Atom-type-based AI topological descriptors: application in structure-boiling point correlations of oxo organic compounds.

PubMed

Ren, Biye

2003-01-01

Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.

Cytotoxic lanostane-type triterpenoids from the fruiting bodies of Ganoderma lucidum and their structure-activity relationships.

PubMed

Chen, Shaodan; Li, Xiangmin; Yong, Tianqiao; Wang, Zhanggen; Su, Jiyan; Jiao, Chunwei; Xie, Yizhen; Yang, Burton B

2017-02-07

We conducted a study of Ganoderma lucidum metabolites and isolated 35 lanostane-type triterpenoids, including 5 new ganoderols (1-5). By spectroscopy, we compared the structures of these compounds with known related compounds in this group. All of the isolated compounds were assayed for their effect against the human breast carcinoma cell line MDA-MB-231 and hepatocellular carcinoma cell line HepG2. Corresponding three-dimensional quantitative structure-activity relationship (3D-QSAR) models were built and analyzed using Discovery Studio. These results provide further evidence for anti-cancer constituents within Ganoderma lucidum, and may provide a theoretical foundation for designing novel therapeutic compounds.

Cytotoxic lanostane-type triterpenoids from the fruiting bodies of Ganoderma lucidum and their structure–activity relationships

PubMed Central

Wang, Zhanggen; Su, Jiyan; Jiao, Chunwei; Xie, Yizhen; Yang, Burton B.

2017-01-01

We conducted a study of Ganoderma lucidum metabolites and isolated 35 lanostane-type triterpenoids, including 5 new ganoderols (1-5). By spectroscopy, we compared the structures of these compounds with known related compounds in this group. All of the isolated compounds were assayed for their effect against the human breast carcinoma cell line MDA-MB-231 and hepatocellular carcinoma cell line HepG2. Corresponding three-dimensional quantitative structure–activity relationship (3D-QSAR) models were built and analyzed using Discovery Studio. These results provide further evidence for anti-cancer constituents within Ganoderma lucidum, and may provide a theoretical foundation for designing novel therapeutic compounds. PMID:28052025

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.

Identification of potential influenza virus endonuclease inhibitors through virtual screening based on the 3D-QSAR model.

PubMed

Kim, J; Lee, C; Chong, Y

2009-01-01

Influenza endonucleases have appeared as an attractive target of antiviral therapy for influenza infection. With the purpose of designing a novel antiviral agent with enhanced biological activities against influenza endonuclease, a three-dimensional quantitative structure-activity relationships (3D-QSAR) model was generated based on 34 influenza endonuclease inhibitors. The comparative molecular similarity index analysis (CoMSIA) with a steric, electrostatic and hydrophobic (SEH) model showed the best correlative and predictive capability (q(2) = 0.763, r(2) = 0.969 and F = 174.785), which provided a pharmacophore composed of the electronegative moiety as well as the bulky hydrophobic group. The CoMSIA model was used as a pharmacophore query in the UNITY search of the ChemDiv compound library to give virtual active compounds. The 3D-QSAR model was then used to predict the activity of the selected compounds, which identified three compounds as the most likely inhibitor candidates.

Decomposition of the compound Atwood machine

NASA Astrophysics Data System (ADS)

Lopes Coelho, R.

2017-11-01

Non-standard solving strategies for the compound Atwood machine problem have been proposed. The present strategy is based on a very simple idea. Taking an Atwood machine and replacing one of its bodies by another Atwood machine, we have a compound machine. As this operation can be repeated, we can construct any compound Atwood machine. This rule of construction is transferred to a mathematical model, whereby the equations of motion are obtained. The only difference between the machine and its model is that instead of pulleys and bodies, we have reference frames that move solidarily with these objects. This model provides us with the accelerations in the non-inertial frames of the bodies, which we will use to obtain the equations of motion. This approach to the problem will be justified by the Lagrange method and exemplified by machines with six and eight bodies.

Designing Multi-target Compound Libraries with Gaussian Process Models.

PubMed

Bieler, Michael; Reutlinger, Michael; Rodrigues, Tiago; Schneider, Petra; Kriegl, Jan M; Schneider, Gisbert

2016-05-01

We present the application of machine learning models to selecting G protein-coupled receptor (GPCR)-focused compound libraries. The library design process was realized by ant colony optimization. A proprietary Boehringer-Ingelheim reference set consisting of 3519 compounds tested in dose-response assays at 11 GPCR targets served as training data for machine learning and activity prediction. We compared the usability of the proprietary data with a public data set from ChEMBL. Gaussian process models were trained to prioritize compounds from a virtual combinatorial library. We obtained meaningful models for three of the targets (5-HT2c , MCH, A1), which were experimentally confirmed for 12 of 15 selected and synthesized or purchased compounds. Overall, the models trained on the public data predicted the observed assay results more accurately. The results of this study motivate the use of Gaussian process regression on public data for virtual screening and target-focused compound library design. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Reactions of Free Radicals with Nitro-Compounds and Nitrates

DTIC Science & Technology

1981-03-31

PAGE(I/hmm a•Ia ntatemd the fragment derived from the nitrates but not from the nitro-compounds could undergo exothermic rearrangement. Product analyses...compounds could undergo exothermic rearrangement. Product analyses and computer modelling were undertaken, these provided a clear explanation of why the...Nitrate 14 Reaction of Oxygen Atoms with Nitromethane 16 Reaction of Oxygen Atoms with Nitroethane 17 Products from Nitrocompounds 18 Effect of Carbon

Identification of intestinal loss of a drug through physiologically based pharmacokinetic simulation of plasma concentration-time profiles.

PubMed

Peters, Sheila Annie

2008-01-01

Despite recent advances in understanding of the role of the gut as a metabolizing organ, recognition of gut wall metabolism and/or other factors contributing to intestinal loss of a compound has been a challenging task due to the lack of well characterized methods to distinguish it from first-pass hepatic extraction. The implications of identifying intestinal loss of a compound in drug discovery and development can be enormous. Physiologically based pharmacokinetic (PBPK) simulations of pharmacokinetic profiles provide a simple, reliable and cost-effective way to understand the mechanisms underlying pharmacokinetic processes. The purpose of this article is to demonstrate the application of PBPK simulations in bringing to light intestinal loss of orally administered drugs, using two example compounds: verapamil and an in-house compound that is no longer in development (referred to as compound A in this article). A generic PBPK model, built in-house using MATLAB software and incorporating absorption, metabolism, distribution, biliary and renal elimination models, was employed for simulation of concentration-time profiles. Modulation of intrinsic hepatic clearance and tissue distribution parameters in the generic PBPK model was done to achieve a good fit to the observed intravenous pharmacokinetic profiles of the compounds studied. These optimized clearance and distribution parameters are expected to be invariant across different routes of administration, as long as the kinetics are linear, and were therefore employed to simulate the oral profiles of the compounds. For compounds with reasonably good solubility and permeability, an area under the concentration-time curve for the simulated oral profile that far exceeded the observed would indicate some kind of loss in the intestine. PBPK simulations applied to compound A showed substantial loss of the compound in the gastrointestinal tract in humans but not in rats. This accounted for the lower bioavailability of the compound in humans than in rats. PBPK simulations of verapamil identified gut wall metabolism, well established in the literature, and showed large interspecies differences with respect to both gut wall metabolism and drug-induced delays in gastric emptying. Mechanistic insights provided by PBPK simulations can be very valuable in answering vital questions in drug discovery and development. However, such applications of PBPK models are limited by the lack of accurate inputs for clearance and distribution. This article demonstrates a successful application of PBPK simulations to identify and quantify intestinal loss of two model compounds in rats and humans. The limitation of inaccurate inputs for the clearance and distribution parameters was overcome by optimizing these parameters through fitting intravenous profiles. The study also demonstrated that the large interspecies differences associated with gut wall metabolism and gastric emptying, evident for the compounds studied, make animal model extrapolations to humans unreliable. It is therefore important to do PBPK simulations of human pharmacokinetic profiles to understand the relevance of intestinal loss of a compound in humans.

Biological activity and molecular docking studies of curcumin-related α,β-unsaturated carbonyl-based synthetic compounds as anticancer agents and mushroom tyrosinase inhibitors.

PubMed

Bukhari, Syed Nasir Abbas; Jantan, Ibrahim; Unsal Tan, Oya; Sher, Muhammad; Naeem-Ul-Hassan, M; Qin, Hua-Li

2014-06-18

Hyperpigmentation in human skin and enzymatic browning in fruits, which are caused by tyrosinase enzyme, are not desirable. Investigations in the discovery of tyrosinase enzyme inhibitors and search for improved cytotoxic agents continue to be an important line in drug discovery and development. In present work, a new series of 30 compounds bearing α,β-unsaturated carbonyl moiety was designed and synthesized following curcumin as model. All compounds were evaluated for their effects on human cancer cell lines and mushroom tyrosinase enzyme. Moreover, the structure-activity relationships of these compounds are also explained. Molecular modeling studies of these new compounds were carried out to explore interactions with tyrosinase enzyme. Synthetic curcumin-like compounds (2a-b) were identified as potent anticancer agents with 81-82% cytotoxicity. Five of these newly synthesized compounds (1a, 8a-b, 10a-b) emerged to be the potent inhibitors of mushroom tyrosinase, providing further insight into designing compounds useful in fields of food, health, and agriculture.

Data Mining and Machine Learning Models for Predicting Drug Likeness and their Disease or Organ Category

NASA Astrophysics Data System (ADS)

Yosipof, Abraham; Guedes, Rita C.; García-Sosa, Alfonso T.

2018-05-01

Data mining approaches can uncover underlying patterns in chemical and pharmacological property space decisive for drug discovery and development. Two of the most common approaches are visualization and machine learning methods. Visualization methods use dimensionality reduction techniques in order to reduce multi-dimension data into 2D or 3D representations with a minimal loss of information. Machine learning attempts to find correlations between specific activities or classifications for a set of compounds and their features by means of recurring mathematical models. Both models take advantage of the different and deep relationships that can exist between features of compounds, and helpfully provide classification of compounds based on such features. Drug-likeness has been studied from several viewpoints, but here we provide the first implementation in chemoinformatics of the t-Distributed Stochastic Neighbor Embedding (t-SNE) method for the visualization and the representation of chemical space, and the use of different machine learning methods separately and together to form a new ensemble learning method called AL Boost. The models obtained from AL Boost synergistically combine decision tree, random forests (RF), support vector machine (SVM), artificial neuronal network (ANN), k nearest neighbors (kNN), and logistic regression models. In this work, we show that together they form a predictive model that not only improves the predictive force but also decreases bias. This resulted in a corrected classification rate of over 0.81, as well as higher sensitivity and specificity rates for the models. In addition, separation and good models were also achieved for disease categories such as antineoplastic compounds and nervous system diseases, among others. Such models can be used to guide decision on the feature landscape of compounds and their likeness to either drugs or other characteristics, such as specific or multiple disease-category(ies) or organ(s) of action of a molecule.

Data Mining and Machine Learning Models for Predicting Drug Likeness and Their Disease or Organ Category.

PubMed

Yosipof, Abraham; Guedes, Rita C; García-Sosa, Alfonso T

2018-01-01

Data mining approaches can uncover underlying patterns in chemical and pharmacological property space decisive for drug discovery and development. Two of the most common approaches are visualization and machine learning methods. Visualization methods use dimensionality reduction techniques in order to reduce multi-dimension data into 2D or 3D representations with a minimal loss of information. Machine learning attempts to find correlations between specific activities or classifications for a set of compounds and their features by means of recurring mathematical models. Both models take advantage of the different and deep relationships that can exist between features of compounds, and helpfully provide classification of compounds based on such features or in case of visualization methods uncover underlying patterns in the feature space. Drug-likeness has been studied from several viewpoints, but here we provide the first implementation in chemoinformatics of the t-Distributed Stochastic Neighbor Embedding (t-SNE) method for the visualization and the representation of chemical space, and the use of different machine learning methods separately and together to form a new ensemble learning method called AL Boost. The models obtained from AL Boost synergistically combine decision tree, random forests (RF), support vector machine (SVM), artificial neural network (ANN), k nearest neighbors (kNN), and logistic regression models. In this work, we show that together they form a predictive model that not only improves the predictive force but also decreases bias. This resulted in a corrected classification rate of over 0.81, as well as higher sensitivity and specificity rates for the models. In addition, separation and good models were also achieved for disease categories such as antineoplastic compounds and nervous system diseases, among others. Such models can be used to guide decision on the feature landscape of compounds and their likeness to either drugs or other characteristics, such as specific or multiple disease-category(ies) or organ(s) of action of a molecule.

Ionic liquid [OMIm][OAc] directly inducing oxidation cleavage of the β-O-4 bond of lignin model compounds.

PubMed

Yang, Yingying; Fan, Honglei; Meng, Qinglei; Zhang, Zhaofu; Yang, Guanying; Han, Buxing

2017-08-03

We explored the oxidation reactions of lignin model compounds directly induced by ionic liquids under metal-free conditions. In this work, it was found that ionic liquid 1-octyl-3-methylimidazolium acetate as a solvent could promote the aerobic oxidation of lignin model compound 2-phenoxyacetophenone (1) and the yields of phenol and benzoic acid from 1 could be as high as 96% and 86%, respectively. A possible reaction pathway was proposed based on a series of control experiments. An acetate anion from the ionic liquid attacked the hydrogen from the β-carbon thereby inducing the cleavage of the C-O bond of the aromatic ether. Furthermore, it was found that 2-(2-methoxyphenoxy)-1-phenylethanone (4) with a methoxyl group could also be transformed into aromatic products in this simple reaction system and the yields of phenol and benzoic acid from 4 could be as high as 98% and 85%, respectively. This work provides a simple way for efficient transformation of lignin model compounds.

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.

eTOXlab, an open source modeling framework for implementing predictive models in production environments.

PubMed

Carrió, Pau; López, Oriol; Sanz, Ferran; Pastor, Manuel

2015-01-01

Computational models based in Quantitative-Structure Activity Relationship (QSAR) methodologies are widely used tools for predicting the biological properties of new compounds. In many instances, such models are used as a routine in the industry (e.g. food, cosmetic or pharmaceutical industry) for the early assessment of the biological properties of new compounds. However, most of the tools currently available for developing QSAR models are not well suited for supporting the whole QSAR model life cycle in production environments. We have developed eTOXlab; an open source modeling framework designed to be used at the core of a self-contained virtual machine that can be easily deployed in production environments, providing predictions as web services. eTOXlab consists on a collection of object-oriented Python modules with methods mapping common tasks of standard modeling workflows. This framework allows building and validating QSAR models as well as predicting the properties of new compounds using either a command line interface or a graphic user interface (GUI). Simple models can be easily generated by setting a few parameters, while more complex models can be implemented by overriding pieces of the original source code. eTOXlab benefits from the object-oriented capabilities of Python for providing high flexibility: any model implemented using eTOXlab inherits the features implemented in the parent model, like common tools and services or the automatic exposure of the models as prediction web services. The particular eTOXlab architecture as a self-contained, portable prediction engine allows building models with confidential information within corporate facilities, which can be safely exported and used for prediction without disclosing the structures of the training series. The software presented here provides full support to the specific needs of users that want to develop, use and maintain predictive models in corporate environments. The technologies used by eTOXlab (web services, VM, object-oriented programming) provide an elegant solution to common practical issues; the system can be installed easily in heterogeneous environments and integrates well with other software. Moreover, the system provides a simple and safe solution for building models with confidential structures that can be shared without disclosing sensitive information.

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.

Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.

PubMed

Murrell, Daniel S; Cortes-Ciriano, Isidro; van Westen, Gerard J P; Stott, Ian P; Bender, Andreas; Malliavin, Thérèse E; Glen, Robert C

2015-01-01

In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2). Overall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.Graphical abstractFrom compounds and data to models: a complete model building workflow in one package.

Frontiers of chemical bioaccumulation modeling with fish

EPA Science Inventory

Predictive models for chemical accumulation in fish have been provided by numerous authors. Historically, these models were developed to describe the accumulation of neutral hydrophobic compounds which undergo little or no biotransformation. In such cases, accumulation can be p...

A model for tracking concentration of chemical compounds within a tank of an automatic film processor.

PubMed

Sobol, Wlad T

2002-01-01

A simple kinetic model that describes the time evolution of the chemical concentration of an arbitrary compound within the tank of an automatic film processor is presented. It provides insights into the kinetics of chemistry concentration inside the processor's tank; the results facilitate the tasks of processor tuning and quality control (QC). The model has successfully been used in several troubleshooting sessions of low-volume mammography processors for which maintaining consistent QC tracking was difficult due to fluctuations of bromide levels in the developer tank.

Nature and kinetic analysis of carbon-carbon bond fragmentation reactions of cation radicals derived from SET-oxidation of lignin model compounds.

PubMed

Cho, Dae Won; Parthasarathi, Ramakrishnan; Pimentel, Adam S; Maestas, Gabriel D; Park, Hea Jung; Yoon, Ung Chan; Dunaway-Mariano, Debra; Gnanakaran, S; Langan, Paul; Mariano, Patrick S

2010-10-01

Features of the oxidative cleavage reactions of diastereomers of dimeric lignin model compounds, which are models of the major types of structural units found in the lignin backbone, were examined. Cation radicals of these substances were generated by using SET-sensitized photochemical and Ce(IV) and lignin peroxidase promoted oxidative processes, and the nature and kinetics of their C-C bond cleavage reactions were determined. The results show that significant differences exist between the rates of cation radical C1-C2 bond cleavage reactions of 1,2-diaryl-(β-1) and 1-aryl-2-aryloxy-(β-O-4) propan-1,3-diol structural units found in lignins. Specifically, under all conditions C1-C2 bond cleavage reactions of cation radicals of the β-1 models take place more rapidly than those of the β-O-4 counterparts. The results of DFT calculations on cation radicals of the model compounds show that the C1-C2 bond dissociation energies of the β-1 lignin model compounds are significantly lower than those of the β-O-4 models, providing clear evidence for the source of the rate differences.

Highly predictive and interpretable models for PAMPA permeability.

PubMed

Sun, Hongmao; Nguyen, Kimloan; Kerns, Edward; Yan, Zhengyin; Yu, Kyeong Ri; Shah, Pranav; Jadhav, Ajit; Xu, Xin

2017-02-01

Cell membrane permeability is an important determinant for oral absorption and bioavailability of a drug molecule. An in silico model predicting drug permeability is described, which is built based on a large permeability dataset of 7488 compound entries or 5435 structurally unique molecules measured by the same lab using parallel artificial membrane permeability assay (PAMPA). On the basis of customized molecular descriptors, the support vector regression (SVR) model trained with 4071 compounds with quantitative data is able to predict the remaining 1364 compounds with the qualitative data with an area under the curve of receiver operating characteristic (AUC-ROC) of 0.90. The support vector classification (SVC) model trained with half of the whole dataset comprised of both the quantitative and the qualitative data produced accurate predictions to the remaining data with the AUC-ROC of 0.88. The results suggest that the developed SVR model is highly predictive and provides medicinal chemists a useful in silico tool to facilitate design and synthesis of novel compounds with optimal drug-like properties, and thus accelerate the lead optimization in drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative structure-activity relationship of organosulphur compounds as soybean 15-lipoxygenase inhibitors using CoMFA and CoMSIA.

PubMed

Caballero, Julio; Fernández, Michael; Coll, Deysma

2010-12-01

Three-dimensional quantitative structure-activity relationship studies were carried out on a series of 28 organosulphur compounds as 15-lipoxygenase inhibitors using comparative molecular field analysis and comparative molecular similarity indices analysis. Quantitative information on structure-activity relationships is provided for further rational development and direction of selective synthesis. All models were carried out over a training set including 22 compounds. The best comparative molecular field analysis model only included steric field and had a good Q² = 0.789. Comparative molecular similarity indices analysis overcame the comparative molecular field analysis results: the best comparative molecular similarity indices analysis model also only included steric field and had a Q² = 0.894. In addition, this model predicted adequately the compounds contained in the test set. Furthermore, plots of steric comparative molecular similarity indices analysis field allowed conclusions to be drawn for the choice of suitable inhibitors. In this sense, our model should prove useful in future 15-lipoxygenase inhibitor design studies. © 2010 John Wiley & Sons A/S.

Feasibility in multispectral imaging for predicting the content of bioactive compounds in intact tomato fruit.

PubMed

Liu, Changhong; Liu, Wei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2015-04-15

Tomato is an important health-stimulating fruit because of the antioxidant properties of its main bioactive compounds, dominantly lycopene and phenolic compounds. Nowadays, product differentiation in the fruit market requires an accurate evaluation of these value-added compounds. An experiment was conducted to simultaneously and non-destructively measure lycopene and phenolic compounds content in intact tomatoes using multispectral imaging combined with chemometric methods. Partial least squares (PLS), least squares-support vector machines (LS-SVM) and back propagation neural network (BPNN) were applied to develop quantitative models. Compared with PLS and LS-SVM, BPNN model considerably improved the performance with coefficient of determination in prediction (RP(2))=0.938 and 0.965, residual predictive deviation (RPD)=4.590 and 9.335 for lycopene and total phenolics content prediction, respectively. It is concluded that multispectral imaging is an attractive alternative to the standard methods for determination of bioactive compounds content in intact tomatoes, providing a useful platform for infield fruit sorting/grading. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dual functional cholinesterase and MAO inhibitors for the treatment of Alzheimer's disease: synthesis, pharmacological analysis and molecular modeling of homoisoflavonoid derivatives.

PubMed

Wang, Yali; Sun, Yang; Guo, Yueyan; Wang, Zechen; Huang, Ling; Li, Xingshu

2016-01-01

Because of the complexity of Alzheimer's disease (AD), the multi-target-directed ligand (MTDL) strategy is expected to provide superior effects for the treatment of AD, instead of the classic one-drug-one-target strategy. In this context, we focused on the design, synthesis and evaluation of homoisoflavonoid derivatives as dual acetyl cholinesterase (AChE) and monoamine oxidase (MAO-B) inhibitors. Among all the synthesized compounds, compound 10 provided a desired balance of AChE and hMAO-B inhibition activities, with IC50 value of 3.94 and 3.44 μM, respectively. Further studies revealed that compound 10 was a mixed-type inhibitor of AChE and an irreversible inhibitor of hMAO-B, which was also confirmed by molecular modeling studies. Taken together, the data indicated that 10 was a promising dual functional agent for the treatment of AD.

Multivariate analysis of volatile compounds detected by headspace solid-phase microextraction/gas chromatography: A tool for sensory classification of cork stoppers.

PubMed

Prat, Chantal; Besalú, Emili; Bañeras, Lluís; Anticó, Enriqueta

2011-06-15

The volatile fraction of aqueous cork macerates of tainted and non-tainted agglomerate cork stoppers was analysed by headspace solid-phase microextraction (HS-SPME)/gas chromatography. Twenty compounds containing terpenoids, aliphatic alcohols, lignin-related compounds and others were selected and analysed in individual corks. Cork stoppers were previously classified in six different classes according to sensory descriptions including, 2,4,6-trichloroanisole taint and other frequent, non-characteristic odours found in cork. A multivariate analysis of the chromatographic data of 20 selected chemical compounds using linear discriminant analysis models helped in the differentiation of the a priori made groups. The discriminant model selected five compounds as the best combination. Selected compounds appear in the model in the following order; 2,4,6 TCA, fenchyl alcohol, 1-octen-3-ol, benzyl alcohol and benzothiazole. Unfortunately, not all six a priori differentiated sensory classes were clearly discriminated in the model, probably indicating that no measurable differences exist in the chromatographic data for some categories. The predictive analyses of a refined model in which two sensory classes were fused together resulted in a good classification. Prediction rates of control (non-tainted), TCA, musty-earthy-vegetative, vegetative and chemical descriptions were 100%, 100%, 85%, 67.3% and 100%, respectively, when the modified model was used. The multivariate analysis of chromatographic data will help in the classification of stoppers and provide a perfect complement to sensory analyses. Copyright © 2010 Elsevier Ltd. All rights reserved.

Advanced Model Compounds for Understanding Acid-Catalyzed Lignin Depolymerization: Identification of Renewable Aromatics and a Lignin-Derived Solvent.

PubMed

Lahive, Ciaran W; Deuss, Peter J; Lancefield, Christopher S; Sun, Zhuohua; Cordes, David B; Young, Claire M; Tran, Fanny; Slawin, Alexandra M Z; de Vries, Johannes G; Kamer, Paul C J; Westwood, Nicholas J; Barta, Katalin

2016-07-20

The development of fundamentally new approaches for lignin depolymerization is challenged by the complexity of this aromatic biopolymer. While overly simplified model compounds often lack relevance to the chemistry of lignin, the direct use of lignin streams poses significant analytical challenges to methodology development. Ideally, new methods should be tested on model compounds that are complex enough to mirror the structural diversity in lignin but still of sufficiently low molecular weight to enable facile analysis. In this contribution, we present a new class of advanced (β-O-4)-(β-5) dilinkage models that are highly realistic representations of a lignin fragment. Together with selected β-O-4, β-5, and β-β structures, these compounds provide a detailed understanding of the reactivity of various types of lignin linkages in acid catalysis in conjunction with stabilization of reactive intermediates using ethylene glycol. The use of these new models has allowed for identification of novel reaction pathways and intermediates and led to the characterization of new dimeric products in subsequent lignin depolymerization studies. The excellent correlation between model and lignin experiments highlights the relevance of this new class of model compounds for broader use in catalysis studies. Only by understanding the reactivity of the linkages in lignin at this level of detail can fully optimized lignin depolymerization strategies be developed.

Stilbene epoxidation and detoxification in a Photorhabdus luminescens-nematode symbiosis

PubMed Central

Park, Hyun Bong; Sampathkumar, Parthasarathy; Perez, Corey E.; Lee, Joon Ha; Tran, Jeannie; Bonanno, Jeffrey B.; Hallem, Elissa A.; Almo, Steven C.; Crawford, Jason M.

2017-01-01

Members of the gammaproteobacterial Photorhabdus genus share mutualistic relationships with Heterorhabditis nematodes, and the pairs infect a wide swath of insect larvae. Photorhabdus species produce a family of stilbenes, with two major components being 3,5-dihydroxy-4-isopropyl-trans-stilbene (compound 1) and its stilbene epoxide (compound 2). This family of molecules harbors antimicrobial and immunosuppressive activities, and its pathway is responsible for producing a nematode “food signal” involved in nematode development. However, stilbene epoxidation biosynthesis and its biological roles remain unknown. Here, we identified an orphan protein (Plu2236) from Photorhabdus luminescens that catalyzes stilbene epoxidation. Structural, mutational, and biochemical analyses confirmed the enzyme adopts a fold common to FAD-dependent monooxygenases, contains a tightly bound FAD prosthetic group, and is required for the stereoselective epoxidation of compounds 1 and 2. The epoxidase gene was dispensable in a nematode-infective juvenile recovery assay, indicating the oxidized compound is not required for the food signal. The epoxide exhibited reduced cytotoxicity toward its producer, suggesting this may be a natural route for intracellular detoxification. In an insect infection model, we also observed two stilbene-derived metabolites that were dependent on the epoxidase. NMR, computational, and chemical degradation studies established their structures as new stilbene-l-proline conjugates, prolbenes A (compound 3) and B (compound 4). The prolbenes lacked immunosuppressive and antimicrobial activities compared with their stilbene substrates, suggesting a metabolite attenuation mechanism in the animal model. Collectively, our studies provide a structural view for stereoselective stilbene epoxidation and functionalization in an invertebrate animal infection model and provide new insights into stilbene cellular detoxification. PMID:28246174

Binding to the DNA Minor Groove by Heterocyclic Dications: From AT Specific Monomers to GC Recognition with Dimers

PubMed Central

Nanjunda, Rupesh; Wilson, W. David

2012-01-01

Compounds that bind in the DNA minor groove have provided critical information on DNA molecular recognition, they have found extensive uses in biotechnology and they are providing clinically useful drugs against diseases as diverse as cancer and sleeping sickness. This review focuses on the development of clinically useful heterocyclic diamidine minor groove binders. These compounds have shown us that the classical model for minor groove binding in AT DNA sequences must be expanded in several ways: compounds with nonstandard shapes can bind strongly to the groove, water can be directly incorporated into the minor groove complex in an interfacial interaction, and the compounds can form cooperative stacked dimers to recognize GC and mixed AT/GC base pair sequences. PMID:23255206

The impact of desorption kinetics from albumin on hepatic extraction efficiency and hepatic clearance: a model study.

PubMed

Krause, Sophia; Goss, Kai-Uwe

2018-05-23

Until now, the question whether slow desorption of compounds from transport proteins like the plasma protein albumin can affect hepatic uptake and thereby hepatic metabolism of these compounds has not yet been answered conclusively. This work now combines recently published experimental desorption rate constants with a liver model to address this question. For doing so, the used liver model differentiates the bound compound in blood, the unbound compound in blood and the compound within the hepatocytes as three well-stirred compartments. Our calculations show that slow desorption kinetics from albumin can indeed limit hepatic metabolism of a compound by decreasing hepatic extraction efficiency and hepatic clearance. The extent of this decrease, however, depends not only on the value of the desorption rate constant but also on how much of the compound is bound to albumin in blood and how fast intrinsic metabolism of the compound in the hepatocytes is. For strongly sorbing and sufficiently fast metabolized compounds, our calculations revealed a twentyfold lower hepatic extraction efficiency and hepatic clearance for the slowest known desorption rate constant compared to the case when instantaneous equilibrium between bound and unbound compound is assumed. The same desorption rate constant, however, has nearly no effect on hepatic extraction efficiency and hepatic clearance of weakly sorbing and slowly metabolized compounds. This work examines the relevance of desorption kinetics in various example scenarios and provides the general approach needed to quantify the effect of flow limitation, membrane permeability and desorption kinetics on hepatic metabolism at the same time.

Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds.

PubMed

Baurin, N; Baker, R; Richardson, C; Chen, I; Foloppe, N; Potter, A; Jordan, A; Roughley, S; Parratt, M; Greaney, P; Morley, D; Hubbard, R E

2004-01-01

We have implemented five drug-like filters, based on 1D and 2D molecular descriptors, and applied them to characterize the drug-like properties of commercially available chemical compounds. In addition to previously published filters (Lipinski and Veber), we implemented a filter for medicinal chemistry tractability based on lists of chemical features drawn up by a panel of medicinal chemists. A filter based on the modeling of aqueous solubility (>1 microM) was derived in-house, as well as another based on the modeling of Caco-2 passive membrane permeability (>10 nm/s). A library of 2.7 million compounds was collated from the 23 compound suppliers and analyzed with these filters, highlighting a tendency toward highly lipophilic compounds. The library contains 1.6 M unique structures, of which 37% (607,223) passed all five drug-like filters. None of the 23 suppliers provides all the members of the drug-like subset, emphasizing the benefit of considering compounds from various compound suppliers as a source of diversity for drug discovery.

Molecular mechanisms underlying the antitumor activity of (E)-N-hydroxy-3-(1-(4-methoxyphenylsulfonyl)-1,2,3,4-tetrahydroquinolin-6-yl)acrylamide in human colorectal cancer cells in vitro and in vivo

PubMed Central

Chen, Chun-Han; Lee, Chia-Hwa; Liou, Jing-Ping; Teng, Che-Ming; Pan, Shiow-Lin

2015-01-01

Upregulation of class I histone deacetylases (HDAC) correlates with poor prognosis in colorectal cancer (CRC) patients. Previous study revealed that (E)-N-hydroxy-3-(1-(4-methoxyphenylsulfonyl)-1,2,3,4-tetrahydroquinolin-6-yl)acrylamide (Compound 11) is a potent and selective class I HDAC inhibitor, exhibited significant anti-proliferative activity in various human cancer cell lines. In current study, we demonstrated that compound 11 exhibited significant anti-proliferative and cytotoxic activity in CRC cells. Notably, compound 11 was less potent than SAHA in inhibiting HDAC6 as evident from the lower expression of acetyl-α-tubulin, suggesting higher selectivity for class I HDACs. Mechanistically, compound 11 induced cell-cycle arrest at the G2/M phase, activated both intrinsic- and extrinsic-apoptotic pathways, altered the expression of Bcl-2 family proteins and exerted a potent inhibitory effect on survival signals (p-Akt, p-ERK) in CRC cells. Moreover, we provide evidence that compound 11 suppressed motility, decreased mesenchymal markers (N-cadherin and vimentin) and increased epithelial marker (E-cadherin) through down-regulation of Akt. The anti-tumor activity and underlying molecular mechanisms of compound 11 were further confirmed using the HCT116 xenograft model in vivo. Our findings provide evidence of the significant anti-tumor activity of compound 11 in a preclinical model, supporting its potential as a novel therapeutic agent for CRC. PMID:26462017

Testing chemical carcinogenicity by using a transcriptomics HepaRG-based model?

PubMed Central

Doktorova, T. Y.; Yildirimman, Reha; Ceelen, Liesbeth; Vilardell, Mireia; Vanhaecke, Tamara; Vinken, Mathieu; Ates, Gamze; Heymans, Anja; Gmuender, Hans; Bort, Roque; Corvi, Raffaella; Phrakonkham, Pascal; Li, Ruoya; Mouchet, Nicolas; Chesne, Christophe; van Delft, Joost; Kleinjans, Jos; Castell, Jose; Herwig, Ralf; Rogiers, Vera

2014-01-01

The EU FP6 project carcinoGENOMICS explored the combination of toxicogenomics and in vitro cell culture models for identifying organotypical genotoxic- and non-genotoxic carcinogen-specific gene signatures. Here the performance of its gene classifier, derived from exposure of metabolically competent human HepaRG cells to prototypical non-carcinogens (10 compounds) and hepatocarcinogens (20 compounds), is reported. Analysis of the data at the gene and the pathway level by using independent biostatistical approaches showed a distinct separation of genotoxic from non-genotoxic hepatocarcinogens and non-carcinogens (up to 88 % correct prediction). The most characteristic pathway responding to genotoxic exposure was DNA damage. Interlaboratory reproducibility was assessed by blindly testing of three compounds, from the set of 30 compounds, by three independent laboratories. Subsequent classification of these compounds resulted in correct prediction of the genotoxicants. As expected, results on the non-genotoxic carcinogens and the non-carcinogens were less predictive. In conclusion, the combination of transcriptomics with the HepaRG in vitro cell model provides a potential weight of evidence approach for the evaluation of the genotoxic potential of chemical substances. PMID:26417288

From Broad-Spectrum Biocides to Quorum Sensing Disruptors and Mussel Repellents: Antifouling Profile of Alkyl Triphenylphosphonium Salts

PubMed Central

Martín-Rodríguez, Alberto J.; Babarro, Jose M. F.; Lahoz, Fernando; Sansón, Marta; Martín, Víctor S.; Norte, Manuel; Fernández, José J.

2015-01-01

‘Onium’ compounds, including ammonium and phosphonium salts, have been employed as antiseptics and disinfectants. These cationic biocides have been incorporated into multiple materials, principally to avoid bacterial attachment. In this work, we selected 20 alkyl-triphenylphosphonium salts, differing mainly in the length and functionalization of their alkyl chains, in fulfilment of two main objectives: 1) to provide a comprehensive evaluation of the antifouling profile of these molecules with relevant marine fouling organisms; and 2) to shed new light on their potential applications, beyond their classic use as broad-spectrum biocides. In this regard, we demonstrate for the first time that these compounds are also able to act as non-toxic quorum sensing disruptors in two different bacterial models (Chromobacterium violaceum and Vibrio harveyi) as well as repellents in the mussel Mytilus galloprovincialis. In addition, their inhibitory activity on a fouling-relevant enzymatic model (tyrosinase) is characterized. An analysis of the structure-activity relationships of these compounds for antifouling purposes is provided, which may result useful in the design of targeted antifouling solutions with these molecules. Altogether, the findings reported herein provide a different perspective on the biological activities of phosphonium compounds that is particularly focused on, but, as the reader will realize, is not limited to their use as antifouling agents. PMID:25897858

Actually, What Is an Actuary?

ERIC Educational Resources Information Center

Oudshoorn, Susan; Finkelstein, Gary

1991-01-01

The actuarial profession is described to provide secondary school mathematics teachers insights into how actuaries use mathematics in solving real life problems. Examples are provided involving compound interest, the probability of dying, and inflation with computer modeling. (MDH)

Modeling the Biodegradability of Chemical Compounds Using the Online CHEmical Modeling Environment (OCHEM)

PubMed Central

Vorberg, Susann

2013-01-01

Abstract Biodegradability describes the capacity of substances to be mineralized by free‐living bacteria. It is a crucial property in estimating a compound’s long‐term impact on the environment. The ability to reliably predict biodegradability would reduce the need for laborious experimental testing. However, this endpoint is difficult to model due to unavailability or inconsistency of experimental data. Our approach makes use of the Online Chemical Modeling Environment (OCHEM) and its rich supply of machine learning methods and descriptor sets to build classification models for ready biodegradability. These models were analyzed to determine the relationship between characteristic structural properties and biodegradation activity. The distinguishing feature of the developed models is their ability to estimate the accuracy of prediction for each individual compound. The models developed using seven individual descriptor sets were combined in a consensus model, which provided the highest accuracy. The identified overrepresented structural fragments can be used by chemists to improve the biodegradability of new chemical compounds. The consensus model, the datasets used, and the calculated structural fragments are publicly available at http://ochem.eu/article/31660. PMID:27485201

Identification of compounds with anti-convulsant properties in a zebrafish model of epileptic seizures

PubMed Central

Baxendale, Sarah; Holdsworth, Celia J.; Meza Santoscoy, Paola L.; Harrison, Michael R. M.; Fox, James; Parkin, Caroline A.; Ingham, Philip W.; Cunliffe, Vincent T.

2012-01-01

SUMMARY The availability of animal models of epileptic seizures provides opportunities to identify novel anticonvulsants for the treatment of people with epilepsy. We found that exposure of 2-day-old zebrafish embryos to the convulsant agent pentylenetetrazole (PTZ) rapidly induces the expression of synaptic-activity-regulated genes in the CNS, and elicited vigorous episodes of calcium (Ca2+) flux in muscle cells as well as intense locomotor activity. We then screened a library of ∼2000 known bioactive small molecules and identified 46 compounds that suppressed PTZ-inducedtranscription of the synaptic-activity-regulated gene fos in 2-day-old (2 dpf) zebrafish embryos. Further analysis of a subset of these compounds, which included compounds with known and newly identified anticonvulsant properties, revealed that they exhibited concentration-dependent inhibition of both locomotor activity and PTZ-induced fos transcription, confirming their anticonvulsant characteristics. We conclude that this in situ hybridisation assay for fos transcription in the zebrafish embryonic CNS is a robust, high-throughput in vivo indicator of the neural response to convulsant treatment and lends itself well to chemical screening applications. Moreover, our results demonstrate that suppression of PTZ-induced fos expression provides a sensitive means of identifying compounds with anticonvulsant activities. PMID:22730455

Secondary metabolites from three Florida sponges with antidepressant activity.

PubMed

Kochanowska, Anna J; Rao, Karumanchi V; Childress, Suzanne; El-Alfy, Abir; Matsumoto, Rae R; Kelly, Michelle; Stewart, Gina S; Sufka, Kenneth J; Hamann, Mark T

2008-02-01

Brominated indole alkaloids are a common class of metabolites reported from sponges of the order Verongida. Herein we report the isolation, structure determination, and activity of metabolites from three Florida sponges, namely, Verongula rigida (order Verongida, family Aplysinidae), Smenospongia aurea, and S. cerebriformis (order Dictyoceratida, family Thorectidae). All three species were investigated chemically, revealing similarities in secondary metabolites. Brominated compounds, as well as sesquiterpene quinones and hydroquinones, were identified from both V. rigida and S. aurea despite their apparent taxonomic differences at the ordinal level. Similar metabolites found in these distinct sponge species of two different genera provide evidence for a microbial origin of the metabolites. Isolated compounds were evaluated in the Porsolt forced swim test (FST) and the chick anxiety-depression continuum model. Among the isolated compounds, 5,6-dibromo- N,N-dimethyltryptamine ( 1) exhibited significant antidepressant-like action in the rodent FST model, while 5-bromo- N,N-dimethyltryptamine ( 2) caused significant reduction of locomotor activity indicative of a potential sedative action. The current study provides ample evidence that marine natural products with the diversity of brominated marine alkaloids will provide potential leads for antidepressant and anxiolytic drugs.

New Linear Partitioning Models Based on Experimental Water: Supercritical CO2 Partitioning Data of Selected Organic Compounds.

PubMed

Burant, Aniela; Thompson, Christopher; Lowry, Gregory V; Karamalidis, Athanasios K

2016-05-17

Partitioning coefficients of organic compounds between water and supercritical CO2 (sc-CO2) are necessary to assess the risk of migration of these chemicals from subsurface CO2 storage sites. Despite the large number of potential organic contaminants, the current data set of published water-sc-CO2 partitioning coefficients is very limited. Here, the partitioning coefficients of thiophene, pyrrole, and anisole were measured in situ over a range of temperatures and pressures using a novel pressurized batch-reactor system with dual spectroscopic detectors: a near-infrared spectrometer for measuring the organic analyte in the CO2 phase and a UV detector for quantifying the analyte in the aqueous phase. Our measured partitioning coefficients followed expected trends based on volatility and aqueous solubility. The partitioning coefficients and literature data were then used to update a published poly parameter linear free-energy relationship and to develop five new linear free-energy relationships for predicting water-sc-CO2 partitioning coefficients. A total of four of the models targeted a single class of organic compounds. Unlike models that utilize Abraham solvation parameters, the new relationships use vapor pressure and aqueous solubility of the organic compound at 25 °C and CO2 density to predict partitioning coefficients over a range of temperature and pressure conditions. The compound class models provide better estimates of partitioning behavior for compounds in that class than does the model built for the entire data set.

New Linear Partitioning Models Based on Experimental Water: Supercritical CO 2 Partitioning Data of Selected Organic Compounds

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

Burant, Aniela; Thompson, Christopher; Lowry, Gregory V.

