-dimensional edge-sharing chains along the direction of the metal–metal bonds. Furthermore, these compounds can have a local magnetic moment due to the noninteger oxidation state (+4.5) of the transition metal, in contrast to the conspicuous lack of a local moment that is commonly observed when oxide compounds with direct metal–metal bonding have integer oxidation states resulting from the lifting of orbital degeneracymore » typically induced by the metal–metal bonding. Although a monoclinic C2/m structure has been previously proposed for Ln 5Mo 2O 12 (Ln = La–Lu and Y) members of this family based on prior single crystal diffraction data, it is found that this structural model misses many important structural features. On the basis of synchrotron powder diffraction data, it is shown in this paper that the C2/m monoclinic unit cell represents a superstructure relative to a previously unrecognized orthorhombic Immm subcell and that the superstructure derives from the ordering of interchangeable Mo 2O 10 and LaO 6 building blocks. The superstructure for this reason is typically highly faulted, as evidenced by the increased breadth of superstructure diffraction peaks associated with a coherence length of 1–2 nm in the c* direction. Finally, it is shown that oxygen vacancies can occur when Ln = La, producing an oxygen deficient stoichiometry of La 5Mo 2O 11.55 and an approximately 10-fold reduction in the number of unpaired electrons due to the reduction of the average Mo valence from +4.5 to +4.05, a result confirmed by magnetic susceptibility measurements. Finally, this represents the first observation of oxygen vacancies in this family of compounds and provides an important means of continuously tuning the magnetic interactions within the one-dimensional octahedral chains of this system.« less

Observation of Vacancies, Faults, and Superstructures in Ln 5Mo 2O 12 (Ln = La, Y, and Lu) Compounds with Direct Mo–Mo Bonding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Colabello, Diane M.; Sobalvarro, Elizabeth M.; Sheckelton, John P.

Among oxide compounds with direct metal–metal bonding, the Y 5Mo 2O 12 (A 5B 2O 12) structural family of compounds has a particularly intriguing low-dimensional structure due to the presence of bioctahedral B 2O 10 dimers arranged in one-dimensional edge-sharing chains along the direction of the metal–metal bonds. Furthermore, these compounds can have a local magnetic moment due to the noninteger oxidation state (+4.5) of the transition metal, in contrast to the conspicuous lack of a local moment that is commonly observed when oxide compounds with direct metal–metal bonding have integer oxidation states resulting from the lifting of orbital degeneracymore » typically induced by the metal–metal bonding. Although a monoclinic C2/m structure has been previously proposed for Ln 5Mo 2O 12 (Ln = La–Lu and Y) members of this family based on prior single crystal diffraction data, it is found that this structural model misses many important structural features. On the basis of synchrotron powder diffraction data, it is shown in this paper that the C2/m monoclinic unit cell represents a superstructure relative to a previously unrecognized orthorhombic Immm subcell and that the superstructure derives from the ordering of interchangeable Mo 2O 10 and LaO 6 building blocks. The superstructure for this reason is typically highly faulted, as evidenced by the increased breadth of superstructure diffraction peaks associated with a coherence length of 1–2 nm in the c* direction. Finally, it is shown that oxygen vacancies can occur when Ln = La, producing an oxygen deficient stoichiometry of La 5Mo 2O 11.55 and an approximately 10-fold reduction in the number of unpaired electrons due to the reduction of the average Mo valence from +4.5 to +4.05, a result confirmed by magnetic susceptibility measurements. Finally, this represents the first observation of oxygen vacancies in this family of compounds and provides an important means of continuously tuning the magnetic interactions within the one-dimensional octahedral chains of this system.« less

Number of Sense Effects of Chinese Disyllabic Compounds in the Two Hemispheres

ERIC Educational Resources Information Center

Huang, Chih-Ying; Lee, Chia-Ying; Huang, Hsu-Wen; Chou, Chia-Ju

2011-01-01

The current study manipulated the visual field and the number of senses of the first character in Chinese disyllabic compounds to investigate how the related senses (polysemy) of the constituted character in the compounds were represented and processed in the two hemispheres. The ERP results in experiment 1 revealed crossover patterns in the left…

Elucidating compound mechanism of action by network perturbation analysis | Office of Cancer Genomics

Cancer.gov

Genome-wide identification of the mechanism of action (MoA) of small-molecule compounds characterizing their targets, effectors, and activity modulators represents a highly relevant yet elusive goal, with critical implications for assessment of compound efficacy and toxicity. Current approaches are labor intensive and mostly limited to elucidating high-affinity binding target proteins.

Measuring and modeling surface sorption dynamics of organophosphate flame retardants on impervious surfaces.

PubMed

Liang, Y; Liu, X; Allen, M R

2018-02-01

Understanding the sorption mechanisms for organophosphate flame retardants (OPFRs) on impervious surfaces is important to improve our knowledge of the fate and transport of OPFRs in indoor environments. The sorption processes of semivolatile organic compounds (SVOCs) on indoor surfaces are heterogeneous (multilayer sorption) or homogeneous (monolayer sorption). In this study, we adopted simplified Langmuir isotherm and Freundlich isotherm in a dynamic sink model to characterize the sorption dynamics of OPFRs on impervious surfaces such as stainless steel and made comparisons between the two models through a series of empty chamber studies. The tests involve two types of stainless steel chambers (53-L small chambers and 44-mL micro chambers) using tris(2-chloroethyl)phosphate (TCEP) and tris(1-chloro-2-propyl)phosphate (TCPP) as target compounds. Our test results show that the dynamic sink model using Freundlich isotherm can better represent the sorption process in the empty small chamber. Micro chamber test results from this study show that the sink model using both simplified Langmuir isotherm and Freundlich isotherm can well fit the measured gas-phase concentrations of OPFRs. We further applied both models and the parameters obtained to predict the gas phase concentrations of OPFRs in a small chamber with an emission source. Comparisons between model predictions and measurements demonstrate the reliability and applicability of the sorption parameters. Published by Elsevier Ltd.

Modelling bidirectional fluxes of methanol and acetaldehyde with the FORCAsT canopy exchange model

DOE PAGES

Ashworth, Kirsti; Chung, Serena H.; McKinney, Karena A.; ...

2016-12-15

Here, the FORCAsT canopy exchange model was used to investigate the underlying mechanisms governing foliage emissions of methanol and acetaldehyde, two short chain oxygenated volatile organic compounds ubiquitous in the troposphere and known to have strong biogenic sources, at a northern mid-latitude forest site. The explicit representation of the vegetation canopy within the model allowed us to test the hypothesis that stomatal conductance regulates emissions of these compounds to an extent that its influence is observable at the ecosystem scale, a process not currently considered in regional- or global-scale atmospheric chemistry models. Here, we found that FORCAsT could only reproducemore » the magnitude and diurnal profiles of methanol and acetaldehyde fluxes measured at the top of the forest canopy at Harvard Forest if light-dependent emissions were introduced to the model. With the inclusion of such emissions, FORCAsT was able to successfully simulate the observed bidirectional exchange of methanol and acetaldehyde. Although we found evidence that stomatal conductance influences methanol fluxes and concentrations at scales beyond the leaf level, particularly at dawn and dusk, we were able to adequately capture ecosystem exchange without the addition of stomatal control to the standard parameterisations of foliage emissions, suggesting that ecosystem fluxes can be well enough represented by the emissions models currently used.« less

Homology modeling, docking and structure-based pharmacophore of inhibitors of DNA methyltransferase

NASA Astrophysics Data System (ADS)

Yoo, Jakyung; Medina-Franco, José L.

2011-06-01

DNA methyltransferase 1 (DNMT1) is an emerging epigenetic target for the treatment of cancer and other diseases. To date, several inhibitors from different structural classes have been published. In this work, we report a comprehensive molecular modeling study of 14 established DNTM1 inhibitors with a herein developed homology model of the catalytic domain of human DNTM1. The geometry of the homology model was in agreement with the proposed mechanism of DNA methylation. Docking results revealed that all inhibitors studied in this work have hydrogen bond interactions with a glutamic acid and arginine residues that play a central role in the mechanism of cytosine DNA methylation. The binding models of compounds such as curcumin and parthenolide suggest that these natural products are covalent blockers of the catalytic site. A pharmacophore model was also developed for all DNMT1 inhibitors considered in this work using the most favorable binding conformations and energetic terms of the docked poses. To the best of our knowledge, this is the first pharmacophore model proposed for compounds with inhibitory activity of DNMT1. The results presented in this work represent a conceptual advance for understanding the protein-ligand interactions and mechanism of action of DNMT1 inhibitors. The insights obtained in this work can be used for the structure-based design and virtual screening for novel inhibitors targeting DNMT1.

Applications of the solvation parameter model in reversed-phase liquid chromatography.

PubMed

Poole, Colin F; Lenca, Nicole

2017-02-24

The solvation parameter model is widely used to provide insight into the retention mechanism in reversed-phase liquid chromatography, for column characterization, and in the development of surrogate chromatographic models for biopartitioning processes. The properties of the separation system are described by five system constants representing all possible intermolecular interactions for neutral molecules. The general model can be extended to include ions and enantiomers by adding new descriptors to encode the specific properties of these compounds. System maps provide a comprehensive overview of the separation system as a function of mobile phase composition and/or temperature for method development. The solvation parameter model has been applied to gradient elution separations but here theory and practice suggest a cautious approach since the interpretation of system and compound properties derived from its use are approximate. A growing application of the solvation parameter model in reversed-phase liquid chromatography is the screening of surrogate chromatographic systems for estimating biopartitioning properties. Throughout the discussion of the above topics success as well as known and likely deficiencies of the solvation parameter model are described with an emphasis on the role of the heterogeneous properties of the interphase region on the interpretation and understanding of the general retention mechanism in reversed-phase liquid chromatography for porous chemically bonded sorbents. Copyright © 2016 Elsevier B.V. All rights reserved.

Bayesian Models Leveraging Bioactivity and Cytotoxicity Information for Drug Discovery

PubMed Central

Ekins, Sean; Reynolds, Robert C.; Kim, Hiyun; Koo, Mi-Sun; Ekonomidis, Marilyn; Talaue, Meliza; Paget, Steve D.; Woolhiser, Lisa K.; Lenaerts, Anne J.; Bunin, Barry A.; Connell, Nancy; Freundlich, Joel S.

2013-01-01

SUMMARY Identification of unique leads represents a significant challenge in drug discovery. This hurdle is magnified in neglected diseases such as tuberculosis. We have leveraged public high-throughput screening (HTS) data, to experimentally validate virtual screening approach employing Bayesian models built with bioactivity information (single-event model) as well as bioactivity and cytotoxicity information (dual-event model). We virtually screen a commercial library and experimentally confirm actives with hit rates exceeding typical HTS results by 1-2 orders of magnitude. The first dual-event Bayesian model identified compounds with antitubercular whole-cell activity and low mammalian cell cytotoxicity from a published set of antimalarials. The most potent hit exhibits the in vitro activity and in vitro/in vivo safety profile of a drug lead. These Bayesian models offer significant economies in time and cost to drug discovery. PMID:23521795

Improving olefin tolerance and production in E. coli using native and evolved AcrB

DOE PAGES

Mingardon, Florence; Clement, Camille; Hirano, Kathleen; ...

2015-01-20

Microorganisms can be engineered for the production of chemicals utilized in the polymer industry. However many such target compounds inhibit microbial growth and might correspondingly limit production levels. Here, we focus on compounds that are precursors to bioplastics, specifically styrene and representative alpha-olefins; 1-hexene, 1-octene, and 1-nonene. We evaluated the role of the Escherichia coli efflux pump, AcrAB-TolC, in enhancing tolerance towards these olefin compounds. AcrAB-TolC is involved in the tolerance towards all four compounds in E. coli. Both styrene and 1-hexene are highly toxic to E. coli. Styrene is a model plastics precursor with an established route for productionmore » in E. coli (McKenna and Nielsen, 2011). Though our data indicates that AcrAB-TolC is important for its optimal production, we observed a strong negative selection against the production of styrene in E. coli. Thus we used 1-hexene as a model compound to implement a directed evolution strategy to further improve the tolerance phenotype towards this alpha-olefin. We focused on optimization of AcrB, the inner membrane domain known to be responsible for substrate binding, and found several mutations (A279T, Q584R, F617L, L822P, F927S, and F1033Y) that resulted in improved tolerance. Several of these mutations could also be combined in a synergistic manner. Our study shows efflux pumps to be an important mechanism in host engineering for olefins, and one that can be further improved using strategies such as directed evolution, to increase tolerance and potentially production.« less

Sorption and biodegradation of organic micropollutants during river bank filtration: a laboratory column study.

PubMed

Bertelkamp, C; Reungoat, J; Cornelissen, E R; Singhal, N; Reynisson, J; Cabo, A J; van der Hoek, J P; Verliefde, A R D

2014-04-01

This study investigated sorption and biodegradation behaviour of 14 organic micropollutants (OMP) in soil columns representative of the first metre (oxic conditions) of the river bank filtration (RBF) process. Breakthrough curves were modelled to differentiate between OMP sorption and biodegradation. The main objective of this study was to investigate if the OMP biodegradation rate could be related to the physico-chemical properties (charge, hydrophobicity and molecular weight) or functional groups of the OMPs. Although trends were observed between charge or hydrophobicity and the biodegradation rate for charged compounds, a statistically significant linear relationship for the complete OMP mixture could not be obtained using these physico-chemical properties. However, a statistically significant relationship was obtained between biological degradation rates and the OMP functional groups. The presence of ethers and carbonyl groups will increase biodegradability, while the presence of amines, ring structures, aliphatic ethers and sulphur will decrease biodegradability. This predictive model based on functional groups can be used by drinking water companies to make a first estimate whether a newly detected compound will be biodegraded during the first metre of RBF or that additional treatment is required. In addition, the influence of active and inactive biomass (biosorption), sand grains and the water matrix on OMP sorption was found to be negligible under the conditions investigated in this study. Retardation factors for most compounds were close to 1, indicating mobile behaviour of these compounds during soil passage. Adaptation of the biomass towards the dosed OMPs was not observed for a 6 month period, implying that new developed RBF sites might not be able to biodegrade compounds such as atrazine and sulfamethoxazole in the first few months of operation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Molecular Features Underlying Selectivity in Chicken Bitter Taste Receptors.

PubMed

Di Pizio, Antonella; Shy, Nitzan; Behrens, Maik; Meyerhof, Wolfgang; Niv, Masha Y

2018-01-01

Chickens sense the bitter taste of structurally different molecules with merely three bitter taste receptors ( Gallus gallus taste 2 receptors, ggTas2rs), representing a minimal case of bitter perception. Some bitter compounds like quinine, diphenidol and chlorpheniramine, activate all three ggTas2rs, while others selectively activate one or two of the receptors. We focus on bitter compounds with different selectivity profiles toward the three receptors, to shed light on the molecular recognition complexity in bitter taste. Using homology modeling and induced-fit docking simulations, we investigated the binding modes of ggTas2r agonists. Interestingly, promiscuous compounds are predicted to establish polar interactions with position 6.51 and hydrophobic interactions with positions 3.32 and 5.42 in all ggTas2rs; whereas certain residues are responsible for receptor selectivity. Lys 3.29 and Asn 3.36 are suggested as ggTas2r1-specificity-conferring residues; Gln 6.55 as ggTas2r2-specificity-conferring residue; Ser 5.38 and Gln 7.42 as ggTas2r7-specificity conferring residues. The selectivity profile of quinine analogs, quinidine, epiquinidine and ethylhydrocupreine, was then characterized by combining calcium-imaging experiments and in silico approaches. ggTas2r models were used to virtually screen BitterDB compounds. ~50% of compounds known to be bitter to human are likely to be bitter to chicken, with 25, 20, 37% predicted to be ggTas2r1, ggTas2r2, ggTas2r7 agonists, respectively. Predicted ggTas2rs agonists can be tested with in vitro and in vivo experiments, contributing to our understanding of bitter taste in chicken and, consequently, to the improvement of chicken feed.

Adverse Effect of Antifouling Compounds on the Reproductive Mechanisms of the Ascidian Ciona intestinalis

PubMed Central

Gallo, Alessandra; Tosti, Elisabetta

2013-01-01

Fertilization and embryo development that occur in sea water are sensitive to xenobiotics from anthropogenic sources. In this work, we evaluated the influence of two antifouling biocides, tributyltin (TBT) and diuron, on the reproductive mechanisms of the marine invertebrate Ciona intestinalis. By using electrophysiological techniques, we examined the impact of these compounds on the electrical properties of the mature oocytes and of events occurring at fertilization. With different toxicity assays, we studied the effect of the two biocides on the gametes by evaluating fertilization rate and embryo development. Results show that sodium (Na+) currents were significantly reduced by either of the two biocides, whereas conductance was significantly increased. The fertilization current frequency and amplitude, fertilization rate and larval development were affected only by TBT. This study suggests that: (i) the two biocides affect either the electrical properties of the oocyte plasma membrane and the reproductive success representing a risk factor for the survival of the species exposed to environmental pollution; (ii) the ascidian Ciona intestinalis may represent a good model organism to test toxicity of marine pollutants. Possible mechanisms of action of the two biocides are discussed. PMID:24065165

Laboratory study of high performance curing compounds for concrete pavements : phase I.

DOT National Transportation Integrated Search

2012-06-01

Three emulsion-type and two sealing-type curing compounds were evaluated for their ability to impart freezethaw : scaling resistance, and restrict evaporation, carbonation and chloride penetration to concrete specimens : prepared to represent common ...

Ultrasound mediated catalyst free synthesis of 6H-1-benzopyrano[4,3-b]quinolin-6-ones leading to novel quinoline derivatives: their evaluation as potential anti-cancer agents.

PubMed

Mulakayala, Naveen; Rambabu, D; Raja, Mohan Rao; M, Chaitanya; Kumar, Chitta Suresh; Kalle, Arunasree M; Rama Krishna, G; Malla Reddy, C; Basaveswara Rao, M V; Pal, Manojit

2012-01-15

A facile and catalyst free synthesis of 6H-1-benzopyrano[4,3-b]quinolin-6-ones has been accomplished via the reaction of 4-chloro-2-oxo-2H-chromene-3-carbaldehyde with various aromatic amines in the presence of ultrasound. Some of these compounds were converted to the corresponding 2-(3-(hydroxymethyl)quinolin-2-yl)phenols and further structure elaboration of a representative quinoline derivative is presented. Molecular structure of two representative compounds was confirmed by single crystal X-ray diffraction study. Many of these compounds were evaluated for their anti-proliferative properties in vitro against four cancer cell lines and several compounds were found to be active. Further in vitro studies indicated that inhibition of sirtuins could be the possible mechanism of action of these molecules. Copyright © 2011 Elsevier Ltd. All rights reserved.

Observations of diurnal to weekly variations of monoterpene-dominated fluxes of volatile organic compounds from mediterranean forests: implications for regional modeling.

PubMed

Fares, Silvano; Schnitzhofer, Ralf; Jiang, Xiaoyan; Guenther, Alex; Hansel, Armin; Loreto, Francesco

2013-10-01

The Estate of Castelporziano (Rome, Italy) hosts many ecosystems representative of Mediterranean vegetation, especially holm oak and pine forests and dune vegetation. In this work, basal emission factors (BEFs) of biogenic volatile organic compounds (BVOCs) obtained by Eddy Covariance in a field campaign using a proton transfer reaction-time-of-flight-mass spectrometer (PTR-TOF-MS) were compared to BEFs reported in previous studies that could not measure fluxes in real-time. Globally, broadleaf forests are dominated by isoprene emissions, but these Mediterranean ecosystems are dominated by strong monoterpene emitters, as shown by the new BEFs. The original and new BEFs were used to parametrize the model of emissions of gases and aerosols from nature (MEGAN v2.1), and model outputs were compared with measured fluxes. Results showed good agreement between modeled and measured fluxes when a model was used to predict radiative transfer and energy balance across the canopy. We then evaluated whether changes in BVOC emissions can affect the chemistry of the atmosphere and climate at a regional level. MEGAN was run together with the land surface model (community land model, CLM v4.0) of the community earth system model (CESM v1.0). Results highlighted that tropospheric ozone concentration and air temperature predicted from the model are sensitive to the magnitude of BVOC emissions, thus demonstrating the importance of adopting the proper BEF values for model parametrization.

Atmospheric Composition Change: Climate-Chemistry Interactions

NASA Technical Reports Server (NTRS)

Isaksen, I.S.A.; Granier, C.; Myhre, G.; Bernsten, T. K.; Dalsoren, S. B.; Gauss, S.; Klimont, Z.; Benestad, R.; Bousquet, P.; Collins, W.;

Experimental investigation of the auto-ignition characteristics of oxygenated reference fuel compounds

NASA Astrophysics Data System (ADS)

Walton, Stephen Michael

The increased use of biofuels presents an opportunity to improve combustion performance while simultaneously reducing greenhouse gases and pollutant emissions. This work focused on improving the fundamental understanding of the auto-ignition chemistry of oxygenated reference fuel compounds. A systematic study of the effects of ester structure on ignition chemistry was performed using the University of Michigan Rapid Compression Facility. The ignition properties of the ester compounds were investigated over a broad range of pressures (P=5-20 atm) and temperatures (T=850-1150 K) which are directly relevant to advanced combustion engine strategies. Ignition delay times for five esters were determined using the RCF. The esters were selected to systematically consider the chemical structure of the compounds. Three esters were saturated: methyl butanoate, butyl methanoate, and ethyl propanoate; and two were unsaturated: methyl crotonate and methyl trans-3-hexenoate. The unsaturated esters were more reactive than their saturated counterparts, with the largest unsaturated ester, methyl trans-3-hexenoate having the highest reactivity. Two isomers of the saturated esters, butyl methanoate and ethyl propanoate, were more reactive than the isomer methyl butanoate. The results are explained if we assume that butyl methanoate and ethyl propanoate form intermediate ring structures which decompose more rapidly than esters such as methyl butanoate, which do not form ring structures. Modeling studies of the reaction chemistry were conducted for methyl butanoate and ethyl propanoate, for which detailed mechanisms were available in the literature. The new experimental data indicated that literature rate coefficients for some of the methyl butanoate/HO2 reactions were too fast. Modifying these within the theoretical uncertainties for the reaction rates, led to excellent agreement between the model predictions and the experimental data. Comparison of the modeling results with the intermediates measured during methyl butanoate ignition indicated that pathways leading to the formation of small hydrocarbons are relatively well represented in the reaction mechanism. The results of this work provide archival benchmark data for improved understanding of the dominant reaction pathways and species controlling the auto-ignition of oxygenated reference fuel compounds. These data also provide a path for continued development of chemical kinetic models to optimize practical combustion systems.

Basics of compounding: Tips and hints: powders, capsules, tablets, suppositories, and sticks, part 1.

PubMed

Allen, Loyd V

2014-01-01

No matter the profession, professionals should never stop learning. This is especially true and important in the profession of compounding pharmacy. Compounding pharmacists are continuously faced with the challenge of finding new and inventive ways to assist patients with their individual and specific drug requirements. As compounding pharmacists learn, be it through formal continuing education or experience, they should be willing to share their knowledge with other compounders. In our goal of providing compounding pharmacists with additional knowledge to improve their skills in the art and practice of compounding, this article, which provides tips and hits on compounding with powders, capsules, tablets, suppositories, and sticks, represents the first in a series of articles to assist compounding pharmacists in the preparation of compounded medications.

Antimicrobial Action of Compounds from Marine Seaweed

PubMed Central

Pérez, María José; Falqué, Elena; Domínguez, Herminia

2016-01-01

Seaweed produces metabolites aiding in the protection against different environmental stresses. These compounds show antiviral, antiprotozoal, antifungal, and antibacterial properties. Macroalgae can be cultured in high volumes and would represent an attractive source of potential compounds useful for unconventional drugs able to control new diseases or multiresistant strains of pathogenic microorganisms. The substances isolated from green, brown and red algae showing potent antimicrobial activity belong to polysaccharides, fatty acids, phlorotannins, pigments, lectins, alkaloids, terpenoids and halogenated compounds. This review presents the major compounds found in macroalga showing antimicrobial activities and their most promising applications. PMID:27005637

Small-Molecule “BRCA1-Mimetics” Are Antagonists of Estrogen Receptor-α

PubMed Central

Ma, Yongxian; Tomita, York; Preet, Anju; Clarke, Robert; Englund, Erikah; Grindrod, Scott; Nathan, Shyam; De Oliveira, Eliseu; Brown, Milton L.

2014-01-01

Context: Resistance to conventional antiestrogens is a major cause of treatment failure and, ultimately, death in breast cancer. Objective: The objective of the study was to identify small-molecule estrogen receptor (ER)-α antagonists that work differently from tamoxifen and other selective estrogen receptor modulators. Design: Based on in silico screening of a pharmacophore database using a computed model of the BRCA1-ER-α complex (with ER-α liganded to 17β-estradiol), we identified a candidate group of small-molecule compounds predicted to bind to a BRCA1-binding interface separate from the ligand-binding pocket and the coactivator binding site of ER-α. Among 40 candidate compounds, six inhibited estradiol-stimulated ER-α activity by at least 50% in breast carcinoma cells, with IC50 values ranging between 3 and 50 μM. These ER-α inhibitory compounds were further studied by molecular and cell biological techniques. Results: The compounds strongly inhibited ER-α activity at concentrations that yielded little or no nonspecific toxicity, but they produced only a modest inhibition of progesterone receptor activity. Importantly, the compounds blocked proliferation and inhibited ER-α activity about equally well in antiestrogen-sensitive and antiestrogen-resistant breast cancer cells. Representative compounds disrupted the interaction of BRCA1 and ER-α in the cultured cells and blocked the interaction of ER-α with the estrogen response element. However, the compounds had no effect on the total cellular ER-α levels. Conclusions: These findings suggest that we have identified a new class of ER-α antagonists that work differently from conventional antiestrogens (eg, tamoxifen and fulvestrant). PMID:25264941

Re-Creation of Historical Chrysotile-Containing Joint Compounds

PubMed Central

Brorby, G. P.; Sheehan, P. J.; Berman, D. W.; Greene, J. F.; Holm, S. E.

2008-01-01

Chrysotile-containing joint compound was commonly used in construction of residential and commercial buildings through the mid 1970s; however, these products have not been manufactured in the United States for more than 30 years. Little is known about actual human exposures to chrysotile fibers that may have resulted from use of chrysotile-containing joint compounds, because few exposure and no health-effects studies have been conducted specifically with these products. Because limited amounts of historical joint compounds are available (and the stability or representativeness of aged products is suspect), it is currently impossible to conduct meaningful studies to better understand the nature and magnitude of potential exposures to chrysotile that may have been associated with historical use of these products. Therefore, to support specific exposure and toxicology research activities, two types of chrysotile-containing joint compounds were produced according to original formulations from the late 1960s. To the extent possible, ingredients were the same as those used originally, with many obtained from the original suppliers. The chrysotile used historically in these products was primarily Grade 7RF9 from the Philip Carey mine. Because this mine is closed, a suitable alternate was identified by comparing the sizes and mineral composition of asbestos structures in a sample of what has been represented to be historical joint compound (all of which were chrysotile) to those in samples of three currently commercially available Grade 7 chrysotile products. The re-created materials generally conformed to original product specifications (e.g. viscosity, workability, crack resistance), indicating that these materials are sufficiently representative of the original products to support research activities. PMID:18788019

Targeting RORs nuclear receptors by novel synthetic steroidal inverse agonists for autoimmune disorders.

PubMed

Dal Prà, Matteo; Carta, Davide; Szabadkai, Gyorgy; Suman, Matteo; Frión-Herrera, Yahima; Paccagnella, Nicola; Castellani, Giulia; De Martin, Sara; Ferlin, Maria Grazia

2018-05-01

Designing novel inverse agonists of NR RORγt still represents a challenge for the pharmaceutical community to develop therapeutics for treating immune diseases. By exploring the structure of NRs natural ligands, the representative arotenoid ligands and RORs specific ligands share some chemical homologies which can be exploited to design a novel molecular structure characterized by a polycyclic core bearing a polar head and a hydrophobic tail. Compound MG 2778 (8), a cyclopenta[a]phenantrene derivative, was identified as lead compound which was chemically modified at position 2 in order to obtain a small library for preliminary SARs. Cell viability and estrogenic activity of compounds 7, 8, 19a, 30, 31 and 32 were evaluated to attest selectivity. The selected 7, 8, 19a and 31 compounds were assayed in a Gal4 UAS-Luc co-transfection system in order to determine their ability to modulate RORγt activity in a cellular environment. They were evaluated as inverse agonists taken ursolic acid as reference compound. The potency of compounds was lower than that of ursolic acid, but their efficacy was similar. Compound 19a was the most active, significantly reducing RORγt activity at low micromolar concentrations. Copyright © 2018 Elsevier Ltd. All rights reserved.

QSAR and docking studies on xanthone derivatives for anticancer activity targeting DNA topoisomerase IIα

PubMed Central

Alam, Sarfaraz; Khan, Feroz

2014-01-01

Due to the high mortality rate in India, the identification of novel molecules is important in the development of novel and potent anticancer drugs. Xanthones are natural constituents of plants in the families Bonnetiaceae and Clusiaceae, and comprise oxygenated heterocycles with a variety of biological activities along with an anticancer effect. To explore the anticancer compounds from xanthone derivatives, a quantitative structure activity relationship (QSAR) model was developed by the multiple linear regression method. The structure–activity relationship represented by the QSAR model yielded a high activity–descriptors relationship accuracy (84%) referred by regression coefficient (r2=0.84) and a high activity prediction accuracy (82%). Five molecular descriptors – dielectric energy, group count (hydroxyl), LogP (the logarithm of the partition coefficient between n-octanol and water), shape index basic (order 3), and the solvent-accessible surface area – were significantly correlated with anticancer activity. Using this QSAR model, a set of virtually designed xanthone derivatives was screened out. A molecular docking study was also carried out to predict the molecular interaction between proposed compounds and deoxyribonucleic acid (DNA) topoisomerase IIα. The pharmacokinetics parameters, such as absorption, distribution, metabolism, excretion, and toxicity, were also calculated, and later an appraisal of synthetic accessibility of organic compounds was carried out. The strategy used in this study may provide understanding in designing novel DNA topoisomerase IIα inhibitors, as well as for other cancer targets. PMID:24516330

The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study

NASA Astrophysics Data System (ADS)

Kuz'min, Victor E.; Muratov, Eugene N.; Artemenko, Anatoly G.; Gorb, Leonid; Qasim, Mohammad; Leszczynski, Jerzy

2008-10-01

The present study applies the Hierarchical Technology for Quantitative Structure-Activity Relationships (HiT QSAR) for (i) evaluation of the influence of the characteristics of 28 nitroaromatic compounds (some of which belong to a widely known class of explosives) as to their toxicity; (ii) prediction of toxicity for new nitroaromatic derivatives; (iii) analysis of the effects of substituents in nitroaromatic compounds on their toxicity in vivo. The 50% lethal dose concentration for rats (LD50) was used to develop the QSAR models based on simplex representation of molecular structure. The preliminary 1D QSAR results show that even the information on the composition of molecules reveals the main tendencies of changes in toxicity. The statistic characteristics for partial least squares 2D QSAR models are quite satisfactory ( R 2 = 0.96-0.98; Q 2 = 0.91-0.93; R 2 test = 0.89-0.92), which allows us to carry out the prediction of activity for 41 novel compounds designed by the application of new combinations of substituents represented in the training set. The comprehensive analysis of toxicity changes as a function of substituent position and nature was carried out. Molecular fragments that promote and interfere with toxicity were defined on the basis of the obtained models. It was shown that the mutual influence of substituents in the benzene ring plays a crucial role regarding toxicity. The influence of different substituents on toxicity can be mediated via different C-H fragments of the aromatic ring.

Heat treatment of organics for increasing anaerobic biodegradability. Annual progress report, June 1, 1976-May 31, 1977. Civil engineering technical report No. 222

DOE Office of Scientific and Technical Information (OSTI.GOV)

Healy, J.B. Jr.; Owen, W.F.; Stuckey, D.C.

1977-06-30

This report represents the results of the first year of study on the heat treatment of organics to increase its biodegradability by anaerobic bacteria for the microbial production of methane. The purpose of this study is to develop a means for increasing the yield and reducing the cost of methane, a useful energy source. The procedures being evaluated are heat treatment at temperatures up to 250/sup 0/C, under pH ranges of 1 to 13. Included in this report are results on: (1) lignocellulose digestion and acclimation to its products from heat treatment; (2) the fate of waste activated sludge andmore » its cellular nitrogenous compounds; and (3) the biodegradability of model compounds likely to be formed during heat treatment.« less

Experimental Investigation of a Wing-in-Ground Effect Craft

PubMed Central

Tofa, M. Mobassher; Ahmed, Yasser M.; Jamei, Saeed; Priyanto, Agoes; Rahimuddin

2014-01-01

The aerodynamic characteristics of the wing-in-ground effect (WIG) craft model that has a noble configuration of a compound wing was experimentally investigated and Universiti Teknologi Malaysia (UTM) wind tunnel with and without endplates. Lift and drag forces, pitching moment coefficients, and the centre of pressure were measured with respect to the ground clearance and the wing angle of attack. The ground effect and the existence of the endplates increase the wing lift-to-drag ratio at low ground clearance. The results of this research work show new proposed design of the WIG craft with compound wing and endplates, which can clearly increase the aerodynamic efficiency without compromising the longitudinal stability. The use of WIG craft is representing an ambitious technology that will help in reducing time, effort, and money of the conventional marine transportation in the future. PMID:24701170

Experimental investigation of a wing-in-ground effect craft.

PubMed

Tofa, M Mobassher; Maimun, Adi; Ahmed, Yasser M; Jamei, Saeed; Priyanto, Agoes; Rahimuddin

2014-01-01

The aerodynamic characteristics of the wing-in-ground effect (WIG) craft model that has a noble configuration of a compound wing was experimentally investigated and Universiti Teknologi Malaysia (UTM) wind tunnel with and without endplates. Lift and drag forces, pitching moment coefficients, and the centre of pressure were measured with respect to the ground clearance and the wing angle of attack. The ground effect and the existence of the endplates increase the wing lift-to-drag ratio at low ground clearance. The results of this research work show new proposed design of the WIG craft with compound wing and endplates, which can clearly increase the aerodynamic efficiency without compromising the longitudinal stability. The use of WIG craft is representing an ambitious technology that will help in reducing time, effort, and money of the conventional marine transportation in the future.

New imidazolidinedione derivatives as antimalarial agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Liang; Sathunuru, Ramadas; Luong, ThuLan

2012-04-30

A series of new N-alky- and N-alkoxy-imidazolidinediones was prepared and assessed for prophylactic and radical curative activities in mouse and Rhesus monkey models. New compounds are generally metabolically stable, weakly active in vitro against Plasmodium falciparum clones (D6 and W2) and in mice infected with Plasmodium berghei sporozoites. Representative compounds 8e and 9c showed good causal prophylactic activity in Rhesus monkeys dosed 30 mg/kg/day for 3 consecutive days by IM, delayed patency for 19-21 days and 54-86 days, respectively, as compared to the untreated control. By oral, 9c showed only marginal activity in causal prophylactic and radical curative tests atmore » 50 mg/kg/day x 3 and 30 mg/kg/day x 7 plus chloroquine 10 mg/kg for 7 days, respectively.« less

Single jugular vein cannulated rats may not be suitable for intravenous pharmacokinetic screening of high logP compounds.

PubMed

Gaud, Nilesh; Kumar, Anoop; Matta, Muralikrishna; Kole, Prashant; Sridhar, Srikanth; Mandlekar, Sandhya; Holenarsipur, Vinay K

2017-03-01

Rat is commonly used for pharmacokinetic screening during pharmaceutical lead optimization. To handle the large number of compounds, rats with a single jugular vein cannulation are commonly utilized for intravenous pharmacokinetic studies, where the same cannula is used both for dose administration and blood sampling. We demonstrate that the single cannula method is not suitable for all compounds, especially for high logP compounds. We propose an alternative dual cannulation technique in which two cannulas are placed in the same jugular vein, thus avoiding an additional surgery. Compounds were administered orally or via intravenous infusion to compare PK parameters, including bioavailability, using both procedures. For itraconazole and amiodarone, known to bind to the cannula, the measured plasma exposures were substantially higher in the single cannulated rats than those from dual cannulated rats. Area under the plasma concentration time curve differed by 79% and 74% for itraconazole and amiodarone, respectively. When compared to the single cannulation approach, clearance, volume of distribution and bioavailability determined by dual cannulation were 39%, 60% and 38% higher for itraconazole, and 46%, 34% and 42% higher for amiodarone, respectively. In contrast, all pharmacokinetic parameters were similar between single and dual-cannulated rats for the hydrophilic compound atenolol. Based on these results, we recommend the use of dual cannulated rats for intravenous pharmacokinetic studies when testing a series of hydrophobic compounds that may be prone to non-specific binding to the cannula. If single cannulated model is selected for pharmacokinetic screening, we recommend a bridging study with dual cannulated rats with representative compounds of a given chemical series. Copyright © 2016 Elsevier B.V. All rights reserved.

Contamination levels of human pharmaceutical compounds in French surface and drinking water.

PubMed

Mompelat, S; Thomas, O; Le Bot, B

2011-10-01

The occurrence of 20 human pharmaceutical compounds and metabolites from 10 representative therapeutic classes was analysed from resource and drinking water in two catchment basins located in north-west France. 98 samples were analysed from 63 stations (surface water and drinking water produced from surface water). Of the 20 human pharmaceutical compounds selected, 16 were quantified in both the surface water and drinking water, with 22% of the values above the limit of quantification for surface water and 14% for drinking water). Psychostimulants, non-steroidal anti-inflammatory drugs, iodinated contrast media and anxiolytic drugs were the main therapeutic classes of human pharmaceutical compounds detected in the surface water and drinking water. The results for surface water were close to results from previous studies in spite of differences in prescription rates of human pharmaceutical compounds in different countries. The removal rate of human pharmaceutical compounds at 11 water treatment units was also determined. Only caffeine proved to be resistant to drinking water treatment processes (with a minimum rate of 5%). Other human pharmaceutical compounds seemed to be removed more efficiently (average elimination rate of over 50%) by adsorption onto activated carbon and oxidation/disinfection with ozone or chlorine (not taking account of the disinfection by-products). These results add to the increasing evidence of the occurrence of human pharmaceutical compounds in drinking water that may represent a threat to human beings exposed to a cocktail of human pharmaceutical compounds and related metabolites and by-products in drinking water.

Late-Transition-Metal-Modified β-Mo 2C Catalysts for Enhanced Hydrogenation during Guaiacol Deoxygenation

DOE PAGES

Baddour, Frederick G.; Witte, Vanessa A.; Nash, Connor P.; ...

2017-10-26

Molybdenum carbide has been identified as a promising bifunctional catalyst in the deoxygenation of a variety of pyrolysis vapor model compounds. Although high deoxygenation activity has been demonstrated, complementary hydrogenation activity has been limited, especially for lignin-derived, aromatic model compounds. The ability to control the relative site densities of acidic and hydrogenation functionalities represents a catalyst design challenge for these materials with the goal to improve hydrogenation activity under ex situ catalytic fast pyrolysis (CFP) conditions. Here in this paper, we demonstrate that the addition of Pt and Ni to Mo 2C resulted in an increase in the H*-site densitymore » with only a minor decrease in the acid-site density. In contrast, the addition of Pd did not significantly alter the H* or acid site densities. High conversions (>94%) and high selectivities to 0-oxygen products (>80%) were observed in guaiacol deoxygenation under ex situ CFP conditions (350 °C and 0.44 MPa H 2) for all catalysts. Pt addition resulted in the greatest deoxygenation, and site-time yields to hydrogenated products over the Pt/Mo 2C catalyst were increased to 0.048 s -1 compared to 0.015-0.019 s -1 for all other catalysts. The Pt/Mo 2C catalyst demonstrated the highest hydrogenation performance, but modification with Ni also significantly enhanced hydrogenation performance, representing a promising lower-cost alternative.« less

Late-Transition-Metal-Modified β-Mo 2C Catalysts for Enhanced Hydrogenation during Guaiacol Deoxygenation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baddour, Frederick G.; Witte, Vanessa A.; Nash, Connor P.

Molybdenum carbide has been identified as a promising bifunctional catalyst in the deoxygenation of a variety of pyrolysis vapor model compounds. Although high deoxygenation activity has been demonstrated, complementary hydrogenation activity has been limited, especially for lignin-derived, aromatic model compounds. The ability to control the relative site densities of acidic and hydrogenation functionalities represents a catalyst design challenge for these materials with the goal to improve hydrogenation activity under ex situ catalytic fast pyrolysis (CFP) conditions. Here in this paper, we demonstrate that the addition of Pt and Ni to Mo 2C resulted in an increase in the H*-site densitymore » with only a minor decrease in the acid-site density. In contrast, the addition of Pd did not significantly alter the H* or acid site densities. High conversions (>94%) and high selectivities to 0-oxygen products (>80%) were observed in guaiacol deoxygenation under ex situ CFP conditions (350 °C and 0.44 MPa H 2) for all catalysts. Pt addition resulted in the greatest deoxygenation, and site-time yields to hydrogenated products over the Pt/Mo 2C catalyst were increased to 0.048 s -1 compared to 0.015-0.019 s -1 for all other catalysts. The Pt/Mo 2C catalyst demonstrated the highest hydrogenation performance, but modification with Ni also significantly enhanced hydrogenation performance, representing a promising lower-cost alternative.« less

Observations of Diurnal to Weekly Variations of Monoterpene-Dominated Fluxes of Volatile Organic Compounds from Mediterranean Forests: Implications for Regional Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fares, Silvano; Schnitzhofer, Ralf; Jiang, Xiaoyan

2013-10-01

The Estate of Castelporziano (Rome, Italy) hosts many ecosystems representative of Mediterranean vegetation, especially holm oak and pine forests and dune vegetation. In this work, basal emission factors (BEFs) of biogenic volatile organic compounds (BVOCs) obtained by Eddy Covariance in a field campaign using a proton transfer reaction–time-of-flight–mass spectrometer (PTR-TOF-MS) were compared to BEFs reported in previous studies that could not measure fluxes in real-time. Globally, broadleaf forests are dominated by isoprene emissions, but these Mediterranean ecosystems are dominated by strong monoterpene emitters, as shown by the new BEFs. The original and new BEFs were used to parametrize the modelmore » of emissions of gases and aerosols from nature (MEGAN v2.1), and model outputs were compared with measured fluxes. Results showed good agreement between modeled and measured fluxes when a model was used to predict radiative transfer and energy balance across the canopy. We then evaluated whether changes in BVOC emissions can affect the chemistry of the atmosphere and climate at a regional level. MEGAN was run together with the land surface model (community land model, CLM v4.0) of the community earth system model (CESM v1.0). Finally, results highlighted that tropospheric ozone concentration and air temperature predicted from the model are sensitive to the magnitude of BVOC emissions, thus demonstrating the importance of adopting the proper BEF values for model parametrization.« less

Volatile compounds of dry beans (Phaseolus vulgaris L.).

PubMed

Oomah, B Dave; Liang, Lisa S Y; Balasubramanian, Parthiba

2007-12-01

Volatile compounds of uncooked dry bean (Phaseolus vulgaris L.) cultivars representing three market classes (black, dark red kidney and pinto) grown in 2005 were isolated with headspace solid phase microextraction (HS-SPME), and analyzed with gas chromatography mass spectrometry (GC-MS). A total of 62 volatiles consisting of aromatic hydrocarbons, aldehydes, alkanes, alcohols and ketones represented on average 62, 38, 21, 12, and 9 x 10(6) total area counts, respectively. Bean cultivars differed in abundance and profile of volatiles. The combination of 18 compounds comprising a common profile explained 79% of the variance among cultivars based on principal component analysis (PCA). The SPME technique proved to be a rapid and effective method for routine evaluation of dry bean volatile profile.

Pharmacophore Modelling and 4D-QSAR Study of Ruthenium(II) Arene Complexes as Anticancer Agents (Inhibitors) by Electron Conformational- Genetic Algorithm Method.

PubMed

Yavuz, Sevtap Caglar; Sabanci, Nazmiye; Saripinar, Emin

2018-01-01

The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity. The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically. The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R2 training= 0.817, q 2=0.718 and SEtraining=0.066, q2 ext1 = 0.867, q2 ext2 = 0.849, q2 ext3 =0.895, ccctr = 0.895, ccctest = 0.930 and cccall = 0.905. Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Cuticular Compounds Bring New Insight in the Post-Glacial Recolonization of a Pyrenean Area: Deutonura deficiens Deharveng, 1979 Complex, a Case Study

PubMed Central

Porco, David; Bedos, Anne; Deharveng, Louis

2010-01-01

Background In most Arthropod groups, the study of systematics and evolution rely mostly on neutral characters, in this context cuticular compounds, as non-neutral characters, represent an underexplored but potentially informative type of characters at the infraspecific level as they have been routinely proven to be involved in sexual attraction. Methods and Findings The collembolan species complex Deutonura deficiens was chosen as a model in order to test the utility of these characters for delineating four infraspecific entities of this group. Specimens were collected for three subspecies (D. d. deficiens, D. d. meridionalis, D. d. sylvatica) and two morphotypes (D. d. sylvatica morphoype A and B) of the complex; an additional species D. monticola was added. Cuticular compounds were extracted and separated by gas chromatography for each individual. Our results demonstrate that cuticular compounds succeeded in separating the different elements of this complex. Those data allowed also the reconstruction of the phylogenetic relationships among them. Conclusions The discriminating power of cuticular compounds is directly related to their involvement in sexual attraction and mate recognition. These findings allowed a discussion on the potential involvement of intrinsic and paleoclimatic factors in the origin and the diversification of this complex in the Pyrenean zone. This character type brings the first advance from pattern to process concerning the origin of this species complex. PMID:21209797

Cuticular compounds bring new insight in the post-glacial recolonization of a Pyrenean area: Deutonura deficiens Deharveng, 1979 complex, a case study.

PubMed

Porco, David; Bedos, Anne; Deharveng, Louis

2010-12-21

In most Arthropod groups, the study of systematics and evolution rely mostly on neutral characters, in this context cuticular compounds, as non-neutral characters, represent an underexplored but potentially informative type of characters at the infraspecific level as they have been routinely proven to be involved in sexual attraction. The collembolan species complex Deutonura deficiens was chosen as a model in order to test the utility of these characters for delineating four infraspecific entities of this group. Specimens were collected for three subspecies (D. d. deficiens, D. d. meridionalis, D. d. sylvatica) and two morphotypes (D. d. sylvatica morphoype A and B) of the complex; an additional species D. monticola was added. Cuticular compounds were extracted and separated by gas chromatography for each individual. Our results demonstrate that cuticular compounds succeeded in separating the different elements of this complex. Those data allowed also the reconstruction of the phylogenetic relationships among them. The discriminating power of cuticular compounds is directly related to their involvement in sexual attraction and mate recognition. These findings allowed a discussion on the potential involvement of intrinsic and paleoclimatic factors in the origin and the diversification of this complex in the Pyrenean zone. This character type brings the first advance from pattern to process concerning the origin of this species complex.

QSAR modeling of GPCR ligands: methodologies and examples of applications.

PubMed

Tropsha, A; Wang, S X

2006-01-01

GPCR ligands represent not only one of the major classes of current drugs but the major continuing source of novel potent pharmaceutical agents. Because 3D structures of GPCRs as determined by experimental techniques are still unavailable, ligand-based drug discovery methods remain the major computational molecular modeling approaches to the analysis of growing data sets of tested GPCR ligands. This paper presents an overview of modern Quantitative Structure Activity Relationship (QSAR) modeling. We discuss the critical issue of model validation and the strategy for applying the successfully validated QSAR models to virtual screening of available chemical databases. We present several examples of applications of validated QSAR modeling approaches to GPCR ligands. We conclude with the comments on exciting developments in the QSAR modeling of GPCR ligands that focus on the study of emerging data sets of compounds with dual or even multiple activities against two or more of GPCRs.

Synthesis and fundamental properties of stable Ph(3)SnSiH(3) and Ph(3)SnGeH(3) hydrides: model compounds for the design of Si-Ge-Sn photonic alloys.

PubMed

Tice, Jesse B; Chizmeshya, Andrew V G; Groy, Thomas L; Kouvetakis, John

2009-07-06

The compounds Ph(3)SnSiH(3) and Ph(3)SnGeH(3) (Ph = C(6)H(5)) have been synthesized as colorless solids containing Sn-MH(3) (M = Si, Ge) moieties that are stable in air despite the presence of multiple and highly reactive Si-H and Ge-H bonds. These molecules are of interest since they represent potential model compounds for the design of new classes of IR semiconductors in the Si-Ge-Sn system. Their unexpected stability and high solubility also makes them a safe, convenient, and potentially useful delivery source of -SiH(3) and -GeH(3) ligands in molecular synthesis. The structure and composition of both compounds has been determined by chemical analysis and a range of spectroscopic methods including multinuclear NMR. Single crystal X-ray structures were determined and indicated that both compounds condense in a Z = 2 triclinic (P1) space group with lattice parameters (a = 9.7754(4) A, b = 9.8008(4) A, c = 10.4093(5) A, alpha = 73.35(10)(o), beta = 65.39(10)(o), gamma = 73.18(10)(o)) for Ph(3)SnSiH(3) and (a = 9.7927(2) A, b = 9.8005(2) A, c = 10.4224(2) A, alpha = 74.01(3)(o), beta = 65.48(3)(o), gamma = 73.43(3)(o)) for Ph(3)SnGeH(3). First principles density functional theory simulations are used to corroborate the molecular structures of Ph(3)SnSiH(3) and Ph(3)SnGeH(3), gain valuable insight into the relative stability of the two compounds, and provide correlations between the Si-Sn and Ge-Sn bonds in the molecules and those in tetrahedral Si-Ge-Sn solids.

Using Graph Indices for the Analysis and Comparison of Chemical Datasets.

PubMed

Fourches, Denis; Tropsha, Alexander

2013-10-01

In cheminformatics, compounds are represented as points in multidimensional space of chemical descriptors. When all pairs of points found within certain distance threshold in the original high dimensional chemistry space are connected by distance-labeled edges, the resulting data structure can be defined as Dataset Graph (DG). We show that, similarly to the conventional description of organic molecules, many graph indices can be computed for DGs as well. We demonstrate that chemical datasets can be effectively characterized and compared by computing simple graph indices such as the average vertex degree or Randic connectivity index. This approach is used to characterize and quantify the similarity between different datasets or subsets of the same dataset (e.g., training, test, and external validation sets used in QSAR modeling). The freely available ADDAGRA program has been implemented to build and visualize DGs. The approach proposed and discussed in this report could be further explored and utilized for different cheminformatics applications such as dataset diversification by acquiring external compounds, dataset processing prior to QSAR modeling, or (dis)similarity modeling of multiple datasets studied in chemical genomics applications. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

From small sweeteners to sweet proteins: anatomy of the binding sites of the human T1R2_T1R3 receptor.

PubMed

Morini, Gabriella; Bassoli, Angela; Temussi, Piero A

2005-08-25

The sweet taste receptor, a heterodimeric G protein coupled receptor (GPCR) protein, formed by the T1R2 and T1R3 subunits, recognizes several sweet compounds including carbohydrates, amino acids, peptides, proteins, and synthetic sweeteners. Its similarity with the metabotropic glutamate mGluR1 receptor allowed us to build homology models. All possible dimers formed by combinations of the human T1R2 and T1R3 subunits, modeled on the A (closed) or B (open) chains of the extracellular ligand binding domain of the mGluR1 template, yield four ligand binding sites for low-molecular-weight sweeteners. These sites were probed by docking a set of molecules representative of all classes of sweet compounds and calculating the free energy of ligand binding. These sites are not easily accessible to sweet proteins, but docking experiments in silico showed that sweet proteins can bind to a secondary site without entering the deep cleft. Our models account for many experimental observations on the tastes of sweeteners, including sweetness synergy, and can help to design new sweeteners.

Removal of trace organic micropollutants by drinking water biological filters.

PubMed

Zearley, Thomas L; Summers, R Scott

2012-09-04

The long-term removal of 34 trace organic micropollutants (<1 μg L(-1)) was evaluated and modeled in drinking water biological filters with sand media from a full-scale plant. The micropollutants included pesticides, pharmaceuticals, and personal care products, some of which are endocrine disrupting chemicals, and represent a wide range of uses, chemical structures, adsorbabilities, and biodegradabilities. Micropollutant removal ranged from no measurable removal (<15%) for 13 compounds to removal below the detection limit and followed one of four trends over the one year study period: steady state removal throughout, increasing removal to steady state (acclimation), decreasing removal, or no removal (recalcitrant). Removals for all 19 nonrecalcitrant compounds followed first-order kinetics when at steady state with increased removal at longer empty bed contact times (EBCT). Rate constants were calculated, 0.02-0.37 min(-1), and used in a pseudo-first-order rate model with the EBCT to predict removals in laboratory biofilters at a different EBCT and influent conditions. Drinking water biofiltration has the potential to be an effective process for the control of many trace organic contaminants and a pseudo-first-order model can serve as an appropriate method for approximating performance.

Measurements of PANs during the New England Air Quality Study 2002

NASA Astrophysics Data System (ADS)

Roberts, J. M.; Marchewka, M.; Bertman, S. B.; Sommariva, R.; Warneke, C.; de Gouw, J.; Kuster, W.; Goldan, P.; Williams, E.; Lerner, B. M.; Murphy, P.; Fehsenfeld, F. C.

2007-10-01

Measurements of peroxycarboxylic nitric anhydrides (PANs) were made during the New England Air Quality Study 2002 cruise of the NOAA RV Ronald H Brown. The four compounds observed, PAN, peroxypropionic nitric anhydride (PPN), peroxymethacrylic nitric anhydride (MPAN), and peroxyisobutyric nitric anhydride (PiBN) were compared with results from other continental and Gulf of Maine sites. Systematic changes in PPN/PAN ratio, due to differential thermal decomposition rates, were related quantitatively to air mass aging. At least one early morning period was observed when O3 seemed to have been lost probably due to NO3 and N2O5 chemistry. The highest O3 episode was observed in the combined plume of isoprene sources and anthropogenic volatile organic compounds (VOCs) and NOx sources from the greater Boston area. A simple linear combination model showed that the organic precursors leading to elevated O3 were roughly half from the biogenic and half from anthropogenic VOC regimes. An explicit chemical box model confirmed that the chemistry in the Boston plume is well represented by the simple linear combination model. This degree of biogenic hydrocarbon involvement in the production of photochemical ozone has significant implications for air quality control strategies in this region.

Literature-based compound profiling: application to toxicogenomics.

PubMed

Frijters, Raoul; Verhoeven, Stefan; Alkema, Wynand; van Schaik, René; Polman, Jan

2007-11-01

To reduce continuously increasing costs in drug development, adverse effects of drugs need to be detected as early as possible in the process. In recent years, compound-induced gene expression profiling methodologies have been developed to assess compound toxicity, including Gene Ontology term and pathway over-representation analyses. The objective of this study was to introduce an additional approach, in which literature information is used for compound profiling to evaluate compound toxicity and mode of toxicity. Gene annotations were built by text mining in Medline abstracts for retrieval of co-publications between genes, pathology terms, biological processes and pathways. This literature information was used to generate compound-specific keyword fingerprints, representing over-represented keywords calculated in a set of regulated genes after compound administration. To see whether keyword fingerprints can be used for assessment of compound toxicity, we analyzed microarray data sets of rat liver treated with 11 hepatotoxicants. Analysis of keyword fingerprints of two genotoxic carcinogens, two nongenotoxic carcinogens, two peroxisome proliferators and two randomly generated gene sets, showed that each compound produced a specific keyword fingerprint that correlated with the experimentally observed histopathological events induced by the individual compounds. By contrast, the random sets produced a flat aspecific keyword profile, indicating that the fingerprints induced by the compounds reflect biological events rather than random noise. A more detailed analysis of the keyword profiles of diethylhexylphthalate, dimethylnitrosamine and methapyrilene (MPy) showed that the differences in the keyword fingerprints of these three compounds are based upon known distinct modes of action. Visualization of MPy-linked keywords and MPy-induced genes in a literature network enabled us to construct a mode of toxicity proposal for MPy, which is in agreement with known effects of MPy in literature. Compound keyword fingerprinting based on information retrieved from literature is a powerful approach for compound profiling, allowing evaluation of compound toxicity and analysis of the mode of action.

Hygroscopicity of organic surrogate compounds from biomass burning and their effect on the efflorescence of ammonium sulfate in mixed aerosol particles

NASA Astrophysics Data System (ADS)

Lei, Ting; Zuend, Andreas; Cheng, Yafang; Su, Hang; Wang, Weigang; Ge, Maofa

2018-01-01

Hygroscopic growth factors of organic surrogate compounds representing biomass burning and mixed organic-inorganic aerosol particles exhibit variability during dehydration experiments depending on their chemical composition, which we observed using a hygroscopicity tandem differential mobility analyzer (HTDMA). We observed that levoglucosan and humic acid aerosol particles release water upon dehumidification in the range from 90 to 5 % relative humidity (RH). However, 4-Hydroxybenzoic acid aerosol particles remain in the solid state upon dehumidification and exhibit a small shrinking in size at higher RH compared to the dry size. For example, the measured growth factor of 4-hyroxybenzoic acid aerosol particles is ˜ 0.96 at 90 % RH. The measurements were accompanied by RH-dependent thermodynamic equilibrium calculations using the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model and Extended Aerosol Inorganics Model (E-AIM), the Zdanovskii-Stokes-Robinson (ZSR) relation, and a fitted hygroscopicity expression. We observed several effects of organic components on the hygroscopicity behavior of mixtures containing ammonium sulfate (AS) in relation to the different mass fractions of organic compounds: (1) a shift of efflorescence relative humidity (ERH) of ammonium sulfate to higher RH due to the presence of 25 wt % levoglucosan in the mixture. (2) There is a distinct efflorescence transition at 25 % RH for mixtures consisting of 25 wt % of 4-hydroxybenzoic acid compared to the ERH at 35 % for organic-free AS particles. (3) There is indication for a liquid-to-solid phase transition of 4-hydroxybenzoic acid in the mixed particles during dehydration. (4) A humic acid component shows no significant effect on the efflorescence of AS in mixed aerosol particles. In addition, consideration of a composition-dependent degree of dissolution of crystallization AS (solid-liquid equilibrium) in the AIOMFAC and E-AIM models leads to a relatively good agreement between models and observed growth factors, as well as ERH of AS in the mixed system. The use of the ZSR relation leads to good agreement with measured diameter growth factors of aerosol particles containing humic acid and ammonium sulfate. Lastly, two distinct mixtures of organic surrogate compounds, including levoglucosan, 4-hydroxybenzoic acid, and humic acid, were used to represent the average water-soluble organic carbon (WSOC) fractions observed during the wet and dry seasons in the central Amazon Basin. A comparison of the organic fraction's hygroscopicity parameter for the simple mixtures, e.g., κ ≈ 0.12 to 0.15 for the wet-season mixture in the 90 to 40 % RH range, shows good agreement with field data for the wet season in the Amazon Basin (WSOC κ ≈ 0.14±0.06 at 90 % RH). This suggests that laboratory-generated mixtures containing organic surrogate compounds and ammonium sulfate can be used to mimic, in a simplified manner, the chemical composition of ambient aerosols from the Amazon Basin for the purpose of RH-dependent hygroscopicity studies.

Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

PubMed

Lane, Thomas; Russo, Daniel P; Zorn, Kimberley M; Clark, Alex M; Korotcov, Alexandru; Tkachenko, Valery; Reynolds, Robert C; Perryman, Alexander L; Freundlich, Joel S; Ekins, Sean

2018-04-26

Tuberculosis is a global health dilemma. In 2016, the WHO reported 10.4 million incidences and 1.7 million deaths. The need to develop new treatments for those infected with Mycobacterium tuberculosis ( Mtb) has led to many large-scale phenotypic screens and many thousands of new active compounds identified in vitro. However, with limited funding, efforts to discover new active molecules against Mtb needs to be more efficient. Several computational machine learning approaches have been shown to have good enrichment and hit rates. We have curated small molecule Mtb data and developed new models with a total of 18,886 molecules with activity cutoffs of 10 μM, 1 μM, and 100 nM. These data sets were used to evaluate different machine learning methods (including deep learning) and metrics and to generate predictions for additional molecules published in 2017. One Mtb model, a combined in vitro and in vivo data Bayesian model at a 100 nM activity yielded the following metrics for 5-fold cross validation: accuracy = 0.88, precision = 0.22, recall = 0.91, specificity = 0.88, kappa = 0.31, and MCC = 0.41. We have also curated an evaluation set ( n = 153 compounds) published in 2017, and when used to test our model, it showed the comparable statistics (accuracy = 0.83, precision = 0.27, recall = 1.00, specificity = 0.81, kappa = 0.36, and MCC = 0.47). We have also compared these models with additional machine learning algorithms showing Bayesian machine learning models constructed with literature Mtb data generated by different laboratories generally were equivalent to or outperformed deep neural networks with external test sets. Finally, we have also compared our training and test sets to show they were suitably diverse and different in order to represent useful evaluation sets. Such Mtb machine learning models could help prioritize compounds for testing in vitro and in vivo.

Preliminary Evaluation of a Turbine/Rotary Combustion Compound Engine for a Subsonic Transport. [fuel consumption and engine tests of turbofan engines

NASA Technical Reports Server (NTRS)

Civinskas, K. C.; Kraft, G. A.