2016-05-17

Partitioning coefficients of organic compounds between water and supercritical CO2 (sc-CO2) are necessary to assess the risk of migration of these chemicals from subsurface CO2 storage sites. Despite the large number of potential organic contaminants, the current data set of published water-sc-CO2 partitioning coefficients is very limited. Here, the partitioning coefficients of thiophene, pyrrole, and anisole were measured in situ over a range of temperatures and pressures using a novel pressurized batch reactor system with dual spectroscopic detectors: a near infrared spectrometer for measuring the organic analyte in the CO2 phase, and a UV detector for quantifying the analyte inmore » the aqueous phase. Our measured partitioning coefficients followed expected trends based on volatility and aqueous solubility. The partitioning coefficients and literature data were then used to update a published poly-parameter linear free energy relationship and to develop five new linear free energy relationships for predicting water-sc-CO2 partitioning coefficients. Four of the models targeted a single class of organic compounds. Unlike models that utilize Abraham solvation parameters, the new relationships use vapor pressure and aqueous solubility of the organic compound at 25 °C and CO2 density to predict partitioning coefficients over a range of temperature and pressure conditions. The compound class models provide better estimates of partitioning behavior for compounds in that class than the model built for the entire dataset.« less

Convenient QSAR model for predicting the complexation of structurally diverse compounds with beta-cyclodextrins.

PubMed

Pérez-Garrido, Alfonso; Morales Helguera, Aliuska; Abellán Guillén, Adela; Cordeiro, M Natália D S; Garrido Escudero, Amalio

2009-01-15

This paper reports a QSAR study for predicting the complexation of a large and heterogeneous variety of substances (233 organic compounds) with beta-cyclodextrins (beta-CDs). Several different theoretical molecular descriptors, calculated solely from the molecular structure of the compounds under investigation, and an efficient variable selection procedure, like the Genetic Algorithm, led to models with satisfactory global accuracy and predictivity. But the best-final QSAR model is based on Topological descriptors meanwhile offering a reasonable interpretation. This QSAR model was able to explain ca. 84% of the variance in the experimental activity, and displayed very good internal cross-validation statistics and predictivity on external data. It shows that the driving forces for CD complexation are mainly hydrophobic and steric (van der Waals) interactions. Thus, the results of our study provide a valuable tool for future screening and priority testing of beta-CDs guest molecules.

Patient-centered care as value-added service by compounding pharmacists.

PubMed

McPherson, Timothy B; Fontane, Patrick E; Day, Jonathan R

2013-01-01

The term "value-added" is widely used to describe business and professional services that complement a product or service or that differentiate it from competing products and services. The objective of this study was to determine compounding pharmacists' self-perceptions of the value-added services they provide. A web-based survey method was used. Respondents' perceptions of their most important value-added service frequently fell into one of two categories: (1) enhanced pharmacist contribution to developing and implementing patient therapeutic plans and (2) providing customized medications of high pharmaceutical quality. The results were consistent with a hybrid community clinical practice model for compounding pharmacists wherein personalization of the professional relationship is the value-added characteristic.

Synthesis, biological evaluation and molecular modeling studies of imidazo[1,2-a]pyridines derivatives as protein kinase inhibitors.

PubMed

Lawson, Marie; Rodrigo, Jordi; Baratte, Blandine; Robert, Thomas; Delehouzé, Claire; Lozach, Olivier; Ruchaud, Sandrine; Bach, Stéphane; Brion, Jean-Daniel; Alami, Mouad; Hamze, Abdallah

2016-11-10

We report here the synthesis, the biological evaluation and the molecular modeling studies of new imidazo[1,2-a]pyridines derivatives designed as potent kinase inhibitors. This collection was obtained from 2-aminopyridines and 2-bromoacetophenone which afforded final compound in only one step. The bioactivity of this family of new compounds was tested using protein kinase and ATP competition assays. The structure-activity relationship (SAR) revealed that six compounds inhibit DYRK1A and CLK1 at a micromolar range. Docking studies provided possible explanations that correlate with the SAR data. The most active compound 4c inhibits CLK1 (IC50 of 0.7 μM) and DYRK1A (IC50 of 2.6 μM). Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Pharmacokinetic properties and in silico ADME modeling in drug discovery.

PubMed

Honório, Kathia M; Moda, Tiago L; Andricopulo, Adriano D

2013-03-01

The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME--absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.

Lindley frailty model for a class of compound Poisson processes

NASA Astrophysics Data System (ADS)

Kadilar, Gamze Özel; Ata, Nihal

2013-10-01

The Lindley distribution gain importance in survival analysis for the similarity of exponential distribution and allowance for the different shapes of hazard function. Frailty models provide an alternative to proportional hazards model where misspecified or omitted covariates are described by an unobservable random variable. Despite of the distribution of the frailty is generally assumed to be continuous, it is appropriate to consider discrete frailty distributions In some circumstances. In this paper, frailty models with discrete compound Poisson process for the Lindley distributed failure time are introduced. Survival functions are derived and maximum likelihood estimation procedures for the parameters are studied. Then, the fit of the models to the earthquake data set of Turkey are examined.

Methylpyrrole inhibitors of BET bromodomains

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

Hasvold, Lisa A.; Sheppard, George S.; Wang, Le

2017-05-01

An NMR fragment screen for binders to the bromodomains of BRD4 identified 2-methyl-3-ketopyrroles 1 and 2. Elaboration of these fragments guided by structure-based design provided lead molecules with significant activity in a mouse tumor model. Further modifications to the methylpyrrole core provided compounds with improved properties and enhanced activity in a mouse model of multiple myeloma.

Progress with modeling activity landscapes in drug discovery.

PubMed

Vogt, Martin

2018-04-19

Activity landscapes (ALs) are representations and models of compound data sets annotated with a target-specific activity. In contrast to quantitative structure-activity relationship (QSAR) models, ALs aim at characterizing structure-activity relationships (SARs) on a large-scale level encompassing all active compounds for specific targets. The popularity of AL modeling has grown substantially with the public availability of large activity-annotated compound data sets. AL modeling crucially depends on molecular representations and similarity metrics used to assess structural similarity. Areas covered: The concepts of AL modeling are introduced and its basis in quantitatively assessing molecular similarity is discussed. The different types of AL modeling approaches are introduced. AL designs can broadly be divided into three categories: compound-pair based, dimensionality reduction, and network approaches. Recent developments for each of these categories are discussed focusing on the application of mathematical, statistical, and machine learning tools for AL modeling. AL modeling using chemical space networks is covered in more detail. Expert opinion: AL modeling has remained a largely descriptive approach for the analysis of SARs. Beyond mere visualization, the application of analytical tools from statistics, machine learning and network theory has aided in the sophistication of AL designs and provides a step forward in transforming ALs from descriptive to predictive tools. To this end, optimizing representations that encode activity relevant features of molecules might prove to be a crucial step.

Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale

DOE PAGES

Das, Dhrubajyoti D.; St. John, Peter C.; McEnally, Charles S.; ...

2017-12-27

Databases of sooting indices, based on measuring some aspect of sooting behavior in a standardized combustion environment, are useful in providing information on the comparative sooting tendencies of different fuels or pure compounds. However, newer biofuels have varied chemical structures including both aromatic and oxygenated functional groups, which expands the chemical space of relevant compounds. In this work, we propose a unified sooting tendency database for pure compounds, including both regular and oxygenated hydrocarbons, which is based on combining two disparate databases of yield-based sooting tendency measurements in the literature. Unification of the different databases was made possible by leveragingmore » the greater dynamic range of the color ratio pyrometry soot diagnostic. This unified database contains a substantial number of pure compounds (≥ 400 total) from multiple categories of hydrocarbons important in modern fuels and establishes the sooting tendencies of aromatic and oxygenated hydrocarbons on the same numeric scale for the first time. Then, using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons. The model decomposes each compound into single-carbon fragments and assigns a sooting tendency contribution to each fragment based on regression against the unified database. The model’s predictive accuracy (as demonstrated by leave-one-out cross-validation) is comparable to a previously developed, more detailed predictive model. The fitted model provides insight into the effects of chemical structure on soot formation, and cases where its predictions fail reveal the presence of more complicated kinetic sooting mechanisms. Our work will therefore enable the rational design of low-sooting fuel blends from a wide range of feedstocks and chemical functionalities.« less

A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases

PubMed Central

Chernomoretz, Ariel; Agüero, Fernán

2016-01-01

Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantage of data from extensively studied organisms like human, mouse, E. coli and yeast, among others, to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes, and bioactive drug-like molecules. We modeled genomic (proteins) and chemical (bioactive compounds) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species, chemical similarities between 1.7 105 compounds and several functional relations among 1.67 105 proteins. These relations comprised orthology, sharing of protein domains, and shared participation in defined biochemical pathways. We showcase the application of this network graph to the problem of prioritization of new candidate targets, based on the information available in the graph for known compound-target associations. We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches. Moreover, our model provides additional flexibility as two different network definitions could be considered, finding in both cases qualitatively different but sensible candidate targets. We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens. In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound. Moreover, we found that some predictions highlighted by our network model were supported by independent experimental validations as found post-facto in the literature. PMID:26735851

Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale

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

Das, Dhrubajyoti D.; St. John, Peter C.; McEnally, Charles S.

Databases of sooting indices, based on measuring some aspect of sooting behavior in a standardized combustion environment, are useful in providing information on the comparative sooting tendencies of different fuels or pure compounds. However, newer biofuels have varied chemical structures including both aromatic and oxygenated functional groups, which expands the chemical space of relevant compounds. In this work, we propose a unified sooting tendency database for pure compounds, including both regular and oxygenated hydrocarbons, which is based on combining two disparate databases of yield-based sooting tendency measurements in the literature. Unification of the different databases was made possible by leveragingmore » the greater dynamic range of the color ratio pyrometry soot diagnostic. This unified database contains a substantial number of pure compounds (≥ 400 total) from multiple categories of hydrocarbons important in modern fuels and establishes the sooting tendencies of aromatic and oxygenated hydrocarbons on the same numeric scale for the first time. Then, using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons. The model decomposes each compound into single-carbon fragments and assigns a sooting tendency contribution to each fragment based on regression against the unified database. The model’s predictive accuracy (as demonstrated by leave-one-out cross-validation) is comparable to a previously developed, more detailed predictive model. The fitted model provides insight into the effects of chemical structure on soot formation, and cases where its predictions fail reveal the presence of more complicated kinetic sooting mechanisms. Our work will therefore enable the rational design of low-sooting fuel blends from a wide range of feedstocks and chemical functionalities.« less

A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases.

PubMed

Berenstein, Ariel José; Magariños, María Paula; Chernomoretz, Ariel; Agüero, Fernán

2016-01-01

Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantage of data from extensively studied organisms like human, mouse, E. coli and yeast, among others, to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes, and bioactive drug-like molecules. We modeled genomic (proteins) and chemical (bioactive compounds) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species, chemical similarities between 1.7 105 compounds and several functional relations among 1.67 105 proteins. These relations comprised orthology, sharing of protein domains, and shared participation in defined biochemical pathways. We showcase the application of this network graph to the problem of prioritization of new candidate targets, based on the information available in the graph for known compound-target associations. We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches. Moreover, our model provides additional flexibility as two different network definitions could be considered, finding in both cases qualitatively different but sensible candidate targets. We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens. In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound. Moreover, we found that some predictions highlighted by our network model were supported by independent experimental validations as found post-facto in the literature.

2 H-fractionations during the biosynthesis of carbohydrates and lipids imprint a metabolic signal on the δ2 H values of plant organic compounds.

PubMed

Cormier, Marc-André; Werner, Roland A; Sauer, Peter E; Gröcke, Darren R; Leuenberger, Markus C; Wieloch, Thomas; Schleucher, Jürgen; Kahmen, Ansgar

2018-04-01

Hydrogen (H) isotope ratio (δ 2 H) analyses of plant organic compounds have been applied to assess ecohydrological processes in the environment despite a large part of the δ 2 H variability observed in plant compounds not being fully elucidated. We present a conceptual biochemical model based on empirical H isotope data that we generated in two complementary experiments that clarifies a large part of the unexplained variability in the δ 2 H values of plant organic compounds. The experiments demonstrate that information recorded in the δ 2 H values of plant organic compounds goes beyond hydrological signals and can also contain important information on the carbon and energy metabolism of plants. Our model explains where 2 H-fractionations occur in the biosynthesis of plant organic compounds and how these 2 H-fractionations are tightly coupled to a plant's carbon and energy metabolism. Our model also provides a mechanistic basis to introduce H isotopes in plant organic compounds as a new metabolic proxy for the carbon and energy metabolism of plants and ecosystems. Such a new metabolic proxy has the potential to be applied in a broad range of disciplines, including plant and ecosystem physiology, biogeochemistry and palaeoecology. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

A herbicide structure-activity analysis of the antimalarial lead compound MMV007978 against Arabidopsis thaliana.

PubMed

Corral, Maxime G; Leroux, Julie; Tresch, Stefan; Newton, Trevor; Stubbs, Keith A; Mylne, Joshua S

2018-07-01

To fight herbicide-resistant weeds, new herbicides are needed; particularly ones with new modes of action. Building on the revelation that many antimalarial drugs are herbicidal, here we focus on the Medicines for Malaria Venture antimalarial lead compound MMV007978 that has herbicidal activity against the model plant Arabidopsis thaliana. Twenty-two variations of the lead compound thiophenyl motif revealed that change was tolerated provided ring size and charge were retained. MMV007978 was active against select monocot and dicot weeds, and physiological profiling indicated that its mode of action is related to germination and cell division. Of interest is the fact that the compound has a profile that is currently not found among known herbicides. We demonstrate that the antimalarial compound MMV007978 is also herbicidal and that exploiting lead compounds that are often understudied could lead to the identification of interesting herbicidal scaffolds. Further structural investigation of MMV007978 could provide improved herbicidal chemistries with a potential new mode of action. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

The influence of emulsion structure on the Maillard reaction of ghee.

PubMed

Newton, Angela E; Fairbanks, Antony J; Golding, Matt; Andrewes, Paul; Gerrard, Juliet A

2015-04-15

Food systems, such as cream and butter, have an emulsion or emulsion-like structure. When these food emulsions are heated to high temperatures to make products such as ghee, the Maillard reaction forms a range of volatile flavour compounds. The objective of this paper was to unravel the specific influence of emulsion structure on the Maillard reaction pathways that occur during the cooking of ghee using model systems. Switching the dispersed phase from oil to water provided a means of altering the ratios of volatile compounds produced in the cooked samples. The oil-in-water emulsion generated a volatile compound profile similar to that of the fat containing two phase model matrix, whereas the water-in-oil emulsion produced a different ratio of these compounds. The ability to generate different volatile compound profiles through the use of inverted emulsion structures could point to a new avenue for control of the Maillard reaction in high temperature food systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Discovery of potential LXRβ agonists from Chinese herbs using molecular simulation methods].

PubMed

Luo, Gang-Gang; Lu, Fang; Qiao, Lian-Sheng; Li, Yong; Zhang, Yan-Ling

2016-08-01

Liver X receptor β (LXRβ) has been a new target in the treatment of hyperlipemia, which was related to the cholesterol homeostasis. In this study, the quantitative pharmacophores were constructed by 3D-QSAR pharmacophore (Hypogen) method based on the LXRβ agonists. The optimal pharmacophore model containing one hydrogen bond acceptor, two hydrophobics and one ring aromatic was obtained based on five assessment indictors, including the correlation between predicted value and experimental value of the compounds in training set (correlation), Δcost of the models (Δcost), hit rate of active compounds (HRA), identification of effectiveness index (IEI) and comprehensive evaluation index (CAI). And the values of the five assessment indicators were 0.95, 128.65, 84.44%, 2.58 and 2.18 respectively. The best model as a query to screen the traditional Chinese medicine database (TCMD), a list of 309 compounds was obtained andwere then refined using Libdock program. Finally, based on the screening rules of the Libdock score of initial compound and the key interactions between initial compound and receptor, four compounds, demethoxycurcumin, isolicoflavonol, licochalcone E and silydianin, were selected as potential LXRβ agonists. The molecular simulation methods were high-efficiency and time-saving to obtainthe potential LXRβ agonists, which could provide assistance for further researchingnovel anti-hyperlipidemia drugs. Copyright© by the Chinese Pharmaceutical Association.

Source apportionment of airborne particulate matter using organic compounds as tracers

NASA Astrophysics Data System (ADS)

Schauer, James J.; Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

A chemical mass balance receptor model based on organic compounds has been developed that relates source contributions to airborne fine particle mass concentrations. Source contributions to the concentrations of specific organic compounds are revealed as well. The model is applied to four air quality monitoring sites in southern California using atmospheric organic compound concentration data and source test data collected specifically for the purpose of testing this model. The contributions of up to nine primary particle source types can be separately identified in ambient samples based on this method, and approximately 85% of the organic fine aerosol is assigned to primary sources on an annual average basis. The model provides information on source contributions to fine mass concentrations, fine organic aerosol concentrations and individual organic compound concentrations. The largest primary source contributors to fine particle mass concentrations in Los Angeles are found to include diesel engine exhaust, paved road dust, gasoline-powered vehicle exhaust, plus emissions from food cooking and wood smoke, with smaller contribution from tire dust, plant fragments, natural gas combustion aerosol, and cigarette smoke. Once these primary aerosol source contributions are added to the secondary sulfates, nitrates and organics present, virtually all of the annual average fine particle mass at Los Angeles area monitoring sites can be assigned to its source.

Source apportionment of airborne particulate matter using organic compounds as tracers

NASA Astrophysics Data System (ADS)

Schauer, James J.; Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

A chemical mass balance receptor model based on organic compounds has been developed that relates sours; contributions to airborne fine particle mass concentrations. Source contributions to the concentrations of specific organic compounds are revealed as well. The model is applied to four air quality monitoring sites in southern California using atmospheric organic compound concentration data and source test data collected specifically for the purpose of testing this model. The contributions of up to nine primary particle source types can be separately identified in ambient samples based on this method, and approximately 85% of the organic fine aerosol is assigned to primary sources on an annual average basis. The model provides information on source contributions to fine mass concentrations, fine organic aerosol concentrations and individual organic compound concentrations. The largest primary source contributors to fine particle mass concentrations in Los Angeles are found to include diesel engine exhaust, paved road dust, gasoline-powered vehicle exhaust, plus emissions from food cooking and wood smoke, with smaller contribution:; from tire dust, plant fragments, natural gas combustion aerosol, and cigarette smoke. Once these primary aerosol source contributions are added to the secondary sulfates, nitrates and organics present, virtually all of the annual average fine particle mass at Los Angeles area monitoring sites can be assigned to its source.

ECONOMIC GROWTH ANALYSIS SYSTEM: USER'S GUIDE

EPA Science Inventory

The two-volume report describes the development of, and provides information needed to operate, a prototype Economic Growth Analysis System (E-GAS) modeling system. The model will be used to project emissions inventories of volatile organic compounds (VOCs), oxides of nitrogen (...

ECONOMIC GROWTH ANALYSIS SYSTEM: REFERENCE MANUAL

EPA Science Inventory

The two-volume report describes the development of, and provides information needed to operate, a prototype Economic Growth Analysis System (E-GAS) modeling system. The model will be used to project emissions inventories of volatile organic compounds (VOCs), oxides of nitrogen (...

Traditional medicine and gastroprotective crude drugs.

PubMed

Schmeda-Hirschmann, Guillermo; Yesilada, Erdem

2005-08-22

A frequent question when dealing with the search for gastroprotective compounds from natural sources is how far or close are both the plant preparations and extract amounts from the doses recommended in traditional medicine and what should be considered realistic levels for experimental studies. The administration way is oral and therefore extracts and products should be administered by gavage when looking for validation of ethnopharmacological uses. Suggestions of doses for both crude extracts and pure compounds are presented and discussed. For plant extracts prepared from single herbs and herbal mixtures, dose-response studies in the range between 100 and 300 mg/kg are suggested, with more than a single gastric ulcer model either in rats or mice. A suitable reference compound should be used according to the ulcer model and in doses resembling those used for human patients. For pure compounds and structure-activity studies or trends, dose-response results should be provided for at least a parent compound in order to select a reasonable dose for comparison purposes. We suggest an evaluation of the activity of the parent compound in the 50-300 mg/kg range and to look for structural modification leading to derivatives with similar or higher gastroprotective effects than the reference antiulcer compounds.

Estimation of reliability of predictions and model applicability domain evaluation in the analysis of acute toxicity (LD50).

PubMed

Sazonovas, A; Japertas, P; Didziapetris, R

2010-01-01

This study presents a new type of acute toxicity (LD(50)) prediction that enables automated assessment of the reliability of predictions (which is synonymous with the assessment of the Model Applicability Domain as defined by the Organization for Economic Cooperation and Development). Analysis involved nearly 75,000 compounds from six animal systems (acute rat toxicity after oral and intraperitoneal administration; acute mouse toxicity after oral, intraperitoneal, intravenous, and subcutaneous administration). Fragmental Partial Least Squares (PLS) with 100 bootstraps yielded baseline predictions that were automatically corrected for non-linear effects in local chemical spaces--a combination called Global, Adjusted Locally According to Similarity (GALAS) modelling methodology. Each prediction obtained in this manner is provided with a reliability index value that depends on both compound's similarity to the training set (that accounts for similar trends in LD(50) variations within multiple bootstraps) and consistency of experimental results with regard to the baseline model in the local chemical environment. The actual performance of the Reliability Index (RI) was proven by its good (and uniform) correlations with Root Mean Square Error (RMSE) in all validation sets, thus providing quantitative assessment of the Model Applicability Domain. The obtained models can be used for compound screening in the early stages of drug development and prioritization for experimental in vitro testing or later in vivo animal acute toxicity studies.

BitterSweetForest: A random forest based binary classifier to predict bitterness and sweetness of chemical compounds

NASA Astrophysics Data System (ADS)

Banerjee, Priyanka; Preissner, Robert

2018-04-01

Taste of a chemical compounds present in food stimulates us to take in nutrients and avoid poisons. However, the perception of taste greatly depends on the genetic as well as evolutionary perspectives. The aim of this work was the development and validation of a machine learning model based on molecular fingerprints to discriminate between sweet and bitter taste of molecules. BitterSweetForest is the first open access model based on KNIME workflow that provides platform for prediction of bitter and sweet taste of chemical compounds using molecular fingerprints and Random Forest based classifier. The constructed model yielded an accuracy of 95% and an AUC of 0.98 in cross-validation. In independent test set, BitterSweetForest achieved an accuracy of 96 % and an AUC of 0.98 for bitter and sweet taste prediction. The constructed model was further applied to predict the bitter and sweet taste of natural compounds, approved drugs as well as on an acute toxicity compound data set. BitterSweetForest suggests 70% of the natural product space, as bitter and 10 % of the natural product space as sweet with confidence score of 0.60 and above. 77 % of the approved drug set was predicted as bitter and 2% as sweet with a confidence scores of 0.75 and above. Similarly, 75% of the total compounds from acute oral toxicity class were predicted only as bitter with a minimum confidence score of 0.75, revealing toxic compounds are mostly bitter. Furthermore, we applied a Bayesian based feature analysis method to discriminate the most occurring chemical features between sweet and bitter compounds from the feature space of a circular fingerprint.

BitterSweetForest: A Random Forest Based Binary Classifier to Predict Bitterness and Sweetness of Chemical Compounds

PubMed Central

Banerjee, Priyanka; Preissner, Robert

2018-01-01

Taste of a chemical compound present in food stimulates us to take in nutrients and avoid poisons. However, the perception of taste greatly depends on the genetic as well as evolutionary perspectives. The aim of this work was the development and validation of a machine learning model based on molecular fingerprints to discriminate between sweet and bitter taste of molecules. BitterSweetForest is the first open access model based on KNIME workflow that provides platform for prediction of bitter and sweet taste of chemical compounds using molecular fingerprints and Random Forest based classifier. The constructed model yielded an accuracy of 95% and an AUC of 0.98 in cross-validation. In independent test set, BitterSweetForest achieved an accuracy of 96% and an AUC of 0.98 for bitter and sweet taste prediction. The constructed model was further applied to predict the bitter and sweet taste of natural compounds, approved drugs as well as on an acute toxicity compound data set. BitterSweetForest suggests 70% of the natural product space, as bitter and 10% of the natural product space as sweet with confidence score of 0.60 and above. 77% of the approved drug set was predicted as bitter and 2% as sweet with a confidence score of 0.75 and above. Similarly, 75% of the total compounds from acute oral toxicity class were predicted only as bitter with a minimum confidence score of 0.75, revealing toxic compounds are mostly bitter. Furthermore, we applied a Bayesian based feature analysis method to discriminate the most occurring chemical features between sweet and bitter compounds using the feature space of a circular fingerprint. PMID:29696137

Discovery of Quinoline-Derived Trifluoromethyl Alcohols, Determination of Their in vivo Toxicity and Anticancer Activity in a Zebrafish Embryo Model.

PubMed

Sittaramane, Vinoth; Padgett, Jihan; Salter, Philip; Williams, Ashley; Luke, Shauntelle; McCall, Rebecca; Arambula, Jonathan F; Graves, Vincent B; Blocker, Mark; Van Leuven, David; Bowe, Keturah; Heimberger, Julia; Cade, Hannah C; Immaneni, Supriya; Shaikh, Abid

2015-11-01

In this study the rational design, synthesis, and anticancer activity of quinoline-derived trifluoromethyl alcohols were evaluated. Members of this novel class of trifluoromethyl alcohols were identified as potent growth inhibitors in a zebrafish embryo model. Synthesis of these compounds was carried out with an sp(3) -C-H functionalization strategy of methyl quinolines with trifluoromethyl ketones. A zebrafish embryo model was also used to explore the toxicity of ethyl 4,4,4-trifluoro-3-hydroxy-3-(quinolin-2-ylmethyl)butanoate (1), 2-benzyl-1,1,1-trifluoro-3-(quinolin-2-yl)propan-2-ol (2), and trifluoro-3-(isoquinolin-1-yl)-2-(thiophen-2-yl)propan-2-ol (3). Compounds 2 and 3 were found to be more toxic than compound 1; apoptotic staining assays indicated that compound 3 causes increased cell death. In vitro cell proliferation assays showed that compound 2, with an LC50 value of 14.14 μm, has more potent anticancer activity than cisplatin. This novel class of inhibitors provides a new direction in the discovery of effective anticancer agents. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Effect of sodium carbonate catalyst weight on production of bio-oil via thermochemical liquefaction of corncobs in ethanol-water solution

NASA Astrophysics Data System (ADS)

Sembodo, Bregas Siswahjono Tatag; Sulistyo, Hary; Sediawan, Wahyudi Budi; Fahrurrozi, Mohammad

2018-02-01

Lignocellulosic biomass has recently received serious attention as an energy source that can replace fossil fuels. Corncob is one of lignocellulosic biomass wastes, which can be further processed into bio-oil through thermochemical liquefaction process. Bio-oil is expected to be further processed into fuel oil. In this research the effect of Na2CO3 catalyst weight on the yield of bio-oil was investigated. The composition of bio-oil produced in this process was analyzed by GC-MS. Bio-oil formation rate were analyzed through mathematical model development. First model aasumed as an isothermal process, while second model was not. It is found that both models were able to provide a good approach to experimental data. The average reaction rate constants was obtained from isothermal model, while the activation energy level and collision factors were obtained from non-isothermal model. The reaction rate will increase by addition of Na2CO3 (0 - 0.5 g) as catalyst to 250 mL system solution, then the activation energy will decrease from 1964.265 joules/mole to 1029.994 joules/mole. The GC-MS analysis results showed that the bio-oil were contained of ester compounds, phenolic compounds, cyclic compunds, heterocyclic compounds, and poly-alcohols compounds.

On the electrostatic and steric similarity of lactam compounds and the natural substrate for bacterial cell-wall biosynthesis

NASA Astrophysics Data System (ADS)

Frau, J.; Price, S. L.

1996-04-01

Electrostatic and structural properties of a set of β-lactam, γ-lactam and nonlactam compounds have been analyzed and compared with those of a model of the natural substrate d-alanyl- d-alanine for the carboxy- and transpeptidase enzymes. This first comparison of the electrostatic properties has been based on a distributed multipole analysis of high-quality ab initio wave functions of the substrate and potential antibiotics. The electrostatic similarity of the substrate and active compounds is apparent, and contrasts with the electrostatic properties of the noninhibitors. This has been quantified to give a reasonable correlation with the MIC (Minimum Concentration for Inhibition) and with kinetic data (k2/K) in accordance with the model for interaction of the lactam compounds with dd-peptidase. These correlations provide a better prediction of antibacterial activity than purely structural criteria.

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.

A Review of the Molecular Mechanisms of Chemically-Induced Neoplasia in Rat and Mouse Models in National Toxicology Program Bioassays and Their Relevance to Human Cancer

PubMed Central

Hoenerhoff, Mark J.; Hong, Hue Hua; Ton, Tai-Vu; Lahousse, Stephanie A.; Sills, Robert C.

2012-01-01

Tumor response in the B6C3F1 mouse, F344 rat, and other animal models following exposure to various compounds provides evidence that people exposed to these or similar compounds may be at risk for developing cancer. Although tumors in rodents and humans are often morphologically similar, underlying mechanisms of tumorigenesis are often unknown and may be different between the species. Therefore, the relevance of an animal tumor response to human health would be better determined if the molecular pathogenesis were understood. The underlying molecular mechanisms leading to carcinogenesis are complex and involve multiple genetic and epigenetic events and other factors. To address the molecular pathogenesis of environmental carcinogens, we examine rodent tumors (e.g., lung, colon, mammary gland, skin, brain, mesothelioma) for alterations in cancer genes and epigenetic events that are associated with human cancer. Our NTP studies have identified several genetic alterations in chemically induced rodent neoplasms that are important in human cancer. Identification of such alterations in rodent models of chemical carcinogenesis caused by exposure to environmental contaminants, occupational chemicals, and other compounds lends further support that they are of potential human health risk. These studies also emphasize the importance of molecular evaluation of chemically induced rodent tumors for providing greater public health significance for NTP evaluated compounds. PMID:19846892

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.

The Effect of Excipients on the Permeability of BCS Class III Compounds and Implications for Biowaivers.

PubMed

Parr, Alan; Hidalgo, Ismael J; Bode, Chris; Brown, William; Yazdanian, Mehran; Gonzalez, Mario A; Sagawa, Kazuko; Miller, Kevin; Jiang, Wenlei; Stippler, Erika S

2016-01-01

Currently, the FDA allows biowaivers for Class I (high solubility and high permeability) and Class III (high solubility and low permeability) compounds of the Biopharmaceutics Classification System (BCS). Scientific evidence should be provided to support biowaivers for BCS Class I and Class III (high solubility and low permeability) compounds. Data on the effects of excipients on drug permeability are needed to demonstrate that commonly used excipients do not affect the permeability of BCS Class III compounds, which would support the application of biowaivers to Class III compounds. This study was designed to generate such data by assessing the permeability of four BCS Class III compounds and one Class I compound in the presence and absence of five commonly used excipients. The permeability of each of the compounds was assessed, at three to five concentrations, with each excipient in two different models: Caco-2 cell monolayers, and in situ rat intestinal perfusion. No substantial increases in the permeability of any of the compounds were observed in the presence of any of the tested excipients in either of the models, with the exception of disruption of Caco-2 cell monolayer integrity by sodium lauryl sulfate at 0.1 mg/ml and higher. The results suggest that the absorption of these four BCS Class III compounds would not be greatly affected by the tested excipients. This may have implications in supporting biowaivers for BCS Class III compounds in general.

Assessment of Inhibition of Ebola Virus Progeny Production by Antiviral Compounds.

PubMed

Falzarano, Darryl

2017-01-01

Assessment of small molecule compounds against filoviruses, such as Ebola virus, has identified numerous compounds that appear to have antiviral activity and should presumably be further investigated in animal efficacy trials. However, despite the many compounds that are purported to have good antiviral activity in in vitro studies, there are few instances where any efficacy has been reported in nonhuman primate models. Many of the high-throughput screening assays use reporter systems that only recapitulate a portion of the virus life cycle, while other assays only assess antiviral activity at relatively early time points. Moreover, many assays do not assess virus progeny production. A more in-depth evaluation of small numbers of test compounds is useful to economize resources and to generate higher quality antiviral hits. Assessing virus progeny production as late as 5 days post-infection allows for the elimination of compounds that have initial antiviral effects that are not sustained or where the virus rapidly develops resistance. While this eliminates many potential lead compounds that may be worthy of further structure-activity relationship (SAR) development, it also quickly excludes compounds that in their current form are unlikely to be effective in animal models. In addition, the inclusion of multiple assays that assess both cell viability and cell cytotoxicity, via different mechanisms, provides a more thorough assessment to exclude compounds that are not direct-acting antivirals.

Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

PubMed

Tropsha, Alexander; Golbraikh, Alexander

2007-01-01

Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data. Model extrapolation was considered if only in hypothetical sense in terms of potential modifications of known biologically active chemicals that could improve compounds' activity. This critical review re-examines the strategy and the output of the modern QSAR modeling approaches. We provide examples and arguments suggesting that current methodologies may afford robust and validated models capable of accurate prediction of compound properties for molecules not included in the training sets. We discuss a data-analytical modeling workflow developed in our laboratory that incorporates modules for combinatorial QSAR model development (i.e., using all possible binary combinations of available descriptor sets and statistical data modeling techniques), rigorous model validation, and virtual screening of available chemical databases to identify novel biologically active compounds. Our approach places particular emphasis on model validation as well as the need to define model applicability domains in the chemistry space. We present examples of studies where the application of rigorously validated QSAR models to virtual screening identified computational hits that were confirmed by subsequent experimental investigations. The emerging focus of QSAR modeling on target property forecasting brings it forward as predictive, as opposed to evaluative, modeling approach.

Effects of steam-microwave blanching and different drying processes on drying characteristics and quality attributes of Thunbergia laurifolia Linn. leaves.

PubMed

Phahom, Traiphop; Phoungchandang, Singhanat; Kerr, William L

2017-08-01

Dried Thunbergia laurifolia leaves are usually prepared using tray drying, resulting in products that have lost substantial amounts of bioactive compounds and antioxidant activity. The maturity of the raw material, blanching techniques and drying methods were investigated in order to select the best condition to produce high qualities of dried T. laurifolia leaves. The 1st stage of maturity was selected and steam-microwave blanching (SMB) for 4 min was adequate for blanching leading to the maximum recovery of bioactive compounds. The modified Halsey model was the best desorption isotherm model. A new drying model proposed in this study was the best to fit the drying curves as compared to five common drying models. Moisture diffusivities were increased with the increase of drying temperature when combining SMB and heat pump-dehumidified drying. Microwave heat pump-dehumidified drying (MHPD) provided the shortest drying time, high specific moisture extraction rate (SMER) and could reduce drying time by 67.5% and increase caffeic acid and quercetin by 51.24% and 60.89%, respectively. MHPD was found to be the best drying method and provided the highest antioxidant activity and bioactive compounds content, high SMER and short drying time. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Availability of Acute and/or Subacute Toxicokinetic Data for Select Compounds for the Rat and Physiologically Based Pharmacokinetic (PBPK) Models for Rats and Humans for Those Compounds

DTIC Science & Technology

2017-05-04

course data for blood were available for both high and low doses (Sanzgiri et al., 1995), while tissue data were available only for high doses...Naval Medical Research Unit Dayton AVAILABILITY OF ACUTE AND/OR SUBACUTE TOXICOKI- NETIC DATA FOR SELECT COMPOUNDS FOR THE RAT AND...provides that ‘Copyright protection under this title is not available for any work of the United States Government.’ Title 17 U.S.C. §101 defines a

SPECIATE--EPA'S DATABASE OF SPECIATED EMISSION PROFILES

EPA Science Inventory

SPECIATE is EPA's repository of Total Organic Compound and Particulate Matter speciated profiles for a wide variety of sources. The profiles in this system are provided for air quality dispersion modeling and as a library for source-receptor and source apportionment type models. ...

A Chemical Containment Model for the General Purpose Work Station

NASA Technical Reports Server (NTRS)

Flippen, Alexis A.; Schmidt, Gregory K.

1994-01-01

Contamination control is a critical safety requirement imposed on experiments flying on board the Spacelab. The General Purpose Work Station, a Spacelab support facility used for life sciences space flight experiments, is designed to remove volatile compounds from its internal airpath and thereby minimize contamination of the Spacelab. This is accomplished through the use of a large, multi-stage filter known as the Trace Contaminant Control System. Many experiments planned for the Spacelab require the use of toxic, volatile fixatives in order to preserve specimens prior to postflight analysis. The NASA-Ames Research Center SLS-2 payload, in particular, necessitated the use of several toxic, volatile compounds in order to accomplish the many inflight experiment objectives of this mission. A model was developed based on earlier theories and calculations which provides conservative predictions of the resultant concentrations of these compounds given various spill scenarios. This paper describes the development and application of this model.

Secondary Metabolites from Three Florida Sponges with Antidepressant Activity

PubMed Central

Kochanowska, Anna J.; Rao, Karumanchi V.; Childress, Suzanne; El-Alfy, Abir; Matsumoto, Rae R.; Kelly, Michelle; Stewart, Gina S.; Sufka, Kenneth J.; Hamann, Mark T.

2016-01-01

Brominated indole alkaloids are a common class of metabolites reported from sponges of the order Verongida. Herein we report the isolation, structure determination, and activity of metabolites from three Florida sponges, namely, Verongula rigida (order Verongida, family Aplysinidae), Smenospongia aurea, and S. cerebriformis (order Dictyoceratida, family Thorectidae). All three species were investigated chemically, revealing similarities in secondary metabolites. Brominated compounds, as well as sesquiterpene quinones and hydroquinones, were identified from both V. rigida and S. aurea despite their apparent taxonomic differences at the ordinal level. Similar metabolites found in these distinct sponge species of two different genera provide evidence for a microbial origin of the metabolites. Isolated compounds were evaluated in the Porsolt forced swim test (FST) and the chick anxiety–depression continuum model. Among the isolated compounds, 5,6-dibromo-N,N-dimethyltryptamine (1) exhibited significant antidepressant-like action in the rodent FST model, while 5-bromo-N,N-dimethyltryptamine (2) caused significant reduction of locomotor activity indicative of a potential sedative action. The current study provides ample evidence that marine natural products with the diversity of brominated marine alkaloids will provide potential leads for antidepressant and anxiolytic drugs. PMID:18217716

Discovery of Novel HIV-1 Integrase Inhibitors Using QSAR-Based Virtual Screening of the NCI Open Database.

PubMed

Ko, Gene M; Garg, Rajni; Bailey, Barbara A; Kumar, Sunil

2016-01-01

Quantitative structure-activity relationship (QSAR) models can be used as a predictive tool for virtual screening of chemical libraries to identify novel drug candidates. The aims of this paper were to report the results of a study performed for descriptor selection, QSAR model development, and virtual screening for identifying novel HIV-1 integrase inhibitor drug candidates. First, three evolutionary algorithms were compared for descriptor selection: differential evolution-binary particle swarm optimization (DE-BPSO), binary particle swarm optimization, and genetic algorithms. Next, three QSAR models were developed from an ensemble of multiple linear regression, partial least squares, and extremely randomized trees models. A comparison of the performances of three evolutionary algorithms showed that DE-BPSO has a significant improvement over the other two algorithms. QSAR models developed in this study were used in consensus as a predictive tool for virtual screening of the NCI Open Database containing 265,242 compounds to identify potential novel HIV-1 integrase inhibitors. Six compounds were predicted to be highly active (plC50 > 6) by each of the three models. The use of a hybrid evolutionary algorithm (DE-BPSO) for descriptor selection and QSAR model development in drug design is a novel approach. Consensus modeling may provide better predictivity by taking into account a broader range of chemical properties within the data set conducive for inhibition that may be missed by an individual model. The six compounds identified provide novel drug candidate leads in the design of next generation HIV- 1 integrase inhibitors targeting drug resistant mutant viruses.

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).

Use of molecular modeling aided design to dial out hERG liability in adenosine A(2A) receptor antagonists.

PubMed

Deng, Qiaolin; Lim, Yeon-Hee; Anand, Rajan; Yu, Younong; Kim, Jae-hun; Zhou, Wei; Zheng, Junying; Tempest, Paul; Levorse, Dorothy; Zhang, Xiaoping; Greene, Scott; Mullins, Deborra; Culberson, Chris; Sherborne, Brad; Parker, Eric M; Stamford, Andrew; Ali, Amjad

2015-08-01

Molecular modeling was performed on a triazolo quinazoline lead compound to help develop a series of adenosine A2A receptor antagonists with improved hERG profile. Superposition of the lead compound onto MK-499, a benchmark hERG inhibitor, combined with pKa calculations and measurement, identified terminal fluorobenzene to be responsible for hERG activity. Docking of the lead compound into an A2A crystal structure suggested that this group is located at a flexible, spacious, and solvent-exposed opening of the binding pocket, making it possible to tolerate various functional groups. Transformation analysis (MMP, matched molecular pair) of in-house available experimental data on hERG provided suggestions for modifications in order to mitigate this liability. This led to the synthesis of a series of compounds with significantly reduced hERG activity. The strategy used in the modeling work can be applied to other medicinal chemistry programs to help improve hERG profile. Copyright © 2015 Elsevier Ltd. All rights reserved.

A semi-synthetic natural product blocks collagen induced arthritis by preferentially suppressing the production of IL-6.

PubMed

Kulkarni-Almeida, Asha; Shah, Meet; Jadhav, Mahesh; Hegde, Bindu; Trivedi, Jacqueline; Mishra, Prabhu D; Mahajan, Girish B; Dadarkar, Shruta; Gupte, Ravindra; Dagia, Nilesh

2016-04-01

Rheumatoid arthritis (RA), an autoimmune-inflammatory disease is characterized by dysregulation of signal transduction pathways, increased production of pro-inflammatory cytokines, enhanced leukocyte infiltration into synovial microvascular endothelium, extensive formation of hyper proliferative pannus, degradation of cartilage and bone erosion. Several compounds that abrogate cytokine production demonstrate a therapeutic effect in experimental models of arthritis. In this study, we report that a novel semi-synthetic natural product (Compound A) being a preferential IL-6 inhibitor, is efficacious in a murine model of arthritis. In vitro evaluations of pro-inflammatory cytokine production reveal that Compound A preferentially inhibits induced production of IL-6 and not TNF-α from THP-1 cells and isolated human monocytes. Furthermore, Compound A robustly inhibits the spontaneous production of IL-6 from pathologically relevant synovial tissue cells isolated from patients with active RA. In a physiologically relevant assay, Compound A selectively inhibits the activated T cell contact-mediated production of IL-6 from human monocytes. Compound A, at pharmacologically efficacious concentrations, does not significantly curtail the LPS-induced activation of p38 MAPKs. In the collagen-induced arthritis (CIA) mouse model (i) macroscopic observations demonstrate that Compound A, administered subcutaneously in a therapeutic regimen, significantly and dose-dependently inhibits disease associated increases in articular index and paw thickness; (ii) histological analyses of paw tissues reveal that Compound A prominently diminishes joint destruction, hyperproliferative pannus formation and infiltration of inflammatory cells. Collectively, these results provide direct evidence that Compound A, a novel preferential IL-6 inhibitor, suppresses collagen-induced arthritis, and may be a potential therapeutic for treating patients with active RA. Copyright © 2016. Published by Elsevier B.V.

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.

Identification of New Antifungal Compounds Targeting Thioredoxin Reductase of Paracoccidioides Genus

PubMed Central

Abadio, Ana Karina Rodrigues; Kioshima, Erika Seki; Leroux, Vincent; Martins, Natalia Florêncio; Maigret, Bernard; Felipe, Maria Sueli Soares

2015-01-01

The prevalence of invasive fungal infections worldwide has increased in the last decades. The development of specific drugs targeting pathogenic fungi without producing collateral damage to mammalian cells is a daunting pharmacological challenge. Indeed, many of the toxicities and drug interactions observed with contemporary antifungal therapies can be attributed to “nonselective” interactions with enzymes or cell membrane systems found in mammalian host cells. A computer-aided screening strategy against the TRR1 protein of Paracoccidioides lutzii is presented here. Initially, a bank of commercially available compounds from Life Chemicals provider was docked to model by virtual screening simulations. The small molecules that interact with the model were ranked and, among the best hits, twelve compounds out of 3,000 commercially-available candidates were selected. These molecules were synthesized for validation and in vitro antifungal activity assays for Paracoccidioides lutzii and P. brasiliensis were performed. From 12 molecules tested, 3 harbor inhibitory activity in antifungal assays against the two pathogenic fungi. Corroborating these findings, the molecules have inhibitory activity against the purified recombinant enzyme TRR1 in biochemical assays. Therefore, a rational combination of molecular modeling simulations and virtual screening of new drugs has provided a cost-effective solution to an early-stage medicinal challenge. These results provide a promising technique to the development of new and innovative drugs. PMID:26569405

Periodic and Aperiodic Close Packing: A Spontaneous Hard-Sphere Model.

ERIC Educational Resources Information Center

van de Waal, B. W.

1985-01-01

Shows how to make close-packed models from balloons and table tennis balls to illustrate structural features of clusters and organometallic cluster-compounds (which are of great interest in the study of chemical reactions). These models provide a very inexpensive and tactile illustration of the organization of matter for concrete operational…

Quantitative structure-permeability relationships at various pH values for acidic and basic drugs and drug-like compounds.

PubMed

Oja, M; Maran, U

2015-01-01

Absorption in gastrointestinal tract compartments varies and is largely influenced by pH. Therefore, considering pH in studies and analyses of membrane permeability provides an opportunity to gain a better understanding of the behaviour of compounds and to obtain good permeability estimates for prediction purposes. This study concentrates on relationships between the chemical structure and membrane permeability of acidic and basic drugs and drug-like compounds. The membrane permeability of 36 acidic and 61 basic compounds was measured using the parallel artificial membrane permeability assay (PAMPA) at pH 3, 5, 7.4 and 9. Descriptive and/or predictive single-parameter quantitative structure-permeability relationships were derived for all pH values. For acidic compounds, membrane permeability is mainly influenced by hydrogen bond donor properties, as revealed by models with r(2) > 0.8 for pH 3 and pH 5. For basic compounds, the best (r(2) > 0.7) structure-permeability relationships are obtained with the octanol-water distribution coefficient for pH 7.4 and pH 9, indicating the importance of partition properties. In addition to the validation set, the prediction quality of the developed models was tested with folic acid and astemizole, showing good matches between experimental and calculated membrane permeabilities at key pHs. Selected QSAR models are available at the QsarDB repository ( http://dx.doi.org/10.15152/QDB.166 ).

ECONOMIC GROWTH ANALYSIS SYSTEM: USER'S GUIDE VERSION 2.0

EPA Science Inventory

The two-volume report describes the development of and provides information needed to operate, the Economic Growth Analysis System (E-GAS) Version 2.0 model. The model will be used to project emissions inventories of volatile organic compounds (VOCs), oxides of nitrogen (NOx), a...

ECONOMIC GROWTH ANALYSIS SYSTEM: REFERENCE MANUAL VERSION 2.0

EPA Science Inventory

The two-volume report describes the development of and provides information needed to operate, the Economic Growth Analysis System (E-GAS) Version 2.0 model. The model will be used to project emissions inventories of volatile organic compounds (VOCs), oxides of nitrogen (NOx), a...

ECONOMIC GROWTH ANALYSIS SYSTEM: USER'S GUIDE - VERSION 3.0

EPA Science Inventory

The two-volume report describes the development of, and provides information needed to operate, the Economic Growth Analysis System (E-GAS) Version 3.0 model. The model will be used to project emissions inventories of volatile organic compounds, oxides of nitrogen, and carbon mon...

ECONOMIC GROWTH ANALYSIS SYSTEM: REFERENCE MANUAL VERSION 3.0

EPA Science Inventory

The two-volume report describes the development of, and provides information needed to operate, the Economic Growth Analysis System (E-GAS) Version 3.0 model. The model will be used to project emissions inventories of volatile organic compounds, oxides of nitrogen, and carbon mon...

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...

Competition between conceptual relations affects compound recognition: the role of entropy.

PubMed

Schmidtke, Daniel; Kuperman, Victor; Gagné, Christina L; Spalding, Thomas L

2016-04-01

Previous research has suggested that the conceptual representation of a compound is based on a relational structure linking the compound's constituents. Existing accounts of the visual recognition of modifier-head or noun-noun compounds posit that the process involves the selection of a relational structure out of a set of competing relational structures associated with the same compound. In this article, we employ the information-theoretic metric of entropy to gauge relational competition and investigate its effect on the visual identification of established English compounds. The data from two lexical decision megastudies indicates that greater entropy (i.e., increased competition) in a set of conceptual relations associated with a compound is associated with longer lexical decision latencies. This finding indicates that there exists competition between potential meanings associated with the same complex word form. We provide empirical support for conceptual composition during compound word processing in a model that incorporates the effect of the integration of co-activated and competing relational information.

High-Throughput Gene Expression Profiles to Define Drug Similarity and Predict Compound Activity.

PubMed

De Wolf, Hans; Cougnaud, Laure; Van Hoorde, Kirsten; De Bondt, An; Wegner, Joerg K; Ceulemans, Hugo; Göhlmann, Hinrich

2018-04-01

By adding biological information, beyond the chemical properties and desired effect of a compound, uncharted compound areas and connections can be explored. In this study, we add transcriptional information for 31K compounds of Janssen's primary screening deck, using the HT L1000 platform and assess (a) the transcriptional connection score for generating compound similarities, (b) machine learning algorithms for generating target activity predictions, and (c) the scaffold hopping potential of the resulting hits. We demonstrate that the transcriptional connection score is best computed from the significant genes only and should be interpreted within its confidence interval for which we provide the stats. These guidelines help to reduce noise, increase reproducibility, and enable the separation of specific and promiscuous compounds. The added value of machine learning is demonstrated for the NR3C1 and HSP90 targets. Support Vector Machine models yielded balanced accuracy values ≥80% when the expression values from DDIT4 & SERPINE1 and TMEM97 & SPR were used to predict the NR3C1 and HSP90 activity, respectively. Combining both models resulted in 22 new and confirmed HSP90-independent NR3C1 inhibitors, providing two scaffolds (i.e., pyrimidine and pyrazolo-pyrimidine), which could potentially be of interest in the treatment of depression (i.e., inhibiting the glucocorticoid receptor (i.e., NR3C1), while leaving its chaperone, HSP90, unaffected). As such, the initial hit rate increased by a factor 300, as less, but more specific chemistry could be screened, based on the upfront computed activity predictions.

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.

Wet scrubbing of biomass producer gas tars using vegetable oil

NASA Astrophysics Data System (ADS)

Bhoi, Prakashbhai Ramabhai

The overall aims of this research study were to generate novel design data and to develop an equilibrium stage-based thermodynamic model of a vegetable oil based wet scrubbing system for the removal of model tar compounds (benzene, toluene and ethylbenzene) found in biomass producer gas. The specific objectives were to design, fabricate and evaluate a vegetable oil based wet scrubbing system and to optimize the design and operating variables; i.e., packed bed height, vegetable oil type, solvent temperature, and solvent flow rate. The experimental wet packed bed scrubbing system includes a liquid distributor specifically designed to distribute a high viscous vegetable oil uniformly and a mixing section, which was designed to generate a desired concentration of tar compounds in a simulated air stream. A method and calibration protocol of gas chromatography/mass spectroscopy was developed to quantify tar compounds. Experimental data were analyzed statistically using analysis of variance (ANOVA) procedure. Statistical analysis showed that both soybean and canola oils are potential solvents, providing comparable removal efficiency of tar compounds. The experimental height equivalent to a theoretical plate (HETP) was determined as 0.11 m for vegetable oil based scrubbing system. Packed bed height and solvent temperature had highly significant effect (p0.05) effect on the removal of model tar compounds. The packing specific constants, Ch and CP,0, for the Billet and Schultes pressure drop correlation were determined as 2.52 and 2.93, respectively. The equilibrium stage based thermodynamic model predicted the removal efficiency of model tar compounds in the range of 1-6%, 1-4% and 1-2% of experimental data for benzene, toluene and ethylbenzene, respectively, for the solvent temperature of 30° C. The NRTL-PR property model and UNIFAC for estimating binary interaction parameters are recommended for modeling absorption of tar compounds in vegetable oils. Bench scale experimental data from the wet scrubbing system would be useful in the design and operation of a pilot scale vegetable oil based system. The process model, validated using experimental data, would be a key design tool for the design and optimization of a pilot scale vegetable oil based system.

[Screen potential CYP450 2E1 inhibitors from Chinese herbal medicine based on support vector regression and molecular docking method].

PubMed

Chen, Xi; Lu, Fang; Jiang, Lu-di; Cai, Yi-Lian; Li, Gong-Yu; Zhang, Yan-Ling

2016-07-01

Inhibition of cytochrome P450 (CYP450) enzymes is the most common reasons for drug interactions, so the study on early prediction of CYPs inhibitors can help to decrease the incidence of adverse reactions caused by drug interactions.CYP450 2E1(CYP2E1), as a key role in drug metabolism process, has broad spectrum of drug metabolism substrate. In this study, 32 CYP2E1 inhibitors were collected for the construction of support vector regression (SVR) model. The test set data were used to verify CYP2E1 quantitative models and obtain the optimal prediction model of CYP2E1 inhibitor. Meanwhile, one molecular docking program, CDOCKER, was utilized to analyze the interaction pattern between positive compounds and active pocket to establish the optimal screening model of CYP2E1 inhibitors.SVR model and molecular docking prediction model were combined to screen traditional Chinese medicine database (TCMD), which could improve the calculation efficiency and prediction accuracy. 6 376 traditional Chinese medicine (TCM) compounds predicted by SVR model were obtained, and in further verification by using molecular docking model, 247 TCM compounds with potential inhibitory activities against CYP2E1 were finally retained. Some of them have been verified by experiments. The results demonstrated that this study could provide guidance for the virtual screening of CYP450 inhibitors and the prediction of CYPs-mediated DDIs, and also provide references for clinical rational drug use. Copyright© by the Chinese Pharmaceutical Association.

Identification of small molecule lead compounds for visceral leishmaniasis using a novel ex vivo splenic explant model system.

PubMed

Osorio, Yaneth; Travi, Bruno L; Renslo, Adam R; Peniche, Alex G; Melby, Peter C

2011-02-15

New drugs are needed to treat visceral leishmaniasis (VL) because the current therapies are toxic, expensive, and parasite resistance may weaken drug efficacy. We established a novel ex vivo splenic explant culture system from hamsters infected with luciferase-transfected Leishmania donovani to screen chemical compounds for anti-leishmanial activity. THIS MODEL HAS ADVANTAGES OVER IN VITRO SYSTEMS IN THAT IT: 1) includes the whole cellular population involved in the host-parasite interaction; 2) is initiated at a stage of infection when the immunosuppressive mechanisms that lead to progressive VL are evident; 3) involves the intracellular form of Leishmania; 4) supports parasite replication that can be easily quantified by detection of parasite-expressed luciferase; 5) is adaptable to a high-throughput screening format; and 6) can be used to identify compounds that have both direct and indirect anti-parasitic activity. The assay showed excellent discrimination between positive (amphotericin B) and negative (vehicle) controls with a Z' Factor >0.8. A duplicate screen of 4 chemical libraries containing 4,035 compounds identified 202 hits (5.0%) with a Z score of <-1.96 (p<0.05). Eighty-four (2.1%) of the hits were classified as lead compounds based on the in vitro therapeutic index (ratio of the compound concentration causing 50% cytotoxicity in the HepG(2) cell line to the concentration that caused 50% reduction in the parasite load). Sixty-nine (82%) of the lead compounds were previously unknown to have anti-leishmanial activity. The most frequently identified lead compounds were classified as quinoline-containing compounds (14%), alkaloids (10%), aromatics (11%), terpenes (8%), phenothiazines (7%) and furans (5%). The ex vivo splenic explant model provides a powerful approach to identify new compounds active against L. donovani within the pathophysiologic environment of the infected spleen. Further in vivo evaluation and chemical optimization of these lead compounds may generate new candidates for preclinical studies of treatment for VL.

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.

Large-Scale Phenotype-Based Antiepileptic Drug Screening in a Zebrafish Model of Dravet Syndrome1,2,3

PubMed Central

Dinday, Matthew T.

2015-01-01

Abstract Mutations in a voltage-gated sodium channel (SCN1A) result in Dravet Syndrome (DS), a catastrophic childhood epilepsy. Zebrafish with a mutation in scn1Lab recapitulate salient phenotypes associated with DS, including seizures, early fatality, and resistance to antiepileptic drugs. To discover new drug candidates for the treatment of DS, we screened a chemical library of ∼1000 compounds and identified 4 compounds that rescued the behavioral seizure component, including 1 compound (dimethadione) that suppressed associated electrographic seizure activity. Fenfluramine, but not huperzine A, also showed antiepileptic activity in our zebrafish assays. The effectiveness of compounds that block neuronal calcium current (dimethadione) or enhance serotonin signaling (fenfluramine) in our zebrafish model suggests that these may be important therapeutic targets in patients with DS. Over 150 compounds resulting in fatality were also identified. We conclude that the combination of behavioral and electrophysiological assays provide a convenient, sensitive, and rapid basis for phenotype-based drug screening in zebrafish mimicking a genetic form of epilepsy. PMID:26465006

Numerical modeling of sorption kinetics of organic compounds to soil and sediment particles

NASA Astrophysics Data System (ADS)

Wu, Shian-chee; Gschwend, Phillip M.

1988-08-01

A numerical model is developed to simulate hydrophobic organic compound sorption kinetics, based on a retarded intraaggregate diffusion conceptualization of this solid-water exchange process. This model was used to ascertain the sensitivity of the sorption process for various sorbates to nonsteady solution concentrations and to polydisperse soil or sediment aggregate particle size distributions. Common approaches to modeling sorption kinetics amount to simplifications of our model and appear justified only when (1) the concentration fluctuations occur on a time scale which matches the sorption timescale of interest and (2) the particle size distribution is relatively narrow. Finally, a means is provided to estimate the extent of approach of a sorbing system to equilibrium as a function of aggregate size, chemical diffusivity and hydrophobicity, and system solids concentration.

Odor composition analysis and odor indicator selection during sewage sludge composting

PubMed Central

Zhu, Yan-li; Zheng, Guo-di; Gao, Ding; Chen, Tong-bin; Wu, Fang-kun; Niu, Ming-jie; Zou, Ke-hua

2016-01-01

ABSTRACT On the basis of total temperature increase, normal dehydration, and maturity, the odor compositions of surface and internal piles in a well-run sewage sludge compost plant were analyzed using gas chromatography–mass spectrometry with a liquid nitrogen cooling system and a portable odor detector. Approximately 80 types of substances were detected, including 2 volatile inorganic compounds, 4 sulfur organic compounds, 16 benzenes, 27 alkanes, 15 alkenes, and 19 halogenated compounds. Most pollutants were mainly produced in the mesophilic and pre-thermophilic periods. The sulfur volatile organic compounds contributed significantly to odor and should be controlled primarily. Treatment strategies should be based on the properties of sulfur organic compounds. Hydrogen sulfide, methyl mercaptan, dimethyl disulfide, dimethyl sulfide, ammonia, and carbon disulfide were selected as core indicators. Ammonia, hydrogen sulfide, carbon disulfide, dimethyl disulfide, methyl mercaptan, dimethylbenzene, phenylpropane, and isopentane were designated as concentration indicators. Benzene, m-xylene, p-xylene, dimethylbenzene, dichloromethane, toluene, chlorobenzene, trichloromethane, carbon tetrachloride, and ethylbenzene were selected as health indicators. According to the principle of odor pollution indicator selection, dimethyl disulfide was selected as an odor pollution indicator of sewage sludge composting. Monitoring dimethyl disulfide provides a highly scientific method for modeling and evaluating odor pollution from sewage sludge composting facilities. Implications: Composting is one of the most important methods for sewage sludge treatment and improving the low organic matter content of many agricultural soils. However, odors are inevitably produced during the composting process. Understanding the production and emission patterns of odors is important for odor control and treatment. Core indicators, concentration indicators, and health indicators provide an index system to odor evaluation. An odor pollution indicator provides theoretical support for further modelling and evaluating odor pollution from sewage sludge composting facilities. PMID:27192607

Odor composition analysis and odor indicator selection during sewage sludge composting.

PubMed

Zhu, Yan-Li; Zheng, Guo-di; Gao, Ding; Chen, Tong-Bin; Wu, Fang-Kun; Niu, Ming-Jie; Zou, Ke-Hua

2016-09-01

On the basis of total temperature increase, normal dehydration, and maturity, the odor compositions of surface and internal piles in a well-run sewage sludge compost plant were analyzed using gas chromatography-mass spectrometry with a liquid nitrogen cooling system and a portable odor detector. Approximately 80 types of substances were detected, including 2 volatile inorganic compounds, 4 sulfur organic compounds, 16 benzenes, 27 alkanes, 15 alkenes, and 19 halogenated compounds. Most pollutants were mainly produced in the mesophilic and pre-thermophilic periods. The sulfur volatile organic compounds contributed significantly to odor and should be controlled primarily. Treatment strategies should be based on the properties of sulfur organic compounds. Hydrogen sulfide, methyl mercaptan, dimethyl disulfide, dimethyl sulfide, ammonia, and carbon disulfide were selected as core indicators. Ammonia, hydrogen sulfide, carbon disulfide, dimethyl disulfide, methyl mercaptan, dimethylbenzene, phenylpropane, and isopentane were designated as concentration indicators. Benzene, m-xylene, p-xylene, dimethylbenzene, dichloromethane, toluene, chlorobenzene, trichloromethane, carbon tetrachloride, and ethylbenzene were selected as health indicators. According to the principle of odor pollution indicator selection, dimethyl disulfide was selected as an odor pollution indicator of sewage sludge composting. Monitoring dimethyl disulfide provides a highly scientific method for modeling and evaluating odor pollution from sewage sludge composting facilities. Composting is one of the most important methods for sewage sludge treatment and improving the low organic matter content of many agricultural soils. However, odors are inevitably produced during the composting process. Understanding the production and emission patterns of odors is important for odor control and treatment. Core indicators, concentration indicators, and health indicators provide an index system to odor evaluation. An odor pollution indicator provides theoretical support for further modelling and evaluating odor pollution from sewage sludge composting facilities.

Group-based QSAR and molecular dynamics mechanistic analysis revealing the mode of action of novel piperidinone derived protein-protein inhibitors of p53-MDM2.

PubMed

Goyal, Sukriti; Grover, Sonam; Dhanjal, Jaspreet Kaur; Tyagi, Chetna; Goyal, Manisha; Grover, Abhinav

2014-06-01

Tumour suppressor p53 is known to play a central role in prevention of tumour development, DNA repair, senescence and apoptosis which is in normal cells maintained by negative feedback regulator MDM2 (Murine Double Minute 2). In case of dysfunctioning of this regulatory loop, tumour development starts thus resulting in cancerous condition. Inhibition of p53-MDM2 binding would result in activation of the tumour suppressor. In this study, a novel robust fragment-based QSAR model has been developed for piperidinone derived compounds experimentally known to inhibit p53-MDM2 interaction. The QSAR model developed showed satisfactory statistical parameters for the experimentally reported dataset (r(2)=0.9415, q(2)=0.8958, pred_r(2)=0.8894 and F-test=112.7314), thus judging the robustness of the model. Low standard error values (r(2)_se=0.3003, q(2)_se=0.4009 and pred_r(2)_se=0.3315) confirmed the accuracy of the developed model. The regression equation obtained constituted three descriptors (R2-DeltaEpsilonA, R1-RotatableBondCount and R2-SssOCount), two of which had positive contribution while third showed negative correlation. Based on the developed QSAR model, a combinatorial library was generated and activities of the compounds were predicted. These compounds were docked with MDM2 and two top scoring compounds with binding affinities of -10.13 and -9.80kcal/mol were selected. The binding modes of actions of these complexes were analyzed using molecular dynamics simulations. Analysis of the developed fragment-based QSAR model revealed that addition of unsaturated electronegative groups at R2 site and groups with more rotatable bonds at R1 improved the inhibitory activity of these potent lead compounds. The detailed analysis carried out in this study provides a considerable basis for the design and development of novel piperidinone-based lead molecules against cancer and also provides mechanistic insights into their mode of actions. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Quest for consistent modelling of statistical decay of the compound nucleus

NASA Astrophysics Data System (ADS)

Banerjee, Tathagata; Nath, S.; Pal, Santanu

2018-01-01

A statistical model description of heavy ion induced fusion-fission reactions is presented where shell effects, collective enhancement of level density, tilting away effect of compound nuclear spin and dissipation are included. It is shown that the inclusion of all these effects provides a consistent picture of fission where fission hindrance is required to explain the experimental values of both pre-scission neutron multiplicities and evaporation residue cross-sections in contrast to some of the earlier works where a fission hindrance is required for pre-scission neutrons but a fission enhancement for evaporation residue cross-sections.

On the first polyarsenic organic compound from nature: arsenicin A from the New Caledonian marine sponge Echinochalina bargibanti.

PubMed

Mancini, Ines; Guella, Graziano; Frostin, Maryvonne; Hnawia, Edouard; Laurent, Dominique; Debitus, Cecile; Pietra, Francesco

2006-12-04

Reported here is the first polyarsenic compound ever found in nature. Denominated arsenicin A, it was isolated along a bioassay-guided fractionation of the organic extract of the poecilosclerid sponge Echinochalina bargibanti collected from the north-eastern coast of New Caledonia. In defining an adamantine-type polyarsenic structure for this compound, deceptively simple NMR spectra were complemented by extensive mass spectral analysis. However, it was only the synthesis of a model compound that provided the basis to discriminate structure 4 from other spectrally compatible structures for arsenicin A; to this end, a comparative ab initio simulation of IR spectra for the natural and the synthetic compounds was decisive. Arsenicin A is endowed with potent bactericidal and fungicidal activities on human pathogenic strains. All this may revive pharmacological interest in arsenic compounds while prompting us to rethink the arsenic cycle in nature.

Removal of volatile organic compounds using amphiphilic cyclodextrin-coated polypropylene.

PubMed

Lumholdt, Ludmilla; Fourmentin, Sophie; Nielsen, Thorbjørn T; Larsen, Kim L

2014-01-01

Polypropylene nonwovens were functionalised using a self-assembled, amphiphilic cyclodextrin coating and the potential for water purification by removal of pollutants was studied. As benzene is one of the problematic compounds in the Water Framework Directive, six volatile organic compounds (benzene and five benzene-based substances) were chosen as model compounds. The compounds were tested as a mixture in order to provide a more realistic situation since the wastewater will be a complex mixture containing multiple pollutants. The volatile organic compounds are known to form stable inclusion complexes with cyclodextrins. Six different amphiphilic cyclodextrin derivatives were synthesised in order to elucidate whether or not the uptake abilities of the coating depend on the structure of the derivative. Headspace gas chromatography was used for quantification of the uptake exploiting the volatile nature of benzene and its derivatives. The capacity was shown to increase beyond the expected stoichiometries of guest-host complexes with ratios of up to 16:1.

Quantitative structure-activity relationship for the partition coefficient of hydrophobic compounds between silicone oil and air.

PubMed

Qu, Yanfei; Ma, Yongwen; Wan, Jinquan; Wang, Yan

2018-06-01

The silicon oil-air partition coefficients (K SiO/A ) of hydrophobic compounds are vital parameters for applying silicone oil as non-aqueous-phase liquid in partitioning bioreactors. Due to the limited number of K SiO/A values determined by experiment for hydrophobic compounds, there is an urgent need to model the K SiO/A values for unknown chemicals. In the present study, we developed a universal quantitative structure-activity relationship (QSAR) model using a sequential approach with macro-constitutional and micromolecular descriptors for silicone oil-air partition coefficients (K SiO/A ) of hydrophobic compounds with large structural variance. The geometry optimization and vibrational frequencies of each chemical were calculated using the hybrid density functional theory at the B3LYP/6-311G** level. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates that a regression model derived from logK SiO/A , the number of non-hydrogen atoms (#nonHatoms) and energy gap of E LUMO and E HOMO (E LUMO -E HOMO ) could explain the partitioning mechanism of hydrophobic compounds between silicone oil and air. The correlation coefficient R 2 of the model is 0.922, and the internal and external validation coefficient, Q 2 LOO and Q 2 ext , are 0.91 and 0.89 respectively, implying that the model has satisfactory goodness-of-fit, robustness, and predictive ability and thus provides a robust predictive tool to estimate the logK SiO/A values for chemicals in application domain. The applicability domain of the model was visualized by the Williams plot.

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

Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

PubMed

Ribay, Kathryn; Kim, Marlene T; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

2016-03-01

Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR models, particularly for the activity cliffs that induce prediction errors. The results of this study indicate that the response profile of chemicals from public data provides useful information for modeling and evaluation purposes. The public big data resources should be considered along with chemical structure information when predicting new compounds, such as unknown ERα binding agents.

Prediction of pH-Dependent Hydrophobic Profiles of Small Molecules from Miertus-Scrocco-Tomasi Continuum Solvation Calculations.

PubMed

Zamora, William J; Curutchet, Carles; Campanera, Josep M; Luque, F Javier

2017-10-26

Hydrophobicity is a key physicochemical descriptor used to understand the biological profile of (bio)organic compounds as well as a broad variety of biochemical, pharmacological, and toxicological processes. This property is estimated from the partition coefficient between aqueous and nonaqueous environments for neutral compounds (P N ) and corrected for the pH-dependence of ionizable compounds as the distribution coefficient (D). Here, we have extended the parametrization of the Miertus-Scrocco-Tomasi continuum solvation model in n-octanol to nitrogen-containing heterocyclic compounds, as they are present in many biologically relevant molecules (e.g., purines and pyrimidines bases, amino acids, and drugs), to obtain accurate log P N values for these molecules. This refinement also includes solvation calculations for ionic species in n-octanol with the aim of reproducing the experimental partition of ionic compounds (P I ). Finally, the suitability of different formalisms to estimate the distribution coefficient for a wide range of pH values has been examined for a set of small acidic and basic compounds. The results indicate that in general the simple pH-dependence model of the ionizable compound in water suffices to predict the partitioning at or around physiological pH. However, at extreme pH values, where ionic species are predominant, more elaborate models provide a better prediction of the n-octanol/water distribution coefficient, especially for amino acid analogues. Finally, the results also show that these formalisms are better suited to reproduce the experimental pH-dependent distribution curves of log D for both acidic and basic compounds as well as for amino acid analogues.

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling.

PubMed

Bazeley, Peter S; Prithivi, Sridevi; Struble, Craig A; Povinelli, Richard J; Sem, Daniel S

2006-01-01

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.

Evidence-based selection of training compounds for use in the mechanism-based integrated prediction of drug-induced liver injury in man.

PubMed

Dragovic, Sanja; Vermeulen, Nico P E; Gerets, Helga H; Hewitt, Philip G; Ingelman-Sundberg, Magnus; Park, B Kevin; Juhila, Satu; Snoeys, Jan; Weaver, Richard J

2016-12-01

The current test systems employed by pharmaceutical industry are poorly predictive for drug-induced liver injury (DILI). The 'MIP-DILI' project addresses this situation by the development of innovative preclinical test systems which are both mechanism-based and of physiological, pharmacological and pathological relevance to DILI in humans. An iterative, tiered approach with respect to test compounds, test systems, bioanalysis and systems analysis is adopted to evaluate existing models and develop new models that can provide validated test systems with respect to the prediction of specific forms of DILI and further elucidation of mechanisms. An essential component of this effort is the choice of compound training set that will be used to inform refinement and/or development of new model systems that allow prediction based on knowledge of mechanisms, in a tiered fashion. In this review, we focus on the selection of MIP-DILI training compounds for mechanism-based evaluation of non-clinical prediction of DILI. The selected compounds address both hepatocellular and cholestatic DILI patterns in man, covering a broad range of pharmacologies and chemistries, and taking into account available data on potential DILI mechanisms (e.g. mitochondrial injury, reactive metabolites, biliary transport inhibition, and immune responses). Known mechanisms by which these compounds are believed to cause liver injury have been described, where many if not all drugs in this review appear to exhibit multiple toxicological mechanisms. Thus, the training compounds selection offered a valuable tool to profile DILI mechanisms and to interrogate existing and novel in vitro systems for the prediction of human DILI.

Large-scale annotation of small-molecule libraries using public databases.

PubMed

Zhou, Yingyao; Zhou, Bin; Chen, Kaisheng; Yan, S Frank; King, Frederick J; Jiang, Shumei; Winzeler, Elizabeth A

2007-01-01

While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.

Development of a Computational (in silico) Model of Ocular Teratogenesis

EPA Science Inventory

EPA’s ToxCast™ project is profiling the in vitro bioactivity of chemical compounds to assess pathway-level and cell-based signatures that are highly correlated with observed in vivo toxicity. In silico models provide a framework for interpreting the in vitro results and for simul...

Evaluation of Marijuana Compounds on Neuroimmune Endpoints in Experimental Autoimmune Encephalomyelitis.

PubMed

Kaplan, Barbara L F

2018-02-21

Cannabinoid compounds refer to a group of more than 60 plant-derived compounds in Cannabis sativa, more commonly known as marijuana. Exposure to marijuana and cannabinoid compounds has been increasing due to increased societal acceptance for both recreational and possible medical use. Cannabinoid compounds suppress immune function, and while this could compromise one's ability to fight infections, immune suppression is the desired effect for therapies for autoimmune diseases. It is critical, therefore, to understand the effects and mechanisms by which cannabinoid compounds alter immune function, especially immune responses induced in autoimmune disease. Therefore, this unit will describe induction and assessment of the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis (MS), and its potential alteration by cannabinoid compounds. The unit includes three approaches to induce EAE, two of which provide correlations to two forms of MS, and the third specifically addresses the role of autoreactive T cells in EAE. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Combining structure-based pharmacophore modeling, virtual screening, and in silico ADMET analysis to discover novel tetrahydro-quinoline based pyruvate kinase isozyme M2 activators with antitumor activity

PubMed Central

Chen, Can; Wang, Ting; Wu, Fengbo; Huang, Wei; He, Gu; Ouyang, Liang; Xiang, Mingli; Peng, Cheng; Jiang, Qinglin

2014-01-01

Compared with normal differentiated cells, cancer cells upregulate the expression of pyruvate kinase isozyme M2 (PKM2) to support glycolytic intermediates for anabolic processes, including the synthesis of nucleic acids, amino acids, and lipids. In this study, a combination of the structure-based pharmacophore modeling and a hybrid protocol of virtual screening methods comprised of pharmacophore model-based virtual screening, docking-based virtual screening, and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis were used to retrieve novel PKM2 activators from commercially available chemical databases. Tetrahydroquinoline derivatives were identified as potential scaffolds of PKM2 activators. Thus, the hybrid virtual screening approach was applied to screen the focused tetrahydroquinoline derivatives embedded in the ZINC database. Six hit compounds were selected from the final hits and experimental studies were then performed. Compound 8 displayed a potent inhibitory effect on human lung cancer cells. Following treatment with Compound 8, cell viability, apoptosis, and reactive oxygen species (ROS) production were examined in A549 cells. Finally, we evaluated the effects of Compound 8 on mice xenograft tumor models in vivo. These results may provide important information for further research on novel PKM2 activators as antitumor agents. PMID:25214764

Analysis of phase transitions in spin-crossover compounds by using atom - phonon coupling model

NASA Astrophysics Data System (ADS)

Gîndulescu, A.; Rotaru, A.; Linares, J.; Dimian, M.; Nasser, J.

2011-01-01

The spin - crossover compounds (SCO) have become of great interest recently due to their potential applications in memories, sensors, switches, and display devices. These materials are particularly interesting because upon application of heat, light, pressure or other physical stimulus, they feature a phase transition between a low-spin (LS) diamagnetic ground state and a high-spin (HS) paramagnetic state, accompanied in some cases by color change. The phase transition can be discontinuous (with hysteresis), in two steps or gradual. Our analysis is performed by using the atom - phonon coupling (APC) model which considers that neighboring molecules are connected through a spring characterized by an elastic constant depending on molecules electronic state. By associating a fictitious spin to each molecule that has -1 and +1 eigenvalues corresponding to LS and HS levels respectively, an Ising type model can be developed for the analysis of metastable states and phase transitions in spin-crossover compounds. This contribution is aimed at providing a review of our recent results in this area, as well as novel aspects related to SCO compounds behavior at low temperature. In the framework of the APC model, we will discuss about the existence of metastable and unstable states, phase transitions and hysteresis phenomena, as well as their dependence on sample size.

CoMFA and CoMSIA studies on C-aryl glucoside SGLT2 inhibitors as potential anti-diabetic agents.

PubMed

Vyas, V K; Bhatt, H G; Patel, P K; Jalu, J; Chintha, C; Gupta, N; Ghate, M

2013-01-01

SGLT2 has become a target of therapeutic interest in diabetes research. CoMFA and CoMSIA studies were performed on C-aryl glucoside SGLT2 inhibitors (180 analogues) as potential anti-diabetic agents. Three different alignment strategies were used for the compounds. The best CoMFA and CoMSIA models were obtained by means of Distill rigid body alignment of training and test sets, and found statistically significant with cross-validated coefficients (q²) of 0.602 and 0.618, respectively, and conventional coefficients (r²) of 0.905 and 0.902, respectively. Both models were validated by a test set of 36 compounds giving satisfactory predicted correlation coefficients (r² pred) of 0.622 and 0.584 for CoMFA and CoMSIA models, respectively. A comparison was made with earlier 3D QSAR study on SGLT2 inhibitors, which shows that our 3D QSAR models are better than earlier models to predict good inhibitory activity. CoMFA and CoMSIA models generated in this work can provide useful information to design new compounds and helped in prediction of activity prior to synthesis.

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.

Monitoring and Counteracting Functional Deterioration in Parkinson’s Disease: A Multilevel Integrative Approach in a Primate Model System

DTIC Science & Technology

2007-09-01

1992; Fukuda, 2001). The effects of Riluzole (anti-excitotoxic) treatment, epigallocatechin -3- gallate ( EGCG ; anti-oxidative) treatment and (currently... gallate ( EGCG ) is a compound derived from green tea and is beneficial for a number of conditions like obesity and cardiovascular failure (Chantre and...O- gallate ( EGCG ; Teavigo®) was provided bij DSM, Switserland. The anti-excitotoxic compound Riluzole (Rilutek) was obtained at Wippolder Pharmacy

QSAR and 3D-QSAR studies applied to compounds with anticonvulsant activity.

PubMed

Garro Martinez, Juan C; Vega-Hissi, Esteban G; Andrada, Matías F; Estrada, Mario R

2015-01-01

Quantitative structure-activity relationships (QSAR and 3D-QSAR) have been applied in the last decade to obtain a reliable statistical model for the prediction of the anticonvulsant activities of new chemical entities. However, despite the large amount of information on QSAR, no recent review has published and discussed this data in detail. In this review, the authors provide a detailed discussion of QSAR studies that have been applied to compounds with anticonvulsant activity published between the years 2003 and 2013. They also evaluate the mathematical approaches and the main software used to develop the QSAR and 3D-QSAR model. QSAR methodologies continue to attract the attention of researchers and provide valuable information for the development of new potentially active compounds including those with anticonvulsant activity. This has been helped in part by improvements in the size and performance of computers; the development of specific software and the development of novel molecular descriptors, which have given rise to new and more predictive QSAR models. The extensive development of descriptors, and the way by which descriptor values are derived, have allowed the evolution of the QSAR methods. This evolution could strengthen the QSAR methods as an important tool in research and development of new and more potent anticonvulsant agents.

Thermochemical Stability Study of Alkyl-Tethered Quaternary Ammonium Cations for Anion Exchange Membrane Fuel Cells

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

Mohanty, Angela D.; Tignor, Steven E.; Sturgeon, Matthew R.

2017-01-01

The increased interest in the use of anion exchange membranes (AEMs) for applications in electrochemical devices has prompted significant efforts in designing materials with robust stability in alkaline media. Most reported AEMs suffer from polymer backbone degradation as well as cation functional group degradation. In this report, we provide comprehensive experimental investigations for the analysis of cation functional group stability under alkaline media. A silver oxide-mediated ion exchange method and an accelerated stability test in aqueous KOH solutions at elevated temperatures using a Parr reactor were used to evaluate a broad scope of quaternary ammonium (QA) cationic model compound structures,more » particularly focusing on alkyl-tethered cations. Additionally, byproduct analysis was employed to gain better understanding of degradation pathways and trends of alkaline stability. Experimental results under different conditions gave consistent trends in the order of cation stability of various QA small molecule model compounds. Overall, cations that are benzyl-substituted or that are near to electronegative atoms (such as oxygen) degrade faster in alkaline media in comparison to alkyl-tethered QAs. These comprehensive model compound stability studies provide valuable information regarding the relative stability of various cation structures and can help guide researchers towards designing new and promising candidates for AEM materials.« less

Classification and modelling of non-extractable residue (NER) formation from xenobiotics in soil - a synthesis

NASA Astrophysics Data System (ADS)

Kaestner, Matthias; Nowak, Karolina; Miltner, Anja; Trapp, Stefan; Schaeffer, Andreas

2014-05-01

This presentation provides a comprehensive overview about the formation of non-extractable residues (NER) from organic pesticides and contaminants in soil and tries classifying the different types. Anthropogenic organic chemicals are deliberately (e.g. pesticides) or unintentionally (e.g. polyaromatic hydrocarbons [PAH], chlorinated solvents, pharmaceuticals) released in major amounts to nearly all compartments of the environment. Soils and sediments as complex matrices provide a wide variety of binding sites and are the major sinks for these compounds. Many of the xenobiotics entering soil undergo turnover processes and can be volatilised, leached to the groundwater, degraded by microorganisms or taken up and enriched by living organisms. Xenobiotic NER may be derived from parent compounds and primary metabolites that are sequestered (sorbed or entrapped) within the soil organic matter (type I NER) or can be covalently bound (type II NER). Especially type I NER may pose a considerably environmental risk of potential release. However, NER resulting from productive biodegradation, which means the conversion of carbon (or nitrogen) from the compounds into microbial biomass molecules during microbial degradation (type III, bioNER), do not pose any risk. Experimental and analytical approaches to clearly distinguish between the types are provided and a model to prospectively estimate their fate in soil is proposed.

Acoustic rhinometry in the dog: a novel large animal model for studies of nasal congestion.

PubMed

Koss, Michael C; Yu, Yongxin; Hey, John A; McLeod, Robbie L

2002-01-01

The aim of this project was to develop and pharmacologically characterize an experimental dog model of nasal congestion in which nasal patency is measured using acoustic rhinometry. Solubilized compound 48/80 (0.3-3.0%) was administered intranasally to thiopental anesthetized beagle dogs to elicit nasal congestion via localized mast cell degranulation. Compound 48/80-induced effects on parameters of nasal patency were studied in vehicle-treated animals, as well as in the same animals pretreated 2 hours earlier with oral d-pseudoephedrine or chlorpheniramine. Local mast cell degranulation caused a close-related decrease in nasal cavity volume and minimal cross-sectional area (Amin) together with a highly variable increase in nasal secretions. Maximal responses were seen at 90-120 minutes after 48/80 administration. Oral administration of the adrenergic agonist, d-pseudoephedrine (3.0 mg/kg), significantly antagonized all of the nasal effects of compound 48/80 (3.0%). In contrast, oral administration of the histamine H1 receptor antagonist chlorpheniramine (10 mg/kg) appeared to reduce the increased nasal secretions but was without effect on the compound 48/ 80-induced nasal congestion (i.e., volume and Amin). These results show the effectiveness of using acoustic rhinometry in this anesthetized dog model. The observations that compound 48/80-induced nasal congestion was prevented by d-pseudoephedrine pretreatment, but not by chlorpheniramine, suggest that this noninvasive model system may provide an effective tool with which to study the actions of decongestant drugs in preclinical investigations.