1976-01-01

The fuel consumption of a modern compound engine with that of an advanced high pressure ratio turbofan was compared. The compound engine was derived from a turbofan engine by replacing the combustor with a rotary combustion (RC) engine. A number of boost pressure ratios and compression ratios were examined. Cooling of the RC engine was accomplished by heat exchanging to the fan duct. Performance was estimated with an Otto-cycle for two levels of energy lost to cooling. The effects of added complexity on cost and maintainability were not examined and the comparison was solely in terms of cruise performance and weight. Assuming a 25 percent Otto-cycle cooling loss (representative of current experience), the best compound engine gave a 1.2 percent improvement in cruise. Engine weight increased by 23 percent. For a 10 percent Otto-cycle cooling loss (representing advanced insulation/high temperature materials technology), a compound engine with a boost PR of 10 and a compression ratio of 10 gave an 8.1 percent lower cruise than the reference turbofan.

Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014–2015)

PubMed Central

2016-01-01

The renewed urgency to develop new treatments for Mycobacterium tuberculosis (Mtb) infection has resulted in large-scale phenotypic screening and thousands of new active compounds in vitro. The next challenge is to identify candidates to pursue in a mouse in vivo efficacy model as a step to predicting clinical efficacy. We previously analyzed over 70 years of this mouse in vivo efficacy data, which we used to generate and validate machine learning models. Curation of 60 additional small molecules with in vivo data published in 2014 and 2015 was undertaken to further test these models. This represents a much larger test set than for the previous models. Several computational approaches have now been applied to analyze these molecules and compare their molecular properties beyond those attempted previously. Our previous machine learning models have been updated, and a novel aspect has been added in the form of mouse liver microsomal half-life (MLM t1/2) and in vitro-based Mtb models incorporating cytotoxicity data that were used to predict in vivo activity for comparison. Our best Mtbin vivo models possess fivefold ROC values > 0.7, sensitivity > 80%, and concordance > 60%, while the best specificity value is >40%. Use of an MLM t1/2 Bayesian model affords comparable results for scoring the 60 compounds tested. Combining MLM stability and in vitroMtb models in a novel consensus workflow in the best cases has a positive predicted value (hit rate) > 77%. Our results indicate that Bayesian models constructed with literature in vivoMtb data generated by different laboratories in various mouse models can have predictive value and may be used alongside MLM t1/2 and in vitro-based Mtb models to assist in selecting antitubercular compounds with desirable in vivo efficacy. We demonstrate for the first time that consensus models of any kind can be used to predict in vivo activity for Mtb. In addition, we describe a new clustering method for data visualization and apply this to the in vivo training and test data, ultimately making the method accessible in a mobile app. PMID:27335215

Hit Generation in TB Drug Discovery: From Genome to Granuloma

PubMed Central

2018-01-01

Current tuberculosis (TB) drug development efforts are not sufficient to end the global TB epidemic. Recent efforts have focused on the development of whole-cell screening assays because biochemical, target-based inhibitor screens during the last two decades have not delivered new TB drugs. Mycobacterium tuberculosis (Mtb), the causative agent of TB, encounters diverse microenvironments and can be found in a variety of metabolic states in the human host. Due to the complexity and heterogeneity of Mtb infection, no single model can fully recapitulate the in vivo conditions in which Mtb is found in TB patients, and there is no single “standard” screening condition to generate hit compounds for TB drug development. However, current screening assays have become more sophisticated as researchers attempt to mirror the complexity of TB disease in the laboratory. In this review, we describe efforts using surrogates and engineered strains of Mtb to focus screens on specific targets. We explain model culture systems ranging from carbon starvation to hypoxia, and combinations thereof, designed to represent the microenvironment which Mtb encounters in the human body. We outline ongoing efforts to model Mtb infection in the lung granuloma. We assess these different models, their ability to generate hit compounds, and needs for further TB drug development, to provide direction for future TB drug discovery. PMID:29384369

Functional Coupling of Human Microphysiology Systems: Intestine, Liver, Kidney Proximal Tubule, Blood-Brain Barrier and Skeletal Muscle

PubMed Central

Vernetti, Lawrence; Gough, Albert; Baetz, Nicholas; Blutt, Sarah; Broughman, James R.; Brown, Jacquelyn A.; Foulke-Abel, Jennifer; Hasan, Nesrin; In, Julie; Kelly, Edward; Kovbasnjuk, Olga; Repper, Jonathan; Senutovitch, Nina; Stabb, Janet; Yeung, Catherine; Zachos, Nick C.; Donowitz, Mark; Estes, Mary; Himmelfarb, Jonathan; Truskey, George; Wikswo, John P.; Taylor, D. Lansing

2017-01-01

Organ interactions resulting from drug, metabolite or xenobiotic transport between organs are key components of human metabolism that impact therapeutic action and toxic side effects. Preclinical animal testing often fails to predict adverse outcomes arising from sequential, multi-organ metabolism of drugs and xenobiotics. Human microphysiological systems (MPS) can model these interactions and are predicted to dramatically improve the efficiency of the drug development process. In this study, five human MPS models were evaluated for functional coupling, defined as the determination of organ interactions via an in vivo-like sequential, organ-to-organ transfer of media. MPS models representing the major absorption, metabolism and clearance organs (the jejunum, liver and kidney) were evaluated, along with skeletal muscle and neurovascular models. Three compounds were evaluated for organ-specific processing: terfenadine for pharmacokinetics (PK) and toxicity; trimethylamine (TMA) as a potentially toxic microbiome metabolite; and vitamin D3. We show that the organ-specific processing of these compounds was consistent with clinical data, and discovered that trimethylamine-N-oxide (TMAO) crosses the blood-brain barrier. These studies demonstrate the potential of human MPS for multi-organ toxicity and absorption, distribution, metabolism and excretion (ADME), provide guidance for physically coupling MPS, and offer an approach to coupling MPS with distinct media and perfusion requirements. PMID:28176881

Cinnamoyl compounds as simple molecules that inhibit p300 histone acetyltransferase.

PubMed

Costi, Roberta; Di Santo, Roberto; Artico, Marino; Miele, Gaetano; Valentini, Paola; Novellino, Ettore; Cereseto, Anna

2007-04-19

Cinnamoly compounds 1a-c and 2a-d were designed, synthesized, and in vitro tested as p300 inhibitors. At different degrees, all tested compounds were proven to inactivate p300, particularly, derivative 2c was the most active inhibitor, also showing high specificity for p300 as compared to other histone acetyltransferases. Most notably, 2c showed anti-acetylase activity in mammalian cells. These compounds represent a new class of synthetic inhibitors of p300, characterized by simple chemical structures.

Compound curvature laser window development

NASA Technical Reports Server (NTRS)

Verhoff, Vincent G.

1993-01-01

The NASA Lewis Research Center has developed and implemented a unique process for forming flawless compound curvature laser windows. These windows represent a major part of specialized, nonintrusive laser data acquisition systems used in a variety of compressor and turbine research test facilities. This report summarizes the main aspects of compound curvature laser window development. It is an overview of the methodology and the peculiarities associated with the formulation of these windows. Included in this discussion is new information regarding procedures for compound curvature laser window development.

Basics of Compounding: 3D Printing: Pharmacy Applications, Part 3: Compounding, Formulation Considerations, and the Future.

PubMed

Allen, Loyd V

2017-01-01

3D printing is a standard tool in the automotive, aerospace, and consumer goods in industry and is gaining traction in pharmaceutical manufacturing, which has introduced a new element into dosage form development. This article, which represents part 3 of a 3-part article on the topic of 3D printing, discusses the compounding, formulation considerations, and the future of 3D printing. Copyright© by International Journal of Pharmaceutical Compounding, Inc.

Design and Structure-Guided Development of Novel Inhibitors of the Xeroderma Pigmentosum Group A (XPA) Protein-DNA Interaction.

PubMed

Gavande, Navnath S; VanderVere-Carozza, Pamela; Mishra, Akaash K; Vernon, Tyler L; Pawelczak, Katherine S; Turchi, John J

2017-10-12

XPA is a unique and essential protein required for the nucleotide excision DNA repair pathway and represents a therapeutic target in oncology. Herein, we are the first to develop novel inhibitors of the XPA-DNA interaction through structure-guided drug design efforts. Ester derivatives of the compounds 1 (X80), 22, and 24 displayed excellent inhibitory activity (IC 50 of 0.82 ± 0.18 μM and 1.3 ± 0.22 μM, respectively) but poor solubility. We have synthesized novel amide derivatives that retain potency and have much improved solubility. Furthermore, compound 1 analogs exhibited good specificity for XPA over RPA (replication protein A), another DNA-binding protein that participates in the nucleotide excision repair (NER) pathway. Importantly, there were no significant interactions observed by the X80 class of compounds directly with DNA. Molecular docking studies revealed a mechanistic model for the interaction, and these studies could serve as the basis for continued analysis of structure-activity relationships and drug development efforts of this novel target.

Using semipermeable membrane devices (SPMDs) to estimate bioconcentration potential of petroleum additives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crecelius, E.A.; Rausina, G.A.; Biggs, W.R.

1995-12-31

Lubricant additives can be released into the environment during transport, usage, or improper disposal. Therefore, it is necessary to evaluate these substances for their potential to cause adverse environmental effects. Because lubricant additives tend to be large molecular size hydrophobic substances with very limited water solubility, they could possibly bioconcentrate if released into the environment. A test was developed using SPMD technology to assess the bioconcentration potential of lubricant additives. SPMDs are low-density polyethylene tubing with an effective pore size of 600 daltons, similar to that of cellular membranes. SPMDs filled with triolein, the predominant lipid in fish, function asmore » model fish or mollusks, with selective membranes and lipid reservoirs to concentrate organic compounds from water. Using the SPMD test system, bioconcentration factors were determined for a poly alpha olefin (PAO) base stock and lubricant additive compounds that represent three additive use categories. The SPMD test system was validated using a radiocarbon-labeled calcium detergent lubricant additive in side-by-side exposures to SPMDs and aquatic organisms. Radiocarbon-labeled pyrene was used as a reference compound in the tests.« less

A compound chimeric antigen receptor strategy for targeting multiple myeloma.

PubMed

Chen, K H; Wada, M; Pinz, K G; Liu, H; Shuai, X; Chen, X; Yan, L E; Petrov, J C; Salman, H; Senzel, L; Leung, E L H; Jiang, X; Ma, Y

2018-02-01

Current clinical outcomes using chimeric-antigen receptors (CARs) against multiple myeloma show promise in the eradication of bulk disease. However, these anti-BCMA (CD269) CARs observe relapse as a common phenomenon after treatment due to the reemergence of either antigen-positive or -negative cells. Hence, the development of improvements in CAR design to target antigen loss and increase effector cell persistency represents a critical need. Here, we report on the anti-tumor activity of a CAR T-cell possessing two complete and independent CAR receptors against the multiple myeloma antigens BCMA and CS1. We determined that the resulting compound CAR (cCAR) T-cell possesses consistent, potent and directed cytotoxicity against each target antigen population. Using multiple mouse models of myeloma and mixed cell populations, we are further able to show superior in vivo survival by directed cytotoxicity against multiple populations compared to a single-expressing CAR T-cell. These findings indicate that compound targeting of BCMA and CS1 on myeloma cells can potentially be an effective strategy for augmenting the response against myeloma bulk disease and for initiation of broader coverage CAR therapy.

Development of Candidates for Positron Emission Tomography (PET) Imaging of Ghrelin Receptor in Disease: Design, Synthesis, and Evaluation of Fluorine-Bearing Quinazolinone Derivatives.

PubMed

Hou, Jinqiang; Kovacs, Michael S; Dhanvantari, Savita; Luyt, Leonard G

2018-02-08

Molecular imaging with positron emission tomography (PET) is an attractive platform for noninvasive detection and assessment of disease. The development of a PET imaging agent targeting the ghrelin receptor (growth hormone secretagogue receptor type 1a or GHS-R1a) has the potential to lead to the detection and assessment of the higher than normal expression of GHS-R1a in diseases such as prostate, breast, and ovarian cancer. To enable the development of 18 F radiopharmaceuticals, we have designed and synthesized three series of quinazolinone derivatives, resulting in the identification of two compound (5i, 17) with subnanomolar binding affinity and one fluorine-bearing compound (10b) with picomolar binding affinity (20 pM), representing the highest binding affinity for GHS-R1a reported to date. Two lead compounds (5b, IC 50 = 20.6 nM; 5e, IC 50 = 9.3 nM) were successfully 18 F-radiolabeled with radiochemical purity of greater than 99%. Molecular modeling studies were performed to shed light on ligand-receptor interactions.

Discovery of SMP-304, a novel benzylpiperidine derivative with serotonin transporter inhibitory activity and 5-HT1A weak partial agonistic activity showing the antidepressant-like effect.

PubMed

Yoshinaga, Hidefumi; Masumoto, Shuji; Koyama, Koji; Kinomura, Naoya; Matsumoto, Yuji; Kato, Taro; Baba, Satoko; Matsumoto, Kenji; Horisawa, Tomoko; Oki, Hitomi; Yabuuchi, Kazuki; Kodo, Toru

2017-01-01

We report the discovery of a novel benzylpiperidine derivative with serotonin transporter (SERT) inhibitory activity and 5-HT 1A receptor weak partial agonistic activity showing the antidepressant-like effect. The 3-methoxyphenyl group and the phenethyl group of compound 1, which has weak SERT binding activity, but potent 5-HT 1A binding activity, were optimized, leading to compound 35 with potent and balanced dual SERT and 5-HT 1A binding activity, but also potent CYP2D6 inhibitory activity. Replacement of the methoxy group in the left part of compound 35 with a larger alkoxy group, such as ethoxy, isopropoxy or methoxy-ethoxy group ameliorated CYP2D6 inhibition, giving SMP-304 as a candidate. SMP-304 with serotonin uptake inhibitory activity and 5-HT 1A weak partial agonistic activity, which could work as a 5-HT 1A antagonist, displayed faster onset of antidepressant-like effect than a representative SSRI paroxetine in an animal model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimation of the lower flammability limit of organic compounds as a function of temperature.

PubMed

Rowley, J R; Rowley, R L; Wilding, W V

2011-02-15

A new method of estimating the lower flammability limit (LFL) of general organic compounds is presented. The LFL is predicted at 298 K for gases and the lower temperature limit for solids and liquids from structural contributions and the ideal gas heat of formation of the fuel. The average absolute deviation from more than 500 experimental data points is 10.7%. In a previous study, the widely used modified Burgess-Wheeler law was shown to underestimate the effect of temperature on the lower flammability limit when determined in a large-diameter vessel. An improved version of the modified Burgess-Wheeler law is presented that represents the temperature dependence of LFL data determined in large-diameter vessels more accurately. When the LFL is estimated at increased temperatures using a combination of this model and the proposed structural-contribution method, an average absolute deviation of 3.3% is returned when compared with 65 data points for 17 organic compounds determined in an ASHRAE-style apparatus. Copyright © 2010 Elsevier B.V. All rights reserved.

Urea Derivatives of 2-Aryl-benzothiazol-5-amines: A New Class of Potential Drugs for Human African Trypanosomiasis.

PubMed

Patrick, Donald A; Gillespie, J Robert; McQueen, Joshua; Hulverson, Matthew A; Ranade, Ranae M; Creason, Sharon A; Herbst, Zackary M; Gelb, Michael H; Buckner, Frederick S; Tidwell, Richard R

2017-02-09

A previous publication from this lab (Patrick, et al. Bioorg. Med. Chem. 2016, 24 , 2451 - 2465 ) explored the antitrypanosomal activities of novel derivatives of 2-(2-benzamido)ethyl-4-phenylthiazole (1), which had been identified as a hit against Trypanosoma brucei, the causative agent of human African trypanosomiasis. While a number of these compounds, particularly the urea analogues, were quite potent, these molecules as a whole exhibited poor metabolic stability. The present work describes the synthesis of 65 new analogues arising from medicinal chemistry optimization at different sites on the molecule. The most promising compounds were the urea derivatives of 2-aryl-benzothiazol-5-amines. One such analogue, (S)-2-(3,4-difluorophenyl)-5-(3-fluoro-N-pyrrolidylamido)benzothiazole (57) was chosen for in vivo efficacy studies based upon in vitro activity, metabolic stability, and brain penetration. This compound attained 5/5 cures in murine models of both early and late stage human African trypanosomiasis, representing a new lead for the development of drugs to combat this neglected disease.

Cytochrome P450 humanised mice

PubMed Central

2004-01-01

Humans are exposed to countless foreign compounds, typically referred to as xenobiotics. These can include clinically used drugs, environmental pollutants, food additives, pesticides, herbicides and even natural plant compounds. Xenobiotics are metabolised primarily in the liver, but also in the gut and other organs, to derivatives that are more easily eliminated from the body. In some cases, however, a compound is converted to an electrophile that can cause cell toxicity and transformation leading to cancer. Among the most important xenobiotic-metabolising enzymes are the cytochromes P450 (P450s). These enzymes represent a superfamily of multiple forms that exhibit marked species differences in their expression and catalytic activities. To predict how humans will metabolise xenobiotics, including drugs, human liver extracts and recombinant P450s have been used. New humanised mouse models are being developed which will be of great value in the study of drug metabolism, pharmacokinetics and pharmacodynamics in vivo, and in carrying out human risk assessment of xenobiotics. Humanised mice expressing CYP2D6 and CYP3A4, two major drug-metabolising P450s, have revealed the feasibility of this approach. PMID:15588489

The BioGRID interaction database: 2017 update

PubMed Central

Chatr-aryamontri, Andrew; Oughtred, Rose; Boucher, Lorrie; Rust, Jennifer; Chang, Christie; Kolas, Nadine K.; O'Donnell, Lara; Oster, Sara; Theesfeld, Chandra; Sellam, Adnane; Stark, Chris; Breitkreutz, Bobby-Joe; Dolinski, Kara; Tyers, Mike

2017-01-01

The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases. PMID:27980099

Novel analogues of chlormethiazole are neuroprotective in four cellular models of neurodegeneration by a mechanism with variable dependence on GABAA receptor potentiation

PubMed Central

VandeVrede, Lawren; Tavassoli, Ehsan; Luo, Jia; Qin, Zhihui; Yue, Lan; Pepperberg, David R; Thatcher, Gregory R

2014-01-01

Background and Purpose: Chlormethiazole (CMZ), a clinical sedative/anxiolytic agent, did not reach clinical efficacy in stroke trials despite neuroprotection demonstrated in numerous animal models. Using CMZ as a lead compound, neuroprotective methiazole (MZ) analogues were developed, and neuroprotection and GABAA receptor dependence were studied. Experimental Approach: Eight MZs were selected from a novel library, of which two were studied in detail. Neuroprotection, glutamate release, intracellular calcium and response to GABA blockade by picrotoxin were measured in rat primary cortical cultures using four cellular models of neurodegeneration. GABA potentiation was assayed in oocytes expressing the α1β2γ2 GABAA receptor. Key Results: Neuroprotection against a range of insults was retained even with substantial chemical modification. Dependence on GABAA receptor activity was variable: at the extremes, neuroprotection by GN-28 was universally sensitive to picrotoxin, while GN-38 was largely insensitive. In parallel, effects on extracellular glutamate and intracellular calcium were associated with GABAA dependence. Consistent with these findings, GN-28 potentiated α1β2γ2 GABAA function, whereas GN-38 had a weak inhibitory effect. Neuroprotection against moderate dose oligomeric Aβ1–42 was also tolerant to structural changes. Conclusions and Implications: The results support the concept that CMZ does not contain a single pharmacophore, rather that broad-spectrum neuroprotection results from a GABAA-dependent mechanism represented by GN-28, combined with a mechanism represented in GN-38 that shows the least dependence on GABAA receptors. These findings allow further refinement of the neuroprotective pharmacophore and investigation into secondary mechanisms that will assist in identifying MZ-based compounds of use in treating neurodegeneration. PMID:24116891

A multi-scale ensemble-based framework for forecasting compound coastal-riverine flooding: The Hackensack-Passaic watershed and Newark Bay

NASA Astrophysics Data System (ADS)

Saleh, F.; Ramaswamy, V.; Wang, Y.; Georgas, N.; Blumberg, A.; Pullen, J.

2017-12-01

Estuarine regions can experience compound impacts from coastal storm surge and riverine flooding. The challenges in forecasting flooding in such areas are multi-faceted due to uncertainties associated with meteorological drivers and interactions between hydrological and coastal processes. The objective of this work is to evaluate how uncertainties from meteorological predictions propagate through an ensemble-based flood prediction framework and translate into uncertainties in simulated inundation extents. A multi-scale framework, consisting of hydrologic, coastal and hydrodynamic models, was used to simulate two extreme flood events at the confluence of the Passaic and Hackensack rivers and Newark Bay. The events were Hurricane Irene (2011), a combination of inland flooding and coastal storm surge, and Hurricane Sandy (2012) where coastal storm surge was the dominant component. The hydrodynamic component of the framework was first forced with measured streamflow and ocean water level data to establish baseline inundation extents with the best available forcing data. The coastal and hydrologic models were then forced with meteorological predictions from 21 ensemble members of the Global Ensemble Forecast System (GEFS) to retrospectively represent potential future conditions up to 96 hours prior to the events. Inundation extents produced by the hydrodynamic model, forced with the 95th percentile of the ensemble-based coastal and hydrologic boundary conditions, were in good agreement with baseline conditions for both events. The USGS reanalysis of Hurricane Sandy inundation extents was encapsulated between the 50th and 95th percentile of the forecasted inundation extents, and that of Hurricane Irene was similar but with caveats associated with data availability and reliability. This work highlights the importance of accounting for meteorological uncertainty to represent a range of possible future inundation extents at high resolution (∼m).

Inhibitors of type II NADH:menaquinone oxidoreductase represent a class of antitubercular drugs

PubMed Central

Weinstein, Edward A.; Yano, Takahiro; Li, Lin-Sheng; Avarbock, David; Avarbock, Andrew; Helm, Douglas; McColm, Andrew A.; Duncan, Ken; Lonsdale, John T.; Rubin, Harvey

2005-01-01

Mycobacterium tuberculosis (Mtb) is an obligate aerobe that is capable of long-term persistence under conditions of low oxygen tension. Analysis of the Mtb genome predicts the existence of a branched aerobic respiratory chain terminating in a cytochrome bd system and a cytochrome aa3 system. Both chains can be initiated with type II NADH:menaquinone oxidoreductase. We present a detailed biochemical characterization of the aerobic respiratory chains from Mtb and show that phenothiazine analogs specifically inhibit NADH:menaquinone oxidoreductase activity. The emergence of drug-resistant strains of Mtb has prompted a search for antimycobacterial agents. Several phenothiazines analogs are highly tuberculocidal in vitro, suppress Mtb growth in a mouse model of acute infection, and represent lead compounds that may give rise to a class of selective antibiotics. PMID:15767566

Chemosystematics in the Opiliones (Arachnida): a comment on the evolutionary history of alkylphenols and benzoquinones in the scent gland secretions of Laniatores

PubMed Central

Raspotnig, Günther; Bodner, Michaela; Schäffer, Sylvia; Koblmüller, Stephan; Schönhofer, Axel; Karaman, Ivo

2015-01-01

Large prosomal scent glands constitute a major synapomorphic character of the arachnid order Opiliones. These glands produce a variety of chemicals very specific to opilionid taxa of different taxonomic levels, and thus represent a model system to investigate the evolutionary traits in exocrine secretion chemistry across a phylogenetically old group of animals. The chemically best-studied opilionid group is certainly Laniatores, and currently available chemical data allow first hypotheses linking the phylogeny of this group to the evolution of major chemical classes of secretion chemistry. Such hypotheses are essential to decide upon a best-fitting explanation of the distribution of scent-gland secretion compounds across extant laniatorean taxa, and hence represent a key toward a well-founded opilionid chemosystematics. PMID:26074662

Chemosystematics in the Opiliones (Arachnida): a comment on the evolutionary history of alkylphenols and benzoquinones in the scent gland secretions of Laniatores.

PubMed

Raspotnig, Günther; Bodner, Michaela; Schäffer, Sylvia; Koblmüller, Stephan; Schönhofer, Axel; Karaman, Ivo

2015-04-01

Large prosomal scent glands constitute a major synapomorphic character of the arachnid order Opiliones. These glands produce a variety of chemicals very specific to opilionid taxa of different taxonomic levels, and thus represent a model system to investigate the evolutionary traits in exocrine secretion chemistry across a phylogenetically old group of animals. The chemically best-studied opilionid group is certainly Laniatores, and currently available chemical data allow first hypotheses linking the phylogeny of this group to the evolution of major chemical classes of secretion chemistry. Such hypotheses are essential to decide upon a best-fitting explanation of the distribution of scent-gland secretion compounds across extant laniatorean taxa, and hence represent a key toward a well-founded opilionid chemosystematics.

Small Molecule Suppressors of Drosophila Kinesin Deficiency Rescue Motor Axon Development in a Zebrafish Model of Spinal Muscular Atrophy

PubMed Central

Gassman, Andrew; Hao, Le T.; Bhoite, Leena; Bradford, Chad L.; Chien, Chi-Bin; Beattie, Christine E.; Manfredi, John P.

2013-01-01

Proximal spinal muscular atrophy (SMA) is the most common inherited motor neuropathy and the leading hereditary cause of infant mortality. Currently there is no effective treatment for the disease, reflecting a need for pharmacologic interventions that restore performance of dysfunctional motor neurons or suppress the consequences of their dysfunction. In a series of assays relevant to motor neuron biology, we explored the activities of a collection of tetrahydroindoles that were reported to alter the metabolism of amyloid precursor protein (APP). In Drosophila larvae the compounds suppressed aberrant larval locomotion due to mutations in the Khc and Klc genes, which respectively encode the heavy and light chains of kinesin-1. A representative compound of this class also suppressed the appearance of axonal swellings (alternatively termed axonal spheroids or neuritic beads) in the segmental nerves of the kinesin-deficient Drosophila larvae. Given the importance of kinesin-dependent transport for extension and maintenance of axons and their growth cones, three members of the class were tested for neurotrophic effects on isolated rat spinal motor neurons. Each compound stimulated neurite outgrowth. In addition, consistent with SMA being an axonopathy of motor neurons, the three axonotrophic compounds rescued motor axon development in a zebrafish model of SMA. The results introduce a collection of small molecules as pharmacologic suppressors of SMA-associated phenotypes and nominate specific members of the collection for development as candidate SMA therapeutics. More generally, the results reinforce the perception of SMA as an axonopathy and suggest novel approaches to treating the disease. PMID:24023935

Co-culturing of Fungal Strains Against Botrytis cinerea as a Model for the Induction of Chemical Diversity and Therapeutic Agents

PubMed Central

Serrano, Rachel; González-Menéndez, Víctor; Rodríguez, Lorena; Martín, Jesús; Tormo, José R.; Genilloud, Olga

2017-01-01

New fungal SMs (SMs) have been successfully described to be produced by means of in vitro-simulated microbial community interactions. Co-culturing of fungi has proved to be an efficient way to induce cell–cell interactions that can promote the activation of cryptic pathways, frequently silent when the strains are grown in laboratory conditions. Filamentous fungi represent one of the most diverse microbial groups known to produce bioactive natural products. Triggering the production of novel antifungal compounds in fungi could respond to the current needs to fight health compromising pathogens and provide new therapeutic solutions. In this study, we have selected the fungus Botrytis cinerea as a model to establish microbial interactions with a large set of fungal strains related to ecosystems where they can coexist with this phytopathogen, and to generate a collection of extracts, obtained from their antagonic microbial interactions and potentially containing new bioactive compounds. The antifungal specificity of the extracts containing compounds induced after B. cinerea interaction was determined against two human fungal pathogens (Candida albicans and Aspergillus fumigatus) and three phytopathogens (Colletotrichum acutatum, Fusarium proliferatum, and Magnaporthe grisea). In addition, their cytotoxicity was also evaluated against the human hepatocellular carcinoma cell line (HepG2). We have identified by LC-MS the production of a wide variety of known compounds induced from these fungal interactions, as well as novel molecules that support the potential of this approach to generate new chemical diversity and possible new therapeutic agents. PMID:28469610

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Development and evaluation of a semi-empirical two-zone dust exposure model for a dusty construction trade.

PubMed

Jones, Rachael M; Simmons, Catherine; Boelter, Fred

2011-06-01

Drywall finishing is a dusty construction activity. We describe a mathematical model that predicts the time-weighted average concentration of respirable and total dusts in the personal breathing zone of the sander, and in the area surrounding joint compound sanding activities. The model represents spatial variation in dust concentrations using two-zones, and temporal variation using an exponential function. Interzone flux and the relationships between respirable and total dusts are described using empirical factors. For model evaluation, we measured dust concentrations in two field studies, including three workers from a commercial contracting crew, and one unskilled worker. Data from the field studies confirm that the model assumptions and parameterization are reasonable and thus validate the modeling approach. Predicted dust C(twa) were in concordance with measured values for the contracting crew, but under estimated measured values for the unskilled worker. Further characterization of skill-related exposure factors is indicated.

Complex compound polyvinyl alcohol-titanic acid/titanium dioxide

NASA Astrophysics Data System (ADS)

Prosanov, I. Yu.

2013-02-01

A complex compound polyvinyl alcohol-titanic acid has been produced and investigated by means of IR and Raman spectroscopy, X-ray diffraction, and synchronous thermal analysis. It is claimed that it represents an interpolymeric complex of polyvinyl alcohol and hydrated titanium oxide.

Unit Price Scaling Trends for Chemical Products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qi, Wei; Sathre, Roger; William R. Morrow, III

2015-08-01

To facilitate early-stage life-cycle techno-economic modeling of emerging technologies, here we identify scaling relations between unit price and sales quantity for a variety of chemical products of three categories - metal salts, organic compounds, and solvents. We collect price quotations for lab-scale and bulk purchases of chemicals from both U.S. and Chinese suppliers. We apply a log-log linear regression model to estimate the price discount effect. Using the median discount factor of each category, one can infer bulk prices of products for which only lab-scale prices are available. We conduct out-of-sample tests showing that most of the price proxies deviatemore » from their actual reference prices by a factor less than ten. We also apply the bootstrap method to determine if a sample median discount factor should be accepted for price approximation. We find that appropriate discount factors for metal salts and for solvents are both -0.56, while that for organic compounds is -0.67 and is less representative due to greater extent of product heterogeneity within this category.« less

Altered neuronal network and rescue in a human MECP2 duplication model

PubMed Central

Nageshappa, Savitha; Carromeu, Cassiano; Trujillo, Cleber A.; Mesci, Pinar; Espuny-Camacho, Ira; Pasciuto, Emanuela; Vanderhaeghen, Pierre; Verfaillie, Catherine; Raitano, Susanna; Kumar, Anujith; Carvalho, Claudia M.B.; Bagni, Claudia; Ramocki, Melissa B.; Araujo, Bruno H. S.; Torres, Laila B.; Lupski, James R.; Van Esch, Hilde; Muotri, Alysson R.

2015-01-01

Increased dosage of MeCP2 results in a dramatic neurodevelopmental phenotype with onset at birth. We generated induced pluripotent stem cells (iPSC) from patients with the MECP2 duplication syndrome (MECP2dup), carrying different duplication sizes, to study the impact of increased MeCP2 dosage in human neurons. We show that cortical neurons derived from these different MECP2dup iPSC lines have increase synaptogenesis and dendritic complexity. Additionally, using multi-electrodes arrays, we show that neuronal network synchronization was altered in MECP2dup-derived neurons. Given MeCP2 function at the epigenetic level, we tested if these alterations were reversible using a library of compounds with defined activity on epigenetic pathways. One histone deacetylase inhibitor, NCH-51, was validated as a potential clinical candidate. Interestingly, this compound has never been considered before as a therapeutic alternative for neurological disorders. Our model recapitulates early stages of the human MECP2 duplication syndrome and represents a promising cellular tool to facilitate therapeutic drug screening for severe neurodevelopmental disorders. PMID:26347316

Free Radical Chemistry of Disinfection Byproducts. 3. Degradation Mechanisms of Chloronitromethane, Bromonitromethane and Dichloronitromethane

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruce J. Mincher; Stephen P. Mezyk; William J. Cooper

2010-01-01

Halonitromethanes (HNMs) are byproducts formed through ozonation and chlorine/ chloramine disinfection processes in drinking waters that contain dissolved organic matter and bromide ions. These species occur at low concentration, but have been determined to have high cytotoxicity and mutagenicity and therefore may represent a human health hazard. In this study, we have investigated the chemistry involved in the mineralization of HNMs to non-hazardous inorganic products through the application of advanced oxidation and reduction processes. We have combined measured absolute reaction rate constants for the reactions of chloronitromethane, bromonitromethane and dichloronitromethane with the hydroxyl radical and the hydrated electron with amore » kinetic computer model in an attempt to elucidate the reaction pathways of these HNMs. The results are compared to measurements of stable products resulting from steady-state 60Co y-irradiations of the same compounds. The model predicted the decomposition of the parent compounds and ingrowth of chloride and bromide ions with excellent accuracy, but the prediction of the total nitrate ion concentration was slightly in error, reflecting the complexity of nitrogen oxide species reactions in irradiated solution.« less

Compound-Specific Radiocarbon Dating Reveals the Age Distribution of Plant-Wax Biomarkers Exported to the Bengal Fan

NASA Astrophysics Data System (ADS)

Galy, V.; French, K. L.; Hein, C. J.; Haghipour, N.; Wacker, L.; Kudrass, H.; Eglinton, T. I.

2017-12-01

The stable isotope composition of leaf-wax compounds preserved in lacustrine and marine sediments has been widely used to reconstruct terrestrial paleo-environments. However, the timescales of plant-wax storage in continental reservoirs before riverine export are not well known, representing a key uncertainty in paleo-environment studies. We couple numerical models with bulk and leaf-wax fatty acid organic 13C and 14C signatures hosted in a high-deposition-rate sediment core from the Bengal shelf canyon in order to estimate storage timescales within the Ganges-Brahmaputra catchment area. The fatty acid 14C record reveals a muted nuclear weapons bomb spike, requiring that the Ganges-Brahmaputra river system exports a mixture of young and old (pre-aged) leaf-wax compounds. According to numerical simulations, 79-83% of the leaf-wax fatty acids in this core are sourced from continental reservoirs that store organic carbon on an average of 1000-1200 calendar years, while the remainder has an average age of 15 years. These results demonstrate that a majority of the leaf-wax compounds produced in the Ganges-Brahmaputra river basin was stored in soils, floodplains, and wetlands prior to its export to the Bengal Fan. We will discuss the implications of these findings for plant-wax based paleoenvironmental records.

Design and synthesis of L- and D-phenylalanine derived rhodanines with novel C5-arylidenes as inhibitors of HCV NS5B polymerase.

PubMed

Patel, Bhargav A; Krishnan, Ramalingam; Khadtare, Nikhil; Gurukumar, K R; Basu, Amartya; Arora, Payal; Bhatt, Aaditya; Patel, Maulik R; Dana, Dibyendu; Kumar, Sanjai; Kaushik-Basu, Neerja; Talele, Tanaji T

2013-06-01

Hepatitis C virus (HCV) NS5B polymerase is a key target for anti-HCV therapeutics development. Herein, we report the synthesis and in vitro evaluation of anti-NS5B polymerase activity of a molecular hybrid of our previously reported lead compounds 1 (IC50=7.7 μM) and 2 (IC50=10.6 μM) as represented by hybrid compound 27 (IC50=6.7 μM). We have explored the optimal substituents on the terminal phenyl ring of the 3-phenoxybenzylidene moiety in 27, by generating a set of six analogs. This resulted in the identification of compound 34 with an IC50 of 2.6 μM. To probe the role of stereochemistry towards the observed biological activity, we synthesized and evaluated the D-isomers 41 (IC50=19.3 μM) and 45 (IC50=5.4 μM) as enantiomers of the l-isomers 27 and 34, respectively. The binding site of compounds 32 and 34 was mapped to palm pocket-I (PP-I) of NS5B. The docking models of 34 and 45 within the PP-I of NS5B were investigated to envisage the molecular mechanism of inhibition. Copyright © 2013 Elsevier Ltd. All rights reserved.

Design and synthesis of L- and D-phenylalanine derived rhodanines with novel C5-arylidenes as inhibitors of HCV NS5B polymerase

PubMed Central

Patel, Bhargav; Krishnan, Ramalingam; Khadtare, Nikhil; Gurukumar, K. R.; Basu, Amartya; Arora, Payal; Bhatt, Aaditya; Patel, Maulik R.; Dana, Dibyendu; Kumar, Sanjai; Kaushik-Basu, Neerja; Talele, Tanaji T.

2013-01-01

Hepatitis C virus (HCV) NS5B polymerase is a key target for anti-HCV therapeutics development. Herein, we report the synthesis and in vitro evaluation of anti-NS5B polymerase activity of a molecular hybrid of our previously reported lead compounds 1 (IC50 = 7.7 µM) and 2 (IC50 = 10.6 µM) as represented by hybrid compound 27 (IC50 = 6.7 µM). We have explored the optimal substituents on the terminal phenyl ring of the 3-phenoxybenzylidene moiety in 27, by generating a set of six analogs. This resulted in the identification of compound 34 with an IC50 of 2.6 µM. To probe the role of stereochemistry towards the observed biological activity, we synthesized and evaluated the D-isomers 41 (IC50 = 19.3 µM) and 45 (IC50 = 5.4 µM) as enantiomers of the L-isomers 27 and 34, respectively. The binding site of compounds 32 and 34 was mapped to palm pocket-I (PP-I) of NS5B. The docking models of 34 and 45 within the PP-I of NS5B were investigated to envisage the molecular mechanism of inhibition. PMID:23598249

Determination of biodegradability kinetics of RCRA compounds using respirometry for structure-activity relationships

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tabak, H.H.; Desai, S.; Govind, R.

1990-01-01

Electrolytic respirometry is attaining prominence in biodegradation studies and is becoming one of the more suitable experimental methods for measuring the biodegradability and the kinetics of biodegradation of toxic organic compounds by the sewage, sludge, and soil microbiota and for determining substrate inhibitory effects to microorganisms in wastewater treatment systems. The purpose of the study was to obtain information on biological treatability of the benzene, phenol, phthalate, ketone organics and of the Superfund CERCLA organics bearing wastes in wastewater treatment systems which will support the development of an EPA technical guidance document on the discharge of the above organics tomore » POTWs. The paper discusses the experimental design and procedural steps for the respirometric biodegradation and toxicity testing approach for individual organics or specific industrial wastes at different concentration levels in a mineral salts medium. A developed multi-level protocol is presented for determination of the biodegradability, microbial acclimation to toxic substrates and first order kinetic parameters of biodegradation for estimation of the Monod kinetic parameter of toxic organic compounds, in order to correlate the extent and rate of biodegradation with a predictive model based on chemical properties and molecular structure of these compounds. Respirometric biodegradation/inhibition and biokinetic data are provided for representative RCRA alkyl benzene and ketone organics.« less

Ionic electrodeposition of II-VI and III-V compounds. III. Computer simulation of quasi-rest potentials for M/sub 1/X/sub 1/ compounds analogous to CdTe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engelken, R.D.

1987-04-01

The quasi-rest potential (QRP) has been proposed as a key quantity in characterizing compound semiconductor (e.g. CdTe) electrodeposition. This article expands the modeling/simulation representative of Cd/sub x/Te in chemical equilibrium to calculate two ''QRP's'': E/sub M/1/sub /, the mixed potential occurring immediately after current interruption and before any relaxation in double layer ion concentration and significant ion exchange/surface stoichiometry change occur, and E/sub M/2/sub /, another mixed potential occurring after the double layer ion concentrations have relaxed to their bulk values but still before any significant surface composition change occurs. Significant predictions include existence of a dramatic negative transition inmore » QRP, with negative-going deposition potential, centered on the potential of perfect stoichiometry (PPS), inequality, in general, between the PPS and E/sub M/1/sub / unless the deposit remains in equilibrium with the electrolyte (no ion exchange at open circuit), negligible sensitivity of QRP-E curves to the activity coefficient parameter implying the importance of the PPS in characterizing compound deposition, and disappearance of the transition structure for sufficiently positive Gibbs free energies.« less

The surface tension of liquid gallium

NASA Technical Reports Server (NTRS)

Hardy, S. C.

1985-01-01

The surface tension of liquid gallium has been measured using the sessile drop technique in an Auger spectrometer. The experimental method is described. The surface tension in mJ/sq m is found to decrease linearly with increasing temperature and may be represented as 708-0.66(T-29.8), where T is the temperature in centigrade. This result is of interest because gallium has been suggested as a model fluid for Marangoni flow experiments. In addition, the surface tension is of technological significance in the processing of compound semiconductors involving gallium.

Chemistry-First Approach for Nomination of Personalized Treatment in Lung Cancer. | Office of Cancer Genomics

Cancer.gov

Diversity in the genetic lesions that cause cancer is extreme. In consequence, a pressing challenge is the development of drugs that target patient-specific disease mechanisms. To address this challenge, we employed a chemistry-first discovery paradigm for de novo identification of druggable targets linked to robust patient selection hypotheses. In particular, a 200,000 compound diversity-oriented chemical library was profiled across a heavily annotated test-bed of >100 cellular models representative of the diverse and characteristic somatic lesions for lung cancer.

Dual Leucine Zipper Kinase Inhibitors for the Treatment of Neurodegeneration.

PubMed

Siu, Michael; Sengupta Ghosh, Arundhati; Lewcock, Joseph W

2018-06-04

Dual leucine zipper kinase (DLK, MAP3K12) is an essential driver of the neuronal stress response that regulates neurodegeneration in models of acute neuronal injury and chronic neurodegenerative diseases such as Alzheimer's, Parkinson's, and ALS. In this review, we provide an overview of DLK signaling mechanisms and describe selected small molecules that have been utilized to inhibit DLK kinase activity in vivo. These compounds represent valuable tools for understanding the role of DLK signaling and evaluating the potential for DLK inhibition as a therapeutic strategy to prevent neuronal degeneration.

Carbon recycling in materially closed ecological life support systems

NASA Technical Reports Server (NTRS)

Obenhuber, D. C.; Folsome, C. E.

1988-01-01

Results of studies are presented of materially closed energetically open microbial ecosystems or 'closed ecosystems'. These are natural marine ecosystems that have been sealed in glass containers to prevent material exchange with the environment but allow energy to pass freely through them. They represent model life support systems for the future human habitation of space. The results are discussed analytically and indicate that these ecosystems, when subjected to a constant energy flux, seem to be reliable and self-sufficient systems for recycling of biologically produced carbon compounds.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henderson, H.M.; Eskin, N.A.M.; Pinsky, C.

Potato polyphenol oxidase activity was strongly and noncompetitively inhibited by the 'Perov mixture' of coal tar components and by pyridine alone, while phenol competitively inhibited the enzyme. These two inhibitors are structural components of the parkinsonogenic neurotoxin N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). By extension, dopamine and neuromelanin synthesis in the brain may be influenced by the inhibitory effects of such compounds upon the copper-dependent steps of tyrosine metabolism. The non-animal model used in this study may represent an alternative to the use of animal tissues in neurodegenerative disease research.

Saccharide antifreeze compositions

DOEpatents

Walters, Kent; Duman, John G; Serianni, Anthony S

2013-12-10

The invention provides an antifreeze glycolipid compounds and composition comprising a polysaccharide moiety of Formula I; ##STR00001## wherein D-Manp represents a D-mannopyranose moiety, D-Xylp represents a D-xylopyranose moiety, and n is about 5 to about 70; and one or more lipid moieties covalently linked to the polysaccharide moiety of Formula I or electrostatically associated with the polysaccaride moiety for Formula I. The antifreeze glycolipid compounds and compositions can be used for a variety of industrial, agricultural, medical, and cosmetic applications where recrystallization-inhibition, cyroprotection, or cryopreservation is desired. The antifreeze glycolipid compounds or compositions can be used as, for example, as cryoprotectants for tissue preservation and transplantation, improving the texture of processed frozen food and frozen meats, frostbit protection, crop protection, and green alternatives for land vehicle antifreeze and aircraft de-icing.

Simulating Gas-Liquid-Water Partitioning and Fluid Properties of Petroleum under Pressure: Implications for Deep-Sea Blowouts.

PubMed

Gros, Jonas; Reddy, Christopher M; Nelson, Robert K; Socolofsky, Scott A; Arey, J Samuel

2016-07-19

With the expansion of offshore petroleum extraction, validated models are needed to simulate the behaviors of petroleum compounds released in deep (>100 m) waters. We present a thermodynamic model of the densities, viscosities, and gas-liquid-water partitioning of petroleum mixtures with varying pressure, temperature, and composition based on the Peng-Robinson equation-of-state and the modified Henry's law (Krychevsky-Kasarnovsky equation). The model is applied to Macondo reservoir fluid released during the Deepwater Horizon disaster, represented with 279-280 pseudocomponents, including 131-132 individual compounds. We define >n-C8 pseudocomponents based on comprehensive two-dimensional gas chromatography (GC × GC) measurements, which enable the modeling of aqueous partitioning for n-C8 to n-C26 fractions not quantified individually. Thermodynamic model predictions are tested against available laboratory data on petroleum liquid densities, gas/liquid volume fractions, and liquid viscosities. We find that the emitted petroleum mixture was ∼29-44% gas and ∼56-71% liquid, after cooling to local conditions near the broken Macondo riser stub (∼153 atm and 4.3 °C). High pressure conditions dramatically favor the aqueous dissolution of C1-C4 hydrocarbons and also influence the buoyancies of bubbles and droplets. Additionally, the simulated densities of emitted petroleum fluids affect previous estimates of the volumetric flow rate of dead oil from the emission source.

Drude polarizable force field for aliphatic ketones and aldehydes, and their associated acyclic carbohydrates

NASA Astrophysics Data System (ADS)

Small, Meagan C.; Aytenfisu, Asaminew H.; Lin, Fang-Yu; He, Xibing; MacKerell, Alexander D.

2017-04-01

The majority of computer simulations exploring biomolecular function employ Class I additive force fields (FF), which do not treat polarization explicitly. Accordingly, much effort has been made into developing models that go beyond the additive approximation. Development and optimization of the Drude polarizable FF has yielded parameters for selected lipids, proteins, DNA and a limited number of carbohydrates. The work presented here details parametrization of aliphatic aldehydes and ketones (viz. acetaldehyde, propionaldehyde, butaryaldehyde, isobutaryaldehyde, acetone, and butanone) as well as their associated acyclic sugars ( d-allose and d-psicose). LJ parameters are optimized targeting experimental heats of vaporization and molecular volumes, while the electrostatic parameters are optimized targeting QM water interactions, dipole moments, and molecular polarizabilities. Bonded parameters are targeted to both QM and crystal survey values, with the models for ketones and aldehydes shown to be in good agreement with QM and experimental target data. The reported heats of vaporization and molecular volumes represent a compromise between the studied model compounds. Simulations of the model compounds show an increase in the magnitude and the fluctuations of the dipole moments in moving from gas phase to condensed phases, which is a phenomenon that the additive FF is intrinsically unable to reproduce. The result is a polarizable model for aliphatic ketones and aldehydes including the acyclic sugars d-allose and d-psicose, thereby extending the available biomolecules in the Drude polarizable FF.

Drude polarizable force field for aliphatic ketones and aldehydes, and their associated acyclic carbohydrates.

PubMed

Small, Meagan C; Aytenfisu, Asaminew H; Lin, Fang-Yu; He, Xibing; MacKerell, Alexander D

2017-04-01

The majority of computer simulations exploring biomolecular function employ Class I additive force fields (FF), which do not treat polarization explicitly. Accordingly, much effort has been made into developing models that go beyond the additive approximation. Development and optimization of the Drude polarizable FF has yielded parameters for selected lipids, proteins, DNA and a limited number of carbohydrates. The work presented here details parametrization of aliphatic aldehydes and ketones (viz. acetaldehyde, propionaldehyde, butaryaldehyde, isobutaryaldehyde, acetone, and butanone) as well as their associated acyclic sugars (D-allose and D-psicose). LJ parameters are optimized targeting experimental heats of vaporization and molecular volumes, while the electrostatic parameters are optimized targeting QM water interactions, dipole moments, and molecular polarizabilities. Bonded parameters are targeted to both QM and crystal survey values, with the models for ketones and aldehydes shown to be in good agreement with QM and experimental target data. The reported heats of vaporization and molecular volumes represent a compromise between the studied model compounds. Simulations of the model compounds show an increase in the magnitude and the fluctuations of the dipole moments in moving from gas phase to condensed phases, which is a phenomenon that the additive FF is intrinsically unable to reproduce. The result is a polarizable model for aliphatic ketones and aldehydes including the acyclic sugars D-allose and D-psicose, thereby extending the available biomolecules in the Drude polarizable FF.

Drude Polarizable Force Field for Aliphatic Ketones and Aldehydes, and their Associated Acyclic Carbohydrates

PubMed Central

Small, Meagan C.; Aytenfisu, Asaminew H.; Lin, Fang-Yu; He, Xibing; MacKerell, Alexander D.

2017-01-01

The majority of computer simulations exploring biomolecular function employ Class I additive force fields (FF), which do not treat polarization explicitly. Accordingly, much effort has been made into developing models that go beyond the additive approximation. Development and optimization of the Drude polarizable FF has yielded parameters for selected lipids, proteins, DNA and a limited number of carbohydrates. The work presented here details parametrization of aliphatic aldehydes and ketones (viz. acetaldehyde, propionaldehyde, butaryaldehyde, isobutaryaldehyde, acetone, and butanone) as well as their associated acyclic sugars (D-allose and D-psicose). LJ parameters are optimized targeting experimental heats of vaporization and molecular volumes, while the electrostatic parameters are optimized targeting QM water interactions, dipole moments, and molecular polarizabilities. Bonded parameters are targeted to both QM and crystal survey values, with the models for ketones and aldehydes shown to be in good agreement with QM and experimental target data. The reported heats of vaporization and molecular volumes represent a compromise between the studied model compounds. Simulations of the model compounds show an increase in the magnitude and the fluctuations of the dipole moments in moving from gas phase to condensed phases, which is a phenomenon that the additive FF is intrinsically unable to reproduce. The result is a polarizable model for aliphatic ketones and aldehydes including the acyclic sugars D-allose and D-psicose, thereby extending the available biomolecules in the Drude polarizable FF. PMID:28190218

Chemical composition and allelopathic potential of essential oils obtained from Acacia cyanophylla Lindl. Cultivated in Tunisia.

PubMed

El Ayeb-Zakhama, Asma; Sakka-Rouis, Lamia; Bergaoui, Afifa; Flamini, Guido; Ben Jannet, Hichem; Harzallah-Skhiri, Fethia

2015-04-01

Acacia cyanophylla Lindl. (Fabaceae), synonym Acacia saligna (Labill.) H. L.Wendl., native to West Australia and naturalized in North Africa and South Europe, was introduced in Tunisia for rangeland rehabilitation, particularly in the semiarid zones. In addition, this evergreen tree represents a potential forage resource, particularly during periods of drought. A. cyanophylla is abundant in Tunisia and some other Mediterranean countries. The chemical composition of the essential oils obtained by hydrodistillation from different plant parts, viz., roots, stems, phyllodes, flowers, and pods (fully mature fruits without seeds), was characterized for the first time here. According to GC-FID and GC/MS analyses, the principal compound in the phyllode and flower oils was dodecanoic acid (4), representing 22.8 and 66.5% of the total oil, respectively. Phenylethyl salicylate (8; 34.9%), heptyl valerate (3; 17.3%), and nonadecane (36%) were the main compounds in the root, stem, and pod oils, respectively. The phyllode and flower oils were very similar, containing almost the same compounds. Nevertheless, the phyllode oil differed from the flower oil for its higher contents of hexahydrofarnesyl acetone (6), linalool (1), pentadecanal, α-terpineol, and benzyl benzoate (5) and its lower content of 4. Principal component and hierarchical cluster analyses separated the five essential oils into four groups, each characterized by its main constituents. Furthermore, the allelopathic activity of each oil was evaluated using lettuce (Lactuca sativa L.) as a plant model. The phyllode, flower, and pod oils exhibited a strong allelopathic activity against lettuce. Copyright © 2015 Verlag Helvetica Chimica Acta AG, Zürich.

LakeVOC; A Deterministic Model to Estimate Volatile Organic Compound Concentrations in Reservoirs and Lakes

USGS Publications Warehouse

Bender, David A.; Asher, William E.; Zogorski, John S.

2003-01-01

This report documents LakeVOC, a model to estimate volatile organic compound (VOC) concentrations in lakes and reservoirs. LakeVOC represents the lake or reservoir as a two-layer system and estimates VOC concentrations in both the epilimnion and hypolimnion. The air-water flux of a VOC is characterized in LakeVOC in terms of the two-film model of air-water exchange. LakeVOC solves the system of coupled differential equations for the VOC concentration in the epilimnion, the VOC concentration in the hypolimnion, the total mass of the VOC in the lake, the volume of the epilimnion, and the volume of the hypolimnion. A series of nine simulations were conducted to verify LakeVOC representation of mixing, dilution, and gas exchange characteristics in a hypothetical lake, and two additional estimates of lake volume and MTBE concentrations were done in an actual reservoir under environmental conditions. These 11 simulations showed that LakeVOC correctly handled mixing, dilution, and gas exchange. The model also adequately estimated VOC concentrations within the epilimnion in an actual reservoir with daily input parameters. As the parameter-input time scale increased (from daily to weekly to monthly, for example), the differences between the measured-averaged concentrations and the model-estimated concentrations generally increased, especially for the hypolimnion. This may be because as the time scale is increased from daily to weekly to monthly, the averaging of model inputs may cause a loss of detail in the model estimates.

The chemistry of subcritical water reactions of a hardwood derived lignin and lignin model compounds with nitrogen, hydrogen, carbon monoxide and carbon dioxide

NASA Astrophysics Data System (ADS)

Hill Bembenic, Meredith A.

Biofuels, like cellulosic ethanol, may only be cost effective if the lignin byproduct is upgraded to value-added products. However, lignin's inherent aromatic structure and interunit crosslinkages hinder effective conversion. High temperature H2O is considered for lignin conversion, because H2O exhibits unusual properties at higher temperatures (particularly at its supercritical point of 374°C and 3205 psi) including a decreased ion product and a decreased static dielectric constant (similar to those of polar organic solvents at room temperature) such that there is a high solubility for organic compounds, like lignin. Much of the research concerning lignin and supercritical H2O has focused on further decomposition to gases (e.g., H2, CH4, and CO2) where nearly no char formation is expected in the presence of a catalyst. However, the conditions required for supercritical H2O are difficult to maintain, catalysts can be expensive, and gases are not favorable to the current liquid fuel infrastructure. Reactions using Organosolv lignin, subcritical H2O (365°C) and various industrial gases (N2, H2, CO, and CO2 at an initial pressure of 500 psi) for 30 min. were examined to determine both lignin's potential to generate value-added products (e.g., monomer compounds and methanol) and the role (if any) of the H2O and the gases during the reactions. The behavior of H2O at reaction temperature and pressure is expected to be similar to the behavior of supercritical H 2O without the need to maintain supercritical conditions. Different characterization techniques were used for the products collected including primarily GC/FID-TCD of the evolved gases, GC/MS analysis of the organic liquids, solid phase microextraction analysis of the water, and solid state 13C-NMR analysis of the residues. The reactor pressure at temperature was shown to influence the reactivity of the H2O and lignin, and the highest conversions (≈54--62%) were obtained when adding a gas. However, the collected solids from the CO reactions appeared to be the most reacted (i.e., the most changed from the unreacted lignin) according to solid state 13C-NMR analysis, and the widest variety of products (methoxy-substituted phenolic compounds) were obtained when using CO according to GC/MS analysis. Therefore, reactions with CO were completed that varied the initial reaction pressure (300, 500 and 800 psi) in order to elucidate the effects of CO pressure. Similar conversion (≈54--58%) and DCM-soluble liquid product yields (≈53--62%) were obtained for the different pressure reactions, but the reactions with an initial pressure of 500 psi had the greatest change in aromaticity from the unreacted lignin. Additional reactions between Organosolv lignin and H2O with CO (initial pressure of 500 psi) were conducted where the reaction time was varied (15, 30 and 60 min.) to determine the effect of reaction time. Longer reaction time (60 min.) appeared to inhibit conversion to low molecular weight compounds (i.e., conversion and DCM-soluble yields were lower at ≈53% and ≈28%, respectively). Solid state 13C-NMR of collected residues also showed that there are losses in carbons representative of both guaiacyl and syringyl components as reaction time increases, which may indicate that methoxy groups are being cleaved or the products are reacting with each other (i.e., repolymerization) to form high molecular weight compounds as reaction time is increased. The role of H2O and the gases during the baseline reactions and the expanded CO reactions is not intuitive based on the results, so reactions with lignin model compounds (i.e., aromatic aldehydes represented by vanillin and syringaldehyde, aromatic ketones represented by acetovanillone and acetosyringone, and aromatic ethers represented by dibenzyl ether and 2-phenethyl phenyl ether) were completed to study this. From these results, the suggested reaction pathway of Organosolv lignin reactions in subcritical H2O with and without added pressure is: 1) cleavage of ethers (via hydrolysis) to form smaller methoxy-substituted phenolic monomers with aldehyde- or ketone-substituents representative of lignin monomers; 2) cleavage of the methoxy-, aldehyde- and/or ketone-substituents to form primarily methoxy-substituted phenolic monomers; 3) rearrangement of these phenolic monomers due to the enhanced pressure at reaction temperature; 4) formation of oligomers due to interaction amongst the methoxy-substituted phenolic monomers, which is also due to the enhanced pressure at reaction temperature; and 5) repolymerization of the monomers and oligomers to form high molecular weight compounds (i.e., longer reactions times or different pressures seemed to enhance these reactions). Under these conditions, depolymerization seems to be the dominant reaction pathway versus repolymerization. Reactions with lignin and H2O at 365°C have not been previously reported nor has the reaction chemistry for lignin depolymerization at these conditions been established. The results with lignin (or lignin model compounds), subcritical H2O and CO also show that the desired product slate can be modified with different pressure and time conditions. In particular, increasing reaction time (from 15 to 60 min.) caused lignin conversion to decrease, and the products appeared to be reacting with each other. However, the longer reaction time also showed that more methanol is generated (along with more solids).

Correct Representation of Conformational Equilibria.

ERIC Educational Resources Information Center

Fulop, F.; And Others

1983-01-01

In representing conformational equilibria of compounds having only one chiral center, erroneous formulas showing different antipodes on the two sides of the equilibrium are rare. In contrast, with compounds having two or more chiral centers especially with saturated heterocycles, this erroneous representation occurs frequently in the chemical…

Rapid volatile metabolomics and genomics in large strawberry populations segregating for aroma

USDA-ARS?s Scientific Manuscript database

Volatile organic compounds (VOCs) in strawberry (Fragaria spp.) represent a large portion of the fruit secondary metabolome, and contribute significantly to aroma, flavor, disease resistance, pest resistance and overall fruit quality. Understanding the basis for volatile compound biosynthesis and it...

75 FR 22118 - Notice of Invention Available for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-27

... represented by the Department of Commerce. The Department of Commerce's interest in the invention is available... microfluidic apparatus and method for performing electrophoretic separation of compounds. The apparatus... mm. By the foregoing, compounds can be sequentially detected and quantified. Dated: April 21, 2010...

Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms, and organic aerosol

EPA Science Inventory

Oxidation of biogenic volatile organic compounds (BVOC) by the nitrate radical (NO3) represents one of the important interactions between anthropogenic emissions related to combustion and natural emissions from the biosphere. This interaction has been recognized for more than 3 d...

Comprehensive comparative analysis of volatile compounds in citrus fruits of different species.

PubMed

Zhang, Haipeng; Xie, Yunxia; Liu, Cuihua; Chen, Shilin; Hu, Shuangshuang; Xie, Zongzhou; Deng, Xiuxin; Xu, Juan

2017-09-01

The volatile profiles of fruit peels and juice sacs from 108 citrus accessions representing seven species were analyzed. Using GC-MS 162 and 107 compounds were determined in the peels and juice sacs, respectively. In the peels, monoterpene alcohols were accumulated in loose-skin mandarins; clementine tangerines and papedas were rich in sesquiterpene alcohols, sesquiterpenes, monoterpene alcohols and monoterpene aldehydes. β-pinene and sabinene were specifically accumulated in 4 of 5 lemon germplasms. Furthermore, concentrations of 34 distinctive compounds were selected to best represent the volatile profiles of seven species for HCA analysis, and the clustering results were in agreement with classic citrus taxonomy. Comparison of profiles from different growing seasons and production areas indicated that environmental factors play important roles in volatile metabolism. In addition, a few citrus germplasms that accumulated certain compounds were determined as promising breeding materials. Notably, volatile biosynthesis via MVA pathway in C. ichangensis 'Huaihua' was enhanced. Copyright © 2017. Published by Elsevier Ltd.

Fatty acid composition and volatile compounds of caviar from farmed white sturgeon (Acipenser transmontanus).