DPubChem: a web tool for QSAR modeling and high-throughput virtual screening.

PubMed

Soufan, Othman; Ba-Alawi, Wail; Magana-Mora, Arturo; Essack, Magbubah; Bajic, Vladimir B

2018-06-14

High-throughput screening (HTS) performs the experimental testing of a large number of chemical compounds aiming to identify those active in the considered assay. Alternatively, faster and cheaper methods of large-scale virtual screening are performed computationally through quantitative structure-activity relationship (QSAR) models. However, the vast amount of available HTS heterogeneous data and the imbalanced ratio of active to inactive compounds in an assay make this a challenging problem. Although different QSAR models have been proposed, they have certain limitations, e.g., high false positive rates, complicated user interface, and limited utilization options. Therefore, we developed DPubChem, a novel web tool for deriving QSAR models that implement the state-of-the-art machine-learning techniques to enhance the precision of the models and enable efficient analyses of experiments from PubChem BioAssay database. DPubChem also has a simple interface that provides various options to users. DPubChem predicted active compounds for 300 datasets with an average geometric mean and F 1 score of 76.68% and 76.53%, respectively. Furthermore, DPubChem builds interaction networks that highlight novel predicted links between chemical compounds and biological assays. Using such a network, DPubChem successfully suggested a novel drug for the Niemann-Pick type C disease. DPubChem is freely available at www.cbrc.kaust.edu.sa/dpubchem .

Lecithin:Cholesterol Acyltransferase Activation by Sulfhydryl-Reactive Small Molecules: Role of Cysteine-31

PubMed Central

Freeman, Lita A.; Demosky, Stephen J.; Konaklieva, Monika; Kuskovsky, Rostislav; Aponte, Angel; Ossoli, Alice F.; Gordon, Scott M.; Koby, Ross F.; Manthei, Kelly A.; Shen, Min; Vaisman, Boris L.; Shamburek, Robert D.; Jadhav, Ajit; Calabresi, Laura; Gucek, Marjan; Tesmer, John J.G.; Levine, Rodney L.

2017-01-01

Lecithin:cholesterol acyltransferase (LCAT) catalyzes plasma cholesteryl ester formation and is defective in familial lecithin:cholesterol acyltransferase deficiency (FLD), an autosomal recessive disorder characterized by low high-density lipoprotein, anemia, and renal disease. This study aimed to investigate the mechanism by which compound A [3-(5-(ethylthio)-1,3,4-thiadiazol-2-ylthio)pyrazine-2-carbonitrile], a small heterocyclic amine, activates LCAT. The effect of compound A on LCAT was tested in human plasma and with recombinant LCAT. Mass spectrometry and nuclear magnetic resonance were used to determine compound A adduct formation with LCAT. Molecular modeling was performed to gain insight into the effects of compound A on LCAT structure and activity. Compound A increased LCAT activity in a subset (three of nine) of LCAT mutations to levels comparable to FLD heterozygotes. The site-directed mutation LCAT-Cys31Gly prevented activation by compound A. Substitution of Cys31 with charged residues (Glu, Arg, and Lys) decreased LCAT activity, whereas bulky hydrophobic groups (Trp, Leu, Phe, and Met) increased activity up to 3-fold (P < 0.005). Mass spectrometry of a tryptic digestion of LCAT incubated with compound A revealed a +103.017 m/z adduct on Cys31, consistent with the addition of a single hydrophobic cyanopyrazine ring. Molecular modeling identified potential interactions of compound A near Cys31 and structural changes correlating with enhanced activity. Functional groups important for LCAT activation by compound A were identified by testing compound A derivatives. Finally, sulfhydryl-reactive β-lactams were developed as a new class of LCAT activators. In conclusion, compound A activates LCAT, including some FLD mutations, by forming a hydrophobic adduct with Cys31, thus providing a mechanistic rationale for the design of future LCAT activators. PMID:28576974

Electrohydrodynamics of a compound vesicle under an AC electric field

NASA Astrophysics Data System (ADS)

Priti Sinha, Kumari; Thaokar, Rochish M.

2017-07-01

Compound vesicles are relevant as simplified models for biological cells as well as in technological applications such as drug delivery. Characterization of these compound vesicles, especially the inner vesicle, remains a challenge. Similarly their response to electric field assumes importance in light of biomedical applications such as electroporation. Fields lower than that required for electroporation cause electrodeformation in vesicles and can be used to characterize their mechanical and electrical properties. A theoretical analysis of the electrohydrodynamics of a compound vesicle with outer vesicle of radius R o and an inner vesicle of radius λ {{R}o} , is presented. A phase diagram for the compound vesicle is presented and elucidated using detailed plots of electric fields, free charges and electric stresses. The electrohydrodynamics of the outer vesicle in a compound vesicle shows a prolate-sphere and prolate-oblate-sphere shape transitions when the conductivity of the annular fluid is greater than the outer fluid, and vice-versa respectively, akin to single vesicle electrohydrodynamics reported in the literature. The inner vesicle in contrast shows sphere-prolate-sphere and sphere-prolate-oblate-sphere transitions when the inner fluid conductivity is greater and smaller than the annular fluid, respectively. Equations and methodology are provided to determine the bending modulus and capacitance of the outer as well as the inner membrane, thereby providing an easy way to characterize compound vesicles and possibly biological cells.

Structure-Based Virtual Screening for Dopamine D2 Receptor Ligands as Potential Antipsychotics.

PubMed

Kaczor, Agnieszka A; Silva, Andrea G; Loza, María I; Kolb, Peter; Castro, Marián; Poso, Antti

2016-04-05

Structure-based virtual screening using a D2 receptor homology model was performed to identify dopamine D2 receptor ligands as potential antipsychotics. From screening a library of 6.5 million compounds, 21 were selected and were subjected to experimental validation. From these 21 compounds tested, ten D2 ligands were identified (47.6% success rate, among them D2 receptor antagonists, as expected) that have additional affinity for other receptors tested, in particular 5-HT2A receptors. The affinity (Ki values) of the compounds ranged from 58 nm to about 24 μM. Similarity and fragment analysis indicated a significant degree of structural novelty among the identified compounds. We found one D2 receptor antagonist that did not have a protonatable nitrogen atom, which is a key structural element of the classical D2 pharmacophore model necessary for interaction with the conserved Asp(3.32) residue. This compound exhibited greater than 20-fold binding selectivity for the D2 receptor over the D3 receptor. We provide additional evidence that the amide hydrogen atom of this compound forms a hydrogen bond with Asp(3.32), as determined by tests of its derivatives that cannot maintain this interaction. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Experience with compound words influences their processing: An eye movement investigation with English compound words.

PubMed

Juhasz, Barbara J

2016-11-14

Recording eye movements provides information on the time-course of word recognition during reading. Juhasz and Rayner [Juhasz, B. J., & Rayner, K. (2003). Investigating the effects of a set of intercorrelated variables on eye fixation durations in reading. Journal of Experimental Psychology: Learning, Memory and Cognition, 29, 1312-1318] examined the impact of five word recognition variables, including familiarity and age-of-acquisition (AoA), on fixation durations. All variables impacted fixation durations, but the time-course differed. However, the study focused on relatively short, morphologically simple words. Eye movements are also informative for examining the processing of morphologically complex words such as compound words. The present study further examined the time-course of lexical and semantic variables during morphological processing. A total of 120 English compound words that varied in familiarity, AoA, semantic transparency, lexeme meaning dominance, sensory experience rating (SER), and imageability were selected. The impact of these variables on fixation durations was examined when length, word frequency, and lexeme frequencies were controlled in a regression model. The most robust effects were found for familiarity and AoA, indicating that a reader's experience with compound words significantly impacts compound recognition. These results provide insight into semantic processing of morphologically complex words during reading.

Effects and mechanistic aspects of absorbing organic compounds by coking coal.

PubMed

Ning, Kejia; Wang, Junfeng; Xu, Hongxiang; Sun, Xianfeng; Huang, Gen; Liu, Guowei; Zhou, Lingmei

2017-11-01

Coal is a porous medium and natural absorbent. It can be used for its original purpose after adsorbing organic compounds, its value does not reduce and the pollutants are recycled, and then through systemic circulation of coking wastewater zero emissions can be achieved. Thus, a novel method of industrial organic wastewater treatment using adsorption on coal is introduced. Coking coal was used as an adsorbent in batch adsorption experiments. The quinoline, indole, pyridine and phenol removal efficiencies of coal adsorption were investigated. In addition, several operating parameters which impact removal efficiency such as coking coal consumption, oscillation contact time, initial concentration and pH value were also investigated. The coking coal exhibited properties well-suited for organics' adsorption. The experimental data were fitted to Langmuir and Freundlich isotherms as well as Temkin and Redlich-Peterson (R-P) models. The Freundlich isotherm model provided reasonable models of the adsorption process. Furthermore, the purification mechanism of organic compounds' adsorption on coking coal was analysed.

Profiling Animal Toxicants by Automatically Mining Public Bioassay Data: A Big Data Approach for Computational Toxicology

PubMed Central

Zhang, Jun; Hsieh, Jui-Hua; Zhu, Hao

2014-01-01

In vitro bioassays have been developed and are currently being evaluated as potential alternatives to traditional animal toxicity models. Already, the progress of high throughput screening techniques has resulted in an enormous amount of publicly available bioassay data having been generated for a large collection of compounds. When a compound is tested using a collection of various bioassays, all the testing results can be considered as providing a unique bio-profile for this compound, which records the responses induced when the compound interacts with different cellular systems or biological targets. Profiling compounds of environmental or pharmaceutical interest using useful toxicity bioassay data is a promising method to study complex animal toxicity. In this study, we developed an automatic virtual profiling tool to evaluate potential animal toxicants. First, we automatically acquired all PubChem bioassay data for a set of 4,841 compounds with publicly available rat acute toxicity results. Next, we developed a scoring system to evaluate the relevance between these extracted bioassays and animal acute toxicity. Finally, the top ranked bioassays were selected to profile the compounds of interest. The resulting response profiles proved to be useful to prioritize untested compounds for their animal toxicity potentials and form a potential in vitro toxicity testing panel. The protocol developed in this study could be combined with structure-activity approaches and used to explore additional publicly available bioassay datasets for modeling a broader range of animal toxicities. PMID:24950175

Profiling animal toxicants by automatically mining public bioassay data: a big data approach for computational toxicology.

PubMed

Zhang, Jun; Hsieh, Jui-Hua; Zhu, Hao

2014-01-01

In vitro bioassays have been developed and are currently being evaluated as potential alternatives to traditional animal toxicity models. Already, the progress of high throughput screening techniques has resulted in an enormous amount of publicly available bioassay data having been generated for a large collection of compounds. When a compound is tested using a collection of various bioassays, all the testing results can be considered as providing a unique bio-profile for this compound, which records the responses induced when the compound interacts with different cellular systems or biological targets. Profiling compounds of environmental or pharmaceutical interest using useful toxicity bioassay data is a promising method to study complex animal toxicity. In this study, we developed an automatic virtual profiling tool to evaluate potential animal toxicants. First, we automatically acquired all PubChem bioassay data for a set of 4,841 compounds with publicly available rat acute toxicity results. Next, we developed a scoring system to evaluate the relevance between these extracted bioassays and animal acute toxicity. Finally, the top ranked bioassays were selected to profile the compounds of interest. The resulting response profiles proved to be useful to prioritize untested compounds for their animal toxicity potentials and form a potential in vitro toxicity testing panel. The protocol developed in this study could be combined with structure-activity approaches and used to explore additional publicly available bioassay datasets for modeling a broader range of animal toxicities.

Investigation of miscellaneous hERG inhibition in large diverse compound collection using automated patch-clamp assay

PubMed Central

Yu, Hai-bo; Zou, Bei-yan; Wang, Xiao-liang; Li, Min

2016-01-01

Aim: hERG potassium channels display miscellaneous interactions with diverse chemical scaffolds. In this study we assessed the hERG inhibition in a large compound library of diverse chemical entities and provided data for better understanding of the mechanisms underlying promiscuity of hERG inhibition. Methods: Approximately 300 000 compounds contained in Molecular Library Small Molecular Repository (MLSMR) library were tested. Compound profiling was conducted on hERG-CHO cells using the automated patch-clamp platform–IonWorks Quattro™. Results: The compound library was tested at 1 and 10 μmol/L. IC50 values were predicted using a modified 4-parameter logistic model. Inhibitor hits were binned into three groups based on their potency: high (IC50<1 μmol/L), intermediate (1 μmol/L< IC50<10 μmol/L), and low (IC50>10 μmol/L) with hit rates of 1.64%, 9.17% and 16.63%, respectively. Six physiochemical properties of each compound were acquired and calculated using ACD software to evaluate the correlation between hERG inhibition and the properties: hERG inhibition was positively correlative to the physiochemical properties ALogP, molecular weight and RTB, and negatively correlative to TPSA. Conclusion: Based on a large diverse compound collection, this study provides experimental evidence to understand the promiscuity of hERG inhibition. This study further demonstrates that hERG liability compounds tend to be more hydrophobic, high-molecular, flexible and polarizable. PMID:26725739

Predicting drug-induced liver injury using ensemble learning methods and molecular fingerprints.

PubMed

Ai, Haixin; Chen, Wen; Zhang, Li; Huang, Liangchao; Yin, Zimo; Hu, Huan; Zhao, Qi; Zhao, Jian; Liu, Hongsheng

2018-05-21

Drug-induced liver injury (DILI) is a major safety concern in the drug-development process, and various methods have been proposed to predict the hepatotoxicity of compounds during the early stages of drug trials. In this study, we developed an ensemble model using three machine learning algorithms and 12 molecular fingerprints from a dataset containing 1,241 diverse compounds. The ensemble model achieved an average accuracy of 71.1±2.6%, sensitivity of 79.9±3.6%, specificity of 60.3±4.8%, and area under the receiver operating characteristic curve (AUC) of 0.764±0.026 in five-fold cross-validation and an accuracy of 84.3%, sensitivity of 86.9%, specificity of 75.4%, and AUC of 0.904 in an external validation dataset of 286 compounds collected from the Liver Toxicity Knowledge Base (LTKB). Compared with previous methods, the ensemble model achieved relatively high accuracy and sensitivity. We also identified several substructures related to DILI. In addition, we provide a web server offering access to our models (http://ccsipb.lnu.edu.cn/toxicity/HepatoPred-EL/).

Explaining compound generalization in associative and causal learning through rational principles of dimensional generalization.

PubMed

Soto, Fabian A; Gershman, Samuel J; Niv, Yael

2014-07-01

How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here, we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed long-standing problems for rational theories of associative and causal learning. (c) 2014 APA, all rights reserved.

Explaining Compound Generalization in Associative and Causal Learning Through Rational Principles of Dimensional Generalization

PubMed Central

Soto, Fabian A.; Gershman, Samuel J.; Niv, Yael

2014-01-01

How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed longstanding problems for rational theories of associative and causal learning. PMID:25090430

Lower temperature curing thermoset polyimides utilizing a substituted norbornene endcap

NASA Technical Reports Server (NTRS)

Waters, John F.; Sukenik, Chaim N.; Kennedy, Vance O.; Livneh, Mordechai; Youngs, Wiley J.; Sutter, James K.; Meador, Mary A. B.; Burke, Luke A.; Ahn, Myong K.

1992-01-01

Methoxycarbonyl bridgehead substituted nadic diacid monomethyl ester, when used as an endcapping monomer, lowered the cure temperature of thermoset PMR polyimides without seriously affecting other desirable properties, such as glass transition temperature and thermal oxidative stability. The C-13 CP/MAS NMR of model compounds was used to follow the cure of resin systems using both the unmodified nadic endcap and the methoxycarbonyl-substituted endcap. Rheological analysis and differential scanning calorimetry DSC also provided evidence for the lower curing nature of the substituted endcap. Two regioisomers of the bridgehead-substituted endcap were isolated, and their chemical structures were elucidated by X-ray crystallography. The model compound and molecular modeling studies conducted ruled out the possibility of regioisomeric imide formation in the substituted endcaps.

Evaluation of hydrate-screening methods.

PubMed

Cui, Yong; Yao, Erica

2008-07-01

The purpose of this work is to evaluate the effectiveness and reliability of several common hydrate-screening techniques, and to provide guidelines for designing hydrate-screening programs for new drug candidates. Ten hydrate-forming compounds were selected as model compounds and six hydrate-screening approaches were applied to these compounds in an effort to generate their hydrate forms. The results prove that no screening approach is universally effective in finding hydrates for small organic compounds. Rather, a combination of different methods should be used to improve screening reliability. Among the approaches tested, the dynamic water vapor sorption/desorption isotherm (DVI) method and storage under high humidity (HH) yielded 60-70% success ratios, the lowest among all techniques studied. The risk of false negatives arises in particular for nonhygroscopic compounds. On the other hand, both slurry in water (Slurry) and temperature cycling of aqueous suspension (TCS) showed high success rates (90%) with some exceptions. The mixed solvent systems (MSS) procedure also achieved high success rates (90%), and was found to be more suitable for water-insoluble compounds. For water-soluble compounds, MSS may not be the best approach because recrystallization is difficult in solutions with high water activity. Finally, vapor diffusion (VD) yielded a reasonably high success ratio in finding hydrates (80%). However, this method suffers from experimental difficulty and unreliable results for either highly water-soluble or water-insoluble compounds. This study indicates that a reliable hydrate-screening strategy should take into consideration the solubility and hygroscopicity of the compounds studied. A combination of the Slurry or TCS method with the MSS procedure could provide a screening strategy with reasonable reliability.

Wild Roman chamomile extracts and phenolic compounds: enzymatic assays and molecular modelling studies with VEGFR-2 tyrosine kinase.

PubMed

Guimarães, Rafaela; Calhelha, Ricardo C; Froufe, Hugo J C; Abreu, Rui M V; Carvalho, Ana Maria; Queiroz, Maria João R P; Ferreira, Isabel C F R

2016-01-01

Angiogenesis is a process by which new blood vessels are formed from the pre-existing vasculature, and it is a key process that leads to tumour development. Some studies have recognized phenolic compounds as chemopreventive agents; flavonoids, in particular, seem to suppress the growth of tumor cells modifying the cell cycle. Herein, the antiangiogenic activity of Roman chamomile (Chamaemelum nobile L.) extracts (methanolic extract and infusion) and the main phenolic compounds present (apigenin, apigenin-7-O-glucoside, caffeic acid, chlorogenic acid, luteolin, and luteolin-7-O-glucoside) was evaluated through enzymatic assays using the tyrosine kinase intracellular domain of the Vascular Endothelium Growth Factor Receptor-2 (VEGFR-2), which is a transmembrane receptor expressed fundamentally in endothelial cells involved in angiogenesis, and molecular modelling studies. The methanolic extract showed a lower IC50 value (concentration that provided 50% of VEGFR-2 inhibition) than the infusion, 269 and 301 μg mL(-1), respectively. Regarding phenolic compounds, luteolin and apigenin showed the highest capacity to inhibit the phosphorylation of VEGFR-2, leading us to believe that these compounds are involved in the activity revealed by the methanolic extract.

XAFS of short-lived reduction products of structural and functional models of the [Fe Fe] hydrogenase H-cluster

NASA Astrophysics Data System (ADS)

Bondin, Mark I.; Borg, Stacey J.; Cheah, Mun-Hon; Best, Stephen P.

2006-11-01

Thiolate-bridged diiron compounds that are related to the active site of the [Fe-Fe] hydrogenase enzyme have been shown to act as electrocatalysts for reduction of protons. The use of XAFS for clarification of the structures of intermediates formed following reduction of related diiron carbonyl compounds is described. These measurements allow the determination of Fe-Fe and Fe-S bond lengths with good reliability and when used in conjunction with the standard bonding models this provides a means of validating the structures proposed for longer-lived ( t>20 s at -50 °C) reaction intermediates.

Magnesium K-edge XANES spectroscopy of geological standards.

PubMed

Yoshimura, Toshihiro; Tamenori, Yusuke; Iwasaki, Nozomu; Hasegawa, Hiroshi; Suzuki, Atsushi; Kawahata, Hodaka

2013-09-01

Magnesium K-edge X-ray absorption near-edge structure (XANES) spectra have been investigated to develop a systematic understanding of a suite of Mg-bearing geological materials such as silicate and carbonate minerals, sediments, rocks and chemical reagents. For the model compounds the Mg XANES was found to vary widely between compounds and to provide a fingerprint for the form of Mg involved in geologic materials. The energy positions and resonance features obtained from these spectra can be used to specify the dominant molecular host site of Mg, thus shedding light on Mg partitioning and isotope fractionation in geologic materials and providing a valuable complement to existing knowledge of Mg geochemistry.

The use of high-throughput screening techniques to evaluate mitochondrial toxicity.

PubMed

Wills, Lauren P

2017-11-01

Toxicologists and chemical regulators depend on accurate and effective methods to evaluate and predict the toxicity of thousands of current and future compounds. Robust high-throughput screening (HTS) experiments have the potential to efficiently test large numbers of chemical compounds for effects on biological pathways. HTS assays can be utilized to examine chemical toxicity across multiple mechanisms of action, experimental models, concentrations, and lengths of exposure. Many agricultural, industrial, and pharmaceutical chemicals classified as harmful to human and environmental health exert their effects through the mechanism of mitochondrial toxicity. Mitochondrial toxicants are compounds that cause a decrease in the number of mitochondria within a cell, and/or decrease the ability of mitochondria to perform normal functions including producing adenosine triphosphate (ATP) and maintaining cellular homeostasis. Mitochondrial dysfunction can lead to apoptosis, necrosis, altered metabolism, muscle weakness, neurodegeneration, decreased organ function, and eventually disease or death of the whole organism. The development of HTS techniques to identify mitochondrial toxicants will provide extensive databases with essential connections between mechanistic mitochondrial toxicity and chemical structure. Computational and bioinformatics approaches can be used to evaluate compound databases for specific chemical structures associated with toxicity, with the goal of developing quantitative structure-activity relationship (QSAR) models and mitochondrial toxicophores. Ultimately these predictive models will facilitate the identification of mitochondrial liabilities in consumer products, industrial compounds, pharmaceuticals and environmental hazards. Copyright © 2017 Elsevier B.V. All rights reserved.

Confidence Intervals for Weighted Composite Scores under the Compound Binomial Error Model

ERIC Educational Resources Information Center

Kim, Kyung Yong; Lee, Won-Chan

2018-01-01

Reporting confidence intervals with test scores helps test users make important decisions about examinees by providing information about the precision of test scores. Although a variety of estimation procedures based on the binomial error model are available for computing intervals for test scores, these procedures assume that items are randomly…

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.

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.

Probabilistic neural networks modeling of the 48-h LC50 acute toxicity endpoint to Daphnia magna.

PubMed

Niculescu, S P; Lewis, M A; Tigner, J

2008-01-01

Two modeling experiments based on the maximum likelihood estimation paradigm and targeting prediction of the Daphnia magna 48-h LC50 acute toxicity endpoint for both organic and inorganic compounds are reported. The resulting models computational algorithms are implemented as basic probabilistic neural networks with Gaussian kernel (statistical corrections included). The first experiment uses strictly D. magna information for 971 structures as training/learning data and the resulting model targets practical applications. The second experiment uses the same training/learning information plus additional data on another 29 compounds whose endpoint information is originating from D. pulex and Ceriodaphnia dubia. It only targets investigation of the effect of mixing strictly D. magna 48-h LC50 modeling information with small amounts of similar information estimated from related species, and this is done as part of the validation process. A complementary 81 compounds dataset (involving only strictly D. magna information) is used to perform external testing. On this external test set, the Gaussian character of the distribution of the residuals is confirmed for both models. This allows the use of traditional statistical methodology to implement computation of confidence intervals for the unknown measured values based on the models predictions. Examples are provided for the model targeting practical applications. For the same model, a comparison with other existing models targeting the same endpoint is performed.

A Chrysin Derivative Suppresses Skin Cancer Growth by Inhibiting Cyclin-dependent Kinases*

PubMed Central

Liu, Haidan; Liu, Kangdong; Huang, Zunnan; Park, Chan-Mi; Thimmegowda, N. R.; Jang, Jae-Hyuk; Ryoo, In-Ja; He, Long; Kim, Sun-Ok; Oi, Naomi; Lee, Ki Won; Soung, Nak-Kyun; Bode, Ann M.; Yang, Yifeng; Zhou, Xinmin; Erikson, Raymond L.; Ahn, Jong-Seog; Hwang, Joonsung; Kim, Kyoon Eon; Dong, Zigang; Kim, Bo-Yeon

2013-01-01

Chrysin (5,7-dihydroxyflavone), a natural flavonoid widely distributed in plants, reportedly has chemopreventive properties against various cancers. However, the anticancer activity of chrysin observed in in vivo studies has been disappointing. Here, we report that a chrysin derivative, referred to as compound 69407, more strongly inhibited EGF-induced neoplastic transformation of JB6 P+ cells compared with chrysin. It attenuated cell cycle progression of EGF-stimulated cells at the G1 phase and inhibited the G1/S transition. It caused loss of retinoblastoma phosphorylation at both Ser-795 and Ser-807/811, the preferred sites phosphorylated by Cdk4/6 and Cdk2, respectively. It also suppressed anchorage-dependent and -independent growth of A431 human epidermoid carcinoma cells. Compound 69407 reduced tumor growth in the A431 mouse xenograft model and retinoblastoma phosphorylation at Ser-795 and Ser-807/811. Immunoprecipitation kinase assay results showed that compound 69407 attenuated endogenous Cdk4 and Cdk2 kinase activities in EGF-stimulated JB6 P+ cells. Pulldown and in vitro kinase assay results indicated that compound 69407 directly binds with Cdk2 and Cdk4 in an ATP-independent manner and inhibited their kinase activities. A binding model between compound 69407 and a crystal structure of Cdk2 predicted that compound 69407 was located inside the Cdk2 allosteric binding site. The binding was further verified by a point mutation binding assay. Overall results indicated that compound 69407 is an ATP-noncompetitive cyclin-dependent kinase inhibitor with anti-tumor effects, which acts by binding inside the Cdk2 allosteric pocket. This study provides new insights for creating a general pharmacophore model to design and develop novel ATP-noncompetitive agents with chemopreventive or chemotherapeutic potency. PMID:23888052

Discovery of Anthelmintic Drug Targets and Drugs Using Chokepoints in Nematode Metabolic Pathways

PubMed Central

Taylor, Christina M.; Wang, Qi; Rosa, Bruce A.; Huang, Stanley Ching-Cheng; Powell, Kerrie; Schedl, Tim; Pearce, Edward J.; Abubucker, Sahar; Mitreva, Makedonka

2013-01-01

Parasitic roundworm infections plague more than 2 billion people (1/3 of humanity) and cause drastic losses in crops and livestock. New anthelmintic drugs are urgently needed as new drug resistance and environmental concerns arise. A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product. A chokepoint analysis provides a systematic method of identifying novel potential drug targets. Chokepoint enzymes were identified in the genomes of 10 nematode species, and the intersection and union of all chokepoint enzymes were found. By studying and experimentally testing available compounds known to target proteins orthologous to nematode chokepoint proteins in public databases, this study uncovers features of chokepoints that make them successful drug targets. Chemogenomic screening was performed on drug-like compounds from public drug databases to find existing compounds that target homologs of nematode chokepoints. The compounds were prioritized based on chemical properties frequently found in successful drugs and were experimentally tested using Caenorhabditis elegans. Several drugs that are already known anthelmintic drugs and novel candidate targets were identified. Seven of the compounds were tested in Caenorhabditis elegans and three yielded a detrimental phenotype. One of these three drug-like compounds, Perhexiline, also yielded a deleterious effect in Haemonchus contortus and Onchocerca lienalis, two nematodes with divergent forms of parasitism. Perhexiline, known to affect the fatty acid oxidation pathway in mammals, caused a reduction in oxygen consumption rates in C. elegans and genome-wide gene expression profiles provided an additional confirmation of its mode of action. Computational modeling of Perhexiline and its target provided structural insights regarding its binding mode and specificity. Our lists of prioritized drug targets and drug-like compounds have potential to expedite the discovery of new anthelmintic drugs with broad-spectrum efficacy. PMID:23935495

Selective chemical binding enhances cesium tolerance in plants through inhibition of cesium uptake

PubMed Central

Adams, Eri; Chaban, Vitaly; Khandelia, Himanshu; Shin, Ryoung

2015-01-01

High concentrations of cesium (Cs+) inhibit plant growth but the detailed mechanisms of Cs+ uptake, transport and response in plants are not well known. In order to identify small molecules with a capacity to enhance plant tolerance to Cs+, chemical library screening was performed using Arabidopsis. Of 10,000 chemicals tested, five compounds were confirmed as Cs+ tolerance enhancers. Further investigation and quantum mechanical modelling revealed that one of these compounds reduced Cs+ concentrations in plants and that the imidazole moiety of this compound bound specifically to Cs+. Analysis of the analogous compounds indicated that the structure of the identified compound is important for the effect to be conferred. Taken together, Cs+ tolerance enhancer isolated here renders plants tolerant to Cs+ by inhibiting Cs+ entry into roots via specific binding to the ion thus, for instance, providing a basis for phytostabilisation of radiocesium-contaminated farmland. PMID:25740624

Selective chemical binding enhances cesium tolerance in plants through inhibition of cesium uptake.

PubMed

Adams, Eri; Chaban, Vitaly; Khandelia, Himanshu; Shin, Ryoung

2015-03-05

High concentrations of cesium (Cs(+)) inhibit plant growth but the detailed mechanisms of Cs(+) uptake, transport and response in plants are not well known. In order to identify small molecules with a capacity to enhance plant tolerance to Cs(+), chemical library screening was performed using Arabidopsis. Of 10,000 chemicals tested, five compounds were confirmed as Cs(+) tolerance enhancers. Further investigation and quantum mechanical modelling revealed that one of these compounds reduced Cs(+) concentrations in plants and that the imidazole moiety of this compound bound specifically to Cs(+). Analysis of the analogous compounds indicated that the structure of the identified compound is important for the effect to be conferred. Taken together, Cs(+) tolerance enhancer isolated here renders plants tolerant to Cs(+) by inhibiting Cs(+) entry into roots via specific binding to the ion thus, for instance, providing a basis for phytostabilisation of radiocesium-contaminated farmland.

Botanical Compounds: Effects on Major Eye Diseases

PubMed Central

Huynh, Tuan-Phat; Mann, Shivani N.; Mandal, Nawajes A.

2013-01-01

Botanical compounds have been widely used throughout history as cures for various diseases and ailments. Many of these compounds exhibit strong antioxidative, anti-inflammatory, and antiapoptotic properties. These are also common damaging mechanisms apparent in several ocular diseases, including age-related macular degeneration (AMD), glaucoma, diabetic retinopathy, cataract, and retinitis pigmentosa. In recent years, there have been many epidemiological and clinical studies that have demonstrated the beneficial effects of plant-derived compounds, such as curcumin, lutein and zeaxanthin, danshen, ginseng, and many more, on these ocular pathologies. Studies in cell cultures and animal models showed promising results for their uses in eye diseases. While there are many apparent significant correlations, further investigation is needed to uncover the mechanistic pathways of these botanical compounds in order to reach widespread pharmaceutical use and provide noninvasive alternatives for prevention and treatments of the major eye diseases. PMID:23843879

Feasibility of Active Machine Learning for Multiclass Compound Classification.

PubMed

Lang, Tobias; Flachsenberg, Florian; von Luxburg, Ulrike; Rarey, Matthias

2016-01-25

A common task in the hit-to-lead process is classifying sets of compounds into multiple, usually structural classes, which build the groundwork for subsequent SAR studies. Machine learning techniques can be used to automate this process by learning classification models from training compounds of each class. Gathering class information for compounds can be cost-intensive as the required data needs to be provided by human experts or experiments. This paper studies whether active machine learning can be used to reduce the required number of training compounds. Active learning is a machine learning method which processes class label data in an iterative fashion. It has gained much attention in a broad range of application areas. In this paper, an active learning method for multiclass compound classification is proposed. This method selects informative training compounds so as to optimally support the learning progress. The combination with human feedback leads to a semiautomated interactive multiclass classification procedure. This method was investigated empirically on 15 compound classification tasks containing 86-2870 compounds in 3-38 classes. The empirical results show that active learning can solve these classification tasks using 10-80% of the data which would be necessary for standard learning techniques.

Pyrrole-Based Antitubulin Agents: Two Distinct Binding Modalities Are Predicted for C-2 Analogues in the Colchicine Site

PubMed Central

2011-01-01

3,5-Dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2-carboxylic acid ethyl ester is a promising antitubulin lead agent that targets the colchicine site of tubulin. C-2 analogues were synthesized and tested for microtubule depolymerizing and antiproliferative activity. Molecular modeling studies using both GOLD docking and HINT (Hydropathic INTeraction) scoring revealed two distinct binding modes that explain the structure–activity relationships and are in accord with the structural basis of colchicine binding to tubulin. The binding mode of higher activity compounds is buried deeper in the site and overlaps well with rings A and C of colchicine, while the lower activity binding mode shows fewer critical contacts with tubulin. The model distinguishes highly active compounds from those with weaker activities and provides novel insights into the colchicine site and compound design. PMID:22611477

Pyrrole-Based Antitubulin Agents: Two Distinct Binding Modalities are Predicted for C-2 Analogs in the Colchicine Site.

PubMed

Da, Chenxiao; Telang, Nakul; Barelli, Peter; Jia, Xin; Gupton, John T; Mooberry, Susan L; Kellogg, Glen E

2012-01-12

3,5-dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2-carboxylic acid ethyl ester is a promising antitubulin lead agent that targets the colchicine site of tubulin. C-2 analogs were synthesized and tested for microtubule depolymerizing and antiproliferative activity. Molecular modeling studies using both GOLD docking and HINT (Hydropathic INTeraction) scoring revealed two distinct binding modes that explain the structural-activity relationships and are in accord with the structural basis of colchicine binding to tubulin. The binding mode of higher activity compounds is buried deeper in the site and overlaps well with rings A and C of colchicine, while the lower activity binding mode shows fewer critical contacts with tubulin. The model distinguishes highly active compounds from those with weaker activities and provides novel insights into the colchicine site and compound design.

A Low-Cost, Hands-on Module to Characterize Antimicrobial Compounds Using an Interdisciplinary, Biophysical Approach

PubMed Central

Kaushik, Karishma S.; Kessel, Ashley; Ratnayeke, Nalin; Gordon, Vernita D.

2015-01-01

We have developed a hands-on experimental module that combines biology experiments with a physics-based analytical model in order to characterize antimicrobial compounds. To understand antibiotic resistance, participants perform a disc diffusion assay to test the antimicrobial activity of different compounds and then apply a diffusion-based analytical model to gain insights into the behavior of the active antimicrobial component. In our experience, this module was robust, reproducible, and cost-effective, suggesting that it could be implemented in diverse settings such as undergraduate research, STEM (science, technology, engineering, and math) camps, school programs, and laboratory training workshops. By providing valuable interdisciplinary research experience in science outreach and education initiatives, this module addresses the paucity of structured training or education programs that integrate diverse scientific fields. Its low-cost requirements make it especially suitable for use in resource-limited settings. PMID:25602254

Sweetness prediction of natural compounds.

PubMed

Chéron, Jean-Baptiste; Casciuc, Iuri; Golebiowski, Jérôme; Antonczak, Serge; Fiorucci, Sébastien

2017-04-15

Based on the most exhaustive database of sweeteners with known sweetness values, a new quantitative structure-activity relationship model for sweetness prediction has been set up. Analysis of the physico-chemical properties of sweeteners in the database indicates that the structure of most potent sweeteners combines a hydrophobic scaffold functionalized by a limited number of hydrogen bond sites (less than 4 hydrogen bond donors and 10 acceptors), with a moderate molecular weight ranging from 350 to 450g·mol -1 . Prediction of sweetness, bitterness and toxicity properties of the largest database of natural compounds have been performed. In silico screening reveals that the majority of the predicted natural intense sweeteners comprise saponin or stevioside scaffolds. The model highlights that their sweetness potency is comparable to known natural sweeteners. The identified compounds provide a rational basis to initiate the design and chemosensory analysis of new low-calorie sweeteners. Copyright © 2016 Elsevier Ltd. All rights reserved.

Selective Oxidation of Lignin Model Compounds.

PubMed

Gao, Ruili; Li, Yanding; Kim, Hoon; Mobley, Justin K; Ralph, John

2018-05-02

Lignin, the planet's most abundant renewable source of aromatic compounds, is difficult to degrade efficiently to welldefined aromatics. We developed a microwave-assisted catalytic Swern oxidation system using an easily prepared catalyst, MoO 2 Cl 2 (DMSO) 2 , and DMSO as the solvent and oxidant. It demonstrated high efficiency in transforming lignin model compounds containing the units and functional groups found in native lignins. The aromatic ring substituents strongly influenced the selectivity of β-ether phenolic dimer cleavage to generate sinapaldehyde and coniferaldehyde, monomers not usually produced by oxidative methods. Time-course studies on two key intermediates provided insight into the reaction pathway. Owing to the broad scope of this oxidation system and the insight gleaned with regard to its mechanism, this strategy could be adapted and applied in a general sense to the production of useful aromatic chemicals from phenolics and lignin. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The constituents of Cibotium barometz and their permeability in the human Caco-2 monolayer cell model.

PubMed

Wu, Qi; Yang, Xiu-Wei

2009-09-25

Cibotium barometz (L.) J. Sm. (Dicksoniaceae) has been traditionally used as anti-inflammatory and anodyne. To investigate the constituents in the rhizomes of Cibotium barometz, and evaluate their permeability in the human Caco-2 model. The rhizomes extracts of Cibotium barometz were isolated by chromatographic techniques. Structures of isolated compounds were identified by spectroscopic methods. The permeability of the main constituents was evaluated using human Caco-2 cell monolayer as a model system. Three unusual sesquiterpenes having 1-indanone nucleus (1, 3 and 4) and an unusual orthoester spiropyranosyl derivative of protocatechuic acid (2) were isolated from the rhizomes of Cibotium barometz. Among these, the bilateral permeation of 1, 3 and 4 in Caco-2 model was examined. The apparent permeability coefficients (P(app)) of 1 was identical with those of propranolol, which is often used as reference standard of high permeability. The P(app) values of 3 and 4 were in agreement with those of atenolol, which is often used as reference standard of poor permeability. The permeation rates of 1, 3 and 4 increased linearly as a function of time up to 180 min and with the concentration within the test range of 25-200 microM. This is the first report on the presence of compounds 2 and 3 in this plant and 4 was a new compound. Compound 1 is assigned for a well-absorbed, and 2 and 3 are assigned for the poorly absorbed compounds in human intestine. A passive diffusion mechanism for transport of 1, 3 and 4 in Caco-2 model was proposed. The results provided some useful information for predicting the oral bioavailability of 1, 3 and 4.

Use of a least absolute shrinkage and selection operator (LASSO) model to selected ion flow tube mass spectrometry (SIFT-MS) analysis of exhaled breath to predict the efficacy of dialysis: a pilot study.

PubMed

Wang, Maggie Haitian; Chong, Ka Chun; Storer, Malina; Pickering, John W; Endre, Zoltan H; Lau, Steven Yf; Kwok, Chloe; Lai, Maria; Chung, Hau Yin; Ying Zee, Benny Chung

2016-09-28

Selected ion flow tube-mass spectrometry (SIFT-MS) provides rapid, non-invasive measurements of a full-mass scan of volatile compounds in exhaled breath. Although various studies have suggested that breath metabolites may be indicators of human disease status, many of these studies have included few breath samples and large numbers of compounds, limiting their power to detect significant metabolites. This study employed a least absolute shrinkage and selective operator (LASSO) approach to SIFT-MS data of breath samples to preliminarily evaluate the ability of exhaled breath findings to monitor the efficacy of dialysis in hemodialysis patients. A process of model building and validation showed that blood creatinine and urea concentrations could be accurately predicted by LASSO-selected masses. Using various precursors, the LASSO models were able to predict creatinine and urea concentrations with high adjusted R-square (>80%) values. The correlation between actual concentrations and concentrations predicted by the LASSO model (using precursor H 3 O + ) was high (Pearson correlation coefficient  =  0.96). Moreover, use of full mass scan data provided a better prediction than compounds from selected ion mode. These findings warrant further investigations in larger patient cohorts. By employing a more powerful statistical approach to predict disease outcomes, breath analysis using SIFT-MS technology could be applicable in future to daily medical diagnoses.

Animal Models in Cardiovascular Research: Hypertension and Atherosclerosis

PubMed Central

Ng, Chun-Yi; Jaarin, Kamsiah

2015-01-01

Hypertension and atherosclerosis are among the most common causes of mortality in both developed and developing countries. Experimental animal models of hypertension and atherosclerosis have become a valuable tool for providing information on etiology, pathophysiology, and complications of the disease and on the efficacy and mechanism of action of various drugs and compounds used in treatment. An animal model has been developed to study hypertension and atherosclerosis for several reasons. Compared to human models, an animal model is easily manageable, as compounding effects of dietary and environmental factors can be controlled. Blood vessels and cardiac tissue samples can be taken for detailed experimental and biomolecular examination. Choice of animal model is often determined by the research aim, as well as financial and technical factors. A thorough understanding of the animal models used and complete analysis must be validated so that the data can be extrapolated to humans. In conclusion, animal models for hypertension and atherosclerosis are invaluable in improving our understanding of cardiovascular disease and developing new pharmacological therapies. PMID:26064920

Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors

NASA Astrophysics Data System (ADS)

Murumkar, Prashant Revan; Zambre, Vishal Prakash; Yadav, Mange Ram

2010-02-01

A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.

Multi-Layer Identification of Highly-Potent ABCA1 Up-Regulators Targeting LXRβ Using Multiple QSAR Modeling, Structural Similarity Analysis, and Molecular Docking.