PubMed

Caprino, Fabio; Moretti, Vittorio Maria; Bellagamba, Federica; Turchini, Giovanni Mario; Busetto, Maria Letizia; Giani, Ivan; Paleari, Maria Antonietta; Pazzaglia, Mario

2008-06-09

The present study was conducted to characterize caviar obtained from farmed white sturgeons (Acipenser transmontanus) subjected to different dietary treatments. Twenty caviar samples from fish fed two experimental diets containing different dietary lipid sources have been analysed for chemical composition, fatty acids and flavour volatile compounds. Fatty acid make up of caviar was only minimally influenced by dietary fatty acid composition. Irrespective of dietary treatments, palmitic acid (16:0) and oleic acid (OA, 18:1 n-9) were the most abundant fatty acid followed by docosahexaenoic acid (DHA, 22:6 n-3) and eicopentaenoic (EPA, 20:5 n-3). Thirty-three volatile compounds were isolated using simultaneous distillation-extraction (SDE) and identified by GC-MS. The largest group of volatiles were represented by aldehydes with 20 compounds, representing the 60% of the total volatiles. n-Alkanals, 2-alkenals and 2,4-alkadienals are largely the main responsible for a wide range of flavours in caviar from farmed white surgeon.

Speciated Chemical Composition of Biomass Burning Aerosol from Various Fuels during FIREX

NASA Astrophysics Data System (ADS)

Jen, C.; Hatch, L. E.; Kreisberg, N. M.; Selimovic, V.; Yokelson, R. J.; Barsanti, K.; Goldstein, A. H.

2017-12-01

Biomass burning is the largest global source of atmospheric primary carbonaceous aerosols and the second largest global source of non-methane organic compounds, including volatile and semi-volatile organic compounds that are now understood to be major contributors to secondary particle formation in the atmosphere. As wildfires in forested regions such as the western United States become larger and more frequent, understanding the chemical composition of biomass burning organic aerosol is needed to better predict their increasing impact on human health, air quality, and climate. This study presents emission profiles of chemically speciated intermediate and semi-volatile organic compounds present in biomass burning aerosol particles ≤1.0 μm. Biomass burning organic aerosol (BBOA) samples from a variety of fuel types and burning conditions were collected during the FIREX campaign at the USDA Fire Lab (Missoula, MT). Fuels were primarily selected from vegetation commonly found in the western United States, such as ponderosa pine, lodgepole pine, ceanothus, and chaparral. Collected BBOA was thermally desorbed from the filters and analyzed using online derivatization and 2-dimensional gas chromatography with an electron impact (70 eV) and vacuum ultra violet light (10.5 eV) high resolution time of flight mass spectrometer for compound identification. Emission profiles for specific compounds (e.g., levoglucosan) and families of compounds (e.g., sugars and methoxyphenols) show distinct variations between different fuel types, with major differences between fresh and partially decomposed fuels. Results also illustrate the variability in chemical species between burns conducted under similar conditions. Furthermore, chemical fingerprints, representing ratios of normalized emissions for key chemical compounds, were measured for specific fuels/conditions and could be used in future field studies to help identify contributions of various vegetation to total BBOA and in models to estimate the chemical composition of BBOA emissions.

Source Term Modeling for Evaluating the Potential Impacts to Groundwater of Fluids Escaping from a Depleted Oil Reservoir Used for Carbon Sequestration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cantrell, Kirk J.; Brown, Christopher F.

2014-06-13

In recent years depleted oil reservoirs have received special interest as carbon storage reservoirs because of their potential to offset costs through collaboration with enhanced oil recovery projects. Modeling is currently being conducted to evaluate potential risks to groundwater associated with leakage of fluids from depleted oil reservoirs used for storage of CO2. Modeling results reported here focused on understanding how toxic organic compounds found in oil will distribute between the various phases within a storage reservoir after introduction of CO2, understanding the migration potential of these compounds, and assessing potential groundwater impacts should leakage occur. Two model scenarios weremore » conducted to evaluate how organic components in oil will distribute among the phases of interest (oil, CO2, and brine). The first case consisted of 50 wt.% oil and 50 wt.% water; the second case was 90 wt.% CO2 and 10 wt.% oil. Several key organic compounds were selected for special attention in this study based upon their occurrence in oil at significant concentrations, relative toxicity, or because they can serve as surrogate compounds for other more highly toxic compounds for which required input data are not available. The organic contaminants of interest (COI) selected for this study were benzene, toluene, naphthalene, phenanthrene, and anthracene. Partitioning of organic compounds between crude oil and supercritical CO2 was modeled using the Peng-Robinson equation of state over temperature and pressure conditions that represent the entire subsurface system (from those relevant to deep geologic carbon storage environments to near surface conditions). Results indicate that for a typical set of oil reservoir conditions (75°C, and 21,520 kPa) negligible amounts of the COI dissolve into the aqueous phase. When CO2 is introduced into the reservoir such that the final composition of the reservoir is 90 wt.% CO2 and 10 wt.% oil, a significant fraction of the oil dissolves into the vapor phase. As the vapor phase moves up through the stratigraphic column, pressures and temperatures decrease, resulting in significant condensation of oil components. The heaviest organic components condense early in this process (at higher pressures and temperatures), while the lighter components tend to remain in the vapor phase until much lower pressures and temperatures are reached. Based on the model assumptions, the final concentrations of COI to reach an aquifer at 1,520 kPa and 25°C were quite significant for benzene and toluene, whereas the concentrations of polynuclear aromatic hydrocarbons that reach the aquifer were very small. This work demonstrates a methodology that can provide COI source term concentrations in CO2 leaking from a reservoir and entering an overlying aquifer for use in risk assessments.« less

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines.

PubMed

Tian, Sheng; Li, Youyong; Wang, Junmei; Xu, Xiaojie; Xu, Lei; Wang, Xiaohong; Chen, Lei; Hou, Tingjun

2013-01-21

In order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared. First, the different scaffolds were extracted from ACD, MDDR and TCMCD by using three scaffold representations, including Murcko frameworks, Scaffold Tree, and ring systems with different complexity and side chains. Then, by examining the accumulative frequency of the scaffolds in each dataset, we observed that the Level 1 scaffolds of the Scaffold Tree offer advantages over the other scaffold architectures to represent the scaffold diversity of the compound libraries. By comparing the similarity of the scaffold architectures presented in MDDR, ACD and TCMCD, structural overlaps were observed not only between MDDR and TCMCD but also between MDDR and ACD. Finally, Tree Maps were used to cluster the Level 1 scaffolds of the Scaffold Tree and visualize the scaffold space of the three datasets. The analysis of the scaffold architectures of MDDR, ACD and TCMCD shows that, on average, drug-like molecules in MDDR have the highest diversity while natural compounds in TCMCD have the highest complexity. According to the Tree Maps, it can be observed that the Level 1 scaffolds present in MDDR have higher diversity than those presented in TCMCD and ACD. However, some representative scaffolds in MDDR with high frequency show structural similarities to those in TCMCD and ACD, suggesting that some scaffolds in TCMCD and ACD may be potentially drug-like fragments for fragment-based and de novo drug design.

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines

PubMed Central

2013-01-01

Background In order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared. Results First, the different scaffolds were extracted from ACD, MDDR and TCMCD by using three scaffold representations, including Murcko frameworks, Scaffold Tree, and ring systems with different complexity and side chains. Then, by examining the accumulative frequency of the scaffolds in each dataset, we observed that the Level 1 scaffolds of the Scaffold Tree offer advantages over the other scaffold architectures to represent the scaffold diversity of the compound libraries. By comparing the similarity of the scaffold architectures presented in MDDR, ACD and TCMCD, structural overlaps were observed not only between MDDR and TCMCD but also between MDDR and ACD. Finally, Tree Maps were used to cluster the Level 1 scaffolds of the Scaffold Tree and visualize the scaffold space of the three datasets. Conclusion The analysis of the scaffold architectures of MDDR, ACD and TCMCD shows that, on average, drug-like molecules in MDDR have the highest diversity while natural compounds in TCMCD have the highest complexity. According to the Tree Maps, it can be observed that the Level 1 scaffolds present in MDDR have higher diversity than those presented in TCMCD and ACD. However, some representative scaffolds in MDDR with high frequency show structural similarities to those in TCMCD and ACD, suggesting that some scaffolds in TCMCD and ACD may be potentially drug-like fragments for fragment-based and de novo drug design. PMID:23336706

Uncovering the Mechanisms of Chinese Herbal Medicine (MaZiRenWan) for Functional Constipation by Focused Network Pharmacology Approach.

PubMed

Huang, Tao; Ning, Ziwan; Hu, Dongdong; Zhang, Man; Zhao, Ling; Lin, Chengyuan; Zhong, Linda L D; Yang, Zhijun; Xu, Hongxi; Bian, Zhaoxiang

2018-01-01

MaZiRenWan (MZRW, also known as Hemp Seed Pill) is a Chinese Herbal Medicine which has been demonstrated to safely and effectively alleviate functional constipation (FC) in a randomized, placebo-controlled clinical study with 120 subjects. However, the underlying pharmacological actions of MZRW for FC, are still largely unknown. We systematically analyzed the bioactive compounds of MZRW and mechanism-of-action biological targets through a novel approach called "focused network pharmacology." Among the 97 compounds identified by UPLC-QTOF-MS/MS in MZRW extract, 34 were found in rat plasma, while 10 were found in rat feces. Hierarchical clustering analysis suggest that these compounds can be classified into component groups, in which compounds are highly similar to each other and most of them are from the same herb. Emodin, amygdalin, albiflorin, honokiol, and naringin were selected as representative compounds of corresponding component groups. All of them were shown to induce spontaneous contractions of rat colonic smooth muscle in vitro . Network analysis revealed that biological targets in acetylcholine-, estrogen-, prostaglandin-, cannabinoid-, and purine signaling pathways are able to explain the prokinetic effects of representative compounds and corresponding component groups. In conclusion, MZRW active components enhance colonic motility, possibly by acting on multiple targets and pathways.

Uncovering the Mechanisms of Chinese Herbal Medicine (MaZiRenWan) for Functional Constipation by Focused Network Pharmacology Approach

PubMed Central

Huang, Tao; Ning, Ziwan; Hu, Dongdong; Zhang, Man; Zhao, Ling; Lin, Chengyuan; Zhong, Linda L. D.; Yang, Zhijun; Xu, Hongxi; Bian, Zhaoxiang

2018-01-01

MaZiRenWan (MZRW, also known as Hemp Seed Pill) is a Chinese Herbal Medicine which has been demonstrated to safely and effectively alleviate functional constipation (FC) in a randomized, placebo-controlled clinical study with 120 subjects. However, the underlying pharmacological actions of MZRW for FC, are still largely unknown. We systematically analyzed the bioactive compounds of MZRW and mechanism-of-action biological targets through a novel approach called “focused network pharmacology.” Among the 97 compounds identified by UPLC-QTOF-MS/MS in MZRW extract, 34 were found in rat plasma, while 10 were found in rat feces. Hierarchical clustering analysis suggest that these compounds can be classified into component groups, in which compounds are highly similar to each other and most of them are from the same herb. Emodin, amygdalin, albiflorin, honokiol, and naringin were selected as representative compounds of corresponding component groups. All of them were shown to induce spontaneous contractions of rat colonic smooth muscle in vitro. Network analysis revealed that biological targets in acetylcholine-, estrogen-, prostaglandin-, cannabinoid-, and purine signaling pathways are able to explain the prokinetic effects of representative compounds and corresponding component groups. In conclusion, MZRW active components enhance colonic motility, possibly by acting on multiple targets and pathways. PMID:29632490

Systematic development of small molecules to inhibit specific microscopic steps of Aβ42 aggregation in Alzheimer's disease.

PubMed

Habchi, Johnny; Chia, Sean; Limbocker, Ryan; Mannini, Benedetta; Ahn, Minkoo; Perni, Michele; Hansson, Oskar; Arosio, Paolo; Kumita, Janet R; Challa, Pavan Kumar; Cohen, Samuel I A; Linse, Sara; Dobson, Christopher M; Knowles, Tuomas P J; Vendruscolo, Michele

2017-01-10

The aggregation of the 42-residue form of the amyloid-β peptide (Aβ42) is a pivotal event in Alzheimer's disease (AD). The use of chemical kinetics has recently enabled highly accurate quantifications of the effects of small molecules on specific microscopic steps in Aβ42 aggregation. Here, we exploit this approach to develop a rational drug discovery strategy against Aβ42 aggregation that uses as a read-out the changes in the nucleation and elongation rate constants caused by candidate small molecules. We thus identify a pool of compounds that target specific microscopic steps in Aβ42 aggregation. We then test further these small molecules in human cerebrospinal fluid and in a Caenorhabditis elegans model of AD. Our results show that this strategy represents a powerful approach to identify systematically small molecule lead compounds, thus offering an appealing opportunity to reduce the attrition problem in drug discovery.

π-Stacking between Casiopeinas® and DNA bases.

PubMed

Galindo-Murillo, Rodrigo; Hernandez-Lima, Joseelyne; González-Rendón, Mayra; Cortés-Guzmán, Fernando; Ruíz-Azuara, Lena; Moreno-Esparza, Rafael

2011-08-28

Casiopeínas® are copper complexes with the general formula [Cu(N-N)(N-O)]NO(3) and [Cu(N-N)(O-O)]NO(3) where N-N denotes a substituted bipyridine or phenanthroline, N-O indicates α-aminoacidate or peptide and O-O represents acetylacetonate or salicylaldehyde. This family of compounds has been evaluated in vitro and in vivo showing cytotoxic, genotoxic, and antineoplastic activity. The action mechanism is still not completely elucidated, but the possibility exists that these compounds interact with DNA by intercalation due to the aromatic moiety. In this work we found, using the properties of the electron density of a π-complex model base-Casiopeína®-base, that the stacking mechanism between Casiopeínas® and DNA bases is due to an electron density deficiency of the ligand of the Casiopeína® which is compensated for by an electron transfer from adenines by a π-π interaction.

Carbohydrate-Binding Non-Peptidic Pradimicins for the Treatment of Acute Sleeping Sickness in Murine Models.

PubMed

Castillo-Acosta, Víctor M; Ruiz-Pérez, Luis M; Etxebarria, Juan; Reichardt, Niels C; Navarro, Miguel; Igarashi, Yasuhiro; Liekens, Sandra; Balzarini, Jan; González-Pacanowska, Dolores

2016-09-01

Current treatments available for African sleeping sickness or human African trypanosomiasis (HAT) are limited, with poor efficacy and unacceptable safety profiles. Here, we report a new approach to address treatment of this disease based on the use of compounds that bind to parasite surface glycans leading to rapid killing of trypanosomes. Pradimicin and its derivatives are non-peptidic carbohydrate-binding agents that adhere to the carbohydrate moiety of the parasite surface glycoproteins inducing parasite lysis in vitro. Notably, pradimicin S has good pharmaceutical properties and enables cure of an acute form of the disease in mice. By inducing resistance in vitro we have established that the composition of the sugars attached to the variant surface glycoproteins are critical to the mode of action of pradimicins and play an important role in infectivity. The compounds identified represent a novel approach to develop drugs to treat HAT.

Molecular processes from the AGB to the PN stage

NASA Astrophysics Data System (ADS)

García-Hernández, D. Anibal

2012-08-01

Many complex organic molecules and inorganic solid-state compounds have been observed in the circumstellar shell of stars (both C-rich and O-rich) in the transition phase between Asymptotic Giant Branch (AGB) stars and Planetary Nebulae (PNe). This short (~102-104 years) phase of stellar evolution represents a wonderful laboratory for astrochemistry and provides severe constraints on any model of gas-phase and solid-state chemistry. One of the major challenges of present day astrophysics and astrochemistry is to understand the formation pathways of these complex organic molecules and inorganic solid-state compounds (e.g., polycyclic aromatic hydrocarbons, fullerenes, and graphene in the case of a C-rich chemistry and oxides and crystalline silicates in O-rich environments) in space. In this review, I present an observational review of the molecular processes in the late stages of stellar evolution with a special emphasis on the first detections of fullerenes and graphene in PNe.

Carbohydrate-Binding Non-Peptidic Pradimicins for the Treatment of Acute Sleeping Sickness in Murine Models

PubMed Central

Castillo-Acosta, Víctor M.; Ruiz-Pérez, Luis M.; Reichardt, Niels C.; Igarashi, Yasuhiro; Liekens, Sandra; Balzarini, Jan

2016-01-01

Current treatments available for African sleeping sickness or human African trypanosomiasis (HAT) are limited, with poor efficacy and unacceptable safety profiles. Here, we report a new approach to address treatment of this disease based on the use of compounds that bind to parasite surface glycans leading to rapid killing of trypanosomes. Pradimicin and its derivatives are non-peptidic carbohydrate-binding agents that adhere to the carbohydrate moiety of the parasite surface glycoproteins inducing parasite lysis in vitro. Notably, pradimicin S has good pharmaceutical properties and enables cure of an acute form of the disease in mice. By inducing resistance in vitro we have established that the composition of the sugars attached to the variant surface glycoproteins are critical to the mode of action of pradimicins and play an important role in infectivity. The compounds identified represent a novel approach to develop drugs to treat HAT. PMID:27662652

Effect of mid-term drought on Quercus pubescens BVOCs' emission seasonality and their dependency on light and/or temperature

NASA Astrophysics Data System (ADS)

Saunier, Amélie; Ormeño, Elena; Boissard, Christophe; Wortham, Henri; Temime-Roussel, Brice; Lecareux, Caroline; Armengaud, Alexandre; Fernandez, Catherine

2017-06-01

Biogenic volatile organic compounds (BVOCs) emitted by plants represent a large source of carbon compounds released into the atmosphere, where they account for precursors of tropospheric ozone and secondary organic aerosols. Being directly involved in air pollution and indirectly in climate change, understanding what factors drive BVOC emissions is a prerequisite for modeling their emissions and predict air pollution. The main algorithms currently used to model BVOC emissions are mainly light and/or temperature dependent. Additional factors such as seasonality and drought also influence isoprene emissions, especially in the Mediterranean region, which is characterized by a rather long drought period in summer. These factors are increasingly included in models but only for the principal studied BVOC, namely isoprene, but there are still some discrepancies in estimations of emissions. In this study, the main BVOCs emitted by Quercus pubescens - isoprene, methanol, acetone, acetaldehyde, formaldehyde, MACR, MVK and ISOPOOH (these three last compounds detected under the same m/z) - were monitored with a PTR-ToF-MS over an entire seasonal cycle during both in situ natural and amplified drought, which is expected with climate change. Amplified drought impacted all studied BVOCs by reducing emissions in spring and summer while increasing emissions in autumn. All six BVOCs monitored showed daytime light and temperature dependencies while three BVOCs (methanol, acetone and formaldehyde) also showed emissions during the night despite the absence of light under constant temperature. Moreover, methanol and acetaldehyde burst in the early morning and formaldehyde deposition and uptake were also punctually observed, which were not assessed by the classical temperature and light models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuechler, Erich R.; Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455-0431; Giese, Timothy J.

To better represent the solvation effects observed along reaction pathways, and of ionic species in general, a charge-dependent variable-radii smooth conductor-like screening model (VR-SCOSMO) is developed. This model is implemented and parameterized with a third order density-functional tight binding quantum model, DFTB3/3OB-OPhyd, a quantum method which was developed for organic and biological compounds, utilizing a specific parameterization for phosphate hydrolysis reactions. Unlike most other applications with the DFTB3/3OB model, an auxiliary set of atomic multipoles is constructed from the underlying DFTB3 density matrix which is used to interact the solute with the solvent response surface. The resulting method is variational,more » produces smooth energies, and has analytic gradients. As a baseline, a conventional SCOSMO model with fixed radii is also parameterized. The SCOSMO and VR-SCOSMO models shown have comparable accuracy in reproducing neutral-molecule absolute solvation free energies; however, the VR-SCOSMO model is shown to reduce the mean unsigned errors (MUEs) of ionic compounds by half (about 2-3 kcal/mol). The VR-SCOSMO model presents similar accuracy as a charge-dependent Poisson-Boltzmann model introduced by Hou et al. [J. Chem. Theory Comput. 6, 2303 (2010)]. VR-SCOSMO is then used to examine the hydrolysis of trimethylphosphate and seven other phosphoryl transesterification reactions with different leaving groups. Two-dimensional energy landscapes are constructed for these reactions and calculated barriers are compared to those obtained from ab initio polarizable continuum calculations and experiment. Results of the VR-SCOSMO model are in good agreement in both cases, capturing the rate-limiting reaction barrier and the nature of the transition state.« less

Moderate Partially Reduplicated Conditioned Stimuli as Retrieval Cue Can Increase Effect on Preventing Relapse of Fear to Compound Stimuli

PubMed Central

Li, Junjiao; Chen, Wei; Caoyang, Jingwen; Wu, Wenli; Jie, Jing; Xu, Liang; Zheng, Xifu

2017-01-01

The theory of memory reconsolidation argues that consolidated memory is not unchangeable. Once a memory is reactivated it may go back into an unstable state and need new protein synthesis to be consolidated again, which is called “memory reconsolidation”. Boundary studies have shown that interfering with reconsolidation through pharmacologic or behavioral intervention can lead to the updating of the initial memory, for example, erasing undesired memories. Behavioral procedures based on memory reconsolidation interference have been shown to be an effective way to inhibit fear memory relapse after extinction. However, the effectiveness of retrieval–extinction differs by subtle differences in the protocol of the reactivation session. This represents a challenge with regard to finding an optimal operational model to facilitate its clinical use for patients suffering from pathogenic memories such as those associated with post-traumatic stress disorder. Most of the laboratory models for fear learning have used a single conditioned stimulus (CS) paired with an unconditioned stimulus (US). This has simplified the real situation of traumatic events to an excessive degree, and thus, limits the clinical application of the findings based on these models. Here, we used a basic visual compound CS model as the CS to ascertain whether partial repetition of the compound CSs in conditioning can reactivate memory into reconsolidation. The results showed that the no retrieval group or the 1/3 ratio retrieval group failed to open the memory reconsolidation time window. The 2/3 repetition retrieval group and the whole repetition retrieval group were able to prevent fear reinstatement, whereas only a 2/3 ratio repetition of the initial compound CS as a reminder could inhibit spontaneous recovery. We inferred that a retrieval–extinction paradigm was also effective in a more complex model of fear if a sufficient prediction error (PE) could be generated in the reactivation period. In addition, in order to achieve an optimal effect, a CS of moderate discrepancy should be used as a reminder. PMID:29249946

Pluripotent stem cell derived hepatocyte like cells and their potential in toxicity screening.

PubMed

Greenhough, Sebastian; Medine, Claire N; Hay, David C

2010-12-30

Despite considerable progress in modelling human liver toxicity, the requirement still exists for efficient, predictive and cost effective in vitro models to reduce attrition during drug development. Thousands of compounds fail in this process, with hepatotoxicity being one of the significant causes of failure. The cost of clinical studies is substantial, therefore it is essential that toxicological screening is performed early on in the drug development process. Human hepatocytes represent the gold standard model for evaluating drug toxicity, but are a limited resource. Current alternative models are based on immortalised cell lines and animal tissue, but these are limited by poor function, exhibit species variability and show instability in culture. Pluripotent stem cells are an attractive alternative as they are capable of self-renewal and differentiation to all three germ layers, and thereby represent a potentially inexhaustible source of somatic cells. The differentiation of human embryonic stem cells and induced pluripotent stem cells to functional hepatocyte like cells has recently been reported. Further development of this technology could lead to the scalable production of hepatocyte like cells for liver toxicity screening and clinical therapies. Additionally, induced pluripotent stem cell derived hepatocyte like cells may permit in vitro modelling of gene polymorphisms and genetic diseases. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Indexing Natural Products for Their Potential Anti-Diabetic Activity: Filtering and Mapping Discriminative Physicochemical Properties.

PubMed

Zeidan, Mouhammad; Rayan, Mahmoud; Zeidan, Nuha; Falah, Mizied; Rayan, Anwar

2017-09-17

Diabetes mellitus (DM) poses a major health problem, for which there is an unmet need to develop novel drugs. The application of in silico techniques and optimization algorithms is instrumental to achieving this goal. A set of 97 approved anti-diabetic drugs, representing the active domain, and a set of 2892 natural products, representing the inactive domain, were used to construct predictive models and to index anti-diabetic bioactivity. Our recently-developed approach of 'iterative stochastic elimination' was utilized. This article describes a highly discriminative and robust model, with an area under the curve above 0.96. Using the indexing model and a mix ratio of 1:1000 (active/inactive), 65% of the anti-diabetic drugs in the sample were captured in the top 1% of the screened compounds, compared to 1% in the random model. Some of the natural products that scored highly as potential anti-diabetic drug candidates are disclosed. One of those natural products is caffeine, which is noted in the scientific literature as having the capability to decrease blood glucose levels. The other nine phytochemicals await evaluation in a wet lab for their anti-diabetic activity. The indexing model proposed herein is useful for the virtual screening of large chemical databases and for the construction of anti-diabetes focused libraries.

Synthesis and QSAR study of novel α-methylene-γ-butyrolactone derivatives as antifungal agents.

PubMed

Wu, Yong-Ling; Wang, De-Long; Guo, En-Hui; Song, Shuang; Feng, Jun-Tao; Zhang, Xing

2017-03-01

Thirty-six new α-benzylidene-γ-lactone compounds based α-methylene-γ-butyrolactone substructure were prepared and characterized by spectroscopic analysis. All compounds were evaluated for antifungal activities in vitro against six plant pathogenic fungi and the half maximal inhibitory concentration (IC 50 ) against Botrytis cinerea and Colletotrichum lagenarium were investigated. Compounds 5c-3 and 5c-5 with the halogen atom exhibited excellent fungicidal activity against B. cinerea (IC 50 =22.91, 18.89μM). The structure-activity relationships (SARs) analysis indicated that the derivatives with electron-withdrawing substituents at the meta- or para-positions improves the activity. Via the heuristic method, the generated quantitative structure-activity relationship (QSAR) model (R 2 =0.961) revealed a strong correlation of antifungal activity against B. cinerea with molecular structures of these compounds. Meanwhile, the cytotoxicity of 20 representative derivatives was tested in the human tumor cells line (HepG2) and the hepatic L02 cells line, the result indicated that the synthesized compounds showed significant inhibitory activity and limited selectivity. Compound 5c-5 has the highest fungicidal activity with IC 50 =18.89μM (against B. cinerea.) but low cytotoxicity with IC 50 =35.4μM (against HepG2 cell line) and IC 50 =68.8μM (against Hepatic L02 cell line). These encouraging results can be providing an alternative, promising use of α-benzylidene-γ-lactone through the design and exploration of eco-friendly fungicides with low toxicity and high efficiency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adsorption characteristics of selected pharmaceuticals and an endocrine disrupting compound-Naproxen, carbamazepine and nonylphenol-on activated carbon.

PubMed

Yu, Zirui; Peldszus, Sigrid; Huck, Peter M

2008-06-01

The adsorption of two representative pharmaceutically active compounds (PhACs) (naproxen and carbamazepine) and one endocrine disrupting compound (nonylphenol) were evaluated on two types of activated carbon. When determining their isotherms at environmentally relevant concentration levels, it was found that at this low concentration range (10-800 ng/L), removals of the target compounds were contrary to expectations based on their hydrophobicity. Nonylphenol (log K(ow) 5.8) was most poorly adsorbed, whereas carbamazepine (log K(ow) 2.45) was most adsorbable. Nonylphenol Freundlich isotherms at this very low concentration range had a much higher 1/n compared to isotherms at much higher concentrations. This indicates that extrapolation from an isotherm obtained at a high concentration range to predict the adsorption of nonylphenol at a concentration well below the range of the original isotherm, leads to a substantial overestimation of its removals. Comparison of isotherms for the target compounds to those for other conventional micropollutants suggested that naproxen and carbamazepine could be effectively removed by applying the same dosage utilized to remove odorous compounds (geosmin and MIB) at very low concentrations. The impact of competitive adsorption by background natural organic matter (NOM) on the adsorption of the target compounds was quantified by using the ideal adsorbed solution theory (IAST) in combination with the equivalent background compound (EBC) approach. The fulfilment of the requirements for applying the simplified IAST-EBC model, which leads to the conclusion that the percentage removal of the target compounds at a given carbon dosage is independent of the initial contaminant concentration, was confirmed for the situation examined in the paper. On this basis it is suggested that the estimated minimum carbon usage rates (CURs) to achieve 90% removal of these emerging contaminants would be valid at concentrations of less than 500 ng/L in natural water.

The role of within-compound associations in learning about absent cues.

PubMed

Witnauer, James E; Miller, Ralph R

2011-05-01

When two cues are reinforced together (in compound), most associative models assume that animals learn an associative network that includes direct cue-outcome associations and a within-compound association. All models of associative learning subscribe to the importance of cue-outcome associations, but most models assume that within-compound associations are irrelevant to each cue's subsequent behavioral control. In the present article, we present an extension of Van Hamme and Wasserman's (Learning and Motivation 25:127-151, 1994) model of retrospective revaluation based on learning about absent cues that are retrieved through within-compound associations. The model was compared with a model lacking retrieval through within-compound associations. Simulations showed that within-compound associations are necessary for the model to explain higher-order retrospective revaluation and the observed greater retrospective revaluation after partial reinforcement than after continuous reinforcement alone. These simulations suggest that the associability of an absent stimulus is determined by the extent to which the stimulus is activated through the within-compound association.

The role of within-compound associations in learning about absent cues

PubMed Central

Witnauer, James E.

2011-01-01

When two cues are reinforced together (in compound), most associative models assume that animals learn an associative network that includes direct cue–outcome associations and a within-compound association. All models of associative learning subscribe to the importance of cue–outcome associations, but most models assume that within-compound associations are irrelevant to each cue's subsequent behavioral control. In the present article, we present an extension of Van Hamme and Wasserman's (Learning and Motivation 25:127–151, 1994) model of retrospective revaluation based on learning about absent cues that are retrieved through within-compound associations. The model was compared with a model lacking retrieval through within-compound associations. Simulations showed that within-compound associations are necessary for the model to explain higher-order retrospective revaluation and the observed greater retrospective revaluation after partial reinforcement than after continuous reinforcement alone. These simulations suggest that the associability of an absent stimulus is determined by the extent to which the stimulus is activated through the within-compound association. PMID:21264569

A simple, efficient polarizable coarse-grained water model for molecular dynamics simulations.

PubMed

Riniker, Sereina; van Gunsteren, Wilfred F

2011-02-28

The development of coarse-grained (CG) models that correctly represent the important features of compounds is essential to overcome the limitations in time scale and system size currently encountered in atomistic molecular dynamics simulations. Most approaches reported in the literature model one or several molecules into a single uncharged CG bead. For water, this implicit treatment of the electrostatic interactions, however, fails to mimic important properties, e.g., the dielectric screening. Therefore, a coarse-grained model for water is proposed which treats the electrostatic interactions between clusters of water molecules explicitly. Five water molecules are embedded in a spherical CG bead consisting of two oppositely charged particles which represent a dipole. The bond connecting the two particles in a bead is unconstrained, which makes the model polarizable. Experimental and all-atom simulated data of liquid water at room temperature are used for parametrization of the model. The experimental density and the relative static dielectric permittivity were chosen as primary target properties. The model properties are compared with those obtained from experiment, from clusters of simple-point-charge water molecules of appropriate size in the liquid phase, and for other CG water models if available. The comparison shows that not all atomistic properties can be reproduced by a CG model, so properties of key importance have to be selected when coarse graining is applied. Yet, the CG model reproduces the key characteristics of liquid water while being computationally 1-2 orders of magnitude more efficient than standard fine-grained atomistic water models.

METHOD OF LIQUID-LIQUID EXTRACTION OF BLOOD SURROGATES FOR ASSESSING HUMAN EXPOSURE TO JET FUEL

EPA Science Inventory

A baseline method of liquid?liquid extraction for assessing human exposure to JP-8 jet fuel was established by extracting several representative compounds ranging from very volatile to semi-volatile organic compounds, including benzene, toluene, nonane, decane, undecane, tridec...

US EPA Base Study Standard Operating Procedure for Sampling Volatile Organic Compounds in Indoor Air using Multisorbent Samplers

EPA Pesticide Factsheets

The objective of this procedure is to collect representative samples of volatile organic compound (VOC) contaminants present in indoor and outdoor environments using multisorbent samplers, and to subsequently analyze the concentration of VOCs, as selected by EPA.

Compounded effects of heat waves and droughts over the Western Electricity Grid: spatio-temporal scales of impacts and predictability toward mitigation and adaptation.

NASA Astrophysics Data System (ADS)

Voisin, N.; Kintner-Meyer, M.; Skaggs, R.; Xie, Y.; Wu, D.; Nguyen, T. B.; Fu, T.; Zhou, T.

2016-12-01

Heat waves and droughts are projected to be more frequent and intense. We have seen in the past the effects of each of those extreme climate events on electricity demand and constrained electricity generation, challenging power system operations. Our aim here is to understand the compounding effects under historical conditions. We present a benchmark of Western US grid performance under 55 years of historical climate, and including droughts, using 2010-level of water demand and water management infrastructure, and 2010-level of electricity grid infrastructure and operations. We leverage CMIP5 historical hydrology simulations and force a large scale river routing- reservoir model with 2010-level sectoral water demands. The regulated flow at each water-dependent generating plants is processed to adjust water-dependent electricity generation parameterization in a production cost model, that represents 2010-level power system operations with hourly energy demand of 2010. The resulting benchmark includes a risk distribution of several grid performance metrics (unserved energy, production cost, carbon emission) as a function of inter-annual variability in regional water availability and predictability using large scale climate oscillations. In the second part of the presentation, we describe an approach to map historical heat waves onto this benchmark grid performance using a building energy demand model. The impact of the heat waves, combined with the impact of droughts, is explored at multiple scales to understand the compounding effects. Vulnerabilities of the power generation and transmission systems are highlighted to guide future adaptation.

Advanced oxidation of iodinated X-ray contrast media in reverse osmosis brines: the influence of quenching.

PubMed

Azerrad, Sara P; Gur-Reznik, Shirra; Heller-Grossman, Lilly; Dosoretz, Carlos G

2014-10-01

Among the main restrictions for the implementation of advanced oxidation processes (AOPs) for removal of micropollutants present in reverse osmosis (RO) brines of secondary effluents account the quenching performed by background organic and inorganic constituents. Natural organic matter (NOM) and soluble microbial products (SMP) are the main effluent organic matter constituents. The inorganic fraction is largely constituted by chlorides and bicarbonate alkalinity with sodium and calcium as main counterions. The quenching influence of these components, separately and their mixture, in the transformation of model compounds by UVA/TiO2 was studied applying synthetic brines solutions mimicking 2-fold concentrated RO secondary effluents brines. The results were validated using fresh RO brines. Diatrizoate (DTZ) and iopromide (IOPr) were used as model compound. They have been found to exhibit relative high resistance to oxidation process and therefore represent good markers for AOPs techniques. Under the conditions applied, oxidization of DTZ in the background of RO brines was strongly affected by quenching effects. The major contribution to quenching resulted from organic matter (≈70%) followed by bicarbonate alkalinity (≈30%). NOM displayed higher quenching than SMP in spite of its relative lower concentration. Multivalent cations, i.e., Ca(+2), were found to decrease effectiveness of the technique due to agglomeration of the catalyst. However this influence was lowered in presence of NOM. Different patterns of transformation were found for each model compound in which a delayed deiodination was observed for iopromide whereas diatrizoate oxidation paralleled deiodination. Copyright © 2014 Elsevier Ltd. All rights reserved.

A global plasma model for reactive deposition of compound films by modulated pulsed power magnetron sputtering discharges

NASA Astrophysics Data System (ADS)

Zheng, B. C.; Wu, Z. L.; Wu, B.; Li, Y. G.; Lei, M. K.

2017-05-01

A spatially averaged, time-dependent global plasma model has been developed to describe the reactive deposition of a TiAlSiN thin film by modulated pulsed power magnetron sputtering (MPPMS) discharges in Ar/N2 mixture gas, based on the particle balance and the energy balance in the ionization region, and considering the formation and erosion of the compound at the target surface. The modeling results show that, with increasing the N2 partial pressure from 0% to 40% at a constant working pressure of 0.3 Pa, the electron temperature during the strongly ionized period increases from 4 to 7 eV and the effective power transfer coefficient, which represents the power fraction that effectively heats the electrons and maintains the discharge, increases from about 4% to 7%; with increasing the working pressure from 0.1 to 0.7 Pa at a constant N2 partial pressure of 25%, the electron temperature decreases from 10 to 4 eV and the effective power transfer coefficient decreases from 8% to 5%. Using the modeled plasma parameters to evaluate the kinetic energy of arriving ions, the ion-to-neutral flux ratio of deposited species, and the substrate heating, the variations of process parameters that increase these values lead to an enhanced adatom mobility at the target surface and an increased input energy to the substrate, corresponding to the experimental observation of surface roughness reduction, the microstructure transition from the columnar structure to the dense featureless structure, and the enhancement of phase separation. At higher N2 partial pressure or lower working pressure, the modeling results demonstrate an increase in electron temperature, which shifts the discharge balance of Ti species from Ti+ to Ti2+ and results in a higher return fraction of Ti species, corresponding to the higher Al/Ti ratio of deposited films at these conditions. The modeling results are well correlated with the experimental observation of the composition variation and the microstructure transition of deposited TiAlSiN compound films, demonstrating the applicability of this approach in understanding the characteristics of reactive MPPMS discharges as well as the composition and microstructure of deposited compound films. The model for reactive MPPMS discharges has no special limitations and is applicable to high power impulse magnetron sputtering discharges as well.

Synthesis and Evaluation of Cytotoxic Activity of Some Pyrroles and Fused Pyrroles.

PubMed

Fatahala, Samar S; Mohamed, Mosaad S; Youns, Mahmoud; Abd-El Hameed, Rania H

2017-01-01

Pyrrole derivatives represent a very interesting class as biologically active compounds. The objective of our study was to investigate the cytotoxic and apoptotic effects and antioxidant activity of the newly synthesized pyrrole derivatives. A series of novel pyrroles and fused pyrroles (tetrahydroindoles, pyrrolopyrimidines, pyrrolopyridines and pyrrolotriazines) were synthesized and characterized using IR, 1H NMR, 13C NMR, MS and elemental analysis techniques. The antiproliferative activity of our synthesized compounds and their modulatory effect apoptotic pathway were investigated. The effect on cellular proliferation and viability was monitored by resazurin assay. Apoptotic effect was evaluated by caspase glo 3/7 assay. Synthesized compounds are then tested for their anticancer activities against three different cell lines representing three different tumor types, namely; the HepG-2 (Human hepatocellular liver carcinoma cell line), the human MCF-7 cell line (breast cancer) and the pancreatic resistant Panc-1 cells. Compounds Ia-e, IIe, and IXc, d showed a promising anti-cancer activity on all tested cell lines. Antioxidant and wound healing invasion assays were examined for promising anticancer candidate compounds. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Should Torsion Balance Technique Continue to be Taught to Pharmacy Students?

PubMed

Bilger, Rhonda; Chereson, Rasma; Salama, Noha Nabil

2017-06-01

Objective. To determine the types of balances used in compounding pharmacies: torsion or digital. Methods. A survey was mailed to the pharmacist-in-charge at 698 pharmacies, representing 47% of the pharmacies in Missouri as of July 2013. The pharmacies were randomly selected and stratified by region into eight regions to ensure a representative sample. Information was gathered regarding the type and use of balances and pharmacists' perspectives on the need to teach torsion balance technique to pharmacy students. Results. The response rate for the survey was 53.3%. Out of the total responses received, those pharmacies having a torsion balance, digital balance or both were 46.8%, 27.4% and 11.8%, respectively. About 68.3% of respondents compound prescriptions. The study showed that 52% of compounding pharmacies use torsion balances in their practice. Of those with a balance in their pharmacy, 65.6% favored continuation of torsion balance instruction. Conclusions. Digital balances have become increasingly popular and have replaced torsion balances in some pharmacies, especially those that compound a significant number of prescriptions. The results of this study indicate that torsion balances remain integral to compounding practice. Therefore, students should continue being taught torsion balance technique at the college.

Characterization of bioactive compounds in Tunisian bitter orange (Citrus aurantium L.) peel and juice and determination of their antioxidant activities.

PubMed

Jabri Karoui, Iness; Marzouk, Brahim

2013-01-01

Citrus aurantium peel and juice aroma compounds were investigated by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS), whereas phenolic compounds analysis was performed by reversed-phase high-performance liquid chromatography (RP-HPLC). Limonene was the major volatile compound of bitter orange peel (90.25%) and juice (91.61%). HPLC analysis of bitter orange peel and juice methanolic extracts indicated that phenolic acids constitute their main phenolic class representing 73.80% and 71.25%, respectively, followed by flavonoids (23.02% and 23.13%, resp.). p-Coumaric and ferulic acids were the most abundant phenolic compounds representing 24.68% and 23.79%, respectively, in the peel, while the juice contained 18.02% and 19.04%, respectively. The antioxidant activities of bitter orange peel and juice methanolic extracts have been evaluated using four in vitro assays, and the results were compared with the standard antioxidants (BHT, BHA, and ascorbic acid). Our findings demonstrated that Citrus aurantium peel and juice possess antioxidant activities which were less effective than those of antioxidant standards. Both extracts may be suggested as a new potential source of natural antioxidant.

Should Torsion Balance Technique Continue to be Taught to Pharmacy Students?

PubMed Central

Bilger, Rhonda; Chereson, Rasma

2017-01-01

Objective. To determine the types of balances used in compounding pharmacies: torsion or digital. Methods. A survey was mailed to the pharmacist-in-charge at 698 pharmacies, representing 47% of the pharmacies in Missouri as of July 2013. The pharmacies were randomly selected and stratified by region into eight regions to ensure a representative sample. Information was gathered regarding the type and use of balances and pharmacists’ perspectives on the need to teach torsion balance technique to pharmacy students. Results. The response rate for the survey was 53.3%. Out of the total responses received, those pharmacies having a torsion balance, digital balance or both were 46.8%, 27.4% and 11.8%, respectively. About 68.3% of respondents compound prescriptions. The study showed that 52% of compounding pharmacies use torsion balances in their practice. Of those with a balance in their pharmacy, 65.6% favored continuation of torsion balance instruction. Conclusions. Digital balances have become increasingly popular and have replaced torsion balances in some pharmacies, especially those that compound a significant number of prescriptions. The results of this study indicate that torsion balances remain integral to compounding practice. Therefore, students should continue being taught torsion balance technique at the college. PMID:28720913

Characterization of Bioactive Compounds in Tunisian Bitter Orange (Citrus aurantium L.) Peel and Juice and Determination of Their Antioxidant Activities

PubMed Central

Jabri karoui, Iness; Marzouk, Brahim

2013-01-01

Citrus aurantium peel and juice aroma compounds were investigated by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS), whereas phenolic compounds analysis was performed by reversed-phase high-performance liquid chromatography (RP-HPLC). Limonene was the major volatile compound of bitter orange peel (90.25%) and juice (91.61%). HPLC analysis of bitter orange peel and juice methanolic extracts indicated that phenolic acids constitute their main phenolic class representing 73.80% and 71.25%, respectively, followed by flavonoids (23.02% and 23.13%, resp.). p-Coumaric and ferulic acids were the most abundant phenolic compounds representing 24.68% and 23.79%, respectively, in the peel, while the juice contained 18.02% and 19.04%, respectively. The antioxidant activities of bitter orange peel and juice methanolic extracts have been evaluated using four in vitro assays, and the results were compared with the standard antioxidants (BHT, BHA, and ascorbic acid). Our findings demonstrated that Citrus aurantium peel and juice possess antioxidant activities which were less effective than those of antioxidant standards. Both extracts may be suggested as a new potential source of natural antioxidant. PMID:23841062

GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease.

PubMed

Bresso, Emmanuel; Togawa, Roberto; Hammond-Kosack, Kim; Urban, Martin; Maigret, Bernard; Martins, Natalia Florencio

2016-12-15

Fusarium graminearum (FG) is one of the major cereal infecting pathogens causing high economic losses worldwide and resulting in adverse effects on human and animal health. Therefore, the development of new fungicides against FG is an important issue to reduce cereal infection and economic impact. In the strategy for developing new fungicides, a critical step is the identification of new targets against which innovative chemicals weapons can be designed. As several G-protein coupled receptors (GPCRs) are implicated in signaling pathways critical for the fungi development and survival, such proteins could be valuable efficient targets to reduce Fusarium growth and therefore to prevent food contamination. In this study, GPCRs were predicted in the FG proteome using a manually curated pipeline dedicated to the identification of GPCRs. Based on several successive filters, the most appropriate GPCR candidate target for developing new fungicides was selected. Searching for new compounds blocking this particular target requires the knowledge of its 3D-structure. As no experimental X-Ray structure of the selected protein was available, a 3D model was built by homology modeling. The model quality and stability was checked by 100 ns of molecular dynamics simulations. Two stable conformations representative of the conformational families of the protein were extracted from the 100 ns simulation and were used for an ensemble docking campaign. The model quality and stability was checked by 100 ns of molecular dynamics simulations previously to the virtual screening step. The virtual screening step comprised the exploration of a chemical library with 11,000 compounds that were docked to the GPCR model. Among these compounds, we selected the ten top-ranked nontoxic molecules proposed to be experimentally tested to validate the in silico simulation. This study provides an integrated process merging genomics, structural bioinformatics and drug design for proposing innovative solutions to a world wide threat to grain producers and consumers.

Hybrid gels by conjugation of hyaluronic acid with poly(itaconic anhydride-co-3,9-divinyl-2,4,8,10-tetraoxaspiro (5.5)undecane) copolymers.

PubMed

Chiriac, Aurica P; Nita, Loredana Elena; Diaconu, Alina; Bercea, Maria; Tudorachi, Nita; Pamfil, Daniela; Mititelu-Tartau, Liliana

2017-05-01

The approach of covalent conjugation for coupling synthetic polymers with biomolecules represents an appealing strategy to produce new compounds with distinctive properties for biomedical applications. In the present study we generated hybrid gels with tunable characteristics by using hyaluronic acid (HA) and four variants of poly(itaconic anhydride-co-3,9-divinyl-2,4,8,10-tetraoxaspiro[5.5] undecane) (PITAU) copolymers, differing through the molar ratios between comonomers. The new bioconjugate compounds were realized by using a ″grafting to″ strategy, for further ensuring new ways for coupling of various bioactive compounds, taking into account that the grafted copolymers are dual sensitive to pH and temperature. The procedure of chemical crosslinking, by opening the anhydride cycle of the copolymer with the hydroxyl groups of hyaluronic acid, was used to prepare the bioconjugates. The chemical conjugation between HA and PITAU copolymers, as well as the structure of the new compounds, was confirmed by FTIR and NMR techniques. The physical properties of the new gels as thermal stability, swelling capacity, and rheological properties were investigated. The bioconjugate networks were also investigated as drug delivery carriers by using indomethacin as a model drug. In vitro and in vivo tests attested the homogeneity of the bioactive compounds as well as a good biochemical response, showing good biocompatibility for the new structures. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterization of volatile compounds produced by Lactobacillus helveticus strains in a hard cheese model.

PubMed

Cuffia, Facundo; Bergamini, Carina V; Wolf, Irma V; Hynes, Erica R; Perotti, María C

2018-01-01

Starter cultures of Lactobacillus helveticus used in hard cooked cheeses play an important role in flavor development. In this work, we studied the capacity of three strains of L. helveticus, two autochthonous (Lh138 and Lh209) and one commercial (LhB02), to grow and to produce volatile compounds in a hard cheese extract. Bacterial counts, pH, profiles of organic acids, carbohydrates, and volatile compounds were analyzed during incubation of extracts for 14 days at 37 ℃. Lactobacilli populations were maintained at 10 6 CFU ml -1 for Lh138, while decreases of approx. 2 log orders were found for LhB02 and Lh209. Both Lh209 and LhB02 slightly increased the acetic acid content whereas mild increase in lactic acid was produced by Lh138. The patterns of volatiles were dependent on the strain which reflect their distinct enzymatic machineries: LhB02 and Lh209 produced a greater diversity of compounds, while Lh138 was the least producer strain. Extracts inoculated with LhB02 and Lh 209 were characterized by ketones, esters, alcohols, aldehydes, and acids, whereas in the extracts with Lh138 the main compounds belonged to aromatic, aldehydes, and ketones groups. Therefore, Lh209 and LhB02 could represent the best cheese starters to improve and intensify the flavor, and even a starter composed by combinations of LhB02 or Lh209 with Lh138 could also be a strategy to diversify cheese flavor.

Antimicrobial Activity of Serbian Propolis Evaluated by Means of MIC, HPTLC, Bioautography and Chemometrics

PubMed Central

Trifković, Jelena; Berić, Tanja; Vovk, Irena; Milojković-Opsenica, Dušanka; Stanković, Slaviša

2016-01-01

New information has come to light about the biological activity of propolis and the quality of natural products which requires a rapid and reliable assessment method such as High Performance Thin-Layer Chromatography (HPTLC) fingerprinting. This study investigates chromatographic and chemometric approaches for determining the antimicrobial activity of propolis of Serbian origin against various bacterial species. A linear multivariate calibration technique, using Partial Least Squares, was used to extract the relevant information from the chromatographic fingerprints, i.e. to indicate peaks which represent phenolic compounds that are potentially responsible for the antimicrobial capacity of the samples. In addition, direct bioautography was performed to localize the antibacterial activity on chromatograms. The biological activity of the propolis samples against various bacterial species was determined by a minimum inhibitory concentration assay, confirming their affiliation with the European poplar type of propolis and revealing the existence of two types (blue and orange) according to botanical origin. The strongest antibacterial activity was exhibited by sample 26 against Staphylococcus aureus, with a MIC value of 0.5 mg/mL, and Listeria monocytogenes, with a MIC as low as 0.1 mg/mL, which was also the lowest effective concentration observed in our study. Generally, the orange type of propolis shows higher antimicrobial activity compared to the blue type. PLS modelling was performed on the HPTLC data set and the resulting models might qualitatively indicate compounds that play an important role in the activity exhibited by the propolis samples. The most relevant peaks influencing the antimicrobial activity of propolis against all bacterial strains were phenolic compounds at RF values of 0.37, 0.40, 0.45, 0.51, 0.60 and 0.70. The knowledge gained through this study could be important for attributing the antimicrobial activity of propolis to specific chemical compounds, as well as the verification of HPTLC fingerprinting as a reliable method for the identification of compounds that are potentially responsible for antimicrobial activity. This is the first report on the activity of Serbian propolis as determined by several combined methods, including the modelling of antimicrobial activity by HPTLC fingerprinting. PMID:27272728

A pharmacometric case study regarding the sensitivity of structural model parameter estimation to error in patient reported dosing times.

PubMed

Knights, Jonathan; Rohatagi, Shashank

2015-12-01

Although there is a body of literature focused on minimizing the effect of dosing inaccuracies on pharmacokinetic (PK) parameter estimation, most of the work centers on missing doses. No attempt has been made to specifically characterize the effect of error in reported dosing times. Additionally, existing work has largely dealt with cases in which the compound of interest is dosed at an interval no less than its terminal half-life. This work provides a case study investigating how error in patient reported dosing times might affect the accuracy of structural model parameter estimation under sparse sampling conditions when the dosing interval is less than the terminal half-life of the compound, and the underlying kinetics are monoexponential. Additional effects due to noncompliance with dosing events are not explored and it is assumed that the structural model and reasonable initial estimates of the model parameters are known. Under the conditions of our simulations, with structural model CV % ranging from ~20 to 60 %, parameter estimation inaccuracy derived from error in reported dosing times was largely controlled around 10 % on average. Given that no observed dosing was included in the design and sparse sampling was utilized, we believe these error results represent a practical ceiling given the variability and parameter estimates for the one-compartment model. The findings suggest additional investigations may be of interest and are noteworthy given the inability of current PK software platforms to accommodate error in dosing times.

Essential oil composition of Eucalyptus microtheca and Eucalyptus viminalis.

PubMed

Maghsoodlou, Malek Taher; Kazemipoor, Nasrin; Valizadeh, Jafar; Falak Nezhad Seifi, Mohsen; Rahneshan, Nahid

2015-01-01

Eucalyptus (Fam. Myrtaceae) is a medicinal plant and various Eucalyptus species possess potent pharmacological actions against diabetes, hepatotoxicity, and inflammation. This study aims to investigate essential oil composition from leaves and flowers of E. microtheca and E. viminalis leaves growing in the Southeast of Iran. The aerial parts of these plants were collected from Zahedan, Sistan and Baluchestan province, Iran in 2013. After drying the plant materials in the shade, the chemical composition of the essential oils was obtained by hydro-distillation method using a Clevenger-type apparatus and analyzed by GC/MS. In the essential oil of E. microtheca leaves, 101 compounds representing 100%, were identified. Among them, α-phellandrene (16.487%), aromadendrene (12.773%), α-pinene (6.752%), globulol (5.997%), ledene (5.665%), P-cymen (5.251%), and β-pinene (5.006%) were the major constituents. In the oil of E. microtheca flowers, 88 compounds representing 100%, were identified in which α-pinene (16.246%), O-cymen (13.522%), β-pinene (11.082%), aromadendrene (7.444%), α-phellandrene (7.006%), globulol (5.419%), and 9-octadecenamide (5.414%) were the major components. Sixty six compounds representing 100% were identified in the oil of E. viminalis leaves. The major compounds were 1, 8-cineole (57.757%), α-pinene (13.379%), limonene (5.443%), and globulol (3.054%). The results showed the essential oils from the aerial parts of Eucalyptus species are a cheap source for the commercial isolation of α-phellandrene, α-pinene, and 1, 8-cineole compounds to be used in medicinal and food products. Furthermore, these plants could be an alternative source of insecticide agents.

Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization.

PubMed

Dai, Hong-Jie; Lai, Po-Ting; Chang, Yung-Chun; Tsai, Richard Tzong-Han

2015-01-01

The functions of chemical compounds and drugs that affect biological processes and their particular effect on the onset and treatment of diseases have attracted increasing interest with the advancement of research in the life sciences. To extract knowledge from the extensive literatures on such compounds and drugs, the organizers of BioCreative IV administered the CHEMical Compound and Drug Named Entity Recognition (CHEMDNER) task to establish a standard dataset for evaluating state-of-the-art chemical entity recognition methods. This study introduces the approach of our CHEMDNER system. Instead of emphasizing the development of novel feature sets for machine learning, this study investigates the effect of various tag schemes on the recognition of the names of chemicals and drugs by using conditional random fields. Experiments were conducted using combinations of different tokenization strategies and tag schemes to investigate the effects of tag set selection and tokenization method on the CHEMDNER task. This study presents the performance of CHEMDNER of three more representative tag schemes-IOBE, IOBES, and IOB12E-when applied to a widely utilized IOB tag set and combined with the coarse-/fine-grained tokenization methods. The experimental results thus reveal that the fine-grained tokenization strategy performance best in terms of precision, recall and F-scores when the IOBES tag set was utilized. The IOBES model with fine-grained tokenization yielded the best-F-scores in the six chemical entity categories other than the "Multiple" entity category. Nonetheless, no significant improvement was observed when a more representative tag schemes was used with the coarse or fine-grained tokenization rules. The best F-scores that were achieved using the developed system on the test dataset of the CHEMDNER task were 0.833 and 0.815 for the chemical documents indexing and the chemical entity mention recognition tasks, respectively. The results herein highlight the importance of tag set selection and the use of different tokenization strategies. Fine-grained tokenization combined with the tag set IOBES most effectively recognizes chemical and drug names. To the best of the authors' knowledge, this investigation is the first comprehensive investigation use of various tag set schemes combined with different tokenization strategies for the recognition of chemical entities.

Application of the exact exchange potential method for half metallic intermediate band alloy semiconductor.

PubMed

Fernández, J J; Tablero, C; Wahnón, P

2004-06-08

In this paper we present an analysis of the convergence of the band structure properties, particularly the influence on the modification of the bandgap and bandwidth values in half metallic compounds by the use of the exact exchange formalism. This formalism for general solids has been implemented using a localized basis set of numerical functions to represent the exchange density. The implementation has been carried out using a code which uses a linear combination of confined numerical pseudoatomic functions to represent the Kohn-Sham orbitals. The application of this exact exchange scheme to a half-metallic semiconductor compound, in particular to Ga(4)P(3)Ti, a promising material in the field of high efficiency solar cells, confirms the existence of the isolated intermediate band in this compound. (c) 2004 American Institute of Physics.

Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions

PubMed Central

Hosey, Chelsea M; Benet, Leslie Z

2015-01-01

The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor™ or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72±9%, 49±10%, and 66±7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74±7%, 85±2%, and 73±8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly, respectively when the permeability rate is determined in vitro. PMID:25816851

Suspect Screening and Non-Targeted Analysis of Drinking Water Using Point-Of-Use Filters

EPA Science Inventory

Monitored contaminants in drinking water represent a small portion of the total compounds present, many of which may be relevant to human health. To understand the totality of human exposure to compounds in drinking water, broader monitoring methods are imperative. In an effort t...

US EPA Base Study Standard Operating Procedure for Sampling Volatile Organic Compounds in Indoor Air Using Evacuated Canisters

EPA Pesticide Factsheets

The objective of this procedure is to collect a representative sample of air containing volatile organic compound (VOC) contaminants present in an indoor environment using an evacuated canister, and to subsequently analyze the concentration of VOCs, as selected by EPA.

Web Thermo Tables (WTT) - Professional Edition

National Institute of Standards and Technology Data Gateway

SRD 203 NIST/TRC Web Thermo Tables (WTT) - Professional Edition (Online Subscription)   WTT - Professional Edition, a Web version of the TRC Thermodynamic Tables, represents a complete collection of critically evaluated thermodynamic property data primarily for pure organic compounds. As of Nov. 2011, WTT contains information on 23999 compounds.

CHARACTERIZATION OF EMISSIONS OF VOLATILE ORGANIC COMPOUNDS FROM INTERIOR ALKYD PAINT

EPA Science Inventory

Alkyd paint continues to be used indoors for application to wood trim, cabinet surfaces, and some kitchen and bathroom walls. Paint may represent a significant source of volatile organic compounds (VOCs) indoors depending on the frequency of use and amount of surface paint. The U...

A device for emulating cuff recordings of action potentials propagating along peripheral nerves.

PubMed

Rieger, Robert; Schuettler, Martin; Chuang, Sheng-Chih

2014-09-01

This paper describes a device that emulates propagation of action potentials along a peripheral nerve, suitable for reproducible testing of bio-potential recording systems using nerve cuff electrodes. The system is a microcontroller-based stand-alone instrument which uses established nerve and electrode models to represent neural activity of real nerves recorded with a nerve cuff interface, taking into consideration electrode impedance, voltages picked up by the electrodes, and action potential propagation characteristics. The system emulates different scenarios including compound action potentials with selectable propagation velocities and naturally occurring nerve traffic from different velocity fiber populations. Measured results from a prototype implementation are reported and compared with in vitro recordings from Xenopus Laevis frog sciatic nerve, demonstrating that the electrophysiological setting is represented to a satisfactory degree, useful for the development, optimization and characterization of future recording systems.

VR-SCOSMO: A smooth conductor-like screening model with charge-dependent radii for modeling chemical reactions.

PubMed

Kuechler, Erich R; Giese, Timothy J; York, Darrin M

2016-04-28

To better represent the solvation effects observed along reaction pathways, and of ionic species in general, a charge-dependent variable-radii smooth conductor-like screening model (VR-SCOSMO) is developed. This model is implemented and parameterized with a third order density-functional tight binding quantum model, DFTB3/3OB-OPhyd, a quantum method which was developed for organic and biological compounds, utilizing a specific parameterization for phosphate hydrolysis reactions. Unlike most other applications with the DFTB3/3OB model, an auxiliary set of atomic multipoles is constructed from the underlying DFTB3 density matrix which is used to interact the solute with the solvent response surface. The resulting method is variational, produces smooth energies, and has analytic gradients. As a baseline, a conventional SCOSMO model with fixed radii is also parameterized. The SCOSMO and VR-SCOSMO models shown have comparable accuracy in reproducing neutral-molecule absolute solvation free energies; however, the VR-SCOSMO model is shown to reduce the mean unsigned errors (MUEs) of ionic compounds by half (about 2-3 kcal/mol). The VR-SCOSMO model presents similar accuracy as a charge-dependent Poisson-Boltzmann model introduced by Hou et al. [J. Chem. Theory Comput. 6, 2303 (2010)]. VR-SCOSMO is then used to examine the hydrolysis of trimethylphosphate and seven other phosphoryl transesterification reactions with different leaving groups. Two-dimensional energy landscapes are constructed for these reactions and calculated barriers are compared to those obtained from ab initio polarizable continuum calculations and experiment. Results of the VR-SCOSMO model are in good agreement in both cases, capturing the rate-limiting reaction barrier and the nature of the transition state.

All-Atom Polarizable Force Field for DNA Based on the Classical Drude Oscillator Model

PubMed Central

Savelyev, Alexey; MacKerell, Alexander D.

2014-01-01

Presented is a first generation atomistic force field for DNA in which electronic polarization is modeled based on the classical Drude oscillator formalism. The DNA model is based on parameters for small molecules representative of nucleic acids, including alkanes, ethers, dimethylphosphate, and the nucleic acid bases and empirical adjustment of key dihedral parameters associated with the phosphodiester backbone, glycosidic linkages and sugar moiety of DNA. Our optimization strategy is based on achieving a compromise between satisfying the properties of the underlying model compounds in the gas phase targeting QM data and reproducing a number of experimental properties of DNA duplexes in the condensed phase. The resulting Drude force field yields stable DNA duplexes on the 100 ns time scale and satisfactorily reproduces (1) the equilibrium between A and B forms of DNA and (2) transitions between the BI and BII sub-states of B form DNA. Consistency with the gas phase QM data for the model compounds is significantly better for the Drude model as compared to the CHARMM36 additive force field, which is suggested to be due to the improved response of the model to changes in the environment associated with the explicit inclusion of polarizability. Analysis of dipole moments associated with the nucleic acid bases shows the Drude model to have significantly larger values than those present in CHARMM36, with the dipoles of individual bases undergoing significant variations during the MD simulations. Additionally, the dipole moment of water was observed to be perturbed in the grooves of DNA. PMID:24752978

Imidazopyridine Compounds Inhibit Mycobacterial Growth by Depleting ATP Levels.