PubMed

Chen, Meimei; Yang, Fafu; Kang, Jie; Yang, Xuemei; Lai, Xinmei; Gao, Yuxing

2016-11-29

In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, four modeling approaches, including linear discriminant analysis, support vector machine, radial basis function neural network, and classification and regression trees, were applied to construct different QSAR classification models. The statistics results indicated that these four kinds of QSAR models were powerful tools for screening highly potent ABCA1 up-regulators. Then, a consensus QSAR model was developed by combining the predictions from these four models. To discover new ABCA1 up-regulators at maximum accuracy, the compounds in the ZINC database that fulfilled the requirement of structural similarity of 0.7 compared to known potent ABCA1 up-regulator were subjected to the consensus QSAR model, which led to the discovery of 50 compounds. Finally, they were docked into the LXRβ binding site to understand their role in up-regulating ABCA1 expression. The excellent binding modes and docking scores of 10 hit compounds suggested they were highly-potent ABCA1 up-regulators targeting LXRβ. Overall, this study provided an effective strategy to discover highly potent ABCA1 up-regulators.

DESHARKY: automatic design of metabolic pathways for optimal cell growth.

PubMed

Rodrigo, Guillermo; Carrera, Javier; Prather, Kristala Jones; Jaramillo, Alfonso

2008-11-01

The biological solution for synthesis or remediation of organic compounds using living organisms, particularly bacteria and yeast, has been promoted because of the cost reduction with respect to the non-living chemical approach. In that way, computational frameworks can profit from the previous knowledge stored in large databases of compounds, enzymes and reactions. In addition, the cell behavior can be studied by modeling the cellular context. We have implemented a Monte Carlo algorithm (DESHARKY) that finds a metabolic pathway from a target compound by exploring a database of enzymatic reactions. DESHARKY outputs a biochemical route to the host metabolism together with its impact in the cellular context by using mathematical models of the cell resources and metabolism. Furthermore, we provide the sequence of amino acids for the enzymes involved in the route closest phylogenetically to the considered organism. We provide examples of designed metabolic pathways with their genetic load characterizations. Here, we have used Escherichia coli as host organism. In addition, our bioinformatic tool can be applied for biodegradation or biosynthesis and its performance scales with the database size. Software, a tutorial and examples are freely available and open source at http://soft.synth-bio.org/desharky.html

QSAR study on the removal efficiency of organic pollutants in supercritical water based on degradation temperature.

PubMed

Jiang, Ai; Cheng, Zhiwen; Shen, Zhemin; Guo, Weimin

2018-02-13

This paper aims to study temperature-dependent quantitative structure activity relationship (QSAR) models of supercritical water oxidation (SCWO) process which were developed based on Arrhenius equation between oxidation reaction rate and temperature. Through exploring SCWO process, each kinetic rate constant was studied for 21 organic substances, including azo dyes, heterocyclic compounds and ionic compounds. We propose the concept of T R95 , which is defined as the temperature at removal ratio of 95%, it is a key indicator to evaluate compounds' complete oxidation. By using Gaussian 09 and Material Studio 7.0, quantum chemical parameters were conducted for each organic compound. The optimum model is T R95  = 654.775 + 1761.910f(+) n  - 177.211qH with squared regression coefficient R 2  = 0.620 and standard error SE = 35.1. Nearly all the compounds could obtain accurate predictions of their degradation rate. Effective QSAR model exactly reveals three determinant factors, which are directly related to degradation rules. Specifically, the lowest f(+) value of main-chain atoms (f(+) n ) indicates the degree of affinity for nucleophilic attack. qH shows the ease or complexity of valence-bond breakage of organic molecules. BO x refers to the stability of a bond. Coincidentally, the degradation mechanism could reasonably be illustrated from each perspective, providing a deeper insight of universal and propagable oxidation rules. Besides, the satisfactory results of internal and external validations suggest the stability, reliability and predictive ability of optimum model.

Molecular Modeling, de novo Design and Synthesis of a Novel, Extracellular Binding Fibroblast Growth Factor Receptor 2 Inhibitor Alofanib (RPT835).

PubMed

Tsimafeyeu, Ilya; Daeyaert, Frits; Joos, Jean-Baptiste; Aken, Koen V; Ludes-Meyers, John; Byakhov, Mikhail; Tjulandin, Sergei

2016-01-01

Fibroblast growth factor (FGF) receptors (FGFRs) play a key role in tumor growth and angiogenesis. The present report describes our search for an extracellularly binding FGFR inhibitor using a combined molecular modeling and de novo design strategy. Based upon crystal structures of the receptor with its native ligand and knowledge of inhibiting peptides, we have developed a computational protocol that predicts the putative binding of a molecule to the extracellular domains of the receptor. This protocol, or scoring function, was used in combination with the de novo synthesis program 'SYNOPSIS' to generate high scoring and synthetically accessible compounds. Eight compounds belonging to 3 separate chemical classes were synthesized. One of these compounds, alofanib (RPT835), was found to be an effective inhibitor of the FGF/FGFR2 pathway. The preclinical in vitro data support an allosteric inhibition mechanism of RPT835. RPT835 potently inhibited growth of KATO III gastric cancer cells expressing FGFR2, with GI50 value of 10 nmol/L. These results provide strong rationale for the evaluation of compound in advanced cancers.

Synthesis and Evaluation of 3-(furo[2,3-b]pyridin-3-yl)-4-(1H-indol-3-yl)-maleimides as Novel GSK-3β Inhibitors and Anti-Ischemic Agents.

PubMed

Ye, Qing; Li, Qiu; Zhou, Yubo; Xu, Lei; Mao, Weili; Gao, Yuanxue; Li, Chenhui; Xu, Yuan; Xu, Yazhou; Liao, Hong; Zhang, Luyong; Gao, Jianrong; Li, Jia; Pang, Tao

2015-10-01

A series of novel 3-(furo[2,3-b]pyridin-3-yl)-4-(1H-indol-3-yl)-maleimides were designed, synthesized, and biologically evaluated for their GSK-3β inhibitory activities. Most compounds showed favorable inhibitory activities against GSK-3β protein. Among them, compounds 5n, 5o, and 5p significantly reduced GSK-3β substrate tau phosphorylation at Ser396 in primary neurons, indicating inhibition of cellular GSK-3β activity. In the in vitro neuronal injury models, compounds 5n, 5o, and 5p prevented neuronal death against glutamate, oxygen-glucose deprivation, and nutrient serum deprivation which are closely associated with cerebral ischemic stroke. In the in vivo cerebral ischemia animal model, compound 5o reduced infarct size by 10% and improved the neurological deficit. The results may provide new insights into the development of novel GSK-3β inhibitors with potential neuroprotective activity against brain ischemic stroke. © 2015 John Wiley & Sons A/S.

Biological Activities of Extracts from Loquat (Eriobotrya japonica Lindl.): A Review

PubMed Central

Liu, Yilong; Zhang, Wenna; Xu, Changjie; Li, Xian

2016-01-01

Loquat (Eriobotrya japonica Lindl.) is a subtropical fruit tree with high medicinal value native to China. Different organs of loquat have been used historically as folk medicines and this has been recorded in Chinese history for thousands of years. Research shows that loquat extracts contain many antioxidants, and different extracts exhibit bioactivity capable of counteracting inflammation, diabetes, cancer, bacterial infection, aging, pain, allergy and other health issues. Bioactive compounds such as phenolics and terpenoids have been isolated and characterized to provide a better understanding of the chemical mechanisms underlying the biological activities of loquat extracts. As the identification of compounds progresses, studies investigating the in vivo metabolism, bioavailability, and structure–activity relationships, as well as potential toxicity of loquat extracts in animal or cell models are receiving more attention. In addition, genetic studies and breeding of loquat germplasms for high contents of health-benefiting compounds may provide new insight for the loquat industry and research. This review is focused on the main medicinal properties reported and the possible pharmaceutically active compounds identified in different loquat extracts. PMID:27929430

The formation and study of titanium, zirconium, and hafnium complexes

NASA Technical Reports Server (NTRS)

Wilson, Bobby; Sarin, Sam; Smith, Laverne; Wilson, Melanie

1989-01-01

Research involves the preparation and characterization of a series of Ti, Zr, Hf, TiO, and HfO complexes using the poly(pyrazole) borates as ligands. The study will provide increased understanding of the decomposition of these coordination compounds which may lead to the production of molecular oxygen on the Moon from lunar materials such as ilmenite and rutile. The model compounds are investigated under reducing conditions of molecular hydrogen by use of a high temperature/pressure stainless steel autoclave reactor and by thermogravimetric analysis.

A Quantitative Model for the Prediction of Sooting Tendency from Molecular Structure

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

St. John, Peter C.; Kairys, Paul; Das, Dhrubajyoti D.

Particulate matter emissions negatively affect public health and global climate, yet newer fuel-efficient gasoline direct injection engines tend to produce more soot than their port-fuel injection counterparts. Fortunately, the search for sustainable biomass-based fuel blendstocks provides an opportunity to develop fuels that suppress soot formation in more efficient engine designs. However, as emissions tests are experimentally cumbersome and the search space for potential bioblendstocks is vast, new techniques are needed to estimate the sooting tendency of a diverse range of compounds. In this study, we develop a quantitative structure-activity relationship (QSAR) model of sooting tendency based on the experimental yieldmore » sooting index (YSI), which ranks molecules on a scale from n-hexane, 0, to benzene, 100. The model includes a rigorously defined applicability domain, and the predictive performance is checked using both internal and external validation. Model predictions for compounds in the external test set had a median absolute error of ~3 YSI units. An investigation of compounds that are poorly predicted by the model lends new insight into the complex mechanisms governing soot formation. Predictive models of soot formation can therefore be expected to play an increasingly important role in the screening and development of next-generation biofuels.« less

A Quantitative Model for the Prediction of Sooting Tendency from Molecular Structure

DOE PAGES

St. John, Peter C.; Kairys, Paul; Das, Dhrubajyoti D.; ...

2017-07-24

Particulate matter emissions negatively affect public health and global climate, yet newer fuel-efficient gasoline direct injection engines tend to produce more soot than their port-fuel injection counterparts. Fortunately, the search for sustainable biomass-based fuel blendstocks provides an opportunity to develop fuels that suppress soot formation in more efficient engine designs. However, as emissions tests are experimentally cumbersome and the search space for potential bioblendstocks is vast, new techniques are needed to estimate the sooting tendency of a diverse range of compounds. In this study, we develop a quantitative structure-activity relationship (QSAR) model of sooting tendency based on the experimental yieldmore » sooting index (YSI), which ranks molecules on a scale from n-hexane, 0, to benzene, 100. The model includes a rigorously defined applicability domain, and the predictive performance is checked using both internal and external validation. Model predictions for compounds in the external test set had a median absolute error of ~3 YSI units. An investigation of compounds that are poorly predicted by the model lends new insight into the complex mechanisms governing soot formation. Predictive models of soot formation can therefore be expected to play an increasingly important role in the screening and development of next-generation biofuels.« less

Exploring sources of biogenic secondary organic aerosol compounds using chemical analysis and the FLEXPART model

NASA Astrophysics Data System (ADS)

Martinsson, Johan; Monteil, Guillaume; Sporre, Moa K.; Kaldal Hansen, Anne Maria; Kristensson, Adam; Eriksson Stenström, Kristina; Swietlicki, Erik; Glasius, Marianne

2017-09-01

Molecular tracers in secondary organic aerosols (SOAs) can provide information on origin of SOA, as well as regional scale processes involved in their formation. In this study 9 carboxylic acids, 11 organosulfates (OSs) and 2 nitrooxy organosulfates (NOSs) were determined in daily aerosol particle filter samples from Vavihill measurement station in southern Sweden during June and July 2012. Several of the observed compounds are photo-oxidation products from biogenic volatile organic compounds (BVOCs). Highest average mass concentrations were observed for carboxylic acids derived from fatty acids and monoterpenes (12. 3 ± 15. 6 and 13. 8 ± 11. 6 ng m-3, respectively). The FLEXPART model was used to link nine specific surface types to single measured compounds. It was found that the surface category sea and ocean was dominating the air mass exposure (56 %) but contributed to low mass concentration of observed chemical compounds. A principal component (PC) analysis identified four components, where the one with highest explanatory power (49 %) displayed clear impact of coniferous forest on measured mass concentration of a majority of the compounds. The three remaining PCs were more difficult to interpret, although azelaic, suberic, and pimelic acid were closely related to each other but not to any clear surface category. Hence, future studies should aim to deduce the biogenic sources and surface category of these compounds. This study bridges micro-level chemical speciation to air mass surface exposure at the macro level.

Antibacterial Evaluation of Synthetic Thiazole Compounds In Vitro and In Vivo in a Methicillin-Resistant Staphylococcus aureus (MRSA) Skin Infection Mouse Model.

PubMed

Mohammad, Haroon; Cushman, Mark; Seleem, Mohamed N

2015-01-01

The emergence of community-associated methicillin-resistant Staphylococcus aureus (MRSA), including strains resistant to current antibiotics, has contributed to an increase in the number of skin infections reported in humans in recent years. New therapeutic options are needed to counter this public health challenge. The aim of the present study was to examine the potential of thiazole compounds synthesized by our research group to be used topically to treat MRSA skin and wound infections. The broth microdilution method confirmed that the lead thiazole compound and four analogues are capable of inhibiting MRSA growth at concentrations as low as 1.3 μg/mL. Additionally, three compounds exhibited a synergistic relationship when combined with the topical antibiotic mupirocin against MRSA in vitro via the checkerboard assay. Thus the thiazole compounds have potential to be used alone or in combination with mupirocin against MRSA. When tested against human keratinocytes, four derivatives of the lead compound demonstrated an improved toxicity profile (were found to be non-toxic up to a concentration of 20 μg/mL). Utilizing a murine skin infection model, we confirmed that the lead compound and three analogues exhibited potent antimicrobial activity in vivo, with similar capability as the antibiotic mupirocin, as they reduced the burden of MRSA present in skin wounds by more than 90%. Taken altogether, the present study provides important evidence that these thiazole compounds warrant further investigation for development as novel topical antimicrobials to treat MRSA skin infections.

Zebrafish Caudal Fin Angiogenesis Assay—Advanced Quantitative Assessment Including 3-Way Correlative Microscopy

PubMed Central

Correa Shokiche, Carlos; Schaad, Laura; Triet, Ramona; Jazwinska, Anna; Tschanz, Stefan A.; Djonov, Valentin

2016-01-01

Background Researchers evaluating angiomodulating compounds as a part of scientific projects or pre-clinical studies are often confronted with limitations of applied animal models. The rough and insufficient early-stage compound assessment without reliable quantification of the vascular response counts, at least partially, to the low transition rate to clinics. Objective To establish an advanced, rapid and cost-effective angiogenesis assay for the precise and sensitive assessment of angiomodulating compounds using zebrafish caudal fin regeneration. It should provide information regarding the angiogenic mechanisms involved and should include qualitative and quantitative data of drug effects in a non-biased and time-efficient way. Approach & Results Basic vascular parameters (total regenerated area, vascular projection area, contour length, vessel area density) were extracted from in vivo fluorescence microscopy images using a stereological approach. Skeletonization of the vasculature by our custom-made software Skelios provided additional parameters including “graph energy” and “distance to farthest node”. The latter gave important insights into the complexity, connectivity and maturation status of the regenerating vascular network. The employment of a reference point (vascular parameters prior amputation) is unique for the model and crucial for a proper assessment. Additionally, the assay provides exceptional possibilities for correlative microscopy by combining in vivo-imaging and morphological investigation of the area of interest. The 3-way correlative microscopy links the dynamic changes in vivo with their structural substrate at the subcellular level. Conclusions The improved zebrafish fin regeneration model with advanced quantitative analysis and optional 3-way correlative morphology is a promising in vivo angiogenesis assay, well-suitable for basic research and preclinical investigations. PMID:26950851

Non-Destructive High-Resolution Organic Matter Record on Lake Sediment using Steady-State Solid Phase Fluorescence: Organic Matter Quality and Quantity Assessment.

NASA Astrophysics Data System (ADS)

Quiers, M.; Perrette, Y.; Etienne, D.; Develle, A. L.; Jacq, K.

2017-12-01

The use of organic proxies increases in paleoenvironmental reconstructions from natural archives. Major advances have been achieved by the development of new highly informative molecular proxies usually linked to specific compounds. While studies focused on targeted compounds, offering a high information degree, advances on bulk organic matter are limited. However, this bulk is the main contributor to carbon cycle and has been shown to be a driver of many mineral or organic compounds transfer and record. Development of target proxies need complementary information on bulk organic matter to understand biases link to controlling factors or analytical methods, and provide a robust interpretation. Fluorescence methods have often been employed to characterize and quantify organic matter. However, these technics are mainly developed for liquid samples, inducing material and resolution loss when working on natural archives (either stalagmite or sediments). High-resolution solid phase fluorescence (SPF) was developed on speleothems. This method allows now to analyse organic matter quality and quantity if procedure to constrain the optical density are adopted. In fact, a calibration method using liquid phase fluorescence (LPF) was developed for speleothem, allowing to quantify organic carbon at high-resolution. We report here an application of such a procedure SPF/LPF measurements on lake sediments. In order to avoid sediment matrix effects on the fluorescence signal, a calibration using LPF measurements was realised. First results using this method provided organic matter quality record of different organic matter compounds (humic-like, protein-like and chlorophylle-like compounds) at high resolution for the sediment core. High resolution organic matter fluxes are obtained in a second time, applying pragmatic chemometrics model (non linear models, partial least square models) on high resolution fluorescence data. SPF method can be considered as a promising tool for high resolution record on organic matter quality and quantity. Potential application of this method will be evocated (lake ecosystem dynamic, changes in trophic levels)

Modeling Compound Flood Hazards in Coastal Embayments

NASA Astrophysics Data System (ADS)

Moftakhari, H.; Schubert, J. E.; AghaKouchak, A.; Luke, A.; Matthew, R.; Sanders, B. F.

2017-12-01

Coastal cities around the world are built on lowland topography adjacent to coastal embayments and river estuaries, where multiple factors threaten increasing flood hazards (e.g. sea level rise and river flooding). Quantitative risk assessment is required for administration of flood insurance programs and the design of cost-effective flood risk reduction measures. This demands a characterization of extreme water levels such as 100 and 500 year return period events. Furthermore, hydrodynamic flood models are routinely used to characterize localized flood level intensities (i.e., local depth and velocity) based on boundary forcing sampled from extreme value distributions. For example, extreme flood discharges in the U.S. are estimated from measured flood peaks using the Log-Pearson Type III distribution. However, configuring hydrodynamic models for coastal embayments is challenging because of compound extreme flood events: events caused by a combination of extreme sea levels, extreme river discharges, and possibly other factors such as extreme waves and precipitation causing pluvial flooding in urban developments. Here, we present an approach for flood risk assessment that coordinates multivariate extreme analysis with hydrodynamic modeling of coastal embayments. First, we evaluate the significance of correlation structure between terrestrial freshwater inflow and oceanic variables; second, this correlation structure is described using copula functions in unit joint probability domain; and third, we choose a series of compound design scenarios for hydrodynamic modeling based on their occurrence likelihood. The design scenarios include the most likely compound event (with the highest joint probability density), preferred marginal scenario and reproduced time series of ensembles based on Monte Carlo sampling of bivariate hazard domain. The comparison between resulting extreme water dynamics under the compound hazard scenarios explained above provides an insight to the strengths/weaknesses of each approach and helps modelers choose the appropriate scenario that best fit to the needs of their project. The proposed risk assessment approach can help flood hazard modeling practitioners achieve a more reliable estimate of risk, by cautiously reducing the dimensionality of the hazard analysis.

Long-range Coulomb forces and localized bonds.

PubMed

Preiser; Lösel; Brown; Kunz; Skowron

1999-10-01

The ionic model is shown to be applicable to all compounds in which the atoms carry a net charge and their electron density is spherically symmetric regardless of the covalent character of the bonding. By examining the electric field generated by an array of point charges placed at the positions of the ions in over 40 inorganic compounds, we show that the Coulomb field naturally partitions itself into localized regions (bonds) which are characterized by the electric flux that links neighbouring ions of opposite charge. This flux is identified with the bond valence, and Gauss' law with the valence-sum rule, providing a secure theoretical foundation for the bond-valence model. The localization of the Coulomb field provides an unambiguous definition of coordination number and our calculations show that, in addition to the expected primary coordination sphere, there are a number of weak bonds between cations and the anions in the second coordination sphere. Long-range Coulomb interactions are transmitted through the crystal by the application of Gauss' law at each of the intermediate atoms. Bond fluxes have also been calculated for compounds containing ions with non-spherical electron densities (e.g. cations with stereoactive lone electron pairs). In these cases the point-charge model continues to describe the distant field, but multipoles must be added to the point charges to give the correct local field.

New public QSAR model for carcinogenicity

PubMed Central

2010-01-01

Background One of the main goals of the new chemical regulation REACH (Registration, Evaluation and Authorization of Chemicals) is to fulfill the gaps in data concerned with properties of chemicals affecting the human health. (Q)SAR models are accepted as a suitable source of information. The EU funded CAESAR project aimed to develop models for prediction of 5 endpoints for regulatory purposes. Carcinogenicity is one of the endpoints under consideration. Results Models for prediction of carcinogenic potency according to specific requirements of Chemical regulation were developed. The dataset of 805 non-congeneric chemicals extracted from Carcinogenic Potency Database (CPDBAS) was used. Counter Propagation Artificial Neural Network (CP ANN) algorithm was implemented. In the article two alternative models for prediction carcinogenicity are described. The first model employed eight MDL descriptors (model A) and the second one twelve Dragon descriptors (model B). CAESAR's models have been assessed according to the OECD principles for the validation of QSAR. For the model validity we used a wide series of statistical checks. Models A and B yielded accuracy of training set (644 compounds) equal to 91% and 89% correspondingly; the accuracy of the test set (161 compounds) was 73% and 69%, while the specificity was 69% and 61%, respectively. Sensitivity in both cases was equal to 75%. The accuracy of the leave 20% out cross validation for the training set of models A and B was equal to 66% and 62% respectively. To verify if the models perform correctly on new compounds the external validation was carried out. The external test set was composed of 738 compounds. We obtained accuracy of external validation equal to 61.4% and 60.0%, sensitivity 64.0% and 61.8% and specificity equal to 58.9% and 58.4% respectively for models A and B. Conclusion Carcinogenicity is a particularly important endpoint and it is expected that QSAR models will not replace the human experts opinions and conventional methods. However, we believe that combination of several methods will provide useful support to the overall evaluation of carcinogenicity. In present paper models for classification of carcinogenic compounds using MDL and Dragon descriptors were developed. Models could be used to set priorities among chemicals for further testing. The models at the CAESAR site were implemented in java and are publicly accessible. PMID:20678182

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

NASA Astrophysics Data System (ADS)

Jain, Sankalp; Grandits, Melanie; Richter, Lars; Ecker, Gerhard F.

2017-06-01

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

Functional Validation of Virtual Screening for Novel Agents with General Anesthetic Action at Ligand-Gated Ion Channels

PubMed Central

Heusser, Stephanie A.; Howard, Rebecca J.; Borghese, Cecilia M.; Cullins, Madeline A.; Broemstrup, Torben; Lee, Ui S.; Lindahl, Erik; Carlsson, Jens

2013-01-01

GABAA receptors play a crucial role in the actions of general anesthetics. The recently published crystal structure of the general anesthetic propofol bound to Gloeobacter violaceus ligand-gated ion channel (GLIC), a bacterial homolog of GABAA receptors, provided an opportunity to explore structure-based ligand discovery for pentameric ligand-gated ion channels (pLGICs). We used molecular docking of 153,000 commercially available compounds to identify molecules that interact with the propofol binding site in GLIC. In total, 29 compounds were selected for functional testing on recombinant GLIC, and 16 of these compounds modulated GLIC function. Active compounds were also tested on recombinant GABAA receptors, and point mutations around the presumed binding pocket were introduced into GLIC and GABAA receptors to test for binding specificity. The potency of active compounds was only weakly correlated with properties such as lipophilicity or molecular weight. One compound was found to mimic the actions of propofol on GLIC and GABAA, and to be sensitive to mutations that reduce the action of propofol in both receptors. Mutant receptors also provided insight about the position of the binding sites and the relevance of the receptor’s conformation for anesthetic actions. Overall, the findings support the feasibility of the use of virtual screening to discover allosteric modulators of pLGICs, and suggest that GLIC is a valid model system to identify novel GABAA receptor ligands. PMID:23950219

Testing a chemical series inspired by plant stress oxylipin signalling agents for herbicide safening activity

PubMed Central

Brazier‐Hicks, Melissa; Knight, Kathryn M; Sellars, Jonathan D

2018-01-01

Abstract BACKGROUND Herbicide safening in cereals is linked to a rapid xenobiotic response (XR), involving the induction of glutathione transferases (GSTs). The XR is also invoked by oxidized fatty acids (oxylipins) released during plant stress, suggesting a link between these signalling agents and safening. To examine this relationship, a series of compounds modelled on the oxylipins 12‐oxophytodienoic acid and phytoprostane 1, varying in lipophilicity and electrophilicity, were synthesized. Compounds were then tested for their ability to invoke the XR in Arabidopsis and protect rice seedlings exposed to the herbicide pretilachlor, as compared with the safener fenclorim. RESULTS Of the 21 compounds tested, three invoked the rapid GST induction associated with fenclorim. All compounds possessed two electrophilic carbon centres and a lipophilic group characteristic of both oxylipins and fenclorim. Minor effects observed in protecting rice seedlings from herbicide damage positively correlated with the XR, but did not provide functional safening. CONCLUSION The design of safeners based on the characteristics of oxylipins proved successful in deriving compounds that invoke a rapid XR in Arabidopsis but not in providing classical safening in a cereal. The results further support a link between safener and oxylipin signalling, but also highlight species‐dependent differences in the responses to these compounds. © 2018 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:29330904

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

Schrock, Richard Royce; Autenrieth, Benjamin

The present invention, among other things, provides highly syndiotactic poly(dicyclopentadiene) and/or hydrogenated poly(dicyclopentadiene), compositions thereof, and compounds and methods for preparing the same. In some embodiments, a provided compound is a compound of formula I, II or III. In some embodiments, a provided method comprises providing a compound of formula I, II or III.

Modeling correlated motion in thermoelectric skutterudite materials

NASA Astrophysics Data System (ADS)

Keiber, Trevor; Bridges, Frank; Bridges Lab Team

2014-03-01

Filled skutterudite compounds, LnT4X12 (Ln=rare earth; T=Fe,Ru,Os; X=P,As,Sb), have previously been modeled using a rigid cage approximation for the ``rattling'' rare earth atom. The large thermal broadening with temperature of the rattler can be fit using an Einstein model. Recent measurements of the second neighbor Ln-T peaks show an unusually large thermal broadening suggesting motion of the cage of atoms. To incorporate these results we developed three and four mass spring models to give the acoustic and optical phonon mode spectra. For the simplest three mass model we identify the low energy optical mode as the rattling mode. This rattling mode is likely coupled to the acoustic mode, and responsible for the low thermal conductivity of the skutterudite compound. We extend this model to four atoms to describe the CuO4 rings in oxy-skutterudites and the X4 rings in LnT4X12. This talk provides a model for the experimental results of the previous presentation. Support: NSF DMR1005568.

Determination of the ultrasound power effects on flavonoid compounds from Psidium guajava L. using ANFIS

NASA Astrophysics Data System (ADS)

Ratu Ayu, Humairoh; Suryono, Suryono; Endro Suseno, Jatmiko; Kurniawati, Ratna

2018-05-01

The Adaptive Neural Fuzzy Inference System (ANFIS) model was used to predict and optimize the content of flavonoid compounds in guava leaves (Psidium Guajava L.). The extraction process was carried out by using ultrasound assisted extraction (UAE) with the variable parameters: temperature ranging from 25°C to 35°C, ultrasonic frequency (30 - 40 kHz) and extraction time (20 - 40 minutes). ANFIS learning procedure began by providing the input variable data set (temperature, frequency and time) and the output of the flavonoid compounds from the experiments that had been done. Subtractive clustering methods was used in the manufacture of FIS (fuzzy inference system) structures by varying the range of influence parameters to generate the ANFIS system. The ANFIS trainingsconducted wereaimed at minimum error value. The results showed that the best ANFIS models used a subtractive clustering method, in which the ranges of influence 0.1 were 0.70 x 10-4 for training RMSE, 8.11 for testing RMSE, 2.7 % MAPE, and 7.72 MAE. The optimum condition was obtained at a temperature of 35°C and frequency of 40 kHz, for 30 minutes. This result proves that the ANFIS model can be used to predict the content of flavonoid compounds in guava leaves.

Rapid Countermeasure Discovery against Francisella tularensis Based on a Metabolic Network Reconstruction

PubMed Central

Chaudhury, Sidhartha; Abdulhameed, Mohamed Diwan M.; Singh, Narender; Tawa, Gregory J.; D’haeseleer, Patrik M.; Zemla, Adam T.; Navid, Ali; Zhou, Carol E.; Franklin, Matthew C.; Cheung, Jonah; Rudolph, Michael J.; Love, James; Graf, John F.; Rozak, David A.; Dankmeyer, Jennifer L.; Amemiya, Kei; Daefler, Simon; Wallqvist, Anders

2013-01-01

In the future, we may be faced with the need to provide treatment for an emergent biological threat against which existing vaccines and drugs have limited efficacy or availability. To prepare for this eventuality, our objective was to use a metabolic network-based approach to rapidly identify potential drug targets and prospectively screen and validate novel small-molecule antimicrobials. Our target organism was the fully virulent Francisella tularensis subspecies tularensis Schu S4 strain, a highly infectious intracellular pathogen that is the causative agent of tularemia and is classified as a category A biological agent by the Centers for Disease Control and Prevention. We proceeded with a staggered computational and experimental workflow that used a strain-specific metabolic network model, homology modeling and X-ray crystallography of protein targets, and ligand- and structure-based drug design. Selected compounds were subsequently filtered based on physiological-based pharmacokinetic modeling, and we selected a final set of 40 compounds for experimental validation of antimicrobial activity. We began screening these compounds in whole bacterial cell-based assays in biosafety level 3 facilities in the 20th week of the study and completed the screens within 12 weeks. Six compounds showed significant growth inhibition of F. tularensis, and we determined their respective minimum inhibitory concentrations and mammalian cell cytotoxicities. The most promising compound had a low molecular weight, was non-toxic, and abolished bacterial growth at 13 µM, with putative activity against pantetheine-phosphate adenylyltransferase, an enzyme involved in the biosynthesis of coenzyme A, encoded by gene coaD. The novel antimicrobial compounds identified in this study serve as starting points for lead optimization, animal testing, and drug development against tularemia. Our integrated in silico/in vitro approach had an overall 15% success rate in terms of active versus tested compounds over an elapsed time period of 32 weeks, from pathogen strain identification to selection and validation of novel antimicrobial compounds. PMID:23704901

Developing and validating predictive decision tree models from mining chemical structural fingerprints and high-throughput screening data in PubChem.

PubMed

Han, Lianyi; Wang, Yanli; Bryant, Stephen H

2008-09-25

Recent advances in high-throughput screening (HTS) techniques and readily available compound libraries generated using combinatorial chemistry or derived from natural products enable the testing of millions of compounds in a matter of days. Due to the amount of information produced by HTS assays, it is a very challenging task to mine the HTS data for potential interest in drug development research. Computational approaches for the analysis of HTS results face great challenges due to the large quantity of information and significant amounts of erroneous data produced. In this study, Decision Trees (DT) based models were developed to discriminate compound bioactivities by using their chemical structure fingerprints provided in the PubChem system http://pubchem.ncbi.nlm.nih.gov. The DT models were examined for filtering biological activity data contained in four assays deposited in the PubChem Bioassay Database including assays tested for 5HT1a agonists, antagonists, and HIV-1 RT-RNase H inhibitors. The 10-fold Cross Validation (CV) sensitivity, specificity and Matthews Correlation Coefficient (MCC) for the models are 57.2 approximately 80.5%, 97.3 approximately 99.0%, 0.4 approximately 0.5 respectively. A further evaluation was also performed for DT models built for two independent bioassays, where inhibitors for the same HIV RNase target were screened using different compound libraries, this experiment yields enrichment factor of 4.4 and 9.7. Our results suggest that the designed DT models can be used as a virtual screening technique as well as a complement to traditional approaches for hits selection.

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

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.

Computer-aided discovery of two novel chalcone-like compounds active and selective against Leishmania infantum.

PubMed

Gomes, Marcelo N; Alcântara, Laura M; Neves, Bruno J; Melo-Filho, Cleber C; Freitas-Junior, Lucio H; Moraes, Carolina B; Ma, Rui; Franzblau, Scott G; Muratov, Eugene; Andrade, Carolina Horta

2017-06-01

Leishmaniasis are infectious diseases caused by parasites of genus Leishmania that affect affects 12 million people in 98 countries mainly in Africa, Asia, and Latin America. Effective treatments for this disease are urgently needed. In this study, we present a computer-aided approach to investigate a set of 32 recently synthesized chalcone and chalcone-like compounds to act as antileishmanial agents. As a result, nine most promising compounds and three potentially inactive compounds were experimentally evaluated against Leishmania infantum amastigotes and mammalian cells. Four compounds exhibited EC 50 in the range of 6.2-10.98μM. In addition, two compounds, LabMol-65 and LabMol-73, exhibited cytotoxicity in macrophages >50μM that resulted in better selectivity compared to standard drug amphotericin B. These two compounds also demonstrated low cytotoxicity and high selectivity towards Vero cells. The results of target fishing followed by homology modeling and docking studies suggest that these chalcone compounds could act in Leishmania because of their interaction with cysteine proteases, such as procathepsin L. Finally, we have provided structural recommendations for designing new antileishmanial chalcones. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discovery of novel EGFR tyrosine kinase inhibitors by structure-based virtual screening.

PubMed

Li, Siyuan; Sun, Xianqiang; Zhao, Hongli; Tang, Yun; Lan, Minbo

2012-06-15

By using of structure-based virtual screening, 13 novel epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors were discovered from 197,116 compounds in the SPECS database here. Among them, 8 compounds significantly inhibited EGFR kinase activity with IC(50) values lower than 10 μM. 3-{[1-(3-Chloro-4-fluorophenyl)-3,5-dioxo-4-pyrazolidinylidene]methyl}phenyl 2-thiophenecarboxylate (13), particularly, was the most potent inhibitor possessing the IC(50) value of 3.5 μM. The docking studies also provide some useful information that the docking models of the 13 compounds are beneficial to find a new path for designing novel EGFR inhibitors. Copyright © 2012 Elsevier Ltd. All rights reserved.

Antibacterial Drug Discovery: Some Assembly Required.

PubMed

Tommasi, Rubén; Iyer, Ramkumar; Miller, Alita A

2018-05-11

Our limited understanding of the molecular basis for compound entry into and efflux out of Gram-negative bacteria is now recognized as a key bottleneck for the rational discovery of novel antibacterial compounds. Traditional, large-scale biochemical or target-agnostic phenotypic antibacterial screening efforts have, as a result, not been very fruitful. A main driver of this knowledge gap has been the historical lack of predictive cellular assays, tools, and models that provide structure-activity relationships to inform optimization of compound accumulation. A variety of recent approaches has recently been described to address this conundrum. This Perspective explores these approaches and considers ways in which their integration could successfully redirect antibacterial drug discovery efforts.

Selected approaches for rational drug design and high throughput screening to identify anti-cancer molecules.

PubMed

Hedvat, Michael; Emdad, Luni; Das, Swadesh K; Kim, Keetae; Dasgupta, Santanu; Thomas, Shibu; Hu, Bin; Zhu, Shan; Dash, Rupesh; Quinn, Bridget A; Oyesanya, Regina A; Kegelman, Timothy P; Sokhi, Upneet K; Sarkar, Siddik; Erdogan, Eda; Menezes, Mitchell E; Bhoopathi, Praveen; Wang, Xiang-Yang; Pomper, Martin G; Wei, Jun; Wu, Bainan; Stebbins, John L; Diaz, Paul W; Reed, John C; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B

2012-11-01

Structure-based modeling combined with rational drug design, and high throughput screening approaches offer significant potential for identifying and developing lead compounds with therapeutic potential. The present review focuses on these two approaches using explicit examples based on specific derivatives of Gossypol generated through rational design and applications of a cancer-specificpromoter derived from Progression Elevated Gene-3. The Gossypol derivative Sabutoclax (BI-97C1) displays potent anti-tumor activity against a diverse spectrum of human tumors. The model of the docked structure of Gossypol bound to Bcl-XL provided a virtual structure-activity-relationship where appropriate modifications were predicted on a rational basis. These structure-based studies led to the isolation of Sabutoclax, an optically pure isomer of Apogossypol displaying superior efficacy and reduced toxicity. These studies illustrate the power of combining structure-based modeling with rational design to predict appropriate derivatives of lead compounds to be empirically tested and evaluated for bioactivity. Another approach to cancer drug discovery utilizes a cancer-specific promoter as readouts of the transformed state. The promoter region of Progression Elevated Gene-3 is such a promoter with cancer-specific activity. The specificity of this promoter has been exploited as a means of constructing cancer terminator viruses that selectively kill cancer cells and as a systemic imaging modality that specifically visualizes in vivo cancer growth with no background from normal tissues. Screening of small molecule inhibitors that suppress the Progression Elevated Gene-3-promoter may provide relevant lead compounds for cancer therapy that can be combined with further structure-based approaches leading to the development of novel compounds for cancer therapy.

Meisoindigo, but not its core chemical structure indirubin, inhibits zebrafish interstitial leukocyte chemotactic migration.

PubMed

Ye, Baixin; Xiong, Xiaoxing; Deng, Xu; Gu, Lijuan; Wang, Qiongyu; Zeng, Zhi; Gao, Xiang; Gao, Qingping; Wang, Yueying

2017-12-01

Inflammatory disease is a big threat to human health. Leukocyte chemotactic migration is required for efficient inflammatory response. Inhibition of leukocyte chemotactic migration to the inflammatory site has been shown to provide therapeutic targets for treating inflammatory diseases. Our study was designed to discover effective and safe compounds that can inhibit leukocyte chemotactic migration, thus providing possible novel therapeutic strategy for treating inflammatory diseases. In this study, we used transgenic zebrafish model (Tg:zlyz-EGFP line) to visualize the process of leukocyte chemotactic migration. Then, we used this model to screen the hit compound and evaluate its biological activity on leukocyte chemotactic migration. Furthermore, western blot analysis was performed to evaluate the effect of the hit compound on the AKT or ERK-mediated pathway, which plays an important role in leukocyte chemotactic migration. In this study, using zebrafish-based chemical screening, we identified that the hit compound meisoindigo (25 μM, 50 μM, 75 μM) can significantly inhibit zebrafish leukocyte chemotactic migration in a dose-dependent manner (p = 0.01, p = 0.0006, p < 0.0001). Also, we found that meisoindigo did not affect the process of leukocyte reverse migration (p = 0.43). Furthermore, our results unexpectedly showed that indirubin, the core structure of meisoindigo, had no significant effect on zebrafish leukocyte chemotactic migration (p = 0.6001). Additionally, our results revealed that meisoindigo exerts no effect on the Akt or Erk-mediated signalling pathway. Our results suggest that meisoindigo, but not indirubin, is effective for inhibiting leukocyte chemotactic migration, thus providing a potential therapeutic agent for treating inflammatory diseases.

QSAR-like models: a potential tool for the selection of PhACs and EDCs for monitoring purposes in drinking water treatment systems--a review.

PubMed

Delgado, Luis F; Charles, Philippe; Glucina, Karl; Morlay, Catherine

2012-12-01

Recent studies have demonstrated the presence of trace-level pharmaceutically active compounds (PhACs) and endocrine disrupting compounds (EDCs) in a number of finished drinking waters (DWs). Since there is sparse knowledge currently available on the potential effects on human health associated with the chronic exposure to trace levels of these Emerging Contaminants (ECs) through routes such as DW, it is suggested that the most appropriate criterion is a treatment criterion in order to prioritize ECs to be monitored during DW preparation. Hence, only the few ECs showing the lowest removals towards a given DW Treatment (DWT) process would serve as indicators of the overall efficiency of this process and would be relevant for DW quality monitoring. In addition, models should be developed for estimating the removal of ECs in DWT processes, thereby overcoming the practical difficulties of experimentally assessing each compound. Therefore, the present review has two objectives: (1) to provide an overview of the recent scientific surveys on the occurrence of PhACs and EDCs in finished DWs; and (2) to propose the potential of Quantitative-Structure-Activity-Relationship-(QSAR)-like models to rank ECs found in environmental waters, including parent compounds, metabolites and transformation products, in order to select the most relevant compounds to be considered as indicators for monitoring purposes in DWT systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Rapid and effective decontamination of chlorophenol-contaminated soil by sorption into commercial polymers: concept demonstration and process modeling.

PubMed

Tomei, M Concetta; Mosca Angelucci, Domenica; Ademollo, Nicoletta; Daugulis, Andrew J

2015-03-01

Solid phase extraction performed with commercial polymer beads to treat soil contaminated by chlorophenols (4-chlorophenol, 2,4-dichlorophenol and pentachlorophenol) as single compounds and in a mixture has been investigated in this study. Soil-water-polymer partition tests were conducted to determine the relative affinities of single compounds in soil-water and polymer-water pairs. Subsequent soil extraction tests were performed with Hytrel 8206, the polymer showing the highest affinity for the tested chlorophenols. Factors that were examined were polymer type, moisture content, and contamination level. Increased moisture content (up to 100%) improved the extraction efficiency for all three compounds. Extraction tests at this upper level of moisture content showed removal efficiencies ≥70% for all the compounds and their ternary mixture, for 24 h of contact time, which is in contrast to the weeks and months, normally required for conventional ex situ remediation processes. A dynamic model characterizing the rate and extent of decontamination was also formulated, calibrated and validated with the experimental data. The proposed model, based on the simplified approach of "lumped parameters" for the mass transfer coefficients, provided very good predictions of the experimental data for the absorptive removal of contaminants from soil at different individual solute levels. Parameters evaluated from calibration by fitting of single compound data, have been successfully applied to predict mixture data, with differences between experimental and predicted data in all cases being ≤3%. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

3D Pharmacophore-Based Virtual Screening and Docking Approaches toward the Discovery of Novel HPPD Inhibitors.