PubMed

O'Malley, Theresa; Alling, Torey; Early, Julie V; Wescott, Heather A; Kumar, Anuradha; Moraski, Garrett C; Miller, Marvin J; Masquelin, Thierry; Hipskind, Philip A; Parish, Tanya

2018-06-01

The imidazopyridines are a promising new class of antitubercular agents with potent activity in vitro and in vivo We isolated mutants of Mycobacterium tuberculosis resistant to a representative imidazopyridine; the mutants had large shifts (>20-fold) in MIC. Whole-genome sequencing revealed mutations in Rv1339, a hypothetical protein of unknown function. We isolated mutants resistant to three further compounds from the series; resistant mutants isolated from two of the compounds had single nucleotide polymorphisms in Rv1339 and resistant mutants isolated from the third compound had single nucleotide polymorphisms in QcrB, the proposed target for the series. All the strains were resistant to two compounds, regardless of the mutation, and a strain carrying the QcrB T313I mutation was resistant to all of the imidazopyridine derivatives tested, confirming cross-resistance. By monitoring pH homeostasis and ATP generation, we confirmed that compounds from the series were targeting QcrB; imidazopyridines disrupted pH homeostasis and depleted ATP, providing further evidence of an effect on the electron transport chain. A representative compound was bacteriostatic against replicating bacteria, consistent with a mode of action against QcrB. The series had a narrow inhibitory spectrum, with no activity against other bacterial species. No synergy or antagonism was seen with other antituberculosis drugs under development. In conclusion, our data support the hypothesis that the imidazopyridine series functions by reducing ATP generation via inhibition of QcrB. Copyright © 2018 O'Malley et al.

Prediction of tautomer ratios by embedded-cluster integral equation theory

NASA Astrophysics Data System (ADS)

Kast, Stefan M.; Heil, Jochen; Güssregen, Stefan; Schmidt, K. Friedemann

2010-04-01

The "embedded cluster reference interaction site model" (EC-RISM) approach combines statistical-mechanical integral equation theory and quantum-chemical calculations for predicting thermodynamic data for chemical reactions in solution. The electronic structure of the solute is determined self-consistently with the structure of the solvent that is described by 3D RISM integral equation theory. The continuous solvent-site distribution is mapped onto a set of discrete background charges ("embedded cluster") that represent an additional contribution to the molecular Hamiltonian. The EC-RISM analysis of the SAMPL2 challenge set of tautomers proceeds in three stages. Firstly, the group of compounds for which quantitative experimental free energy data was provided was taken to determine appropriate levels of quantum-chemical theory for geometry optimization and free energy prediction. Secondly, the resulting workflow was applied to the full set, allowing for chemical interpretations of the results. Thirdly, disclosure of experimental data for parts of the compounds facilitated a detailed analysis of methodical issues and suggestions for future improvements of the model. Without specifically adjusting parameters, the EC-RISM model yields the smallest value of the root mean square error for the first set (0.6 kcal mol-1) as well as for the full set of quantitative reaction data (2.0 kcal mol-1) among the SAMPL2 participants.

Rotor termination is critically dependent on kinetic properties of I kur inhibitors in an in silico model of chronic atrial fibrillation.

PubMed

Scholz, Eberhard P; Carrillo-Bustamante, Paola; Fischer, Fathima; Wilhelms, Mathias; Zitron, Edgar; Dössel, Olaf; Katus, Hugo A; Seemann, Gunnar

2013-01-01

Inhibition of the atrial ultra-rapid delayed rectifier potassium current (I Kur) represents a promising therapeutic strategy in the therapy of atrial fibrillation. However, experimental and clinical data on the antiarrhythmic efficacy remain controversial. We tested the hypothesis that antiarrhythmic effects of I Kur inhibitors are dependent on kinetic properties of channel blockade. A mathematical description of I Kur blockade was introduced into Courtemanche-Ramirez-Nattel models of normal and remodeled atrial electrophysiology. Effects of five model compounds with different kinetic properties were analyzed. Although a reduction of dominant frequencies could be observed in two dimensional tissue simulations for all compounds, a reduction of spiral wave activity could be only be detected in two cases. We found that an increase of the percent area of refractory tissue due to a prolongation of the wavelength seems to be particularly important. By automatic tracking of spiral tip movement we find that increased refractoriness resulted in rotor extinction caused by an increased spiral-tip meandering. We show that antiarrhythmic effects of I Kur inhibitors are dependent on kinetic properties of blockade. We find that an increase of the percent area of refractory tissue is the underlying mechanism for an increased spiral-tip meandering, resulting in the extinction of re-entrant circuits.

Rotor Termination Is Critically Dependent on Kinetic Properties of I Kur Inhibitors in an In Silico Model of Chronic Atrial Fibrillation

PubMed Central

Scholz, Eberhard P.; Carrillo-Bustamante, Paola; Fischer, Fathima; Wilhelms, Mathias; Zitron, Edgar; Dössel, Olaf; Katus, Hugo A.; Seemann, Gunnar

2013-01-01

Inhibition of the atrial ultra-rapid delayed rectifier potassium current (I Kur) represents a promising therapeutic strategy in the therapy of atrial fibrillation. However, experimental and clinical data on the antiarrhythmic efficacy remain controversial. We tested the hypothesis that antiarrhythmic effects of I Kur inhibitors are dependent on kinetic properties of channel blockade. A mathematical description of I Kur blockade was introduced into Courtemanche-Ramirez-Nattel models of normal and remodeled atrial electrophysiology. Effects of five model compounds with different kinetic properties were analyzed. Although a reduction of dominant frequencies could be observed in two dimensional tissue simulations for all compounds, a reduction of spiral wave activity could be only be detected in two cases. We found that an increase of the percent area of refractory tissue due to a prolongation of the wavelength seems to be particularly important. By automatic tracking of spiral tip movement we find that increased refractoriness resulted in rotor extinction caused by an increased spiral-tip meandering. We show that antiarrhythmic effects of I Kur inhibitors are dependent on kinetic properties of blockade. We find that an increase of the percent area of refractory tissue is the underlying mechanism for an increased spiral-tip meandering, resulting in the extinction of re-entrant circuits. PMID:24376659

Development of classification models for identifying "true" P-glycoprotein (P-gp) inhibitors through inhibition, ATPase activation and monolayer efflux assays.

PubMed

Rapposelli, Simona; Coi, Alessio; Imbriani, Marcello; Bianucci, Anna Maria

2012-01-01

P-glycoprotein (P-gp) is an efflux pump involved in the protection of tissues of several organs by influencing xenobiotic disposition. P-gp plays a key role in multidrug resistance and in the progression of many neurodegenerative diseases. The development of new and more effective therapeutics targeting P-gp thus represents an intriguing challenge in drug discovery. P-gp inhibition may be considered as a valid approach to improve drug bioavailability as well as to overcome drug resistance to many kinds of tumours characterized by the over-expression of this protein. This study aims to develop classification models from a unique dataset of 59 compounds for which there were homogeneous experimental data on P-gp inhibition, ATPase activation and monolayer efflux. For each experiment, the dataset was split into a training and a test set comprising 39 and 20 molecules, respectively. Rational splitting was accomplished using a sphere-exclusion type algorithm. After a two-step (internal/external) validation, the best-performing classification models were used in a consensus predicting task for the identification of compounds named as "true" P-gp inhibitors, i.e., molecules able to inhibit P-gp without being effluxed by P-gp itself and simultaneously unable to activate the ATPase function.

Kinetic studies on the removal of phenol by MBBR from saline wastewater.

PubMed

Ahmadi, Mehdi; Jaafarzadeh, Neamat; Rahmat, Zeinab Ghaed; Babaei, Ali Akbar; Alavi, Nadali; Baboli, Zeinab; Niri, Mehdi Vosoughi

2017-01-01

Phenols are chemical compounds which are included in the high priority of pollutants by environmental protection agency (USEPA). The presence of high concentrations of phenols in wastewaters like oil refineries, petrochemical plants, olive oil, pesticide production and oil field operations contain high soluble solids (TDS) and in an olive oil plant, wastewater is acidic, high salty and phenol concentrations are in the range of 0.1- 1%. Kinetic parameters were calculated according to Monod, Modified Stover- Kincannon, Hamoda and Haldane models. The influence of different initial phenol concentrations on the biodegradation rate was performed. The concentrations of phenol varied from 0 to 500 mg / l. The value of K i in saline phenolic wastewater in attached growth systems was higher than suspended growth systems that represented a higher phenol inhibition in suspended growth systems. It was obvious that the best model fitting the obtained data are Hamoda model and the Modified Stover-Kincannon model, having highest R 2 values of 0.991 and 1, respectively. The value of K i in saline phenolic wastewater in attached growth system was higher than suspended growth systems which represented a higher phenol inhibition in suspended growth systems. Hamoda model and the Modified Stover-Kincannon model having highest R2 value of 0.991 and 1, respectively, and also predicting reasonable kinetic coefficient values.

Immortalized human myotonic dystrophy muscle cell lines to assess therapeutic compounds.

PubMed

Arandel, Ludovic; Polay Espinoza, Micaela; Matloka, Magdalena; Bazinet, Audrey; De Dea Diniz, Damily; Naouar, Naïra; Rau, Frédérique; Jollet, Arnaud; Edom-Vovard, Frédérique; Mamchaoui, Kamel; Tarnopolsky, Mark; Puymirat, Jack; Battail, Christophe; Boland, Anne; Deleuze, Jean-Francois; Mouly, Vincent; Klein, Arnaud F; Furling, Denis

2017-04-01

Myotonic dystrophy type 1 (DM1) and type 2 (DM2) are autosomal dominant neuromuscular diseases caused by microsatellite expansions and belong to the family of RNA-dominant disorders. Availability of cellular models in which the DM mutation is expressed within its natural context is essential to facilitate efforts to identify new therapeutic compounds. Here, we generated immortalized DM1 and DM2 human muscle cell lines that display nuclear RNA aggregates of expanded repeats, a hallmark of myotonic dystrophy. Selected clones of DM1 and DM2 immortalized myoblasts behave as parental primary myoblasts with a reduced fusion capacity of immortalized DM1 myoblasts when compared with control and DM2 cells. Alternative splicing defects were observed in differentiated DM1 muscle cell lines, but not in DM2 lines. Splicing alterations did not result from differentiation delay because similar changes were found in immortalized DM1 transdifferentiated fibroblasts in which myogenic differentiation has been forced by overexpression of MYOD1. As a proof-of-concept, we show that antisense approaches alleviate disease-associated defects, and an RNA-seq analysis confirmed that the vast majority of mis-spliced events in immortalized DM1 muscle cells were affected by antisense treatment, with half of them significantly rescued in treated DM1 cells. Immortalized DM1 muscle cell lines displaying characteristic disease-associated molecular features such as nuclear RNA aggregates and splicing defects can be used as robust readouts for the screening of therapeutic compounds. Therefore, immortalized DM1 and DM2 muscle cell lines represent new models and tools to investigate molecular pathophysiological mechanisms and evaluate the in vitro effects of compounds on RNA toxicity associated with myotonic dystrophy mutations. © 2017. Published by The Company of Biologists Ltd.

The gnotobiotic brine shrimp (Artemia franciscana) model system reveals that the phenolic compound pyrogallol protects against infection through its prooxidant activity.

PubMed

Baruah, Kartik; Duy Phong, Ho Phuong Pham; Norouzitallab, Parisa; Defoirdt, Tom; Bossier, Peter

2015-12-01

The phenolic compound pyrogallol is the functional unit of many polyphenols and currently there has been a growing interest in using this compound in human and animal health owing to its health-promoting effects. The biological actions of pyrogallol moiety (and polyphenols) in inducing health benefitting effects have been studied; however, the mechanisms of action remain unclear yet. Here, we aimed at unravelling the underlying mechanism of action behind the protective effects of pyrogallol against bacterial infection by using the gnotobiotically-cultured brine shrimp Artemia franciscana and pathogenic bacteria Vibrio harveyi as host-pathogen model system. The gnotobiotic test system represents an exceptional system for carrying out such studies because it eliminates any possible interference of microbial communities (naturally present in the experimental system) in mechanistic studies and furthermore facilitates the interpretation of the results in terms of a cause effect relationship. We provided clear evidences suggesting that pyrogallol pretreament, at an optimum concentration, induced protective effects in the brine shrimp against V. harveyi infection. By pretreating brine shrimp with pyrogallol in the presence or absence of an antioxidant enzyme mixture (catalase and superoxide dismutase), we showed that the Vibrio-protective effect of the compound was caused by its prooxidant action (e.g. generation of hydrogen peroxide, H2O2). We showed further that generation of prooxidant is linked to the induction of heat shock protein Hsp70, which is involved in eliciting the prophenoloxidase and transglutaminase immune responses. The ability of pyrogallol to induce protective immunity makes it a potential natural protective agent that might be a potential preventive modality for different host-pathogen systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Immortalized human myotonic dystrophy muscle cell lines to assess therapeutic compounds

PubMed Central

Arandel, Ludovic; Polay Espinoza, Micaela; Matloka, Magdalena; Bazinet, Audrey; De Dea Diniz, Damily; Naouar, Naïra; Rau, Frédérique; Jollet, Arnaud; Edom-Vovard, Frédérique; Mamchaoui, Kamel; Tarnopolsky, Mark; Puymirat, Jack; Battail, Christophe; Boland, Anne; Deleuze, Jean-Francois; Mouly, Vincent; Klein, Arnaud F.

2017-01-01

ABSTRACT Myotonic dystrophy type 1 (DM1) and type 2 (DM2) are autosomal dominant neuromuscular diseases caused by microsatellite expansions and belong to the family of RNA-dominant disorders. Availability of cellular models in which the DM mutation is expressed within its natural context is essential to facilitate efforts to identify new therapeutic compounds. Here, we generated immortalized DM1 and DM2 human muscle cell lines that display nuclear RNA aggregates of expanded repeats, a hallmark of myotonic dystrophy. Selected clones of DM1 and DM2 immortalized myoblasts behave as parental primary myoblasts with a reduced fusion capacity of immortalized DM1 myoblasts when compared with control and DM2 cells. Alternative splicing defects were observed in differentiated DM1 muscle cell lines, but not in DM2 lines. Splicing alterations did not result from differentiation delay because similar changes were found in immortalized DM1 transdifferentiated fibroblasts in which myogenic differentiation has been forced by overexpression of MYOD1. As a proof-of-concept, we show that antisense approaches alleviate disease-associated defects, and an RNA-seq analysis confirmed that the vast majority of mis-spliced events in immortalized DM1 muscle cells were affected by antisense treatment, with half of them significantly rescued in treated DM1 cells. Immortalized DM1 muscle cell lines displaying characteristic disease-associated molecular features such as nuclear RNA aggregates and splicing defects can be used as robust readouts for the screening of therapeutic compounds. Therefore, immortalized DM1 and DM2 muscle cell lines represent new models and tools to investigate molecular pathophysiological mechanisms and evaluate the in vitro effects of compounds on RNA toxicity associated with myotonic dystrophy mutations. PMID:28188264

Forest-atmosphere BVOC exchange in diverse and structurally complex canopies: 1-D modeling of a mid-successional forest in northern Michigan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Alexander M.; Cheng, Susan J.; Ashworth, Kirsti

Foliar emissions of biogenic volatile organic compounds (BVOC)dimportant precursors of tropospheric ozone and secondary organic aerosolsdvary widely by vegetation type. Modeling studies to date typi-cally represent the canopy as a single dominant tree type or a blend of tree types, yet many forests are diverse with trees of varying height. To assess the sensitivity of biogenic emissions to tree height vari-ation, we compare two 1-D canopy model simulations in which BVOC emission potentials are homo-geneous or heterogeneous with canopy depth. The heterogeneous canopy emulates the mid-successional forest at the University of Michigan Biological Station (UMBS). In this case, high-isoprene-emitting fo-liagemore » (e.g., aspen and oak) is constrained to the upper canopy, where higher sunlight availability increases the light-dependent isoprene emission, leading to 34% more isoprene and its oxidation products as compared to the homogeneous simulation. Isoprene declines from aspen mortality are 10% larger when heterogeneity is considered. Overall, our results highlight the importance of adequately representing complexities of forest canopy structure when simulating light-dependent BVOC emissions and chemistry.« less

In silico evaluation of human small heat shock protein HSP27: homology modeling, mutation analyses and docking studies.

PubMed

Fossa, Paola; Cichero, Elena

2015-07-01

Small heat-shock proteins, possessing chaperone-like activity, represented crucial proteins actively involved in maintain protein homeostasis, which act to prevent improper polypeptide aggregation and deposition of misfolded proteins. In this context, a number of mutations concerning the HspB1 protein proved to be associated with the development of several neuropathologies. Unfortunately, molecular mechanisms underlying the onset of these diseases and in particular the changes induced by the mutations in HspB1 structure, remain poorly characterized. On the other hand, more recent studies demonstrated that HspB1 overexpression leads to an overactive chaperone activity, which in turn contributes to the anticancer agent resistance. On these basis, Hsp27 could represent a good innovative target for development of novel cancer therapy. Therefore, in this work a computational study, based on the homology model of the complete Hsp27 protein and of several pathological mutant forms, was developed. Finally, the derived model was employed to perform, for the first time, docking simulations on a recently identified Hsp27 inhibitor, disclosing a new useful panorama to be exploited for the further development of new compounds. Copyright © 2015 Elsevier Ltd. All rights reserved.

Chromatographic analysis of toxic phosphylated oximes (POX): a brief overview.

PubMed

Becker, Christian; Worek, Franz; John, Harald

2010-10-01

Poisoning with organophosphorus compounds (OP), e.g. pesticides and nerve agents, causes inhibition of acetylcholinesterase (AChE) by phosphylation of the active site serine residue. Consequently, accumulation of stimulating acetylcholine in the synaptic cleft induces cholinergic crisis which ultimately may lead to death. For standard causal therapy, enzyme reactivators are administered representing oxime derivatives of quarternary pyridinium compounds, e.g. pralidoxime (2-PAM), obidoxime and HI 6. The mechanism of action includes removal of the phosphyl moiety by a nucleophilic attack of the oximate molecule substituting the enzyme and forming a phosphylated oxime (POX). POX is produced in stoichiometric amounts of reactivated enzyme and exhibits a significantly enhanced toxicity (inhibition rate constant) when compared to the parent OP. However, stability of POX under physiological conditions appears to be highly limited. Nevertheless, the presence of POX reveals a potential critical issue for both therapeutic efficacy in vivo and pharmacokinetic and pharmacodynamic (PK-PD) modelling based on cholinesterase activity data. Detailed characterization represents an important need for elaboration of the entire oxime pharmacology.Nevertheless, reports on POX toxicity and analysis are quite rare and may therefore be indicative of the challenge of POX analysis. This review provides a concise overview of chromatographic approaches applied to POX separation. Chromatography represents the key technology for POX purification and quantification in kinetic in vitro studies using buffers and biological fluids. Applications based on reversed-phase chromatography (RPC), ion pair chromatography (IPC) and an affinity approach as well as thin layer chromatography (TLC) are discussed and novel applications and data are presented. Copyright © 2010 John Wiley & Sons, Ltd.

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

PubMed

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O; Sperandio, Olivier

2010-03-05

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com.

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

PubMed Central

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O.; Sperandio, Olivier

2010-01-01

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com. PMID:20221258

Identification of compounds inhibiting the C-S lyase activity of a cell extract from a Staphylococcus sp. isolated from human skin.

PubMed

Egert, M; Höhne, H-M; Weber, T; Simmering, R; Banowski, B; Breves, R

2013-12-01

The C-S lyase activity of bacteria in the human armpit releases highly malodorous, volatile sulfur compounds from nonvolatile precursor molecules. Such compounds significantly contribute to human body odour. Hence, C-S lyase represents an attractive target for anti-body-odour cosmetic products. Here, aiming at a final use in an ethanol-based deodorant formulation, 267 compounds and compound mixtures were screened for their ability to inhibit the C-S lyase activity of a Stapyhlococcus sp. crude extract. Staphylococcus sp. Isolate 128, closely related to Staphylococcus hominis, was chosen as the test bacterium, as it showed a reproducibly high specific C-S lyase activity on three different culturing media. Using a photometric assay and benzylcysteine as substrate, six rather complex, plant-derived compound mixtures and five well defined chemical compounds or compound mixtures were identified as inhibitors, leading to an inhibition of ≥70% at concentrations of ≤0·5% in the assay. The inhibition data have demonstrated that compounds with two vicinal hydroxyl groups or one hydroxyl and one keto group bound to an aryl residue are characteristic for the inhibition. The substances identified as C-S lyase inhibitors have the potential to improve the performance of anti-body-odour cosmetic products, for example, ethanol-based deodorants. Bacterial C-S lyase represents one of the key enzymes involved in human body odour formation. The aim of this study was to identify compounds inhibiting the C-S lyase activity of a Staphylococcus sp. isolate from the human skin. The compounds identified as the best inhibitors are characterized by the following features: two vicinal hydroxyl groups or one hydroxyl and one keto group bound to an aryl residue. They might be used to improve the performance of cosmetic products aiming to prevent the formation of microbially caused human body odour, for example, ethanol-based deodorants. © 2013 The Society for Applied Microbiology.

Network pharmacology-based strategy for predicting active ingredients and potential targets of Yangxinshi tablet for treating heart failure.

PubMed

Chen, Langdong; Cao, Yan; Zhang, Hai; Lv, Diya; Zhao, Yahong; Liu, Yanjun; Ye, Guan; Chai, Yifeng

2018-01-31

Yangxinshi tablet (YXST) is an effective treatment for heart failure and myocardial infarction; it consists of 13 herbal medicines formulated according to traditional Chinese Medicine (TCM) practices. It has been used for the treatment of cardiovascular disease for many years in China. In this study, a network pharmacology-based strategy was used to elucidate the mechanism of action of YXST for the treatment of heart failure. Cardiovascular disease-related protein target and compound databases were constructed for YXST. A molecular docking platform was used to predict the protein targets of YXST. The affinity between proteins and ingredients was determined using surface plasmon resonance (SPR) assays. The action modes between targets and representative ingredients were calculated using Glide docking, and the related pathways were predicted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A protein target database containing 924 proteins was constructed; 179 compounds in YXST were identified, and 48 compounds with high relevance to the proteins were defined as representative ingredients. Thirty-four protein targets of the 48 representative ingredients were analyzed and classified into two categories: immune and cardiovascular systems. The SPR assay and molecular docking partly validated the interplay between protein targets and representative ingredients. Moreover, 28 pathways related to heart failure were identified, which provided directions for further research on YXST. This study demonstrated that the cardiovascular protective effect of YXST mainly involved the immune and cardiovascular systems. Through the research strategy based on network pharmacology, we analysis the complex system of YXST and found 48 representative compounds, 34 proteins and 28 related pathways of YXST, which could help us understand the underlying mechanism of YSXT's anti-heart failure effect. The network-based investigation could help researchers simplify the complex system of YXSY. It may also offer a feasible approach to decipher the chemical and pharmacological bases of other TCM formulas. Copyright © 2018 Elsevier B.V. All rights reserved.

Multiscale dispersion-state characterization of nanocomposites using optical coherence tomography

PubMed Central

Schneider, Simon; Eppler, Florian; Weber, Marco; Olowojoba, Ganiu; Weiss, Patrick; Hübner, Christof; Mikonsaari, Irma; Freude, Wolfgang; Koos, Christian

2016-01-01

Nanocomposite materials represent a success story of nanotechnology. However, development of nanomaterial fabrication still suffers from the lack of adequate analysis tools. In particular, achieving and maintaining well-dispersed particle distributions is a key challenge, both in material development and industrial production. Conventional methods like optical or electron microscopy need laborious, costly sample preparation and do not permit fast extraction of nanoscale structural information from statistically relevant sample volumes. Here we show that optical coherence tomography (OCT) represents a versatile tool for nanomaterial characterization, both in a laboratory and in a production environment. The technique does not require sample preparation and is applicable to a wide range of solid and liquid material systems. Large particle agglomerates can be directly found by OCT imaging, whereas dispersed nanoparticles are detected by model-based analysis of depth-dependent backscattering. Using a model system of polystyrene nanoparticles, we demonstrate nanoparticle sizing with high accuracy. We further prove the viability of the approach by characterizing highly relevant material systems based on nanoclays or carbon nanotubes. The technique is perfectly suited for in-line metrology in a production environment, which is demonstrated using a state-of-the-art compounding extruder. These experiments represent the first demonstration of multiscale nanomaterial characterization using OCT. PMID:27557544

Multiscale dispersion-state characterization of nanocomposites using optical coherence tomography.

PubMed

Schneider, Simon; Eppler, Florian; Weber, Marco; Olowojoba, Ganiu; Weiss, Patrick; Hübner, Christof; Mikonsaari, Irma; Freude, Wolfgang; Koos, Christian

2016-08-25

Nanocomposite materials represent a success story of nanotechnology. However, development of nanomaterial fabrication still suffers from the lack of adequate analysis tools. In particular, achieving and maintaining well-dispersed particle distributions is a key challenge, both in material development and industrial production. Conventional methods like optical or electron microscopy need laborious, costly sample preparation and do not permit fast extraction of nanoscale structural information from statistically relevant sample volumes. Here we show that optical coherence tomography (OCT) represents a versatile tool for nanomaterial characterization, both in a laboratory and in a production environment. The technique does not require sample preparation and is applicable to a wide range of solid and liquid material systems. Large particle agglomerates can be directly found by OCT imaging, whereas dispersed nanoparticles are detected by model-based analysis of depth-dependent backscattering. Using a model system of polystyrene nanoparticles, we demonstrate nanoparticle sizing with high accuracy. We further prove the viability of the approach by characterizing highly relevant material systems based on nanoclays or carbon nanotubes. The technique is perfectly suited for in-line metrology in a production environment, which is demonstrated using a state-of-the-art compounding extruder. These experiments represent the first demonstration of multiscale nanomaterial characterization using OCT.

Automatic analysis of quantitative NMR data of pharmaceutical compound libraries.

PubMed

Liu, Xuejun; Kolpak, Michael X; Wu, Jiejun; Leo, Gregory C

2012-08-07

In drug discovery, chemical library compounds are usually dissolved in DMSO at a certain concentration and then distributed to biologists for target screening. Quantitative (1)H NMR (qNMR) is the preferred method for the determination of the actual concentrations of compounds because the relative single proton peak areas of two chemical species represent the relative molar concentrations of the two compounds, that is, the compound of interest and a calibrant. Thus, an analyte concentration can be determined using a calibration compound at a known concentration. One particularly time-consuming step in the qNMR analysis of compound libraries is the manual integration of peaks. In this report is presented an automated method for performing this task without prior knowledge of compound structures and by using an external calibration spectrum. The script for automated integration is fast and adaptable to large-scale data sets, eliminating the need for manual integration in ~80% of the cases.

Identification and Structural Characterization of Naturally-Occurring Broad-Spectrum Cyclic Antibiotics Isolated from Paenibacillus

NASA Astrophysics Data System (ADS)

Knolhoff, Ann M.; Zheng, Jie; McFarland, Melinda A.; Luo, Yan; Callahan, John H.; Brown, Eric W.; Croley, Timothy R.

2015-08-01

The rise of antimicrobial resistance necessitates the discovery and/or production of novel antibiotics. Isolated strains of Paenibacillus alvei were previously shown to exhibit antimicrobial activity against a number of pathogens, such as E. coli, Salmonella, and methicillin-resistant Staphylococcus aureus (MRSA). The responsible antimicrobial compounds were isolated from these Paenibacillus strains and a combination of low and high resolution mass spectrometry with multiple-stage tandem mass spectrometry was used for identification. A group of closely related cyclic lipopeptides was identified, differing primarily by fatty acid chain length and one of two possible amino acid substitutions. Variation in the fatty acid length resulted in mass differences of 14 Da and yielded groups of related MSn spectra. Despite the inherent complexity of MS/MS spectra of cyclic compounds, straightforward analysis of these spectra was accomplished by determining differences in complementary product ion series between compounds that differ in molecular weight by 14 Da. The primary peptide sequence assignment was confirmed through genome mining; the combination of these analytical tools represents a workflow that can be used for the identification of complex antibiotics. The compounds also share amino acid sequence similarity to a previously identified broad-spectrum antibiotic isolated from Paenibacillus. The presence of such a wide distribution of related compounds produced by the same organism represents a novel class of broad-spectrum antibiotic compounds.

Cognitive Hypnotherapy for Accessing and Healing Emotional Injuries for Anxiety Disorders.

PubMed

Alladin, Assen

2016-07-01

Although anxiety disorders on the surface may appear simple, they often represent complex problems that are compounded by underlying factors. For these reasons, treatment of anxiety disorders should be individualized. This article describes cognitive hypnotherapy, an individual comprehensive treatment protocol that integrates cognitive, behavioral, mindfulness, psychodynamic, and hypnotic strategies in the management of anxiety disorders. The treatment approach is based on the self-wounds model of anxiety disorders, which provides the rationale for integrating diverse strategies in the psychotherapy for anxiety disorders. Due to its evidence-based and integrated nature, the psychotherapy described here provides accuracy, efficacy, and sophistication in the formulation and treatment of anxiety disorders. This model can be easily adapted to the understanding and treatment of other emotional disorders.

Neural integration underlying a time-compensated sun compass in the migratory monarch butterfly

PubMed Central

Shlizerman, Eli; Phillips-Portillo, James; Reppert, Steven M.

2016-01-01

Migrating Eastern North American monarch butterflies use a time-compensated sun compass to adjust their flight to the southwest direction. While the antennal genetic circadian clock and the azimuth of the sun are instrumental for proper function of the compass, it is unclear how these signals are represented on a neuronal level and how they are integrated to produce flight control. To address these questions, we constructed a receptive field model of the compound eye that encodes the solar azimuth. We then derived a neural circuit model, which integrates azimuthal and circadian signals to correct flight direction. The model demonstrates an integration mechanism, which produces robust trajectories reaching the southwest regardless of the time of day and includes a configuration for remigration. Comparison of model simulations with flight trajectories of butterflies in a flight simulator shows analogous behaviors and affirms the prediction that midday is the optimal time for migratory flight. PMID:27149852

Use of a parallel artificial membrane system to evaluate passive absorption and elimination in small fish.