PubMed

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2017-06-09

p -Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking-based virtual screening were performed to identify novel potential HPPD inhibitors. The complex-based pharmacophore model (CBP) with 0.721 of ROC used for screening compounds showed remarkable ability to retrieve known active ligands from among decoy molecules. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5 (DS 2.5) to discern interactions with key residues at the active site of HPPD. Four compounds with top rankings in the HipHop model and well-known binding model were finally chosen as lead compounds with potential inhibitory effects on the active site of target. The results provided powerful insight into the development of novel HPPD inhibitors herbicides using computational techniques.

Drug repurposing for aging research using model organisms.

PubMed

Ziehm, Matthias; Kaur, Satwant; Ivanov, Dobril K; Ballester, Pedro J; Marcus, David; Partridge, Linda; Thornton, Janet M

2017-10-01

Many increasingly prevalent diseases share a common risk factor: age. However, little is known about pharmaceutical interventions against aging, despite many genes and pathways shown to be important in the aging process and numerous studies demonstrating that genetic interventions can lead to a healthier aging phenotype. An important challenge is to assess the potential to repurpose existing drugs for initial testing on model organisms, where such experiments are possible. To this end, we present a new approach to rank drug-like compounds with known mammalian targets according to their likelihood to modulate aging in the invertebrates Caenorhabditis elegans and Drosophila. Our approach combines information on genetic effects on aging, orthology relationships and sequence conservation, 3D protein structures, drug binding and bioavailability. Overall, we rank 743 different drug-like compounds for their likelihood to modulate aging. We provide various lines of evidence for the successful enrichment of our ranking for compounds modulating aging, despite sparse public data suitable for validation. The top ranked compounds are thus prime candidates for in vivo testing of their effects on lifespan in C. elegans or Drosophila. As such, these compounds are promising as research tools and ultimately a step towards identifying drugs for a healthier human aging. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Predicting human liver microsomal stability with machine learning techniques.

PubMed

Sakiyama, Yojiro; Yuki, Hitomi; Moriya, Takashi; Hattori, Kazunari; Suzuki, Misaki; Shimada, Kaoru; Honma, Teruki

2008-02-01

To ensure a continuing pipeline in pharmaceutical research, lead candidates must possess appropriate metabolic stability in the drug discovery process. In vitro ADMET (absorption, distribution, metabolism, elimination, and toxicity) screening provides us with useful information regarding the metabolic stability of compounds. However, before the synthesis stage, an efficient process is required in order to deal with the vast quantity of data from large compound libraries and high-throughput screening. Here we have derived a relationship between the chemical structure and its metabolic stability for a data set of in-house compounds by means of various in silico machine learning such as random forest, support vector machine (SVM), logistic regression, and recursive partitioning. For model building, 1952 proprietary compounds comprising two classes (stable/unstable) were used with 193 descriptors calculated by Molecular Operating Environment. The results using test compounds have demonstrated that all classifiers yielded satisfactory results (accuracy > 0.8, sensitivity > 0.9, specificity > 0.6, and precision > 0.8). Above all, classification by random forest as well as SVM yielded kappa values of approximately 0.7 in an independent validation set, slightly higher than other classification tools. These results suggest that nonlinear/ensemble-based classification methods might prove useful in the area of in silico ADME modeling.

Composite multi-parameter ranking of real and virtual compounds for design of MC4R agonists: renaissance of the Free-Wilson methodology.

PubMed

Nilsson, Ingemar; Polla, Magnus O

2012-10-01

Drug design is a multi-parameter task present in the analysis of experimental data for synthesized compounds and in the prediction of new compounds with desired properties. This article describes the implementation of a binned scoring and composite ranking scheme for 11 experimental parameters that were identified as key drivers in the MC4R project. The composite ranking scheme was implemented in an AstraZeneca tool for analysis of project data, thereby providing an immediate re-ranking as new experimental data was added. The automated ranking also highlighted compounds overlooked by the project team. The successful implementation of a composite ranking on experimental data led to the development of an equivalent virtual score, which was based on Free-Wilson models of the parameters from the experimental ranking. The individual Free-Wilson models showed good to high predictive power with a correlation coefficient between 0.45 and 0.97 based on the external test set. The virtual ranking adds value to the selection of compounds for synthesis but error propagation must be controlled. The experimental ranking approach adds significant value, is parameter independent and can be tuned and applied to any drug discovery project.

An HTS-compatible 3D colony formation assay to identify tumor-specific chemotherapeutics.

PubMed

Horman, Shane R; To, Jeremy; Orth, Anthony P

2013-12-01

There has been increasing interest in the development of cellular behavior models that take advantage of three-dimensional (3D) cell culture. To enable assessment of differential perturbagen impacts on cell growth in 2D and 3D, we have miniaturized and adapted for high-throughput screening (HTS) the soft agar colony formation assay, employing a laser-scanning cytometer to image and quantify multiple cell types simultaneously. The assay is HTS compatible, providing high-quality, image-based, replicable data for multiple, co-cultured cell types. As proof of concept, we subjected colorectal carcinoma colonies in 3D soft agar to a mini screen of 1528 natural product compounds. Hit compounds from the primary screen were rescreened in an HTS 3D co-culture matrix containing colon stromal cells and cancer cells. By combining tumor cells and normal, nontransformed colon epithelial cells in one primary screening assay, we were able to obtain differential IC50 data, thereby distinguishing tumor-specific compounds from general cytotoxic compounds. Moreover, we were able to identify compounds that antagonized tumor colony formation in 3D only, highlighting the importance of this assay in identifying agents that interfere with 3D tumor structural growth. This screening platform provides a fast, simple, and robust method for identification of tumor-specific agents in a biologically relevant microenvironment.

Writing and overwriting short-term memory

PubMed Central

Killeen, Peter R.

2008-01-01

An integrative account of short-term memory is based on data from pigeons trained to report the majority color in a sequence of lights. Performance showed strong recency effects, was invariant over changes in the interstimulus interval, and improved with increases in the intertrial interval. A compound model of binomial variance around geometrically decreasing memory described the data; a logit transformation rendered it isomorphic with other memory models. The model was generalized for variance in the parameters, where it was shown that averaging exponential and power functions from individuals or items with different decay rates generates new functions that are hyperbolic in time and in log time, respectively. The compound model provides a unified treatment of both the accrual and the dissipation of memory and is consistent with data from various experiments, including the choose-short bias in delayed recall, multielement stimuli, and Rubin and Wenzel’s (1996) meta-analyses of forgetting. PMID:11340865

A new model for humic materials and their interactions with hydrophobic organic chemicals in soil-water or sediment-water systems

USGS Publications Warehouse

Wershaw, R. L.

1986-01-01

A generalized model of humic materials in soils and sediments, which is consistent with their observed properties, is presented. This model provides a means of understanding the interaction of hydrophobic pollutants with humic materials. In this model, it is proposed that the humic materials in soils and sediments consist of a number of different oligomers and simple compounds which result from the partial degradation of plant remains. These degradation products are stabilized by incorporation into humic aggregates bound together by weak bonding mechanisms, such as hydrogen bonding, pi bonding, and hydrophobic interactions. The resulting structures are similar to micelles or membranes, in which the interiors of the structures are hydrophobic and the exteriors are hydrophilic. Hydrophobic compounds will partition into the hydrophobic interiors of the humic micelles or "membrane-like" structures. ?? 1986.

Tracking contributions to human body burden of environmental chemicals by correlating environmental measurements with biomarkers.

PubMed

Shin, Hyeong-Moo; McKone, Thomas E; Sohn, Michael D; Bennett, Deborah H

2014-01-01

The work addresses current knowledge gaps regarding causes for correlations between environmental and biomarker measurements and explores the underappreciated role of variability in disaggregating exposure attributes that contribute to biomarker levels. Our simulation-based study considers variability in environmental and food measurements, the relative contribution of various exposure sources (indoors and food), and the biological half-life of a compound, on the resulting correlations between biomarker and environmental measurements. For two hypothetical compounds whose half-lives are on the order of days for one and years for the other, we generate synthetic daily environmental concentrations and food exposures with different day-to-day and population variability as well as different amounts of home- and food-based exposure. Assuming that the total intake results only from home-based exposure and food ingestion, we estimate time-dependent biomarker concentrations using a one-compartment pharmacokinetic model. Box plots of modeled R2 values indicate that although the R2 correlation between wipe and biological (e.g., serum) measurements is within the same range for the two compounds, the relative contribution of the home exposure to the total exposure could differ by up to 20%, thus providing the relative indication of their contribution to body burden. The novel method introduced in this paper provides insights for evaluating scenarios or experiments where sample, exposure, and compound variability must be weighed in order to interpret associations between exposure data.

New clues on carcinogenicity-related substructures derived from mining two large datasets of chemical compounds.

PubMed

Golbamaki, Azadi; Benfenati, Emilio; Golbamaki, Nazanin; Manganaro, Alberto; Merdivan, Erinc; Roncaglioni, Alessandra; Gini, Giuseppina

2016-04-02

In this study, new molecular fragments associated with genotoxic and nongenotoxic carcinogens are introduced to estimate the carcinogenic potential of compounds. Two rule-based carcinogenesis models were developed with the aid of SARpy: model R (from rodents' experimental data) and model E (from human carcinogenicity data). Structural alert extraction method of SARpy uses a completely automated and unbiased manner with statistical significance. The carcinogenicity models developed in this study are collections of carcinogenic potential fragments that were extracted from two carcinogenicity databases: the ANTARES carcinogenicity dataset with information from bioassay on rats and the combination of ISSCAN and CGX datasets, which take into accounts human-based assessment. The performance of these two models was evaluated in terms of cross-validation and external validation using a 258 compound case study dataset. Combining R and H predictions and scoring a positive or negative result when both models are concordant on a prediction, increased accuracy to 72% and specificity to 79% on the external test set. The carcinogenic fragments present in the two models were compared and analyzed from the point of view of chemical class. The results of this study show that the developed rule sets will be a useful tool to identify some new structural alerts of carcinogenicity and provide effective information on the molecular structures of carcinogenic chemicals.

Partitioning of polar and non-polar neutral organic chemicals into human and cow milk.

PubMed

Geisler, Anett; Endo, Satoshi; Goss, Kai-Uwe

2011-10-01

The aim of this work was to develop a predictive model for milk/water partition coefficients of neutral organic compounds. Batch experiments were performed for 119 diverse organic chemicals in human milk and raw and processed cow milk at 37°C. No differences (<0.3 log units) in the partition coefficients of these types of milk were observed. The polyparameter linear free energy relationship model fit the calibration data well (SD=0.22 log units). An experimental validation data set including hormones and hormone active compounds was predicted satisfactorily by the model. An alternative modelling approach based on log K(ow) revealed a poorer performance. The model presented here provides a significant improvement in predicting enrichment of potentially hazardous chemicals in milk. In combination with physiologically based pharmacokinetic modelling this improvement in the estimation of milk/water partitioning coefficients may allow a better risk assessment for a wide range of neutral organic chemicals. Copyright © 2011 Elsevier Ltd. All rights reserved.

Can we use ground-based measurements of HCFCs and HFCs to derive their emissions, lifetimes, and the global OH abundance?

NASA Astrophysics Data System (ADS)

Liang, Q.; Chipperfield, M.; Daniel, J. S.; Burkholder, J. B.; Rigby, M. L.; Velders, G. J. M.

2015-12-01

The hydroxyl radical (OH) is the major oxidant in the atmosphere. Reaction with OH is the primary removal process for many non-CO2greenhouse gases (GHGs), ozone-depleting substances (ODSs) and their replacements, e.g. hydrochlorofluorocarbons (HCFCs) and hydrofluorocarbons (HFCs). Traditionally, the global OH abundance is inferred using the observed atmospheric rate of change for methyl chloroform (MCF). Due to the Montreal Protocol regulation, the atmospheric abundance of MCF has been decreasing rapidly to near-zero values. It is becoming critical to find an alternative reference compound to continue to provide quantitative information for the global OH abundance. Our model analysis using the NASA 3-D GEOS-5 Chemistry Climate Model suggests that the inter-hemispheric gradients (IHG) of the HCFCs and HFCs show a strong linear correlation with their global emissions. Therefore it is possible to use (i) the observed IHGs of HCFCs and HFCs to estimate their global emissions, and (ii) use the derived emissions and the observed long-term trend to calculate their lifetimes and to infer the global OH abundance. Preliminary analysis using a simple global two-box model (one box for each hemisphere) and information from the global 3-D model suggests that the quantitative relationship between IHG and global emissions varies slightly among individual compounds depending on their lifetime, their emissions history and emission fractions from the two hemispheres. While each compound shows different sensitivity to the above quantities, the combined suite of the HCFCs and HFCs provides a means to derive global OH abundance and the corresponding atmospheric lifetimes of long-lived gases with respect to OH (tOH). The fact that the OH partial lifetimes of these compounds are highly correlated, with the ratio of tOH equal to the reverse ratio of their OH thermal reaction rates at 272K, provides an additional constraint that can greatly reduce the uncertainty in the OH abundance and tOH estimates. We will use the observed IHGs and long-term trends of three major HCFCs and six major HFCs in the two-box model to derive their global emissions and atmospheric lifetimes as well as the global OH abundance. The derived global OH abundance between 2000 and 2014 will be compared with that derived using MCF for consistency.

Consultation for Human, Veterinary, and Compounded Medications.

PubMed

Moghadam, Gabriella; Forsythe, Lauren Eichstadt

2017-01-01

Providing consultation on medications is a daily responsibility for pharmacists. However, counseling components for veterinary or compounded medications can differ from those for manufactured medications for humans. This article lists the content that should be provided during consultation, describes differences between counseling for human and veterinary patients, and provides references that can be used. Because many veterinary medications are compounded, this article also provides information that should accompany compounded preparations. Copyright© by International Journal of Pharmaceutical Compounding, Inc.

Catalysts and methods for ring opening metathesis polymerization

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

Schrock, Richard Royce; Autenrieth, Benjamin

The present invention, among other things, provides highly syndiotactic poly(dicyclopentadiene) and/or hydrogenated poly(dicyclopentadiene), compositions thereof, and compounds and methods for preparing the same. In some embodiments, a provided compound is a compound of formula I, II or III. In some embodiments, a provided method comprises providing a compound of formula I, II or III.

Phenotypic Characterization of Toxic Compound Effects on Liver Spheroids Derived from iPSC Using Confocal Imaging and Three-Dimensional Image Analysis.

PubMed

Sirenko, Oksana; Hancock, Michael K; Hesley, Jayne; Hong, Dihui; Cohen, Avrum; Gentry, Jason; Carlson, Coby B; Mann, David A

2016-09-01

Cell models are becoming more complex to better mimic the in vivo environment and provide greater predictivity for compound efficacy and toxicity. There is an increasing interest in exploring the use of three-dimensional (3D) spheroids for modeling developmental and tissue biology with the goal of accelerating translational research in these areas. Accordingly, the development of high-throughput quantitative assays using 3D cultures is an active area of investigation. In this study, we have developed and optimized methods for the formation of 3D liver spheroids derived from human iPS cells and used those for toxicity assessment. We used confocal imaging and 3D image analysis to characterize cellular information from a 3D matrix to enable a multi-parametric comparison of different spheroid phenotypes. The assay enables characterization of compound toxicities by spheroid size (volume) and shape, cell number and spatial distribution, nuclear characterization, number and distribution of cells expressing viability, apoptosis, mitochondrial potential, and viability marker intensities. In addition, changes in the content of live, dead, and apoptotic cells as a consequence of compound exposure were characterized. We tested 48 compounds and compared induced pluripotent stem cell (iPSC)-derived hepatocytes and HepG2 cells in both two-dimensional (2D) and 3D cultures. We observed significant differences in the pharmacological effects of compounds across the two cell types and between the different culture conditions. Our results indicate that a phenotypic assay using 3D model systems formed with human iPSC-derived hepatocytes is suitable for high-throughput screening and can be used for hepatotoxicity assessment in vitro.

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.

In Vitro Enzymatic Depolymerization of Lignin with Release of Syringyl, Guaiacyl, and Tricin Units

PubMed Central

Gall, Daniel L.; Kontur, Wayne S.; Lan, Wu; Kim, Hoon; Li, Yanding; Ralph, John

2017-01-01

ABSTRACT New environmentally sound technologies are needed to derive valuable compounds from renewable resources. Lignin, an abundant polymer in terrestrial plants comprised predominantly of guaiacyl and syringyl monoaromatic phenylpropanoid units, is a potential natural source of aromatic compounds. In addition, the plant secondary metabolite tricin is a recently discovered and moderately abundant flavonoid in grasses. The most prevalent interunit linkage between guaiacyl, syringyl, and tricin units is the β-ether linkage. Previous studies have shown that bacterial β-etherase pathway enzymes catalyze glutathione-dependent cleavage of β-ether bonds in dimeric β-ether lignin model compounds. To date, however, it remains unclear whether the known β-etherase enzymes are active on lignin polymers. Here we report on enzymes that catalyze β-ether cleavage from bona fide lignin, under conditions that recycle the cosubstrates NAD+ and glutathione. Guaiacyl, syringyl, and tricin derivatives were identified as reaction products when different model compounds or lignin fractions were used as substrates. These results demonstrate an in vitro enzymatic system that can recycle cosubstrates while releasing aromatic monomers from model compounds as well as natural and engineered lignin oligomers. These findings can improve the ability to produce valuable aromatic compounds from a renewable resource like lignin. IMPORTANCE Many bacteria are predicted to contain enzymes that could convert renewable carbon sources into substitutes for compounds that are derived from petroleum. The β-etherase pathway present in sphingomonad bacteria could cleave the abundant β–O–4-aryl ether bonds in plant lignin, releasing a biobased source of aromatic compounds for the chemical industry. However, the activity of these enzymes on the complex aromatic oligomers found in plant lignin is unknown. Here we demonstrate biodegradation of lignin polymers using a minimal set of β-etherase pathway enzymes, the ability to recycle needed cofactors (glutathione and NAD+) in vitro, and the release of guaiacyl, syringyl, and tricin as depolymerized products from lignin. These observations provide critical evidence for the use and future optimization of these bacterial β-etherase pathway enzymes for industrial-level biotechnological applications designed to derive high-value monomeric aromatic compounds from lignin. PMID:29180366

Biodegradation of Aromatic Compounds by Escherichia coli

PubMed Central

Díaz, Eduardo; Ferrández, Abel; Prieto, María A.; García, José L.

2001-01-01

Although Escherichia coli has long been recognized as the best-understood living organism, little was known about its abilities to use aromatic compounds as sole carbon and energy sources. This review gives an extensive overview of the current knowledge of the catabolism of aromatic compounds by E. coli. After giving a general overview of the aromatic compounds that E. coli strains encounter and mineralize in the different habitats that they colonize, we provide an up-to-date status report on the genes and proteins involved in the catabolism of such compounds, namely, several aromatic acids (phenylacetic acid, 3- and 4-hydroxyphenylacetic acid, phenylpropionic acid, 3-hydroxyphenylpropionic acid, and 3-hydroxycinnamic acid) and amines (phenylethylamine, tyramine, and dopamine). Other enzymatic activities acting on aromatic compounds in E. coli are also reviewed and evaluated. The review also reflects the present impact of genomic research and how the analysis of the whole E. coli genome reveals novel aromatic catabolic functions. Moreover, evolutionary considerations derived from sequence comparisons between the aromatic catabolic clusters of E. coli and homologous clusters from an increasing number of bacteria are also discussed. The recent progress in the understanding of the fundamentals that govern the degradation of aromatic compounds in E. coli makes this bacterium a very useful model system to decipher biochemical, genetic, evolutionary, and ecological aspects of the catabolism of such compounds. In the last part of the review, we discuss strategies and concepts to metabolically engineer E. coli to suit specific needs for biodegradation and biotransformation of aromatics and we provide several examples based on selected studies. Finally, conclusions derived from this review may serve as a lead for future research and applications. PMID:11729263

Investigation of metal-dithiolate fold angle effects: implications for molybdenum and tungsten enzymes.

PubMed

Joshi, Hemant K; Cooney, J Jon A; Inscore, Frank E; Gruhn, Nadine E; Lichtenberger, Dennis L; Enemark, John H

2003-04-01

Gas-phase photoelectron spectroscopy and density functional theory have been used to investigate the interactions between the sulfur pi-orbitals of arene dithiolates and high-valent transition metals as minimum molecular models of the active site features of pyranopterin MoW enzymes. The compounds (Tp*)MoO(bdt) (compound 1), Cp(2)Mo(bdt) (compound 2), and Cp(2)Ti(bdt) (compound 3) [where Tp* is hydrotris(3,5-dimethyl-1-pyrazolyl)borate, bdt is 1,2-benzenedithiolate, and Cp is eta(5)- cyclopentadienyl] provide access to three different electronic configurations of the metal, formally d(1), d(2), and d(0), respectively. The gas-phase photoelectron spectra show that ionizations from occupied metal and sulfur based valence orbitals are more clearly observed in compounds 2 and 3 than in compound 1. The observed ionization energies and characters compare very well with those calculated by density functional theory. A "dithiolate-folding-effect" involving an interaction of the metal in-plane and sulfur-pi orbitals is proposed to be a factor in the electron transfer reactions that regenerate the active sites of molybdenum and tungsten enzymes.

Substituted Caffeic and Ferulic Acid Phenethyl Esters: Synthesis, Leukotrienes Biosynthesis Inhibition, and Cytotoxic Activity.

PubMed

Morin, Pier; St-Coeur, Patrick-Denis; Doiron, Jérémie A; Cormier, Marc; Poitras, Julie J; Surette, Marc E; Touaibia, Mohamed

2017-07-06

Glioblastoma multiforme (GBM) is an aggressive brain tumor that correlates with short patient survival and for which therapeutic options are limited. Polyphenolic compounds, including caffeic acid phenethyl ester (CAPE, 1a ), have been investigated for their anticancer properties in several types of cancer. To further explore these properties in brain cancer cells, a series of caffeic and ferulic acid esters bearing additional oxygens moieties (OH or OCH₃) were designed and synthesized. (CAPE, 1a ), but not ferulic acid phenethyl ester (FAPE, 1b ), displayed substantial cytotoxicity against two glioma cell lines. Some but not all selected compounds derived from both (CAPE, 1a ) and (FAPE, 1b ) also displayed cytotoxicity. All CAPE-derived compounds were able to significantly inhibit 5-lipoxygenase (5-LO), however FAPE-derived compounds were largely ineffective 5-LO inhibitors. Molecular docking revealed new hydrogen bonds and π-π interactions between the enzyme and some of the investigated compounds. Overall, this work highlights the relevance of exploring polyphenolic compounds in cancer models and provides additional leads in the development of novel therapeutic strategies in gliomas.

Identification of marine neuroactive molecules in behaviour-based screens in the larval zebrafish.

PubMed

Long, Si-Mei; Liang, Feng-Yin; Wu, Qi; Lu, Xi-Lin; Yao, Xiao-Li; Li, Shi-Chang; Li, Jing; Su, Huanxing; Pang, Ji-Yan; Pei, Zhong

2014-05-30

High-throughput behavior-based screen in zebrafish is a powerful approach for the discovery of novel neuroactive small molecules for treatment of nervous system diseases such as epilepsy. To identify neuroactive small molecules, we first screened 36 compounds (1-36) derived from marine natural products xyloketals and marine isoprenyl phenyl ether obtained from the mangrove fungus. Compound 1 demonstrated the most potent inhibition on the locomotor activity in larval zebrafish. Compounds 37-42 were further synthesized and their potential anti-epilepsy action was then examined in a PTZ-induced epilepsy model in zebrafish. Compound 1 and compounds 39, 40 and 41 could significantly attenuate PTZ-induced locomotor hyperactivity and elevation of c-fos mRNA in larval zebrafish. Compound 40 showed the most potent inhibitory action against PTZ-induced hyperactivity. The structure-activity analysis showed that the OH group at 12-position played a critical role and the substituents at the 13-position were well tolerated in the inhibitory activity of xyloketal derivatives. Thus, these derivatives may provide some novel drug candidates for the treatment of epilepsy.

In Silico Investigation of Traditional Chinese Medicine Compounds to Inhibit Human Histone Deacetylase 2 for Patients with Alzheimer's Disease

PubMed Central

Hung, Tzu-Chieh; Lee, Wen-Yuan; Chen, Kuen-Bao; Chan, Yueh-Chiu; Lee, Cheng-Chun

2014-01-01

Human histone deacetylase 2 (HDAC2) has been identified as being associated with Alzheimer's disease (AD), a neuropathic degenerative disease. In this study, we screen the world's largest Traditional Chinese Medicine (TCM) database for natural compounds that may be useful as lead compounds in the search for inhibitors of HDAC2 function. The technique of molecular docking was employed to select the ten top TCM candidates. We used three prediction models, multiple linear regression (MLR), support vector machine (SVM), and the Bayes network toolbox (BNT), to predict the bioactivity of the TCM candidates. Molecular dynamics simulation provides the protein-ligand interactions of compounds. The bioactivity predictions of pIC50 values suggest that the TCM candidatesm, (−)-Bontl ferulate, monomethylcurcumin, and ningposides C, have a greater effect on HDAC2 inhibition. The structure variation caused by the hydrogen bonds and hydrophobic interactions between protein-ligand interactions indicates that these compounds have an inhibitory effect on the protein. PMID:25045700

Alternative Nucleophilic Substrates for the Endonuclease Activities of Human Immunodeficiency Virus Type 1 Integrase

PubMed Central

Ealy, Julie B.; Sudol, Malgorzata; Krzeminski, Jacek; Amin, Shantu; Katzman, Michael

2012-01-01

Retroviral integrase can use water or some small alcohols as the attacking nucleophile to nick DNA. To characterize the range of compounds that human immunodeficiency virus type 1 integrase can accommodate for its endonuclease activities, we tested 45 potential electron donors (having varied size and number or spacing of nucleophilic groups) as substrates during site-specific nicking at viral DNA ends and during nonspecific nicking reactions. We found that integrase used 22 of the 45 compounds to nick DNA, but not all active compounds were used for both activities. In particular, 13 compounds were used for site-specific and nonspecific nicking, 5 only for site-specific nicking, and 4 only for nonspecific nicking; 23 other compounds were not used for either activity. Thus, integrase can accommodate a large number of nucleophilic substrates but has selective requirements for its different activities, underscoring its dynamic properties and providing new information for modeling and understanding integrase. PMID:22910593

Adjuvant effects and antiserum action potentiation by a (herbal) compound 2-hydroxy-4-methoxy benzoic acid isolated from the root extract of the Indian medicinal plant 'sarsaparilla' (Hemidesmus indicus R. Br.).

PubMed

Alam, M I; Gomes, A

1998-10-01

The adjuvant effect and antiserum potentiation of a compound 2-hydroxy-4-methoxy benzoic acid were explored in the present investigation. This compound, isolated and purified from the Indian medicinal plant Hemidesmus indicus R. Br, possessed antisnake venom activity. Rabbits immunized with Vipera russellii venom in the presence and absence of the compound along with Freund's complete adjuvant, produced a precipitating band in immunogel diffusion and immunogel electrophoresis. The venom neutralizing capacity of this antiserum showed positive adjuvant effects as evident by the higher neutralization capacity (lethal and hemorrhage) when compared with the antiserum raised with venom alone. The pure compound potentiated the lethal action neutralization of venom by commercial equine polyvalent snake venom antiserum in experimental models. These observations raised the possibility of the use of chemical antagonists (from herbs) against snake bite, which may provide a better protection in presence of antiserum, especially in the rural parts of India.

ToxAlerts: a Web server of structural alerts for toxic chemicals and compounds with potential adverse reactions.

PubMed

Sushko, Iurii; Salmina, Elena; Potemkin, Vladimir A; Poda, Gennadiy; Tetko, Igor V

2012-08-27

The article presents a Web-based platform for collecting and storing toxicological structural alerts from literature and for virtual screening of chemical libraries to flag potentially toxic chemicals and compounds that can cause adverse side effects. An alert is uniquely identified by a SMARTS template, a toxicological endpoint, and a publication where the alert was described. Additionally, the system allows storing complementary information such as name, comments, and mechanism of action, as well as other data. Most importantly, the platform can be easily used for fast virtual screening of large chemical datasets, focused libraries, or newly designed compounds against the toxicological alerts, providing a detailed profile of the chemicals grouped by structural alerts and endpoints. Such a facility can be used for decision making regarding whether a compound should be tested experimentally, validated with available QSAR models, or eliminated from consideration altogether. The alert-based screening can also be helpful for an easier interpretation of more complex QSAR models. The system is publicly accessible and tightly integrated with the Online Chemical Modeling Environment (OCHEM, http://ochem.eu). The system is open and expandable: any registered OCHEM user can introduce new alerts, browse, edit alerts introduced by other users, and virtually screen his/her data sets against all or selected alerts. The user sets being passed through the structural alerts can be used at OCHEM for other typical tasks: exporting in a wide variety of formats, development of QSAR models, additional filtering by other criteria, etc. The database already contains almost 600 structural alerts for such endpoints as mutagenicity, carcinogenicity, skin sensitization, compounds that undergo metabolic activation, and compounds that form reactive metabolites and, thus, can cause adverse reactions. The ToxAlerts platform is accessible on the Web at http://ochem.eu/alerts, and it is constantly growing.

ToxAlerts: A Web Server of Structural Alerts for Toxic Chemicals and Compounds with Potential Adverse Reactions

PubMed Central

2012-01-01

The article presents a Web-based platform for collecting and storing toxicological structural alerts from literature and for virtual screening of chemical libraries to flag potentially toxic chemicals and compounds that can cause adverse side effects. An alert is uniquely identified by a SMARTS template, a toxicological endpoint, and a publication where the alert was described. Additionally, the system allows storing complementary information such as name, comments, and mechanism of action, as well as other data. Most importantly, the platform can be easily used for fast virtual screening of large chemical datasets, focused libraries, or newly designed compounds against the toxicological alerts, providing a detailed profile of the chemicals grouped by structural alerts and endpoints. Such a facility can be used for decision making regarding whether a compound should be tested experimentally, validated with available QSAR models, or eliminated from consideration altogether. The alert-based screening can also be helpful for an easier interpretation of more complex QSAR models. The system is publicly accessible and tightly integrated with the Online Chemical Modeling Environment (OCHEM, http://ochem.eu). The system is open and expandable: any registered OCHEM user can introduce new alerts, browse, edit alerts introduced by other users, and virtually screen his/her data sets against all or selected alerts. The user sets being passed through the structural alerts can be used at OCHEM for other typical tasks: exporting in a wide variety of formats, development of QSAR models, additional filtering by other criteria, etc. The database already contains almost 600 structural alerts for such endpoints as mutagenicity, carcinogenicity, skin sensitization, compounds that undergo metabolic activation, and compounds that form reactive metabolites and, thus, can cause adverse reactions. The ToxAlerts platform is accessible on the Web at http://ochem.eu/alerts, and it is constantly growing. PMID:22876798

Pathway Profiling and Tissue Modeling Using ToxCast HTS Data

EPA Science Inventory

High-throughput screening (HTS) and high-content screening (HCS) assays are providing data-rich studies to probe and profile the direct cellular effects of thousands of chemical compounds in commerce or potentially entering the environment. In vitro profiling may compare unknown ...

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.

Use of response surface methodology to evaluate the effect of metal ions (Ca2+, Ni2+, Mn2+, Cu2+) on production of antifungal compounds by Paenibacillus polymyxa.

PubMed

Raza, Waseem; Hongsheng, Wu; Qirong, Shen

2010-03-01

The effects of four metal ions (Ca(2+), Ni(2+), Mn(2+) and Cu(2+)) were evaluated on growth and production of antifungal compounds by Paenibacillus polymyxa SQR-21 and a quadratic predictive model was developed using response surface methodology (RSM). The results revealed, Mn(2+) and Ni(2+) showed most positive synergistic interactive affect on production of antifungal compounds followed by the positive interactive synergistic affect of Cu(2+) and Ni(2+) and then Mn(2+) and Cu(2+). While the interactive effect of Ca(2+) with all other three metals inhibited the production of antifungal compounds. The Mn(2+) (P=0.0384), Ni(2+) (P=0.0004) and Cu(2+) (P=0.0117) significantly affected the production of antifungal compounds while the effect of Ca(2+) (P=0.1851) was less significant. The maximum growth (OD(600)=1.55) was obtained at 500 (0), 125 (0), 100 (-2) and 37.5 (0) microM levels and the maximum size of inhibition zone (31 mm) was measured at 400 (-1), 150 (1), 400 (1) and 25 microM (-1) levels of Ca(2+), Mn(2+), Ni(2+) and Cu(2+), respectively. The RSM model provided an easy and effective way to determine the interactive effect of metal ions on production of antifungal compounds by P. polymyxa SQR-21 so that optimum media recipes can be developed to produce maximum amounts of antifungal compounds under laboratory and commercial fermentation conditions. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Extended evaluation on the ES-D3 cell differentiation assay combined with the BeWo transport model, to predict relative developmental toxicity of triazole compounds.

PubMed

Li, Hequn; Flick, Burkhard; Rietjens, Ivonne M C M; Louisse, Jochem; Schneider, Steffen; van Ravenzwaay, Bennard

2016-05-01

The mouse embryonic stem D3 (ES-D3) cell differentiation assay is based on the morphometric measurement of cardiomyocyte differentiation and is a promising tool to detect developmental toxicity of compounds. The BeWo transport model, consisting of BeWo b30 cells grown on transwell inserts and mimicking the placental barrier, is useful to determine relative placental transport velocities of compounds. We have previously demonstrated the usefulness of the ES-D3 cell differentiation assay in combination with the in vitro BeWo transport model to predict the relative in vivo developmental toxicity potencies of a set of reference azole compounds. To further evaluate this combined in vitro toxicokinetic and toxicodynamic approach, we combined ES-D3 cell differentiation data of six novel triazoles with relative transport rates obtained from the BeWo model and compared the obtained ranking to the developmental toxicity ranking as derived from in vivo data. The data show that the combined in vitro approach provided a correct prediction for in vivo developmental toxicity, whereas the ES-D3 cell differentiation assay as stand-alone did not. In conclusion, we have validated the combined in vitro approach for developmental toxicity, which we have previously developed with a set of reference azoles, for a set of six novel triazoles. We suggest that this combined model, which takes both toxicodynamic and toxicokinetic aspects into account, should be further validated for other chemical classes of developmental toxicants.

New cytotoxic benzosuberene analogs. Synthesis, molecular modeling and biological evaluation.

PubMed

Chen, Zecheng; Maderna, Andreas; Sukuru, Sai Chetan K; Wagenaar, Melissa; O'Donnell, Christopher J; Lam, My-Hanh; Musto, Sylvia; Loganzo, Frank

2013-12-15

In this Letter we describe the synthesis and biological evaluation of new benzosuberene analogs with structural modifications on the B-ring. The focus was initially to probe the chemical space around the B-ring C-8 position. This position was readily available for derivatization chemistry using our recently developed new synthesis for this compound class. Furthermore, we describe two new B-ring analogs, one containing a diene and the other a cyclic ether group. Both new analogs show excellent potencies in tumor cell proliferation assays. In addition, we describe molecular modeling studies that provide a binding rationale for reference compound 8 in the colchicine binding site using the known colchicine crystal structure. We also examine whether the cell based potency data obtained with selected new analogs are supported by modeling results. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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

The Effect of Golden Pothos in Reducing the Level of Volatile Organic Compounds in a Simulated Spacecraft Cabin

NASA Technical Reports Server (NTRS)

Ursprung, Matthew; Amiri, Azita; Kayatin, Matthew; Perry, Jay

2016-01-01

The impact of Golden Pothos on indoor air quality was studied against a simulated spacecraft trace contaminant load model, consistent with the International Space Station (ISS), containing volatile organic compounds (VOCs) and formaldehyde. Previous research provides inconclusive results on the efficacy of plant VOC removal which this projects seeks to rectify through a better experimental design. This work develops a passive system for removing common VOC's from spacecraft and household indoor air and decreasing the necessity for active cabin trace contaminant removal systems.

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.

Influence of the exchange and correlation functional on the structure of amorphous InSb and In3SbTe2 compounds

NASA Astrophysics Data System (ADS)

Gabardi, Silvia; Caravati, Sebastiano; Los, Jan H.; Kühne, Thomas D.; Bernasconi, Marco

2016-05-01

We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In3SbTe2 compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtained with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge2Sb2Te5 phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.

Influence of the exchange and correlation functional on the structure of amorphous InSb and In3SbTe2 compounds.

PubMed

Gabardi, Silvia; Caravati, Sebastiano; Los, Jan H; Kühne, Thomas D; Bernasconi, Marco

2016-05-28

We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In3SbTe2 compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtained with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge2Sb2Te5 phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.

Spatial arrangement of organic compounds on a model mineral surface: implications for soil organic matter stabilization.

PubMed

Petridis, Loukas; Ambaye, Haile; Jagadamma, Sindhu; Kilbey, S Michael; Lokitz, Bradley S; Lauter, Valeria; Mayes, Melanie A

2014-01-01

The complexity of the mineral-organic carbon interface may influence the extent of stabilization of organic carbon compounds in soils, which is important for global climate futures. The nanoscale structure of a model interface was examined here by depositing films of organic carbon compounds of contrasting chemical character, hydrophilic glucose and amphiphilic stearic acid, onto a soil mineral analogue (Al2O3). Neutron reflectometry, a technique which provides depth-sensitive insight into the organization of the thin films, indicates that glucose molecules reside in a layer between Al2O3 and stearic acid, a result that was verified by water contact angle measurements. Molecular dynamics simulations reveal the thermodynamic driving force behind glucose partitioning on the mineral interface: The entropic penalty of confining the less mobile glucose on the mineral surface is lower than for stearic acid. The fundamental information obtained here helps rationalize how complex arrangements of organic carbon on soil mineral surfaces may arise.

Combination of virtual screening protocol by in silico towards the discovery of novel 4-hydroxyphenylpyruvate dioxygenase inhibitors

NASA Astrophysics Data System (ADS)

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2018-02-01

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) is a potent new bleaching herbicide target. Therefore, in silico structure-based virtual screening was performed in order to speed up the identification of promising HPPD inhibitors. In this study, an integrated virtual screening protocol by combining 3D-pharmacophore model, molecular docking and molecular dynamics (MD) simulation was established to find novel HPPD inhibitors from four commercial databases. 3D-pharmacophore Hypo1 model was applied to efficiently narrow potential hits. The hit compounds were subsequently submitted to molecular docking studies, showing four compounds as potent inhibitor with the mechanism of the Fe(II) coordination and interaction with Phe360, Phe403 and Phe398. MD result demonstrated that nonpolar term of compound 3881 made great contributions to binding affinities. It showed an IC50 being 2.49 µM against AtHPPD in vitro. The results provided useful information for developing novel HPPD inhibitors, leading to further understanding of the interaction mechanism of HPPD inhibitors.

High performance addition-type thermoplastics (ATTs) - Evidence for the formation of a Diels-Alder adduct in the reaction of an acetylene-terminated material and a bismaleimide

NASA Technical Reports Server (NTRS)

Pater, R. H.; Soucek, M. D.; Chang, A. C.; Partos, R. D.

1991-01-01

Recently, the concept and demonstration of a new versatile synthetic reaction for making a large number of high-performance addition-type thermoplastics (ATTs) were reported. The synthesis shows promise for providing polymers having an attractive combination of easy processability, good toughness, respectable high temperature mechanical performance, and excellent thermo-oxidative stability. The new chemistry involves the reaction of an acetylene-terminated material with a bismaleimide or benzoquinone. In order to clarify the reaction mechanism, model compound studies were undertaken in solutions as well as in the solid state. The reaction products were purified by flash chromatography and characterized by conventional analytical techniques including NMR, FT-IR, UV-visible, mass spectroscopy, and high pressure liquid chromatography. The results are presented of the model compound studies which strongly support the formation of a Diels-Alder adduct in the reaction of an acetylene-terminated compound and a bismaleimide or benzoquinone.

Modeling and Deorphanization of Orphan GPCRs.

PubMed

Diaz, Constantino; Angelloz-Nicoud, Patricia; Pihan, Emilie

2018-01-01

Despite tremendous efforts, approximately 120 GPCRs remain orphan. Their physiological functions and their potential roles in diseases are poorly understood. Orphan GPCRs are extremely important because they may provide novel therapeutic targets for unmet medical needs. As a complement to experimental approaches, molecular modeling and virtual screening are efficient techniques to discover synthetic surrogate ligands which can help to elucidate the role of oGPCRs. Constitutively activated mutants and recently published active structures of GPCRs provide stimulating opportunities for building active molecular models for oGPCRs and identifying activators using virtual screening of compound libraries. We describe the molecular modeling and virtual screening process we have applied in the discovery of surrogate ligands, and provide examples for CCKA, a simulated oGPCR, and for two oGPCRs, GPR52 and GPR34.

Criteria and air-toxic emissions from in-use automobiles in the National Low-Emission Vehicle program.

PubMed

Baldauf, Rich W; Gabele, Pete; Crews, William; Snow, Richard; Cook, J Rich

2005-09-01

The U.S. Environmental Protection Agency (EPA) implemented a program to identify tailpipe emissions of criteria and air-toxic contaminants from in-use, light-duty low-emission vehicles (LEVs). EPA recruited 25 LEVs in 2002 and measured emissions on a chassis dynamometer using the cold-start urban dynamometer driving schedule of the Federal Test Procedure. The emissions measured included regulated pollutants, particulate matter, speciated hydrocarbon compounds, and carbonyl compounds. The results provided a comparison of emissions from real-world LEVs with emission standards for criteria and air-toxic compounds. Emission measurements indicated that a portion of the in-use fleet tested exceeded standards for the criteria gases. Real-time regulated and speciated hydrocarbon measurements demonstrated that the majority of emissions occurred during the initial phases of the cold-start portion of the urban dynamometer driving schedule. Overall, the study provided updated emission factor data for real-world, in-use operation of LEVs for improved emissions modeling and mobile source inventory development.

Novel Carbonyl Analogues of Tamoxifen: Design, Synthesis, and Biological Evaluation

NASA Astrophysics Data System (ADS)

Kasiotis, Konstantinos M.; Lambrinidis, George; Fokialakis, Nikolas; Tzanetou, Evangelia N.; Mikros, Emmanuel; Haroutounian, Serkos A.

2017-09-01

Aim of this work was to provide tamoxifen analogues with enhanced estrogen receptor binding affinity. Hence, several derivatives were prepared using an efficient triarylethylenes synthetic protocol. The novel compounds bioactivity was evaluated through the determination of their receptor binding affinity and their agonist/antagonist activity against breast cancer tissue using a MCF-7 cell-based assay. Phenyl esters 6a,b and 8a,b exhibited binding affinity to both ERα and ERβ higher than 4-hydroxytamoxifen while compounds 13 and 14 have shown cellular antiestrogenic activity similar to 4-hydroxytamoxifen and the known estrogen receptor inhibitor ICI182,780. Theoretical calculations and molecular modelling were applied to investigate, support and explain the biological profile of the new compounds. The relevant data indicated an agreement between calculations and demonstrated biological activity allowing to extract useful structure-activity relationships. Results herein underline that modifications of tamoxifen structure still provide molecules with substantial activity, as portrayed in the inhibition of MCF-7 cells proliferation.

Development of pharmacophore models for small molecules targeting RNA: Application to the RNA repeat expansion in myotonic dystrophy type 1.

PubMed

Angelbello, Alicia J; González, Àlex L; Rzuczek, Suzanne G; Disney, Matthew D

2016-12-01

RNA is an important drug target, but current approaches to identify bioactive small molecules have been engineered primarily for protein targets. Moreover, the identification of small molecules that bind a specific RNA target with sufficient potency remains a challenge. Computer-aided drug design (CADD) and, in particular, ligand-based drug design provide a myriad of tools to identify rapidly new chemical entities for modulating a target based on previous knowledge of active compounds without relying on a ligand complex. Herein we describe pharmacophore virtual screening based on previously reported active molecules that target the toxic RNA that causes myotonic dystrophy type 1 (DM1). DM1-associated defects are caused by sequestration of muscleblind-like 1 protein (MBNL1), an alternative splicing regulator, by expanded CUG repeats (r(CUG) exp ). Several small molecules have been found to disrupt the MBNL1-r(CUG) exp complex, ameliorating DM1 defects. Our pharmacophore model identified a number of potential lead compounds from which we selected 11 compounds to evaluate. Of the 11 compounds, several improved DM1 defects both in vitro and in cells. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dermal uptake and percutaneous penetration of ten flame retardants in a human skin ex vivo model.

PubMed

Frederiksen, Marie; Vorkamp, Katrin; Jensen, Niels Martin; Sørensen, Jens Ahm; Knudsen, Lisbeth E; Sørensen, Lars S; Webster, Thomas F; Nielsen, Jesper B

2016-11-01

The dermal uptake and percutaneous penetration of ten organic flame retardants was measured using an ex vivo human skin model. The studied compounds were DBDPE, BTBPE, TBP-DBPE, EH-TBB, BEH-TEBP, α, β and γ-HBCDD as well as syn- and anti-DDC-CO. Little or none of the applied flame retardants was recovered in either type of the receptor fluids used (physiological and worst-case). However, significant fractions were recovered in the skin depot, particularly in the upper skin layers. The primary effect of the worst-case receptor fluid was deeper penetration into the skin. The recovered mass was used to calculate lower- and upper-bound permeability coefficients kp. Despite large structural variation between the studied compounds, a clear, significant decreasing trend of kp was observed with increasing log Kow. The results indicate that the dermis may provide a significant barrier for these highly lipophilic compounds. However, based on our results, dermal uptake should be considered in exposure assessments, though it may proceed in a time-lagged manner compared to less hydrophobic compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

CLEPS 1.0: A new protocol for cloud aqueous phase oxidation of VOC mechanisms

NASA Astrophysics Data System (ADS)

Mouchel-Vallon, Camille; Deguillaume, Laurent; Monod, Anne; Perroux, Hélène; Rose, Clémence; Ghigo, Giovanni; Long, Yoann; Leriche, Maud; Aumont, Bernard; Patryl, Luc; Armand, Patrick; Chaumerliac, Nadine

2017-03-01

A new detailed aqueous phase mechanism named the Cloud Explicit Physico-chemical Scheme (CLEPS 1.0) is proposed to describe the oxidation of water soluble organic compounds resulting from isoprene oxidation. It is based on structure activity relationships (SARs) which provide global rate constants together with branching ratios for HOṡ abstraction and addition on atmospheric organic compounds. The GROMHE SAR allows the evaluation of Henry's law constants for undocumented organic compounds. This new aqueous phase mechanism is coupled with the MCM v3.3.1 gas phase mechanism through a mass transfer scheme between gas phase and aqueous phase. The resulting multiphase mechanism has then been implemented in a model based on the Dynamically Simple Model for Atmospheric Chemical Complexity (DSMACC) using the Kinetic PreProcessor (KPP) that can serve to analyze data from cloud chamber experiments and field campaigns. The simulation of permanent cloud under low-NOx conditions describes the formation of oxidized monoacids and diacids in the aqueous phase as well as a significant influence on the gas phase chemistry and composition and shows that the aqueous phase reactivity leads to an efficient fragmentation and functionalization of organic compounds.

The therapeutic potential of the cannabinoids in neuroprotection.

PubMed

Grundy, Robert I

2002-10-01

After thousands of years of interest the last few decades have seen a huge increase in our knowledge of the cannabinoids and their mode of action. Their potential as medical therapeutics has long been known. However, very real concerns over their safety and efficacy have lead to caution and suspicion when applying the legislature of modern medicine to these compounds. The ability of this diverse family of compounds to modulate neurotransmission and act as anti-inflammatory and antioxidative agents has prompted researchers to investigate their potential as neuroprotective agents. Indeed, various cannabinoids rescue dying neurones in experimental forms of acute neuronal injury, such as cerebral ischaemia and traumatic brain injury. Cannabinoids also provide symptomatic relief in experimental models of chronic neurodegenerative diseases, such as multiple sclerosis and Huntington's disease. This preclinical evidence has provided the impetus for the launch of a number of clinical trials in various conditions of neurodegeneration and neuronal injury using compounds derived from the cannabis plant. Our understanding of cannabinoid neurobiology, however, must improve if we are to effectively exploit this system and take advantage of the numerous characteristics that make this group of compounds potential neuroprotective agents.

Lidar sprectroscopy instrument (LISSI): An infrastructure facility for chemical aerosol profiling at the University of Hertfordshire

NASA Astrophysics Data System (ADS)

Tesche, Matthias; Tatarov, Boyan; Noh, Youngmin; Müller, Detlef

2018-04-01

The lidar development at the University of Hertfordshire explores the feasibility of using Raman backscattering for chemical aerosol profiling. This paper provides an overview of the new facility. A high-power Nd:YAG/OPO setup is used to excite Raman backscattering at a wide range of wavelengths. The receiver combines a spectrometer with a 32-channel detector or an ICCD camera to resolve Raman signals of various chemical compounds. The new facility will open new avenues for chemical profiling of aerosol pollution from measurements of Raman scattering by selected chemical compounds, provide data that allow to close the gap between optical and microphysical aerosol profiling with lidar and enables connecting lidar measurements to parameters used in atmospheric modelling.

Improving compound-protein interaction prediction by building up highly credible negative samples.

PubMed

Liu, Hui; Sun, Jianjiang; Guan, Jihong; Zheng, Jie; Zhou, Shuigeng

2015-06-15

Computational prediction of compound-protein interactions (CPIs) is of great importance for drug design and development, as genome-scale experimental validation of CPIs is not only time-consuming but also prohibitively expensive. With the availability of an increasing number of validated interactions, the performance of computational prediction approaches is severely impended by the lack of reliable negative CPI samples. A systematic method of screening reliable negative sample becomes critical to improving the performance of in silico prediction methods. This article aims at building up a set of highly credible negative samples of CPIs via an in silico screening method. As most existing computational models assume that similar compounds are likely to interact with similar target proteins and achieve remarkable performance, it is rational to identify potential negative samples based on the converse negative proposition that the proteins dissimilar to every known/predicted target of a compound are not much likely to be targeted by the compound and vice versa. We integrated various resources, including chemical structures, chemical expression profiles and side effects of compounds, amino acid sequences, protein-protein interaction network and functional annotations of proteins, into a systematic screening framework. We first tested the screened negative samples on six classical classifiers, and all these classifiers achieved remarkably higher performance on our negative samples than on randomly generated negative samples for both human and Caenorhabditis elegans. We then verified the negative samples on three existing prediction models, including bipartite local model, Gaussian kernel profile and Bayesian matrix factorization, and found that the performances of these models are also significantly improved on the screened negative samples. Moreover, we validated the screened negative samples on a drug bioactivity dataset. Finally, we derived two sets of new interactions by training an support vector machine classifier on the positive interactions annotated in DrugBank and our screened negative interactions. The screened negative samples and the predicted interactions provide the research community with a useful resource for identifying new drug targets and a helpful supplement to the current curated compound-protein databases. Supplementary files are available at: http://admis.fudan.edu.cn/negative-cpi/. © The Author 2015. Published by Oxford University Press.

Future climate risk from compound events

NASA Astrophysics Data System (ADS)

Zscheischler, Jakob; Westra, Seth; van den Hurk, Bart J. J. M.; Seneviratne, Sonia I.; Ward, Philip J.; Pitman, Andy; AghaKouchak, Amir; Bresch, David N.; Leonard, Michael; Wahl, Thomas; Zhang, Xuebin

2018-06-01

Floods, wildfires, heatwaves and droughts often result from a combination of interacting physical processes across multiple spatial and temporal scales. The combination of processes (climate drivers and hazards) leading to a significant impact is referred to as a `compound event'. Traditional risk assessment methods typically only consider one driver and/or hazard at a time, potentially leading to underestimation of risk, as the processes that cause extreme events often interact and are spatially and/or temporally dependent. Here we show how a better understanding of compound events may improve projections of potential high-impact events, and can provide a bridge between climate scientists, engineers, social scientists, impact modellers and decision-makers, who need to work closely together to understand these complex events.

Chemical signatures and new drug targets for gametocytocidal drug development

NASA Astrophysics Data System (ADS)

Sun, Wei; Tanaka, Takeshi Q.; Magle, Crystal T.; Huang, Wenwei; Southall, Noel; Huang, Ruili; Dehdashti, Seameen J.; McKew, John C.; Williamson, Kim C.; Zheng, Wei

2014-01-01

Control of parasite transmission is critical for the eradication of malaria. However, most antimalarial drugs are not active against P. falciparum gametocytes, responsible for the spread of malaria. Consequently, patients can remain infectious for weeks after the clearance of asexual parasites and clinical symptoms. Here we report the identification of 27 potent gametocytocidal compounds (IC50 < 1 μM) from screening 5,215 known drugs and compounds. All these compounds were active against three strains of gametocytes with different drug sensitivities and geographical origins, 3D7, HB3 and Dd2. Cheminformatic analysis revealed chemical signatures for P. falciparum sexual and asexual stages indicative of druggability and suggesting potential targets. Torin 2, a top lead compound (IC50 = 8 nM against gametocytes in vitro), completely blocked oocyst formation in a mouse model of transmission. These results provide critical new leads and potential targets to expand the repertoire of malaria transmission-blocking reagents.

QSAR Classification Model for Antibacterial Compounds and Its Use in Virtual Screening

DTIC Science & Technology

2012-09-26

test set molecules that were not used to train the models . This allowed us to more accurately estimate the prediction power of the models . As...pathogens and deposited in PubChem Bioassays. Ultimately, the main purpose of this model is to make predictions , based on known antibacterial and non...the model built form the remaining compounds is used to predict the left out compound. Once all the compounds pass through this cycle of prediction , a

Deciphering the underlying mechanisms of Diesun Miaofang in traumatic injury from a systems pharmacology perspective

PubMed Central

ZHENG, CHUN-SONG; FU, CHANG-LONG; PAN, CAI-BIN; BAO, HONG-JUAN; CHEN, XING-QIANG; YE, HONG-ZHI; YE, JIN-XIA; WU, GUANG-WEN; LI, XI-HAI; XU, HUI-FENG; XU, XIAO-JIE; LIU, XIAN-XIANG

2015-01-01

Diesun Miaofang (DSMF) is a traditional herbal formula, which has been reported to activate blood, remove stasis, promote qi circulation and relieve pain. DSMF holds a great promise for the treatment of traumatic injury in an integrative and holistic manner. However, its underlying mechanisms remain to be elucidated. In the present study, a systems pharmacology model, which integrated cluster ligands, human intestinal absorption and aqueous solution prediction, chemical space mapping, molecular docking and network pharmacology techniques were used. The compounds from DSMF were diverse in the clusters and chemical space. The majority of the compounds exhibited drug-like properties. A total of 59 compounds were identified to interact with 16 potential targets. In the herb-compound-target network, the majority of compounds acted on only one target; however, a small number of compounds acted on a large number of targets, up to a maximum of 12. The comparison of key topological properties in compound-target networks associated with the above efficacy intuitively demonstrated that potential active compounds possessed diverse functions. These results successfully explained the polypharmcological mechanism underlying the efficiency of DSMF for the treatment of traumatic injury as well as provided insight into potential novel therapeutic strategies for traumatic injury from herbal medicine. PMID:25891262

Compound K Attenuates the Development of Atherosclerosis in ApoE−/− Mice via LXRα Activation

PubMed Central

Zhou, Li; Zheng, Yu; Li, Zhuoying; Bao, Lingxia; Dou, Yin; Tang, Yuan; Zhang, Jianxiang; Zhou, Jianzhi; Liu, Ya; Jia, Yi; Li, Xiaohui

2016-01-01

Background: Atherosclerosis is a fundamental pathological process responded to some serious cardiovascular events. Although the cholesterol-lowering drugs are widely prescribed for atherosclerosis therapy, it is still the leading cause of death in the developed world. Here we measured the effects of compound K in atherosclerosis formation and investigated the probably mechanisms of the anti-antherosclerosis roles of compound K. Methods: We treated the atherosclerotic model animals (apoE−/− mice on western diet) with compound K and measured the size of atherosclerotic lesions, inflammatory cytokine levels and serum lipid profile. Peritoneal macrophages were collected in vitro for the foam cell and inflammasome experiments. Results: Our results show that treatment with compound K dose-dependently attenuates the formation of atherosclerotic plaques by 55% through activation of reverse cholesterol transport pathway, reduction of systemic inflammatory cytokines and inhibition of local inflammasome activity. Compound K increases the cholesterol efflux of macrophage-derived foam cells, and reduces the inflammasome activity in cholesterol crystal stimulated macrophages. The activation of LXRα may contribute to the athero-protective effects of compound K. Conclusion: These observations provide evidence for an athero-protective effect of compound K via LXRα activation, and support its further evaluation as a potential effective modulator for the prevention and treatment of atherosclerosis. PMID:27399689

Correlation between structure, retention, property, and activity of biologically relevant 1,7-bis(aminoalkyl)diazachrysene derivatives.

PubMed

Šegan, Sandra; Trifković, Jelena; Verbić, Tatjana; Opsenica, Dejan; Zlatović, Mario; Burnett, James; Šolaja, Bogdan; Milojković-Opsenica, Dušanka

2013-01-01

The physicochemical properties, retention parameters (R(M)(0)), partition coefficients (logP(OW)), and pK(a) values for a series of thirteen 1,7-bis(aminoalkyl) diazachrysene (1,7-DAAC) derivatives were determined in order to reveal the characteristics responsible for their biological behavior. The investigated compounds inhibit three unrelated pathogens (the Botulinum neurotoxin serotype A light chain (BoNT/A LC), Plasmodium falciparum malaria, and Ebola filovirus) via three different mechanisms of action. To determine the most influential factors governing the retention and activities of the investigated diazachrysenes, R(M)(0), logP(OW), and biological activity values were correlated with 2D and 3D molecular descriptors, using a partial least squares regression. The resulting quantitative structure-retention (property) relationships indicate the importance of descriptors related to the hydrophobicity of the molecules (e.g., predicted partition coefficients and hydrophobic surface area). Quantitative structure-activity relationship models for describing biological activity against the BoNT/A LC and malarial strains also include overall compound polarity, electron density distribution, and proton donor/acceptor potential. Furthermore, models for Ebola filovirus inhibition are presented qualitatively to provide insights into parameters that may contribute to the compounds' antiviral activities. Overall, the models form the basis for selecting structural features that significantly affect the compound's absorption, distribution, metabolism, excretion, and toxicity profiles. Copyright © 2012 Elsevier B.V. All rights reserved.

Structure⁻Activity Relationship and Molecular Docking of Natural Product Library Reveal Chrysin as a Novel Dipeptidyl Peptidase-4 (DPP-4) Inhibitor: An Integrated In Silico and In Vitro Study.

PubMed

Kalhotra, Poonam; Chittepu, Veera C S R; Osorio-Revilla, Guillermo; Gallardo-Velázquez, Tzayhri

2018-06-06

Numerous studies indicate that diets with a variety of fruits and vegetables decrease the incidence of severe diseases, like diabetes, obesity, and cancer. Diets contain a variety of bioactive compounds, and their features, like diverge scaffolds, and structural complexity make them the most successful source of potential leads or hits in the process of drug discovery and drug development. Recently, novel serine protease dipeptidyl peptidase-4 (DPP-4) inhibitors played a role in the management of diabetes, obesity, and cancer. This study describes the development of field template, field-based qualitative structure⁻activity relationship (SAR) model demonstrating DPP-4 inhibitors of natural origin, and the same model is used to screen virtually focused food database composed of polyphenols as potential DPP-4 inhibitors. Compounds’ similarity to field template, and novelty score “high and very high”, were used as primary criteria to identify novel DPP-4 inhibitors. Molecular docking simulations were performed on the resulting natural compounds using FlexX algorithm. Finally, one natural compound, chrysin, was chosen to be evaluated experimentally to demonstrate the applicability of constructed SAR model. This study provides the molecular insights necessary in the discovery of new leads as DPP-4 inhibitors, to improve the potency of existing DPP-4 natural inhibitors.

Insights into structure and activity of natural compound inhibitors of pneumolysin

PubMed Central

Li, Hongen; Zhao, Xiaoran; Deng, Xuming; Wang, Jianfeng; Song, Meng; Niu, Xiaodi; Peng, Liping

2017-01-01

Pneumolysin is the one of the major virulence factor of the bacterium Streptococcus pneumoniae. In previous report, it is shown that β-sitosterol, a natural compound without antimicrobial activity, is a potent antagonist of pneumolysin. Here, two new pneumolysin natural compound inhibitors, with differential activity, were discovered via haemolysis assay. To explore the key factor of the conformation for the inhibition activity, the interactions between five natural compound inhibitors with differential activity and pneumolysin were reported using molecular modelling, the potential of mean force profiles. Interestingly, it is found that incorporation of the single bond (C22-C23-C24-C25) to replace the double bond (hydrocarbon sidechain) improved the anti-haemolytic activity. In view of the molecular modelling, binding of the five inhibitors to the conserved loop region (Val372, Leu460, and Tyr461) of the cholesterol binding sites led to stable complex systems, which was consistent with the result of β-sitosterol. Owing to the single bond (C22-C23-C24-C25), campesterol and brassicasterol could form strong interactions with Val372 and show higher anti-haemolytic activity, which indicated that the single bond (C22-C23-C24-C25) in inhibitors was required for the anti-haemolytic activity. Overall, the current molecular modelling work provides a starting point for the development of rational design and higher activity pneumolysin inhibitors. PMID:28165051

Homology modeling and virtual screening to discover potent inhibitors targeting the imidazole glycerophosphate dehydratase protein in Staphylococcus xylosus

NASA Astrophysics Data System (ADS)

Chen, Xing-Ru; Wang, Xiao-Ting; Hao, Mei-Qi; Zhou, Yong-Hui; Cui, Wen-Qiang; Xing, Xiao-Xu; Xu, Chang-Geng; Bai, Jing-Wen; Li, Yan-Hua

2017-11-01

The imidazole glycerophosphate dehydratase (IGPD) protein is a therapeutic target for herbicide discovery. It is also regarded as a possible target in Staphylococcus xylosus (S. xylosus) for solving mastitis in the dairy cow. The 3D structure of IGPD protein is essential for discovering novel inhibitors during high-throughput virtual screening. However, to date, the 3D structure of IGPD protein of S. xylosus has not been solved. In this study, a series of computational techniques including homology modeling, Ramachandran Plots, and Verify 3D were performed in order to construct an appropriate 3D model of IGPD protein of S. xylosus. Nine hits were identified from 2500 compounds by docking studies. Then, these 9 compounds were first tested in vitro in S. xylosus biofilm formation using crystal violet staining. One of the potential compounds, baicalin was shown to significantly inhibit S. xylosus biofilm formation. Finally, the baicalin was further evaluated, which showed better inhibition of biofilm formation capability in S. xylosus by scanning electron microscopy. Hence, we have predicted the structure of IGPD protein of S. xylosus using computational techniques. We further discovered the IGPD protein was targeted by baicalin compound which inhibited the biofilm formation in S. xylosus. Our findings here would provide implications for the further development of novel IGPD inhibitors for the treatment of dairy mastitis.

Homology Modeling and Virtual Screening to Discover Potent Inhibitors Targeting the Imidazole Glycerophosphate Dehydratase Protein in Staphylococcus xylosus.

PubMed

Chen, Xing-Ru; Wang, Xiao-Ting; Hao, Mei-Qi; Zhou, Yong-Hui; Cui, Wen-Qiang; Xing, Xiao-Xu; Xu, Chang-Geng; Bai, Jing-Wen; Li, Yan-Hua

2017-01-01

The imidazole glycerophosphate dehydratase (IGPD) protein is a therapeutic target for herbicide discovery. It is also regarded as a possible target in Staphylococcus xylosus ( S. xylosus ) for solving mastitis in the dairy cow. The 3D structure of IGPD protein is essential for discovering novel inhibitors during high-throughput virtual screening. However, to date, the 3D structure of IGPD protein of S. xylosus has not been solved. In this study, a series of computational techniques including homology modeling, Ramachandran Plots, and Verify 3D were performed in order to construct an appropriate 3D model of IGPD protein of S. xylosus . Nine hits were identified from 2,500 compounds by docking studies. Then, these nine compounds were first tested in vitro in S. xylosus biofilm formation using crystal violet staining. One of the potential compounds, baicalin was shown to significantly inhibit S. xylosus biofilm formation. Finally, the baicalin was further evaluated, which showed better inhibition of biofilm formation capability in S. xylosus by scanning electron microscopy. Hence, we have predicted the structure of IGPD protein of S. xylosus using computational techniques. We further discovered the IGPD protein was targeted by baicalin compound which inhibited the biofilm formation in S. xylosus . Our findings here would provide implications for the further development of novel IGPD inhibitors for the treatment of dairy mastitis.

High-throughput screening, predictive modeling and computational embryology

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to profile thousands of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition to projects worldwide,...

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

Ghosh, Arun K.; Takayama, Jun; Rao, Kalapala Venkateswar

The design, synthesis, X-ray crystal structure, molecular modeling, and biological evaluation of a series of new generation SARS-CoV PLpro inhibitors are described. A new lead compound 3 (6577871) was identified via high-throughput screening of a diverse chemical library. Subsequently, we carried out lead optimization and structure-activity studies to provide a series of improved inhibitors that show potent PLpro inhibition and antiviral activity against SARS-CoV infected Vero E6 cells. Interestingly, the (S)-Me inhibitor 15h (enzyme IC{sub 50} = 0.56 {mu}M; antiviral EC{sub 50} = 9.1 {mu}M) and the corresponding (R)-Me 15g (IC{sub 50} = 0.32 {mu}M; antiviral EC{sub 50} = 9.1more » {mu}M) are the most potent compounds in this series, with nearly equivalent enzymatic inhibition and antiviral activity. A protein-ligand X-ray structure of 15g-bound SARS-CoV PLpro and a corresponding model of 15h docked to PLpro provide intriguing molecular insight into the ligand-binding site interactions.« less

Pharmacokinetic and pharmacodynamic modeling to determine the dose of ST-246 to protect against smallpox in humans.

PubMed

Leeds, Janet M; Fenneteau, Frederique; Gosselin, Nathalie H; Mouksassi, Mohamad-Samer; Kassir, Nastya; Marier, J F; Chen, Yali; Grosenbach, Doug; Frimm, Annie E; Honeychurch, Kady M; Chinsangaram, Jarasvech; Tyavanagimatt, Shanthakumar R; Hruby, Dennis E; Jordan, Robert

2013-03-01

Although smallpox has been eradicated, the United States government considers it a "material threat" and has funded the discovery and development of potential therapeutic compounds. As reported here, the human efficacious dose for one of these compounds, ST-246, was determined using efficacy studies in nonhuman primates (NHPs), together with pharmacokinetic and pharmacodynamic analysis that predicted the appropriate dose and exposure levels to provide therapeutic benefit in humans. The efficacy analysis combined the data from studies conducted at three separate facilities that evaluated treatment following infection with a closely related virus, monkeypox virus (MPXV), in a total of 96 NHPs. The effect of infection on ST-246 pharmacokinetics in NHPs was applied to humans using population pharmacokinetic models. Exposure at the selected human dose of 600 mg is more than 4-fold higher than the lowest efficacious dose in NHPs and is predicted to provide protection to more than 95% of the population.

Evaluation of the Percutaneous Absorption of Ketamine HCl, Gabapentin, Clonidine HCl, and Baclofen, in Compounded Transdermal Pain Formulations, Using the Franz Finite Dose Model.

PubMed

Bassani, August S; Banov, Daniel

2016-02-01

This study evaluates the ability of four commonly used analgesics (ketamine HCl, gabapentin, clonidine HCl, and baclofen), when incorporated into two transdermal compounding bases, Lipoderm and Lipoderm ActiveMax, to penetrate human cadaver trunk skin in vitro, using the Franz finite dose model. In vitro experimental study. Methods. Ketamine HCl 5% w/w, gabapentin 10% w/w, clonidine HCl 0.2% w/w, and baclofen 2% w/w were compounded into two transdermal bases, Lipoderm and Lipoderm ActiveMax. Each compounded drug formulation was tested on skin from three different donors and three replicate skin sections per donor. The Franz finite dose model was used in this study to evaluate the percutaneous absorption and distribution of drugs within each formulation. Rapid penetration to peak flux was detected for gabapentin and baclofen at approximately 1 hour after application. Clonidine HCl also had a rapid penetration to peak flux occurring approximately 1 hour after application and had a secondary peak at approximately 40 hours. Ketamine HCl exhibited higher overall absorption rates than the other drugs, and peaked at 6–10 hours. Similar patterns of drug distribution within the skin were also observed using both transdermal bases. This study suggests that the combination of these 4 analgesic drugs can be successfully delivered transdermally, using either Lipoderm or Lipoderm ActiveMax. Compounded transdermal drug preparations may then provide physicians with an alternative to traditional oral pain management regimens that can be personalized to the specific patient with the potential for enhanced pain control.

Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

PubMed

Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

2017-07-01

Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Conducting field studies for testing pesticide leaching models

USGS Publications Warehouse

Smith, Charles N.; Parrish, Rudolph S.; Brown, David S.

1990-01-01

A variety of predictive models are being applied to evaluate the transport and transformation of pesticides in the environment. These include well known models such as the Pesticide Root Zone Model (PRZM), the Risk of Unsaturated-Saturated Transport and Transformation Interactions for Chemical Concentrations Model (RUSTIC) and the Groundwater Loading Effects of Agricultural Management Systems Model (GLEAMS). The potentially large impacts of using these models as tools for developing pesticide management strategies and regulatory decisions necessitates development of sound model validation protocols. This paper offers guidance on many of the theoretical and practical problems encountered in the design and implementation of field-scale model validation studies. Recommendations are provided for site selection and characterization, test compound selection, data needs, measurement techniques, statistical design considerations and sampling techniques. A strategy is provided for quantitatively testing models using field measurements.

Osmotic Compounds Enhance Antibiotic Efficacy against Acinetobacter baumannii Biofilm Communities

PubMed Central

Falghoush, Azeza; Beyenal, Haluk; Besser, Thomas E.; Omsland, Anders

2017-01-01

ABSTRACT Biofilm-associated infections are a clinical challenge, in part because a hydrated matrix protects the bacterial community from antibiotics. Herein, we evaluated how different osmotic compounds (maltodextrin, sucrose, and polyethylene glycol [PEG]) enhance antibiotic efficacy against Acinetobacter baumannii biofilm communities. Established (24-h) test tube biofilms (strain ATCC 17978) were treated with osmotic compounds in the presence or absence of 10× the MIC of different antibiotics (50 μg/ml tobramycin, 20 μg/ml ciprofloxacin, 300 μg/ml chloramphenicol, 30 μg/ml nalidixic acid, or 100 μg/ml erythromycin). Combining antibiotics with hypertonic concentrations of the osmotic compounds for 24 h reduced the number of biofilm bacteria by 5 to 7 log (P < 0.05). Increasing concentrations of osmotic compounds improved the effect, but there was a trade-off with increasing solution viscosity, whereby low-molecular-mass compounds (sucrose, 400-Da PEG) worked better than higher-mass compounds (maltodextrin, 3,350-Da PEG). Ten other A. baumannii strains were similarly treated with 400-Da PEG and tobramycin, resulting in a mean 2.7-log reduction in recoverable bacteria compared with tobramycin treatment alone. Multivariate regression models with data from different osmotic compounds and nine antibiotics demonstrated that the benefit from combining hypertonic treatments with antibiotics is a function of antibiotic mass and lipophilicity (r2 > 0.82; P < 0.002), and the relationship was generalizable for biofilms formed by A. baumannii and Escherichia coli K-12. Augmenting topical antibiotic therapies with a low-mass hypertonic treatment may enhance the efficacy of antibiotics against wound biofilms, particularly when using low-mass hydrophilic antibiotics. IMPORTANCE Biofilms form a barrier that protects bacteria from environmental insults, including exposure to antibiotics. We demonstrated that multiple osmotic compounds can enhance antibiotic efficacy against Acinetobacter baumannii biofilm communities, but viscosity is a limiting factor, and the most effective compounds have lower molecular mass. The synergism between osmotic compounds and antibiotics is also dependent on the hydrophobicity and mass of the antibiotics. The statistical models presented herein provide a basis for predicting the optimal combination of osmotic compounds and antibiotics against surface biofilms communities. PMID:28733283

Emissions databases for polycyclic aromatic compounds in the Canadian Athabasca oil sands region - development using current knowledge and evaluation with passive sampling and air dispersion modelling data

NASA Astrophysics Data System (ADS)

Qiu, Xin; Cheng, Irene; Yang, Fuquan; Horb, Erin; Zhang, Leiming; Harner, Tom

2018-03-01

Two speciated and spatially resolved emissions databases for polycyclic aromatic compounds (PACs) in the Athabasca oil sands region (AOSR) were developed. The first database was derived from volatile organic compound (VOC) emissions data provided by the Cumulative Environmental Management Association (CEMA) and the second database was derived from additional data collected within the Joint Canada-Alberta Oil Sands Monitoring (JOSM) program. CALPUFF modelling results for atmospheric polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, and dibenzothiophenes (DBTs), obtained using each of the emissions databases, are presented and compared with measurements from a passive air monitoring network. The JOSM-derived emissions resulted in better model-measurement agreement in the total PAH concentrations and for most PAH species concentrations compared to results using CEMA-derived emissions. At local sites near oil sands mines, the percent error of the model compared to observations decreased from 30 % using the CEMA-derived emissions to 17 % using the JOSM-derived emissions. The improvement at local sites was likely attributed to the inclusion of updated tailings pond emissions estimated from JOSM activities. In either the CEMA-derived or JOSM-derived emissions scenario, the model underestimated PAH concentrations by a factor of 3 at remote locations. Potential reasons for the disagreement include forest fire emissions, re-emissions of previously deposited PAHs, and long-range transport not considered in the model. Alkylated PAH and DBT concentrations were also significantly underestimated. The CALPUFF model is expected to predict higher concentrations because of the limited chemistry and deposition modelling. Thus the model underestimation of PACs is likely due to gaps in the emissions database for these compounds and uncertainties in the methodology for estimating the emissions. Future work is required that focuses on improving the PAC emissions estimation and speciation methodologies and reducing the uncertainties in VOC emissions which are subsequently used in PAC emissions estimation.

Computational prediction of formulation strategies for beyond-rule-of-5 compounds.

PubMed

Bergström, Christel A S; Charman, William N; Porter, Christopher J H

2016-06-01

The physicochemical properties of some contemporary drug candidates are moving towards higher molecular weight, and coincidentally also higher lipophilicity in the quest for biological selectivity and specificity. These physicochemical properties move the compounds towards beyond rule-of-5 (B-r-o-5) chemical space and often result in lower water solubility. For such B-r-o-5 compounds non-traditional delivery strategies (i.e. those other than conventional tablet and capsule formulations) typically are required to achieve adequate exposure after oral administration. In this review, we present the current status of computational tools for prediction of intestinal drug absorption, models for prediction of the most suitable formulation strategies for B-r-o-5 compounds and models to obtain an enhanced understanding of the interplay between drug, formulation and physiological environment. In silico models are able to identify the likely molecular basis for low solubility in physiologically relevant fluids such as gastric and intestinal fluids. With this baseline information, a formulation scientist can, at an early stage, evaluate different orally administered, enabling formulation strategies. Recent computational models have emerged that predict glass-forming ability and crystallisation tendency and therefore the potential utility of amorphous solid dispersion formulations. Further, computational models of loading capacity in lipids, and therefore the potential for formulation as a lipid-based formulation, are now available. Whilst such tools are useful for rapid identification of suitable formulation strategies, they do not reveal drug localisation and molecular interaction patterns between drug and excipients. For the latter, Molecular Dynamics simulations provide an insight into the interplay between drug, formulation and intestinal fluid. These different computational approaches are reviewed. Additionally, we analyse the molecular requirements of different targets, since these can provide an early signal that enabling formulation strategies will be required. Based on the analysis we conclude that computational biopharmaceutical profiling can be used to identify where non-conventional gateways, such as prediction of 'formulate-ability' during lead optimisation and early development stages, are important and may ultimately increase the number of orally tractable contemporary targets. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Optimization and application of atmospheric pressure chemical and photoionization hydrogen-deuterium exchange mass spectrometry for speciation of oxygen-containing compounds.

PubMed

Acter, Thamina; Kim, Donghwi; Ahmed, Arif; Jin, Jang Mi; Yim, Un Hyuk; Shim, Won Joon; Kim, Young Hwan; Kim, Sunghwan

2016-05-01

This paper presents a detailed investigation of the feasibility of optimized positive and negative atmospheric pressure chemical ionization (APCI) mass spectrometry (MS) and atmospheric pressure photoionization (APPI) MS coupled to hydrogen-deuterium exchange (HDX) for structural assignment of diverse oxygen-containing compounds. The important parameters for optimization of HDX MS were characterized. The optimized techniques employed in the positive and negative modes showed satisfactory HDX product ions for the model compounds when dichloromethane and toluene were employed as a co-solvent in APCI- and APPI-HDX, respectively. The evaluation of the mass spectra obtained from 38 oxygen-containing compounds demonstrated that the extent of the HDX of the ions was structure-dependent. The combination of information provided by different ionization techniques could be used for better speciation of oxygen-containing compounds. For example, (+) APPI-HDX is sensitive to compounds with alcohol, ketone, or aldehyde substituents, while (-) APPI-HDX is sensitive to compounds with carboxylic functional groups. In addition, the compounds with alcohol can be distinguished from other compounds by the presence of exchanged peaks. The combined information was applied to study chemical compositions of degraded oils. The HDX pattern, double bond equivalent (DBE) distribution, and previously reported oxidation products were combined to predict structures of the compounds produced from oxidation of oil. Overall, this study shows that APCI- and APPI-HDX MS are useful experimental techniques that can be applied for the structural analysis of oxygen-containing compounds.

Evaluation of Biogenic and Fire Emissions in a Global Chemistry Model with NOMADSS, DC3 and SEAC4RS observations

NASA Astrophysics Data System (ADS)

Emmons, L. K.; Wiedinmyer, C.; Park, M.; Kaser, L.; Apel, E. C.; Guenther, A. B.

2014-12-01

Numerous measurements of compounds produced by biogenic and fire emissions were made during several recent field campaigns in the southeast United States, providing a unique data set for emissions and chemical model evaluation. The NCAR Community Atmosphere Model with Chemistry (CAM-chem) is coupled to the Community Land Model (CLM), which includes the biogenic emissions model MEGAN-v2.1, allowing for online calculation of emissions from vegetation for 150 compounds. Simulations of CAM-chem for summers 2012 and 2013 are evaluated with the aircraft and ground-based observations from DC3, NOMADSS and SEAC4RS. Comparison of directly emitted biogenic species, such as isoprene, terpenes, methanol and acetone, are used to evaluate the MEGAN emissions. Evaluation of oxidation products, including methyl vinyl ketone (MVK), methacrolein, formaldehyde, and other oxygenated VOCs are used to test the model chemistry mechanism. In addition, several biomass burning inventories are used in the model, including FINN, QFED, and FLAMBE, and are compared for their impact on atmospheric composition and ozone production, and evaluated with the aircraft observations.

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

Aromatase inhibitory activity of 1,4-naphthoquinone derivatives and QSAR study

PubMed Central

Prachayasittikul, Veda; Pingaew, Ratchanok; Worachartcheewan, Apilak; Sitthimonchai, Somkid; Nantasenamat, Chanin; Prachayasittikul, Supaluk; Ruchirawat, Somsak; Prachayasittikul, Virapong

2017-01-01

A series of 2-amino(chloro)-3-chloro-1,4-naphthoquinone derivatives (1-11) were investigated for their aromatase inhibitory activities. 1,4-Naphthoquinones 1 and 4 were found to be the most potent compounds affording IC50 values 5.2 times lower than the reference drug, ketoconazole. A quantitative structure-activity relationship (QSAR) model provided good predictive performance (R2CV = 0.9783 and RMSECV = 0.0748) and indicated mass (Mor04m and H8m), electronegativity (Mor08e), van der Waals volume (G1v) and structural information content index (SIC2) descriptors as key descriptors governing the activity. To investigate the effects of structural modifications on aromatase inhibitory activity, the model was employed to predict the activities of an additional set of 39 structurally modified compounds constructed in silico. The prediction suggested that the 2,3-disubstitution of 1,4-naphthoquinone ring with halogen atoms (i.e., Br, I and F) is the most effective modification for potent activity (1a, 1b and 1c). Importantly, compound 1b was predicted to be more potent than its parent compound 1 (11.90-fold) and the reference drug, letrozole (1.03-fold). The study suggests the 1,4-naphthoquinone derivatives as promising compounds to be further developed as a novel class of aromatase inhibitors. PMID:28827987

Free surface profiles in river flows: Can standard energy-based gradually-varied flow computations be pursued?

NASA Astrophysics Data System (ADS)

Cantero, Francisco; Castro-Orgaz, Oscar; Garcia-Marín, Amanda; Ayuso, José Luis; Dey, Subhasish

2015-10-01

Is the energy equation for gradually-varied flow the best approximation for the free surface profile computations in river flows? Determination of flood inundation in rivers and natural waterways is based on the hydraulic computation of flow profiles. This is usually done using energy-based gradually-varied flow models, like HEC-RAS, that adopts a vertical division method for discharge prediction in compound channel sections. However, this discharge prediction method is not so accurate in the context of advancements over the last three decades. This paper firstly presents a study of the impact of discharge prediction on the gradually-varied flow computations by comparing thirteen different methods for compound channels, where both energy and momentum equations are applied. The discharge, velocity distribution coefficients, specific energy, momentum and flow profiles are determined. After the study of gradually-varied flow predictions, a new theory is developed to produce higher-order energy and momentum equations for rapidly-varied flow in compound channels. These generalized equations enable to describe the flow profiles with more generality than the gradually-varied flow computations. As an outcome, results of gradually-varied flow provide realistic conclusions for computations of flow in compound channels, showing that momentum-based models are in general more accurate; whereas the new theory developed for rapidly-varied flow opens a new research direction, so far not investigated in flows through compound channels.

Novel direct factor Xa inhibitory compounds from Tenebrio molitor with anti-platelet aggregation activity.

PubMed

Lee, Wonhwa; Kim, Mi-Ae; Park, InWha; Hwang, Jae Sam; Na, MinKyun; Bae, Jong-Sup

2017-11-01

Tenebrio molitor is an edible insect that has antimicrobial, anticancer, and antihypertensive effects. The aim of this study was to identify the unreported bioactive compounds from T. molitor larvae with inhibitory activities against factor Xa (FXa) and platelet aggregation. Isolated compounds were evaluated for their anti-FXa and anti-platelet aggregation properties by monitoring clotting time, platelet aggregation, FXa activity, and thrombus formation. A diketopiperazine (1, cyclo( L -Pro- L -Tyr)) and a phenylethanoid (2, N-acetyltyramine) were isolated and inhibited the catalytic activity of FXa in a mixed inhibition model and inhibited platelet aggregation induced by adenosine diphosphate (ADP) and U46619. They inhibited ADP- and U46619-induced phosphorylation of myristoylated alanine-rich C kinase substrate (MARCKS) and the expression of P-selectin and PAC-1 in platelets. They also improved the production of nitric oxide and inhibited the oversecretion of endothelin-1 compared to that of the ADP- or U46619-treated group. In an animal model of arterial and pulmonary thrombosis, the isolated compounds showed enhanced antithrombotic effects. They also elicited anticoagulant effects in mice. Compounds 1-2 inhibited ADP-, collagen-, or U46619-induced platelet aggregation and showed similar anti-thrombotic efficacy to rivaroxaban, a positive control. Therefore, 1-2 could serve as candidates and provide scaffolds for the development of new anti-FXa and anti-platelet drugs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Connectionist models of conditioning: A tutorial

PubMed Central

Kehoe, E. James

1989-01-01

Models containing networks of neuron-like units have become increasingly prominent in the study of both cognitive psychology and artificial intelligence. This article describes the basic features of connectionist models and provides an illustrative application to compound-stimulus effects in respondent conditioning. Connectionist models designed specifically for operant conditioning are not yet widely available, but some current learning algorithms for machine learning indicate that such models are feasible. Conversely, designers for machine learning appear to have recognized the value of behavioral principles in producing adaptive behavior in their creations. PMID:16812604

Schinus terebinthifolius Raddi extract and linoleic acid from Passiflora edulis synergistically decrease melanin synthesis in B16 cells and reconstituted epidermis.