PubMed

Kwon, Jung-Hwan; Katz, Lynn E; Liljestrand, Howard M

2006-12-01

A parallel artificial lipid membrane system was developed to mimic passive mass transfer of hydrophobic organic chemicals in fish. In this physical model system, a membrane filter-supported lipid bilayer separates two aqueous phases that represent the external and internal aqueous environments of fish. To predict bioconcentration kinetics in small fish with this system, literature absorption and elimination rates were analyzed with an allometric diffusion model to quantify the mass transfer resistances in the aqueous and lipid phases of fish. The effect of the aqueous phase mass transfer resistance was controlled by adjusting stirring intensity to mimic bioconcentration rates in small fish. Twenty-three simple aromatic hydrocarbons were chosen as model compounds for purposes of evaluation. For most of the selected chemicals, literature absorption/elimination rates fall into the range predicted from measured membrane permeabilities and elimination rates of the selected chemicals determined by the diffusion model system.

A process-based emission model of volatile organic compounds from silage sources on farms

NASA Astrophysics Data System (ADS)

Bonifacio, H. F.; Rotz, C. A.; Hafner, S. D.; Montes, F.; Cohen, M.; Mitloehner, F. M.

2017-03-01

Silage on dairy farms can emit large amounts of volatile organic compounds (VOCs), a precursor in the formation of tropospheric ozone. Because of the challenges associated with direct measurements, process-based modeling is another approach for estimating emissions of air pollutants from sources such as those from dairy farms. A process-based model for predicting VOC emissions from silage was developed and incorporated into the Integrated Farm System Model (IFSM, v. 4.3), a whole-farm simulation of crop, dairy, and beef production systems. The performance of the IFSM silage VOC emission model was evaluated using ethanol and methanol emissions measured from conventional silage piles (CSP), silage bags (SB), total mixed rations (TMR), and loose corn silage (LCS) at a commercial dairy farm in central California. With transport coefficients for ethanol refined using experimental data from our previous studies, the model performed well in simulating ethanol emission from CSP, TMR, and LCS; its lower performance for SB could be attributed to possible changes in face conditions of SB after silage removal that are not represented in the current model. For methanol emission, lack of experimental data for refinement likely caused the underprediction for CSP and SB whereas the overprediction observed for TMR can be explained as uncertainty in measurements. Despite these limitations, the model is a valuable tool for comparing silage management options and evaluating their relative effects on the overall performance, economics, and environmental impacts of farm production. As a component of IFSM, the silage VOC emission model was used to simulate a representative dairy farm in central California. The simulation showed most silage VOC emissions were from feed lying in feed lanes and not from the exposed face of silage storages. This suggests that mitigation efforts, particularly in areas prone to ozone non-attainment status, should focus on reducing emissions during feeding. For the simulated dairy farm, a reduction of around 30% was found if cows were housed and fed in a barn rather than in an open lot, and 23% if feeds were delivered as four feedings per day rather than as one. Reducing the exposed face of storage can also be useful. Simulated use of silage bags resulted in 90% and 18% reductions in emissions from the storage face and whole farm, respectively.

A model study of laboratory photooxidation experiments of mono- and sesquiterpenes

NASA Astrophysics Data System (ADS)

Capouet, M.; Vereecken, L.; Peeters, J.; Müller, J.

2006-12-01

The importance of monoterpenes in the atmosphere stems from their large emissions from plants, their high reactivity, and their role as precursors for Secondary Organic Aerosol (SOA) production. In order to quantify the impact of α-pinene oxidation (as representative of the monoterpenes) using a CTM, a detailed understanding of its oxidation mechanism is necessary. Past studies have investigated successfully the gas- phase OH-oxidation mechanism of α-pinene [Peeters et al., 2001; Vereecken and Peeters 2004; Capouet et al., 2004]. However, the SOA formation measured in laboratory experiments remains difficult to model, partly due to a poor understanding of the ozonolysis mechanism believed to be the dominant path to formation of condensable compounds. Very recently, Peeters and co-workers have developed a detailed mechanism for the α-pinene ozonolysis based on objective theoretical grounds. Both OH- and O3- oxidation mechanisms have been implemented in a box model and coupled to a module describing the gas/particle partitioning of the semi-volatile products on the basis of a vapour pressure prediction method [Capouet and Müller, 2006]. The photooxidation of primary products has been parameterized in order to evaluate the role of condensable compounds formed by secondary reactions. Simulations of a wide set of α-pinene photooxidation experiments reported in the literature have been performed. Results indicate that the calculated SOA contain a significant fraction of second generation products. Note in particular that our box model simulations as well as theoretical arguments contradict the gas-phase formation routes for pinic acid proposed in the literature and suggest a secondary origin for this compound. Contribution of the sesquiterpenes to biogenic non methane hydrocarbon emissions has been estimated from 9% to 28% in some regions in the U.S. Their high reactivity towards ozone and their complex chemistry make these compounds hardly accessible to theoretical and experimental study. Lately an increasing number of laboratory experiments have been performed and have reported that sesquiterpenes such as β- caryophyllene and α-humulene have much higher aerosol formation potentials than α-pinene on a mass basis. Using parameterizations similar to those developed previously for α-pinene, a simplified box model describing the oxidation of the sesquiterpenes and the related aerosol formation has been developed. Preliminary simulations of photooxidation experiments have been performed and are compared with the monoterpenes model results.

Chemical profiling analysis of Maca using UHPLC-ESI-Orbitrap MS coupled with UHPLC-ESI-QqQ MS and the neuroprotective study on its active ingredients

NASA Astrophysics Data System (ADS)

Zhou, Yanyan; Li, Peng; Brantner, Adelheid; Wang, Hongjie; Shu, Xinbin; Yang, Jian; Si, Nan; Han, Lingyu; Zhao, Haiyu; Bian, Baolin

2017-03-01

Lepidium meyenii (Maca), originated from Peru, has been cultivated widely in China as a popular health care food. However, the chemical and effective studies of Maca were less in-depth, which restricted its application seriously. To ensure the quality of Maca, a feasible and accurate strategy was established. One hundred and sixty compounds including 30 reference standards were identified in 6 fractions of methanol extract of Maca by UHPLC-ESI-Orbitrap MS. Among them, 15 representative active compounds were simultaneously determined in 17 samples by UHPLC-ESI-QqQ MS. The results suggested that Maca from Yunnan province was the potential substitute for the one from Peru. Meanwhile, the neuroprotective effects of Maca were investigated. Three fractions and two pure compounds showed strong activities in the 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP)-induced zebrafish model. Among them, 80% methanol elution fraction (Fr5) showed significant neuroprotective activity, followed by 100% part (Fr6). The inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) was a possible mechanism of its neuroprotective effect.

Chemical profiling analysis of Maca using UHPLC-ESI-Orbitrap MS coupled with UHPLC-ESI-QqQ MS and the neuroprotective study on its active ingredients

PubMed Central

Zhou, Yanyan; Li, Peng; Brantner, Adelheid; Wang, Hongjie; Shu, Xinbin; Yang, Jian; Si, Nan; Han, Lingyu; Zhao, Haiyu; Bian, Baolin

2017-01-01

Lepidium meyenii (Maca), originated from Peru, has been cultivated widely in China as a popular health care food. However, the chemical and effective studies of Maca were less in-depth, which restricted its application seriously. To ensure the quality of Maca, a feasible and accurate strategy was established. One hundred and sixty compounds including 30 reference standards were identified in 6 fractions of methanol extract of Maca by UHPLC-ESI-Orbitrap MS. Among them, 15 representative active compounds were simultaneously determined in 17 samples by UHPLC-ESI-QqQ MS. The results suggested that Maca from Yunnan province was the potential substitute for the one from Peru. Meanwhile, the neuroprotective effects of Maca were investigated. Three fractions and two pure compounds showed strong activities in the 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP)-induced zebrafish model. Among them, 80% methanol elution fraction (Fr5) showed significant neuroprotective activity, followed by 100% part (Fr6). The inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) was a possible mechanism of its neuroprotective effect. PMID:28304399

Chemical profiling analysis of Maca using UHPLC-ESI-Orbitrap MS coupled with UHPLC-ESI-QqQ MS and the neuroprotective study on its active ingredients.

PubMed

Zhou, Yanyan; Li, Peng; Brantner, Adelheid; Wang, Hongjie; Shu, Xinbin; Yang, Jian; Si, Nan; Han, Lingyu; Zhao, Haiyu; Bian, Baolin

2017-03-17

Lepidium meyenii (Maca), originated from Peru, has been cultivated widely in China as a popular health care food. However, the chemical and effective studies of Maca were less in-depth, which restricted its application seriously. To ensure the quality of Maca, a feasible and accurate strategy was established. One hundred and sixty compounds including 30 reference standards were identified in 6 fractions of methanol extract of Maca by UHPLC-ESI-Orbitrap MS. Among them, 15 representative active compounds were simultaneously determined in 17 samples by UHPLC-ESI-QqQ MS. The results suggested that Maca from Yunnan province was the potential substitute for the one from Peru. Meanwhile, the neuroprotective effects of Maca were investigated. Three fractions and two pure compounds showed strong activities in the 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP)-induced zebrafish model. Among them, 80% methanol elution fraction (Fr 5 ) showed significant neuroprotective activity, followed by 100% part (Fr 6 ). The inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) was a possible mechanism of its neuroprotective effect.

Blocking Alcoholic Steatosis in Mice with a Peripherally Restricted Purine Antagonist of the Type 1 Cannabinoid Receptor.

PubMed

Amato, George S; Manke, Amruta; Harris, Danni L; Wiethe, Robert W; Vasukuttan, Vineetha; Snyder, Rodney W; Lefever, Timothy W; Cortes, Ricardo; Zhang, Yanan; Wang, Shaobin; Runyon, Scott P; Maitra, Rangan

2018-05-24

Type 1 cannabinoid receptor (CB1) antagonists have demonstrated promise for the treatment of obesity, liver disease, metabolic syndrome, and dyslipidemias. However, the inhibition of CB1 receptors in the central nervous system can produce adverse effects, including depression, anxiety, and suicidal ideation. Efforts are now underway to produce peripherally restricted CB1 antagonists to circumvent CNS-associated undesirable effects. In this study, a series of analogues were explored in which the 4-aminopiperidine group of compound 2 was replaced with aryl- and heteroaryl-substituted piperazine groups both with and without a spacer. This resulted in mildly basic, potent antagonists of human CB1 (hCB1). The 2-chlorobenzyl piperazine, 25, was found to be potent ( K i = 8 nM); to be >1000-fold selective for hCB1 over hCB2; to have no hERG liability; and to possess favorable ADME properties including high oral absorption and negligible CNS penetration. Compound 25 was tested in a mouse model of alcohol-induced liver steatosis and found to be efficacious. Taken together, 25 represents an exciting lead compound for further clinical development or refinement.

Applied metabolomics in drug discovery.

PubMed

Cuperlovic-Culf, M; Culf, A S

2016-08-01

The metabolic profile is a direct signature of phenotype and biochemical activity following any perturbation. Metabolites are small molecules present in a biological system including natural products as well as drugs and their metabolism by-products depending on the biological system studied. Metabolomics can provide activity information about possible novel drugs and drug scaffolds, indicate interesting targets for drug development and suggest binding partners of compounds. Furthermore, metabolomics can be used for the discovery of novel natural products and in drug development. Metabolomics can enhance the discovery and testing of new drugs and provide insight into the on- and off-target effects of drugs. This review focuses primarily on the application of metabolomics in the discovery of active drugs from natural products and the analysis of chemical libraries and the computational analysis of metabolic networks. Metabolomics methodology, both experimental and analytical is fast developing. At the same time, databases of compounds are ever growing with the inclusion of more molecular and spectral information. An increasing number of systems are being represented by very detailed metabolic network models. Combining these experimental and computational tools with high throughput drug testing and drug discovery techniques can provide new promising compounds and leads.

Establishment of a novel immortalized human prostatic epithelial cell line stably expressing androgen receptor and its application for the functional screening of androgen receptor modulators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Shan; Wang, Ming-Wei; Yao, Xiaoqiang

2009-05-15

In this study, we developed a human prostatic epithelial cell line BPH-1-AR stably expressing AR by lentiviral transduction. Characterization by immunoblot and RT-PCR showed that AR was stably expressed in all representative BPH-1-AR clones. Androgen treatment induced a secretory differentiation phenotype in BPH-1-AR cells but suppressed their cell proliferation. Treatments with AR agonists induced transactivation of a transfected PSA-gene promoter reporter in BPH-1-AR cells, whereas this transactivation was suppressed by an AR antagonist flutamide, indicating that the transduced AR in BPH-1-AR cells was functional. Finally, we utilized BPH-1-AR cells to evaluate the androgenic activities and growth effects of five newlymore » developed non-steroidal compounds. Results showed that these compounds showed androgenic activities and growth-inhibitory effects on BPH-1-AR cells. Our results showed that BPH-1-AR cell line would be a valuable in vitro model for the study of androgen-regulated processes in prostatic epithelial cells and identification of compounds with AR-modulating activities.« less

Aureonitol, a Fungi-Derived Tetrahydrofuran, Inhibits Influenza Replication by Targeting Its Surface Glycoprotein Hemagglutinin.

PubMed

Sacramento, Carolina Q; Marttorelli, Andressa; Fintelman-Rodrigues, Natalia; de Freitas, Caroline S; de Melo, Gabrielle R; Rocha, Marco E N; Kaiser, Carlos R; Rodrigues, Katia F; da Costa, Gisela L; Alves, Cristiane M; Santos-Filho, Osvaldo; Barbosa, Jussara P; Souza, Thiago Moreno L

2015-01-01

The influenza virus causes acute respiratory infections, leading to high morbidity and mortality in groups of patients at higher risk. Antiviral drugs represent the first line of defense against influenza, both for seasonal infections and pandemic outbreaks. Two main classes of drugs against influenza are in clinical use: M2-channel blockers and neuraminidase inhibitors. Nevertheless, because influenza strains that are resistant to these antivirals have been described, the search for novel compounds with different mechanisms of action is necessary. Here, we investigated the anti-influenza activity of a fungi-derived natural product, aureonitol. This compound inhibited influenza A and B virus replication. This compound was more effective against influenza A(H3N2), with an EC50 of 100 nM. Aureonitol cytoxicity was also very low, with a CC50 value of 1426 μM. Aureonitol inhibited influenza hemagglutination and, consequently, significantly impaired virus adsorption. Molecular modeling studies revealed that aureonitol docked in the sialic acid binding site of hemagglutinin, forming hydrogen bonds with highly conserved residues. Altogether, our results indicate that the chemical structure of aureonitol is promising for future anti-influenza drug design.

Aureonitol, a Fungi-Derived Tetrahydrofuran, Inhibits Influenza Replication by Targeting Its Surface Glycoprotein Hemagglutinin

PubMed Central

Sacramento, Carolina Q.; Marttorelli, Andressa; Fintelman-Rodrigues, Natalia; de Freitas, Caroline S.; de Melo, Gabrielle R.; Rocha, Marco E. N.; Kaiser, Carlos R.; Rodrigues, Katia F.; da Costa, Gisela L.; Alves, Cristiane M.; Santos-Filho, Osvaldo; Barbosa, Jussara P.; Souza, Thiago Moreno L.

2015-01-01

The influenza virus causes acute respiratory infections, leading to high morbidity and mortality in groups of patients at higher risk. Antiviral drugs represent the first line of defense against influenza, both for seasonal infections and pandemic outbreaks. Two main classes of drugs against influenza are in clinical use: M2-channel blockers and neuraminidase inhibitors. Nevertheless, because influenza strains that are resistant to these antivirals have been described, the search for novel compounds with different mechanisms of action is necessary. Here, we investigated the anti-influenza activity of a fungi-derived natural product, aureonitol. This compound inhibited influenza A and B virus replication. This compound was more effective against influenza A(H3N2), with an EC50 of 100 nM. Aureonitol cytoxicity was also very low, with a CC50 value of 1426 μM. Aureonitol inhibited influenza hemagglutination and, consequently, significantly impaired virus adsorption. Molecular modeling studies revealed that aureonitol docked in the sialic acid binding site of hemagglutinin, forming hydrogen bonds with highly conserved residues. Altogether, our results indicate that the chemical structure of aureonitol is promising for future anti-influenza drug design. PMID:26462111

Developing a novel dual PI3K–mTOR inhibitor from the prodrug of a metabolite

PubMed Central

Zhou, Yan; Zhang, Genyan; Wang, Feng; Wang, Jin; Ding, Yanwei; Li, Xinyu; Shi, Chongtie; Li, Jiakui; Shih, Chengkon; You, Song

2017-01-01

This study presents a process of developing a novel PI3K–mTOR inhibitor through the prodrug of a metabolite. The lead compound (compound 1) was identified with similar efficacy as that of NVP-BEZ235 in a tumor xenograft model, but the exposure of compound 1 was much lower than that of NVP-BEZ235. After reanalysis of the blood sample, a major metabolite (compound 2) was identified. Compound 2 exerted similar in vitro activity as compound 1, which indicated that compound 2 was an active metabolite and that the in vivo efficacy in the animal model came from compound 2 instead of compound 1. However, compound 1 was metabolized into compound 2 predominantly in the liver microsomes of mouse, but not in the liver microsomes of rat, dog, or human. In order to translate the efficacy in the animal model into clinical development or predict the pharmacokinetic/pharmacodynamic parameters in the clinical study using a preclinical model, we developed the metabolite (compound 2) instead of compound 1. Due to the low bioavailability of compound 2, its prodrug (compound 3) was designed and synthesized to improve the solubility. The prodrug was quickly converted to compound 2 through both intravenous and oral administrations. Because the prodrug (compound 3) did not improve the oral exposure of compound 2, developing compound 3 as an intravenous drug was considered by our team, and the latest results will be reported in the future. PMID:29118584

Investigation of common fluorophores for the detection of nitrated explosives by fluorescence quenching.

PubMed

Meaney, Melissa S; McGuffin, Victoria L

2008-03-03

Previous studies have indicated that nitrated explosives may be detected by fluorescence quenching of pyrene and related compounds. The use of pyrene, however, invokes numerous health and waste disposal hazards. In the present study, ten safer fluorophores are identified for quenching detection of target nitrated compounds. Initially, Stern-Volmer constants are measured for each fluorophore with nitrobenzene and 4-nitrotoluene to determine the sensitivity of the quenching interaction. For quenching constants greater than 50 M(-1), sensitivity and selectivity are investigated further using an extended set of target quenchers. Nitromethane, nitrobenzene, 4-nitrotoluene, and 2,6-dinitrotoluene are chosen to represent nitrated explosives and their degradation products; aniline, benzoic acid, and phenol are chosen to represent potential interfering compounds. Among the fluorophores investigated, purpurin, malachite green, and phenol red demonstrate the greatest sensitivity and selectivity for nitrated compounds. Correlation of the quenching rate constants for these fluorophores to Rehm-Weller theory suggests an electron-transfer quenching mechanism. As a result of the large quenching constants, purpurin, malachite green, and phenol red are the most promising for future detection of nitrated explosives via fluorescence quenching.

Compress compound images in H.264/MPGE-4 AVC by exploiting spatial correlation.

PubMed

Lan, Cuiling; Shi, Guangming; Wu, Feng

2010-04-01

Compound images are a combination of text, graphics and natural image. They present strong anisotropic features, especially on the text and graphics parts. These anisotropic features often render conventional compression inefficient. Thus, this paper proposes a novel coding scheme from the H.264 intraframe coding. In the scheme, two new intramodes are developed to better exploit spatial correlation in compound images. The first is the residual scalar quantization (RSQ) mode, where intrapredicted residues are directly quantized and coded without transform. The second is the base colors and index map (BCIM) mode that can be viewed as an adaptive color quantization. In this mode, an image block is represented by several representative colors, referred to as base colors, and an index map to compress. Every block selects its coding mode from two new modes and the previous intramodes in H.264 by rate-distortion optimization (RDO). Experimental results show that the proposed scheme improves the coding efficiency even more than 10 dB at most bit rates for compound images and keeps a comparable efficient performance to H.264 for natural images.

Screening of pharmacokinetic properties of fifty dihydropyrimidin(thi)one derivatives using a combo of in vitro and in silico assays.

PubMed

Matias, Mariana; Fortuna, Ana; Bicker, Joana; Silvestre, Samuel; Falcão, Amílcar; Alves, Gilberto

2017-11-15

The heterocycles dihydropyrimidin(thi)ones have been under intensive pharmacological research, but their pharmacokinetic properties remain almost unknown. Herein, fifty dihydropyrimidin(thi)ones were submitted to in vitro screening tests using parallel artificial membrane permeability assays (PAMPA) to evaluate their apparent permeability (Papp) through intestinal membrane and blood-brain barrier models, and cell-based assays to assess their interference on the efflux transporter P-glycoprotein (P-gp). Moreover, a set of kinetic and toxicological parameters was also estimated employing a new computational tool, the pkCSM. The in vitro results suggested that 82% of the test compounds have good intestinal permeability (Papp>1.1×10 -6 cm/s), and 66% of these are also expected to exhibit good permeability through blood-brain barrier (Papp>2.0×10 -6 cm/s); these findings are consistent with a high transport rate by passive transcellular pathway. In both PAMPA models, thiourea derivatives presented higher Papp values than the respective urea analogues, which were further corroborated by in silico predictions. The in vitro results also suggested a low extent of plasma protein binding for all compounds (Papp<1.0×10 -5 cm/s), and these findings were also supported by in silico data (unbound fraction ranging from 0.13 to 0.59). In addition, although approximately half of the compounds did not modulate P-gp at the tested concentrations (10 and 50μM), nine of them presented a trend to induce P-gp and particularly the chlorinated compounds exhibited a marked P-gp inhibition at 50μM. Furthermore, the in silico predictions suggested that half of the compounds have hepatotoxic potential. Overall, within this group of compounds, the thiourea derivatives containing an unsubstituted or a monosubstituted (NO 2 , CH 3 , OCH 3 ) phenyl ring attached to the position 4 of the dihydropyrimidine ring represented the most promising structures and should be considered in the subsequent studies of the development of new structurally related drug candidates. Copyright © 2017 Elsevier B.V. All rights reserved.

Tetracyclic Truncated Analogue of the Marine Toxin Gambierol Modifies NMDA, Tau, and Amyloid β Expression in Mice Brains: Implications in AD Pathology.

PubMed

Alonso, Eva; Vieira, Andrés C; Rodriguez, Inés; Alvariño, Rebeca; Gegunde, Sandra; Fuwa, Haruhiko; Suga, Yuto; Sasaki, Makoto; Alfonso, Amparo; Cifuentes, José Manuel; Botana, Luis M

2017-06-21

Gambierol and its two, tetra- and heptacyclic, analogues have been previously proved as promising molecules for the modulation of Alzheimer's disease (AD) hallmarks in primary cortical neurons of 3xTg-AD fetuses. In this work, the effect of the tetracyclic analogue of gambierol was tested in vivo in 3xTg-AD mice (10 months old) after 1 month of weekly treatment with 50 μg/kg. Adverse effects were not reported throughout the whole treatment period and no pathological signs were observed for the analyzed organs. The compound was found in brain samples after intraperitoneal injection. The tetracyclic analogue of gambierol elicited a decrease of amyloid β 1-42 levels and a dose-dependent inhibition of β-secretase enzyme-1 activity. Moreover, this compound also reduced the phosphorylation of tau at the 181 and 159/163 residues with an increase of the inactive isoform of the glycogen synthase kinase-3β. In accordance with our in vitro neuronal model, this compound produced a reduction in the N2A subunit of the N-methyl-d-aspartate (NMDA) receptor. The combined effect of this compound on amyloid β 1-42 and tau phosphorylation represents a multitarget therapeutic approach for AD which might be more effective for this multifactorial and complex neurodegenerative disease than the current treatments.

The Design and Development of Potent Small Molecules as Anticancer Agents Targeting EGFR TK and Tubulin Polymerization

PubMed Central

Ihmaid, Saleh; Ahmed, Hany E. A.; Zayed, Mohamed F.

2018-01-01

Some novel anthranilate diamides derivatives 4a–e, 6a–c and 9a–d were designed and synthesized to be evaluated for their in vitro anticancer activity. Structures of all newly synthesized compounds were confirmed by infra-red (IR), high-resolution mass (HR-MS) spectra, 1H nuclear magnetic resonance (NMR) and 13C nuclear magnetic resonance (NMR) analyses. Cytotoxic screening was performed according to (3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazolium bromide) tetrazolium (MTT) assay method using erlotinib as a reference drug against two different types of breast cancer cells. The molecular docking study was performed for representative compounds against two targets, epidermal growth factor receptor (EGFR) and tubulin in colchicine binding site to assess their binding affinities in order to rationalize their anticancer activity in a qualitative way. The data obtained from the molecular modeling was correlated with that obtained from the biological screening. These data showed considerable anticancer activity for these newly synthesized compounds. Biological data for most of the anthranilate diamide showed excellent activity with nanomolar or sub nanomolar half maximal inhibitory concentration (IC50) values against tumor cells. EGFR tyrosine kinase (TK) inhibition assay, tubulin inhibition assay and apoptosis analysis were performed for selected compounds to get more details about their mechanism of action. Extensive structure activity relationship (SAR) analyses were also carried out. PMID:29385728

Rebelling against the (Insulin) Resistance: A Review of the Proposed Insulin-Sensitizing Actions of Soybeans, Chickpeas, and Their Bioactive Compounds

PubMed Central

Zahradka, Peter

2018-01-01

Insulin resistance is a major risk factor for diseases such as type 2 diabetes and metabolic syndrome. Current methods for management of insulin resistance include pharmacological therapies and lifestyle modifications. Several clinical studies have shown that leguminous plants such as soybeans and pulses (dried beans, dried peas, chickpeas, lentils) are able to reduce insulin resistance and related type 2 diabetes parameters. However, to date, no one has summarized the evidence supporting a mechanism of action for soybeans and pulses that explains their ability to lower insulin resistance. While it is commonly assumed that the biological activities of soybeans and pulses are due to their antioxidant activities, these bioactive compounds may operate independent of their antioxidant properties and, thus, their ability to potentially improve insulin sensitivity via alternative mechanisms needs to be acknowledged. Based on published studies using in vivo and in vitro models representing insulin resistant states, the proposed mechanisms of action for insulin-sensitizing actions of soybeans, chickpeas, and their bioactive compounds include increasing glucose transporter-4 levels, inhibiting adipogenesis by down-regulating peroxisome proliferator-activated receptor-γ, reducing adiposity, positively affecting adipokines, and increasing short-chain fatty acid-producing bacteria in the gut. Therefore, this review will discuss the current evidence surrounding the proposed mechanisms of action for soybeans and certain pulses, and their bioactive compounds, to effectively reduce insulin resistance. PMID:29601521

Anti-inflammatory effects of compounds alpha-humulene and (-)-trans-caryophyllene isolated from the essential oil of Cordia verbenacea.

PubMed

Fernandes, Elizabeth S; Passos, Giselle F; Medeiros, Rodrigo; da Cunha, Fernanda M; Ferreira, Juliano; Campos, Maria M; Pianowski, Luiz F; Calixto, João B

2007-08-27

This study evaluated the anti-inflammatory properties of two sesquiterpenes isolated from Cordia verbenacea's essential oil, alpha-humulene and (-)-trans-caryophyllene. Our results revealed that oral treatment with both compounds displayed marked inhibitory effects in different inflammatory experimental models in mice and rats. alpha-humulene and (-)-trans-caryophyllene were effective in reducing platelet activating factor-, bradykinin- and ovoalbumin-induced mouse paw oedema, while only alpha-humulene was able to diminish the oedema formation caused by histamine injection. Also, both compounds had important inhibitory effects on the mouse and rat carrageenan-induced paw oedema. Systemic treatment with alpha-humulene largely prevented both tumor necrosis factor-alpha (TNFalpha) and interleukin-1beta (IL-1beta) generation in carrageenan-injected rats, whereas (-)-trans-caryophyllene diminished only TNFalpha release. Furthermore, both compounds reduced the production of prostaglandin E(2) (PGE(2)), as well as inducible nitric oxide synthase (iNOS) and cyclooxygenase (COX-2) expression, induced by the intraplantar injection of carrageenan in rats. The anti-inflammatory effects of alpha-humulene and (-)-trans-caryophyllene were comparable to those observed in dexamethasone-treated animals, used as positive control drug. All these findings indicate that alpha-humulene and (-)-trans-caryophyllene, derived from the essential oil of C. verbenacea, might represent important tools for the management and/or treatment of inflammatory diseases.

Discovery of new MD2 inhibitor from chalcone derivatives with anti-inflammatory effects in LPS-induced acute lung injury

PubMed Central

Zhang, Yali; Wu, Jianzhang; Ying, Shilong; Chen, Gaozhi; Wu, Beibei; Xu, Tingting; Liu, Zhiguo; Liu, Xing; Huang, Lehao; Shan, Xiaoou; Dai, Yuanrong; Liang, Guang

2016-01-01

Acute lung injury (ALI) is a life-threatening acute inflammatory disease with limited options available for therapy. Myeloid differentiation protein 2, a co-receptor of TLR4, is absolutely required for TLR4 sense LPS, and represents an attractive target for treating severe inflammatory diseases. In this study, we designed and synthesized 31 chalcone derivatives that contain the moiety of (E)-4-phenylbut-3-en-2-one, which we consider the core structure of current MD2 inhibitors. We first evaluated the anti-inflammatory activities of these compounds in MPMs. For the most active compound 20, we confirmed that it is a specific MD2 inhibitor through a series of biochemical experiments and elucidated that it binds to the hydrophobic pocket of MD2 via hydrogen bonds with Arg90 and Tyr102 residues. Compound 20 also blocked the LPS-induced activation of TLR4/MD2 -downstream pro-inflammatory MAPKs/NF-κB signaling pathways. In a rat model with ALI induced by intracheal LPS instillation, administration with compound 20 exhibited significant protective effect against ALI, accompanied by the inhibition of TLR4/MD2 complex formation in lung tissues. Taken together, the results of this study suggest the specific MD2 inhibitor from chalcone derivatives we identified is a potential candidate for treating acute inflammatory diseases. PMID:27118147

Identification of quinazoline based inhibitors of IRAK4 for the treatment of inflammation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Graham F.; Altman, Michael D.; Andresen, Brian

Interleukin-1 receptor associated kinase 4 (IRAK4) has been implicated in IL-1R and TLR based signaling. Therefore selective inhibition of the kinase activity of this protein represents an attractive target for the treatment of inflammatory diseases. Medicinal chemistry optimization of high throughput screening (HTS) hits with the help of structure based drug design led to the identification of orally-bioavailable quinazoline based IRAK4 inhibitors with excellent pharmacokinetic profile and kinase selectivity. These highly selective IRAK4 compounds show activity in vivo via oral dosing in a TLR7 driven model of inflammation.