PubMed

Jorge, A T S; Arroteia, K F; Santos, I A; Andres, E; Medina, S P H; Ferrari, C R; Lourenço, C B; Biaggio, R M T T; Moreira, P L

2012-10-01

Several treatments for skin whitening are available today, but few of them are completely adequate, especially owing to the carcinogenic potential attributed to classical drugs like hydroquinone, arbutin and kojic acid. To provide an alternative and safer technology for whitening, we developed two botanical compounds originated from Brazilian biodiversity, an extract of Schinus terebinthifolius Raddi and a linoleic acid fraction isolated from Passiflora edulis oil. The whitening effect of these compounds was assessed using biochemical assays and in vitro models including cellular assays and equivalent skin. The results showed that S. terebinthifolius Raddi extract is able to reduce the tyrosinase activity in vitro, and the combination of this extract with linoleic acid is able to decrease the level of melanin produced by B16 cells cultured with melanocyte-stimulating hormone. Furthermore, melanin was also reduced in human reconstituted epidermis (containing melanocytes) treated with the compounds. The combination of the compounds may provide a synergistic positive whitening effect rather than their isolated use. Finally, we demonstrated that the performance of these mixed compounds is comparable to classical molecules used for skin whitening, as kojic acid. This new natural mixture could be considered an alternative therapeutic agent for treating hyperpigmentation and an effective component in whitening cosmetics. © 2012 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations

PubMed Central

Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua

2015-01-01

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q2 (cross-validated correlation coefficient) = 0.557, R2ncv (non-cross-validated correlation coefficient) = 0.740, R2pre (predicted correlation coefficient) = 0.749 and Q2 = 0.598, R2ncv = 0.767, R2pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors. PMID:26307982

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations.

PubMed

Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua

2015-08-25

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q(2) (cross-validated correlation coefficient) = 0.557, R(2)ncv (non-cross-validated correlation coefficient) = 0.740, R(2)pre (predicted correlation coefficient) = 0.749 and Q(2) = 0.598, R(2)ncv = 0.767, R(2)pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors.

Screening a repurposing library for potentiators of antibiotics against Staphylococcus aureus biofilms.

PubMed

Van den Driessche, Freija; Brackman, Gilles; Swimberghe, Rosalie; Rigole, Petra; Coenye, Tom

2017-03-01

Staphylococcus aureus biofilms are involved in a wide range of infections that are extremely difficult to treat with conventional antibiotic therapy. We aimed to identify potentiators of antibiotics against mature biofilms of S. aureus Mu50, a methicillin-resistant and vancomycin-intermediate-resistant strain. Over 700 off-patent drugs from a repurposing library were screened in combination with vancomycin in a microtitre plate (MTP)-based biofilm model system. This led to the identification of 25 hit compounds, including four phenothiazines among which thioridazine was the most potent. Their activity was evaluated in combination with other antibiotics both against planktonic and biofilm-grown S. aureus cells. The most promising combinations were subsequently tested in an in vitro chronic wound biofilm infection model. Although no synergistic activity was observed against planktonic cells, thioridazine potentiated the activity of tobramycin, linezolid and flucloxacillin against S. aureus biofilm cells. However, this effect was only observed in a general biofilm model and not in a chronic wound model of biofilm infection. Several drug compounds were identified that potentiated the activity of vancomycin against biofilms formed in a MTP-based biofilm model. A selected hit compound lost its potentiating activity in a model that mimics specific aspects of wound biofilms. This study provides a platform for discovering and evaluating potentiators against bacterial biofilms and highlights the necessity of using relevant in vitro biofilm model systems. Copyright © 2017 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

Thermal Decomposition Mechanisms of Lignin Model Compounds: From Phenol to Vanillin

NASA Astrophysics Data System (ADS)

Scheer, Adam Michael

Lignin is a complex, aromatic polymer abundant in cellulosic biomass (trees, switchgrass etc.). Thermochemical breakdown of lignin for liquid fuel production results in undesirable polycyclic aromatic hydrocarbons that lead to tar and soot byproducts. The fundamental chemistry governing these processes is not well understood. We have studied the unimolecular thermal decomposition mechanisms of aromatic lignin model compounds using a miniature SiC tubular reactor. Products are detected and characterized using time-of-flight mass spectrometry with both single photon (118.2 nm; 10.487 eV) and 1 + 1 resonance-enhanced multiphoton ionization (REMPI) as well as matrix isolation infrared spectroscopy. Gas exiting the heated reactor (300 K--1600 K) is subject to a free expansion after a residence time of approximately 100 micros. The expansion into vacuum rapidly cools the gas mixture and allows the detection of radicals and other highly reactive intermediates. By understanding the unimolecular fragmentation patterns of phenol (C6H5OH), anisole (C6H 5OCH3) and benzaldehyde (C6H5CHO), the more complicated thermocracking processes of the catechols (HO-C 6H4-OH), methoxyphenols (HO-C6H4-OCH 3) and hydroxybenzaldehydes (HO-C6H4-CHO) can be interpreted. These studies have resulted in a predictive model that allows the interpretation of vanillin, a complex phenolic ether containing methoxy, hydroxy and aldehyde functional groups. This model will serve as a guide for the pyrolyses of larger systems including lignin monomers such as coniferyl alcohol. The pyrolysis mechanisms of the dimethoxybenzenes (H3C-C 6H4-OCH3) and syringol, a hydroxydimethoxybenzene have also been studied. These results will aid in the understanding of the thermal fragmentation of sinapyl alcohol, the most complex lignin monomer. In addition to the model compound work, pyrolyisis of biomass has been studied via the pulsed laser ablation of poplar wood. With the REMPI scheme, aromatic lignin decomposition products are directly and selectively detected. A number of these products are the lignin model compounds listed above, providing a direct link between the model compound studies and the pyrolysis of actual biomass.

A Compound Model for the Origin of Earth's Water

NASA Astrophysics Data System (ADS)

Izidoro, A.; de Souza Torres, K.; Winter, O. C.; Haghighipour, N.

2013-04-01

One of the most important subjects of debate in the formation of the solar system is the origin of Earth's water. Comets have long been considered as the most likely source of the delivery of water to Earth. However, elemental and isotopic arguments suggest a very small contribution from these objects. Other sources have also been proposed, among which local adsorption of water vapor onto dust grains in the primordial nebula and delivery through planetesimals and planetary embryos have become more prominent. However, no sole source of water provides a satisfactory explanation for Earth's water as a whole. In view of that, using numerical simulations, we have developed a compound model incorporating both the principal endogenous and exogenous theories, and investigating their implications for terrestrial planet formation and water delivery. Comets are also considered in the final analysis, as it is likely that at least some of Earth's water has cometary origin. We analyze our results comparing two different water distribution models, and complement our study using the D/H ratio, finding possible relative contributions from each source and focusing on planets formed in the habitable zone. We find that the compound model plays an important role by showing greater advantage in the amount and time of water delivery in Earth-like planets.

A COMPOUND MODEL FOR THE ORIGIN OF EARTH'S WATER

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

Izidoro, A.; Winter, O. C.; De Souza Torres, K.

2013-04-10

One of the most important subjects of debate in the formation of the solar system is the origin of Earth's water. Comets have long been considered as the most likely source of the delivery of water to Earth. However, elemental and isotopic arguments suggest a very small contribution from these objects. Other sources have also been proposed, among which local adsorption of water vapor onto dust grains in the primordial nebula and delivery through planetesimals and planetary embryos have become more prominent. However, no sole source of water provides a satisfactory explanation for Earth's water as a whole. In viewmore » of that, using numerical simulations, we have developed a compound model incorporating both the principal endogenous and exogenous theories, and investigating their implications for terrestrial planet formation and water delivery. Comets are also considered in the final analysis, as it is likely that at least some of Earth's water has cometary origin. We analyze our results comparing two different water distribution models, and complement our study using the D/H ratio, finding possible relative contributions from each source and focusing on planets formed in the habitable zone. We find that the compound model plays an important role by showing greater advantage in the amount and time of water delivery in Earth-like planets.« less

Regulation of Satellite Cell Function in Sarcopenia

PubMed Central

Alway, Stephen E.; Myers, Matthew J.; Mohamed, Junaith S.

2014-01-01

The mechanisms contributing to sarcopenia include reduced satellite cell (myogenic stem cell) function that is impacted by the environment (niche) of these cells. Satellite cell function is affected by oxidative stress, which is elevated in aged muscles, and this along with changes in largely unknown systemic factors, likely contribute to the manner in which satellite cells respond to stressors such as exercise, disuse, or rehabilitation in sarcopenic muscles. Nutritional intervention provides one therapeutic strategy to improve the satellite cell niche and systemic factors, with the goal of improving satellite cell function in aging muscles. Although many elderly persons consume various nutraceuticals with the hope of improving health, most of these compounds have not been thoroughly tested, and the impacts that they might have on sarcopenia and satellite cell function are not clear. This review discusses data pertaining to the satellite cell responses and function in aging skeletal muscle, and the impact that three compounds: resveratrol, green tea catechins, and β-Hydroxy-β-methylbutyrate have on regulating satellite cell function and therefore contributing to reducing sarcopenia or improving muscle mass after disuse in aging. The data suggest that these nutraceutical compounds improve satellite cell function during rehabilitative loading in animal models of aging after disuse (i.e., muscle regeneration). While these compounds have not been rigorously tested in humans, the data from animal models of aging provide a strong basis for conducting additional focused work to determine if these or other nutraceuticals can offset the muscle losses, or improve regeneration in sarcopenic muscles of older humans via improving satellite cell function. PMID:25295003

HYDROXYL RADICAL/OZONE RATIOS DURING OZONATION PROCESSES. I. THE RCT CONCEPT

EPA Science Inventory

The ozonation of model systems and several natural waters was examined in bench-scale batch experiments. In addition to measuring the concentration of ozone (03), the rate of depletion of an in situ hydroxyl radical probe compound was monitored, thus providing information on the ...

Pathway Profiling and Tissue Modeling of Developmental Toxicity

EPA Science Inventory

High-throughput and high-content screening (HTS-HCS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition t...

VIRTUAL EMBRYO: SYSTEMS MODELING IN DEVELOPMENTAL TOXICITY - Symposium: SOT 2012

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. Chemical profiling in ToxCast covered 965 drugs-chemicals in over 500 diverse assays testing...

Virtual Embryo: Systems Modeling in Developmental Toxicity

EPA Science Inventory

High-throughput and high-content screening (HTS-HCS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition t...

Electrospray-assisted encapsulation of caffeine in alginate microhydrogels.

PubMed

Nikoo, Alireza Mehregan; Kadkhodaee, Rassoul; Ghorani, Behrouz; Razzaq, Hussam; Tucker, Nick

2018-05-02

One of the major challenges with microencapsulation and delivery of low molecular weight bioactive compounds is their diffusional loss during storage and process conditions as well as under gastric conditions. In an attempt to slow down the release rate of core material, electrospray fabricated calcium alginate microhydrogels were coated with low molecular weight and high molecular weight chitosans. Caffeine as a hydrophilic model compound was used due to its several advantages on human behavior especially increasing consciousness. Mathematical modeling of the caffeine release by fitting the data with Korsmeyer-Peppas model showed that Fick's diffusion law could be the prevalent mechanism of the release. Electrostatic interaction between alginate and chitosan (particularly in the presence of 1% low molecular weight chitosan) provided an effective barrier against caffeine release and significantly reduced swelling of particles compared to control samples. The results of this study demonstrated that calcium alginate microhydrogels coated by chitosan could be used for encapsulation of low molecular compounds. However, more complementary research must be done in this field. In addition, electrospray, by producing monodisperse particles, would be as an alternative method for fabrication of microparticles based on natural polymers. Copyright © 2018. Published by Elsevier B.V.

Production of organic compounds in plasmas: A comparison among electric sparks, laser-induced plasmas and UV light

NASA Technical Reports Server (NTRS)

Scattergood, T. W.; Mckay, C. P.; Borucki, W. J.; Giver, L. P.; Vanghyseghem, H.; Parris, J. E.; Miller, S. L.

1991-01-01

In order to study the production of organic compounds in plasmas (and shocks), various mixtures of N2, CH4, and H2, modeling the atmosphere of Titan, were exposed to discrete sparks, laser-induced plasmas (LIP) and ultraviolet light. The yields of HCN and simple hydrocarbons were measured and compared to those calculated from a simple quenched thermodynamic equilibrium model. The agreement between experiment and theory was fair for HCN and C2H2. However, the yields of C2H6 and other hydrocarbons were much higher than those predicted by the model. Our experiments suggest that photolysis by ultraviolet light from the plasma is an important process in the synthesis. This was confirmed by the photolysis of gas samples exposed to the light, but not to the plasma or shock waves. The results of these experiments demonstrate that, in addition to the well-known efficient synthesis of organic compounds in plasmas, the yields of saturated species, e.g., ethane, may be higher than predicted by theory and that LIP provide a convenient and clean way of simulating planetary lightning and impact plasmas in the laboratory.

Potential of chromatin modifying compounds for the treatment of Alzheimer's disease

PubMed Central

Karagiannis, Tom C.; Ververis, Katherine

2012-01-01

Alzheimer's disease is a very common progressive neurodegenerative disorder affecting the learning and memory centers in the brain. The hallmarks of disease are the accumulation of β-amyloid neuritic plaques and neurofibrillary tangles formed by abnormally phosphorylated tau protein. Alzheimer's disease is currently incurable and there is an intense interest in the development of new potential therapies. Chromatin modifying compounds such as sirtuin modulators and histone deacetylase inhibitors have been evaluated in models of Alzheimer's disease with some promising results. For example, the natural antioxidant and sirtuin 1 activator resveratrol has been shown to have beneficial effects in animal models of disease. Similarly, numerous histone deacetylase inhibitors including Trichostatin A, suberoylanilide hydroxamic acid, valproic acid and phenylbutyrate reduction have shown promising results in models of Alzheimer's disease. These beneficial effects include a reduction of β-amyloid production and stabilization of tau protein. In this review we provide an overview of the histone deacetylase enzymes, with a focus on enzymes that have been identified to have an important role in the pathobiology of Alzheimer's disease. Further, we discuss the potential for pharmacological intervention with chromatin modifying compounds that modulate histone deacetylase enzymes. PMID:22953035

Potential of chromatin modifying compounds for the treatment of Alzheimer's disease.

PubMed

Karagiannis, Tom C; Ververis, Katherine

2012-01-01

Alzheimer's disease is a very common progressive neurodegenerative disorder affecting the learning and memory centers in the brain. The hallmarks of disease are the accumulation of β-amyloid neuritic plaques and neurofibrillary tangles formed by abnormally phosphorylated tau protein. Alzheimer's disease is currently incurable and there is an intense interest in the development of new potential therapies. Chromatin modifying compounds such as sirtuin modulators and histone deacetylase inhibitors have been evaluated in models of Alzheimer's disease with some promising results. For example, the natural antioxidant and sirtuin 1 activator resveratrol has been shown to have beneficial effects in animal models of disease. Similarly, numerous histone deacetylase inhibitors including Trichostatin A, suberoylanilide hydroxamic acid, valproic acid and phenylbutyrate reduction have shown promising results in models of Alzheimer's disease. These beneficial effects include a reduction of β-amyloid production and stabilization of tau protein. In this review we provide an overview of the histone deacetylase enzymes, with a focus on enzymes that have been identified to have an important role in the pathobiology of Alzheimer's disease. Further, we discuss the potential for pharmacological intervention with chromatin modifying compounds that modulate histone deacetylase enzymes.

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.

Using box models to quantify zonal distributions and emissions of halocarbons in the background atmosphere.

NASA Astrophysics Data System (ADS)

Elkins, J. W.; Nance, J. D.; Dutton, G. S.; Montzka, S. A.; Hall, B. D.; Miller, B.; Butler, J. H.; Mondeel, D. J.; Siso, C.; Moore, F. L.; Hintsa, E. J.; Wofsy, S. C.; Rigby, M. L.

2015-12-01

The Halocarbons and other Atmospheric Trace Species (HATS) of NOAA's Global Monitoring Division started measurements of the major chlorofluorocarbons and nitrous oxide in 1977 from flask samples collected at five remote sites around the world. Our program has expanded to over 40 compounds at twelve sites, which includes six in situ instruments and twelve flask sites. The Montreal Protocol for Substances that Deplete the Ozone Layer and its subsequent amendments has helped to decrease the concentrations of many of the ozone depleting compounds in the atmosphere. Our goal is to provide zonal emission estimates for these trace gases from multi-box models and their estimated atmospheric lifetimes in this presentation and make the emission values available on our web site. We plan to use our airborne measurements to calibrate the exchange times between the boxes for 5-box and 12-box models using sulfur hexafluoride where emissions are better understood.

Nanopyroxene Grafting with β-Cyclodextrin Monomer for Wastewater Applications.

PubMed

Nafie, Ghada; Vitale, Gerardo; Carbognani Ortega, Lante; Nassar, Nashaat N

2017-12-06

Emerging nanoparticle technology provides opportunities for environmentally friendly wastewater treatment applications, including those in the large liquid tailings containments in the Alberta oil sands. In this study, we synthesize β-cyclodextrin grafted nanopyroxenes to offer an ecofriendly platform for the selective removal of organic compounds typically present in these types of applications. We carry out computational modeling at the micro level through molecular mechanics and molecular dynamics simulations and laboratory experiments at the macro level to understand the interactions between the synthesized nanomaterials and two-model naphthenic acid molecules (cyclopentanecarboxylic and trans-4-pentylcyclohexanecarboxylic acids) typically existing in tailing ponds. The proof-of-concept computational modeling and experiments demonstrate that monomer grafted nanopyroxene  or nano-AE of the sodium iron-silicate aegirine are found to be promising candidates for the removal of polar organic compounds from wastewater, among other applications. These nano-AE offer new possibilities for treating tailing ponds generated by the oil sands industry.

Advanced Computational Modeling of Vapor Deposition in a High-Pressure Reactor

NASA Technical Reports Server (NTRS)

Cardelino, Beatriz H.; Moore, Craig E.; McCall, Sonya D.; Cardelino, Carlos A.; Dietz, Nikolaus; Bachmann, Klaus

2004-01-01

In search of novel approaches to produce new materials for electro-optic technologies, advances have been achieved in the development of computer models for vapor deposition reactors in space. Numerical simulations are invaluable tools for costly and difficult processes, such as those experiments designed for high pressures and microgravity conditions. Indium nitride is a candidate compound for high-speed laser and photo diodes for optical communication system, as well as for semiconductor lasers operating into the blue and ultraviolet regions. But InN and other nitride compounds exhibit large thermal decomposition at its optimum growth temperature. In addition, epitaxy at lower temperatures and subatmospheric pressures incorporates indium droplets into the InN films. However, surface stabilization data indicate that InN could be grown at 900 K in high nitrogen pressures, and microgravity could provide laminar flow conditions. Numerical models for chemical vapor deposition have been developed, coupling complex chemical kinetics with fluid dynamic properties.

Advanced Computational Modeling of Vapor Deposition in a High-pressure Reactor

NASA Technical Reports Server (NTRS)

Cardelino, Beatriz H.; Moore, Craig E.; McCall, Sonya D.; Cardelino, Carlos A.; Dietz, Nikolaus; Bachmann, Klaus

2004-01-01

In search of novel approaches to produce new materials for electro-optic technologies, advances have been achieved in the development of computer models for vapor deposition reactors in space. Numerical simulations are invaluable tools for costly and difficult processes, such as those experiments designed for high pressures and microgravity conditions. Indium nitride is a candidate compound for high-speed laser and photo diodes for optical communication system, as well as for semiconductor lasers operating into the blue and ultraviolet regions. But InN and other nitride compounds exhibit large thermal decomposition at its optimum growth temperature. In addition, epitaxy at lower temperatures and subatmospheric pressures incorporates indium droplets into the InN films. However, surface stabilization data indicate that InN could be grown at 900 K in high nitrogen pressures, and microgravity could provide laminar flow conditions. Numerical models for chemical vapor deposition have been developed, coupling complex chemical kinetics with fluid dynamic properties.

Orthotopic mouse models for the preclinical and translational study of targeted therapies against metastatic human thyroid carcinoma with BRAFV600E or wild-type BRAF

PubMed Central

Antonello, ZA; Nucera, C

2015-01-01

Molecular signature of advanced and metastatic thyroid carcinoma involves deregulation of multiple fundamental pathways activated in the tumor microenvironment. They include BRAFV600E and AKT that affect tumor initiation, progression and metastasis. Human thyroid cancer orthotopic mouse models are based on human cell lines that generally harbor genetic alterations found in human thyroid cancers. They can reproduce in vivo and in situ (into the thyroid) many features of aggressive and refractory human advanced thyroid carcinomas, including local invasion and metastasis. Humanized orthotopic mouse models seem to be ideal and commonly used for preclinical and translational studies of compounds and therapies not only because they may mimic key aspects of human diseases (e.g. metastasis), but also for their reproducibility. In addition, they might provide the possibility to evaluate systemic effects of treatments. So far, human thyroid cancer in vivo models were mainly used to test single compounds, non selective and selective. Despite the greater antitumor activity and lower toxicity obtained with different selective drugs in respect to non-selective ones, most of them are only able to delay disease progression, which ultimately could restart with similar aggressive behavior. Aggressive thyroid tumors (for example, anaplastic or poorly differentiated thyroid carcinoma) carry several complex genetic alterations that are likely cooperating to promote disease progression and might confer resistance to single-compound approaches. Orthotopic models of human thyroid cancer also hold the potential to be good models for testing novel combinatorial therapies. In this article, we will summarize results on preclinical testing of selective and nonselective single compounds in orthotopic mouse models based on validated human thyroid cancer cell lines harboring the BRAFV600E mutation or with wild-type BRAF. Furthermore, we will discuss the potential use of this model also for combinatorial approaches, which are expected to take place in the upcoming human thyroid cancer basic and clinical research. PMID:24362526

Do Vertical Gradients in Soil Environmental Conditions Regulate Exudation Rates from Peatland Vegetation?

NASA Astrophysics Data System (ADS)

Proctor, C.; He, Y.

2017-12-01

Deposition of carbon belowground via the root exudation pathway is the net of root-borne efflux and influx processes. For select exudates, root have a remarkable ability to actively recapture lost compounds, suggesting that influx mechanisms regulate exudation. However, roots are not the sole sink for root effluxed carbon. Roots compete with solute sorption and microbial uptake, whom are regulated by a unique set of soil environmental conditions. Peatland soil features stark vertical gradients in their physical, chemical, biological, and hydrological properties, which has downstream implications for the relative competitive ability of each actor in root-soil-microbial interactions. This study developed a single root exudate model using the Barber-Cushman approach to examine the radial accumulation of exudates in simulated peatland soil with vertical gradients. The model simulated efflux, influx, solute diffusion, solute mineralization and solid phase sorption mechanisms as depth dependent on bulk density, porosity, tortuosity, buffer power, temperature, and microbial biomass. Deeper peat soil reduced the porosity that permits solute transport, increased tortuosity which lowered the effective diffusion rate, increased solute-solid sorption, and reduced microbial mineralization of effluxed compounds. Slower mineralization rates were partially juxtaposed by increases in sorption, albeit the net removal of effluxed compounds was lower, leading to a larger amount of exudates to remain in the rhizosphere around deeper roots. Increase in the solid phase, and its subsequent constriction of solute migration, lead to a higher accumulation of effluxed compounds on the rhizoplane, up to 1.23x higher than shallow soil. Subsequently, influx mechanisms captured a larger fraction of effluxed compounds (69.06% at -10cm versus 84.8% at -80 cm), reducing net exudation rates from 0.641 to 0.315 nmol cm-1 hr-1 between -10 and -80cm depths. These results suggest that localized environmental conditions around roots can be a considerable influence on root influx and competition for root exudates. The insights provided by this model help provide a better understanding of exudate regulation in peatlands and the quantity and quality of carbon deposited to the methanogen community.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do.

PubMed

Zhao, Linlin; Wang, Wenyi; Sedykh, Alexander; Zhu, Hao

2017-06-30

Numerous chemical data sets have become available for quantitative structure-activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do

PubMed Central

2017-01-01

Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting. PMID:28691113

Predicting the oral uptake efficiency of chemicals in mammals: Combining the hydrophilic and lipophilic range

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

O'Connor, Isabel A., E-mail: i.oconnor@science.ru.nl; Huijbregts, Mark A.J., E-mail: m.huijbregts@science.ru.nl; Ragas, Ad M.J., E-mail: a.ragas@science.ru.nl

Environmental risk assessment requires models for estimating the bioaccumulation of untested compounds. So far, bioaccumulation models have focused on lipophilic compounds, and only a few have included hydrophilic compounds. Our aim was to extend an existing bioaccumulation model to estimate the oral uptake efficiency of pollutants in mammals for compounds over a wide K{sub ow} range with an emphasis on hydrophilic compounds, i.e. compounds in the lower K{sub ow} range. Usually, most models use octanol as a single surrogate for the membrane and thus neglect the bilayer structure of the membrane. However, compounds with polar groups can have different affinitiesmore » for the different membrane regions. Therefore, an existing bioaccumulation model was extended by dividing the diffusion resistance through the membrane into an outer and inner membrane resistance, where the solvents octanol and heptane were used as surrogates for these membrane regions, respectively. The model was calibrated with uptake efficiencies of environmental pollutants measured in different mammals during feeding studies combined with human oral uptake efficiencies of pharmaceuticals. The new model estimated the uptake efficiency of neutral (RMSE = 14.6) and dissociating (RMSE = 19.5) compounds with logK{sub ow} ranging from − 10 to + 8. The inclusion of the K{sub hw} improved uptake estimation for 33% of the hydrophilic compounds (logK{sub ow} < 0) (r{sup 2} = 0.51, RMSE = 22.8) compared with the model based on K{sub ow} only (r{sup 2} = 0.05, RMSE = 34.9), while hydrophobic compounds (logK{sub ow} > 0) were estimated equally by both model versions with RMSE = 15.2 (K{sub ow} and K{sub hw}) and RMSE = 15.7 (K{sub ow} only). The model can be used to estimate the oral uptake efficiency for both hydrophilic and hydrophobic compounds. -- Highlights: ► A mechanistic model was developed to estimate oral uptake efficiency. ► Model covers wide logK{sub ow} range (- 10 to + 8) and several mammalian species. ► K{sub ow} and the heptane water partition coefficient K{sub hw} were combined. ► K{sub ow} and K{sub hw} reflect the inner and the outer membrane diffusion resistance. ► Combining K{sub ow} and K{sub hw} improved uptake estimation for hydrophilic compounds.« less

New p-methylsulfonamido phenylethylamine analogues as class III antiarrhythmic agents: design, synthesis, biological assay, and 3D-QSAR analysis.

PubMed

Liu, Hong; Ji, Ming; Luo, Xiaomin; Shen, Jianhua; Huang, Xiaoqin; Hua, Weiyi; Jiang, Hualiang; Chen, Kaixian

2002-07-04

Class III antiarrhythmic agents selectively delay the effective refractory period (ERP) and increase the transmembrane action potential duration (APD). Using dofetilide (2) as a template of class III antiarrhythmic agents, we designed and synthesized 16 methylsulfonamido phenylethylamine analogues (4a-d and 5a-l). Pharmacological assay indicated that all of these compounds showed activity for increasing the ERP in isolated animal atrium; among them, the effective concentration of compound 4a is 1.6 x 10(-8) mol/L in increasing ERP by 10 ms, slightly less potent than that of 2, 1.1 x 10(-8) mol/L. Compound 4a also produced a slightly lower change in ERP at 10(-5) M, DeltaERP% = 17.5% (DeltaERP% = 24.0% for dofetilide). On the basis of this bioassay result, these 16 compounds together with dofetilide were investigated by the three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques of comparative molecular field analysis (CoMFA), comparative molecular similarity index analysis (CoMSIA), and the hologram QSAR (HQSAR). The 3D-QSAR models were tested with another 11 compounds (4e-h and 5m-s) that we synthesized later. Results revealed that the CoMFA, CoMSIA, and HQSAR predicted activities for the 11 newly synthesized compounds that have a good correlation with their experimental value, r(2) = 0.943, 0.891, and 0.809 for the three QSAR models, respectively. This indicates that the 3D-QSAR models proved a good predictive ability and could describe the steric, electrostatic, and hydrophobic requirements for recognition forces of the receptor site. On the basis of these results, we designed and synthesized another eight new analogues of methanesulfonamido phenylethyamine (6a-h) according to the clues provided by the 3D-QSAR analyses. Pharmacological assay indicated that the effective concentrations of delaying the ERP by 10 ms of these newly designed compounds correlated well with the 3D-QSAR predicted values. It is remarkable that the percent change of delaying ERP at 10(-5) M compound 6c is much higher than that of dofetilide; the effective concentration of compound 6c is 5.0 x 10(-8)mol/L in increasing the ERP by 10 ms, which is slightly lower than that of 2. The results showed that the 3D-QSAR models are reliable and can be extended to design new antiarrhythmic agents.

Anti-inflammatory Effects of Fungal Metabolites in Mouse Intestine as Revealed by In vitro Models

PubMed Central

Schreiber, Dominik; Marx, Lisa; Felix, Silke; Clasohm, Jasmin; Weyland, Maximilian; Schäfer, Maximilian; Klotz, Markus; Lilischkis, Rainer; Erkel, Gerhard; Schäfer, Karl-Herbert

2017-01-01

Inflammatory bowel diseases (IBD), which include Crohn's disease and ulcerative colitis, are chronic inflammatory disorders that can affect the whole gastrointestinal tract or the colonic mucosal layer. Current therapies aiming to suppress the exaggerated immune response in IBD largely rely on compounds with non-satisfying effects or side-effects. Therefore, new therapeutical options are needed. In the present study, we investigated the anti-inflammatory effects of the fungal metabolites, galiellalactone, and dehydrocurvularin in both an in vitro intestinal inflammation model, as well as in isolated myenteric plexus and enterocyte cells. Administration of a pro-inflammatory cytokine mix through the mesenteric artery of intestinal segments caused an up-regulation of inflammatory marker genes. Treatment of the murine intestinal segments with galiellalactone or dehydrocurvularin by application through the mesenteric artery significantly prevented the expression of pro-inflammatory marker genes on the mRNA and the protein level. Comparable to the results in the perfused intestine model, treatment of primary enteric nervous system (ENS) cells from the murine intestine with the fungal compounds reduced expression of cytokines such as IL-6, TNF-α, IL-1β, and inflammatory enzymes such as COX-2 and iNOS on mRNA and protein levels. Similar anti-inflammatory effects of the fungal metabolites were observed in the human colorectal adenocarcinoma cell line DLD-1 after stimulation with IFN-γ (10 ng/ml), TNF-α (10 ng/ml), and IL-1β (5 ng/ml). Our results show that the mesenterially perfused intestine model provides a reliable tool for the screening of new therapeutics with limited amounts of test compounds. Furthermore, we could characterize the anti-inflammatory effects of two novel active compounds, galiellalactone, and dehydrocurvularin which are interesting candidates for studies with chronic animal models of IBD. PMID:28824460

Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

PubMed

Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

2014-08-01

Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

A Comprehensive Study on Pyrolysis Mechanism of Substituted β-O-4 Type Lignin Dimers.

PubMed

Jiang, Xiaoyan; Lu, Qiang; Hu, Bin; Liu, Ji; Dong, Changqing; Yang, Yongping

2017-11-09

In order to understand the pyrolysis mechanism of β- O -4 type lignin dimers, a pyrolysis model is proposed which considers the effects of functional groups (hydroxyl, hydroxymethyl and methoxyl) on the alkyl side chain and aromatic ring. Furthermore, five specific β- O -4 type lignin dimer model compounds are selected to investigate their integrated pyrolysis mechanism by density functional theory (DFT) methods, to further understand and verify the proposed pyrolysis model. The results indicate that a total of 11 pyrolysis mechanisms, including both concerted mechanisms and homolytic mechanisms, might occur for the initial pyrolysis of the β- O -4 type lignin dimers. Concerted mechanisms are predominant as compared with homolytic mechanisms throughout unimolecular decomposition pathways. The competitiveness of the eleven pyrolysis mechanisms are revealed via different model compounds, and the proposed pyrolysis model is ranked in full consideration of functional groups effects. The proposed pyrolysis model can provide a theoretical basis to predict the reaction pathways and products during the pyrolysis process of β- O -4 type lignin dimers.

A Comprehensive Study on Pyrolysis Mechanism of Substituted β-O-4 Type Lignin Dimers

PubMed Central

Jiang, Xiaoyan; Lu, Qiang; Hu, Bin; Liu, Ji; Dong, Changqing; Yang, Yongping

2017-01-01

In order to understand the pyrolysis mechanism of β-O-4 type lignin dimers, a pyrolysis model is proposed which considers the effects of functional groups (hydroxyl, hydroxymethyl and methoxyl) on the alkyl side chain and aromatic ring. Furthermore, five specific β-O-4 type lignin dimer model compounds are selected to investigate their integrated pyrolysis mechanism by density functional theory (DFT) methods, to further understand and verify the proposed pyrolysis model. The results indicate that a total of 11 pyrolysis mechanisms, including both concerted mechanisms and homolytic mechanisms, might occur for the initial pyrolysis of the β-O-4 type lignin dimers. Concerted mechanisms are predominant as compared with homolytic mechanisms throughout unimolecular decomposition pathways. The competitiveness of the eleven pyrolysis mechanisms are revealed via different model compounds, and the proposed pyrolysis model is ranked in full consideration of functional groups effects. The proposed pyrolysis model can provide a theoretical basis to predict the reaction pathways and products during the pyrolysis process of β-O-4 type lignin dimers. PMID:29120350

Reconfigurable and responsive droplet-based compound micro-lenses.

PubMed

Nagelberg, Sara; Zarzar, Lauren D; Nicolas, Natalie; Subramanian, Kaushikaram; Kalow, Julia A; Sresht, Vishnu; Blankschtein, Daniel; Barbastathis, George; Kreysing, Moritz; Swager, Timothy M; Kolle, Mathias

2017-03-07

Micro-scale optical components play a crucial role in imaging and display technology, biosensing, beam shaping, optical switching, wavefront-analysis, and device miniaturization. Herein, we demonstrate liquid compound micro-lenses with dynamically tunable focal lengths. We employ bi-phase emulsion droplets fabricated from immiscible hydrocarbon and fluorocarbon liquids to form responsive micro-lenses that can be reconfigured to focus or scatter light, form real or virtual images, and display variable focal lengths. Experimental demonstrations of dynamic refractive control are complemented by theoretical analysis and wave-optical modelling. Additionally, we provide evidence of the micro-lenses' functionality for two potential applications-integral micro-scale imaging devices and light field display technology-thereby demonstrating both the fundamental characteristics and the promising opportunities for fluid-based dynamic refractive micro-scale compound lenses.

Structural characteristics of novel symmetrical diaryl derivatives with nitrogenated functions. Requirements for cytotoxic activity.

PubMed

Font, María; Ardaiz, Elena; Cordeu, Lucia; Cubedo, Elena; García-Foncillas, Jesús; Sanmartin, Carmen; Palop, Juan-Antonio

2006-03-15

In an attempt to discover the essential features that would allow us to explain the differences in cytotoxic activity shown by a series of symmetrical diaryl derivatives with nitrogenated functions, we have studied by molecular modelling techniques the variation in Log P and conformational behaviour, in terms of structural modifications. The Log P data--although they provide few clues concerning the observed variability in activity--suggest that an initial separation of active and inactive compounds is possible based on this parameter. The subsequent study of the conformational behaviour of the compounds, selected according to their Log P values, showed that the active compounds preferentially display an extended conformation and inactive ones are associated with a certain type of folding, with a triangular-type conformation adopted in these cases.

Reconfigurable and responsive droplet-based compound micro-lenses

PubMed Central

Nagelberg, Sara; Zarzar, Lauren D.; Nicolas, Natalie; Subramanian, Kaushikaram; Kalow, Julia A.; Sresht, Vishnu; Blankschtein, Daniel; Barbastathis, George; Kreysing, Moritz; Swager, Timothy M.; Kolle, Mathias

2017-01-01

Micro-scale optical components play a crucial role in imaging and display technology, biosensing, beam shaping, optical switching, wavefront-analysis, and device miniaturization. Herein, we demonstrate liquid compound micro-lenses with dynamically tunable focal lengths. We employ bi-phase emulsion droplets fabricated from immiscible hydrocarbon and fluorocarbon liquids to form responsive micro-lenses that can be reconfigured to focus or scatter light, form real or virtual images, and display variable focal lengths. Experimental demonstrations of dynamic refractive control are complemented by theoretical analysis and wave-optical modelling. Additionally, we provide evidence of the micro-lenses' functionality for two potential applications—integral micro-scale imaging devices and light field display technology—thereby demonstrating both the fundamental characteristics and the promising opportunities for fluid-based dynamic refractive micro-scale compound lenses. PMID:28266505

Electron-Impact Total Ionization Cross Sections of Fluorine Compounds

NASA Astrophysics Data System (ADS)

Kim, Y.-K.; Ali, M. A.; Rudd, M. E.

1997-10-01

A theoretical method called the Binary-Encounter-Bethe (BEB) model(M. A. Ali, Y.-K. Kim, H. Hwang, N. M. Weinberger, and M. E. Rudd, J. Chem. Phys. 106), 9602 (1997), and references therein. that combines the Mott cross section at low incident energies T and the Bethe cross section at high T was applied to fluorine compounds of interest to plasma processing of semiconductors (CF_4, CHF_3, C_2F_6, C_4F_8, etc.). The theory provides total ioniztion cross sections in an analytic form from the threshold to a few keV in T, making it convenient to use the theory for modeling. The theory is particularly effective for closed-shell molecules. The theoretical cross sections are compared to available experimental data.

Photo- and radiation chemical induced degradation of lignin model compounds.

PubMed

Lanzalunga; Bietti, M

2000-07-01

The basic mechanistic aspects of the photo- and radiation chemistry of lignin model compounds (LMCs) are discussed with respect to important processes related to lignin degradation. Several reactions occur after direct irradiation, photosensitized or radiation chemically induced oxidation of LMCs. Direct irradiation studies on LMCs have provided supportive evidence for the involvement of hydrogen abstraction reactions from phenols, beta-cleavage of substituted alpha-aryloxyacetophenones and cleavage of ketyl radicals (formed by photoreduction of aromatic ketones or hydrogen abstraction from arylglycerol beta-aryl ethers) in the photoyellowing of lignin rich pulps. Photosensitized and radiation chemically induced generation of reactive oxygen species and their reaction with LMCs are reviewed. The side-chain reactivity of LMC radical cations, generated by radiation chemical means, is also discussed in relation with the enzymatic degradation of lignin.

Investigation of metal–dithiolate fold angle effects: Implications for molybdenum and tungsten enzymes

PubMed Central

Joshi, Hemant K.; Cooney, J. Jon A.; Inscore, Frank E.; Gruhn, Nadine E.; Lichtenberger, Dennis L.; Enemark, John H.

2003-01-01

Gas-phase photoelectron spectroscopy and density functional theory have been used to investigate the interactions between the sulfur π-orbitals of arene dithiolates and high-valent transition metals as minimum molecular models of the active site features of pyranopterin Mo/W enzymes. The compounds (Tp*)MoO(bdt) (compound 1), Cp2Mo(bdt) (compound 2), and Cp2Ti(bdt) (compound 3) [where Tp* is hydrotris(3,5-dimethyl-1-pyrazolyl)borate, bdt is 1,2-benzenedithiolate, and Cp is η5- cyclopentadienyl] provide access to three different electronic configurations of the metal, formally d1, d2, and d0, respectively. The gas-phase photoelectron spectra show that ionizations from occupied metal and sulfur based valence orbitals are more clearly observed in compounds 2 and 3 than in compound 1. The observed ionization energies and characters compare very well with those calculated by density functional theory. A “dithiolate-folding-effect” involving an interaction of the metal in-plane and sulfur-π orbitals is proposed to be a factor in the electron transfer reactions that regenerate the active sites of molybdenum and tungsten enzymes. PMID:12655066

Gas and aerosol carbon in California: comparison of measurements and model predictions in Pasadena and Bakersfield.

EPA Science Inventory

Co-located measurements of fine particulate matter (PM2.5) organic carbon (OC), elemental carbon, radiocarbon (14C), speciated volatile organic compounds (VOCs),and OH radicals during the CalNex field campaign provide a unique opportunity to evaluate the Community Multiscale Air ...

The U.S. EPA's ToxCast Chemical Screening Program and Predictive Modeling of Toxicity

EPA Science Inventory

The ToxCast program was developed by the U.S. EPA's National Center for Computational Toxicology to provide cost-effective high-throughput screening for the potential toxicity of thousands of chemicals. Phase I screened 309 compounds in over 500 assays to evaluate concentration-...

Estimating Likelihood of Fetal In Vivo Interactions Using In Vitro HTS Data (Teratology meeting)

EPA Science Inventory

Tox21/ToxCast efforts provide in vitro concentration-response data for thousands of compounds. Predicting whether chemical-biological interactions observed in vitro will occur in vivo is challenging. We hypothesize that using a modified model from the FDA guidance for drug intera...

Computational Prediction of Electron Ionization Mass Spectra to Assist in GC/MS Compound Identification.

PubMed

Allen, Felicity; Pon, Allison; Greiner, Russ; Wishart, David

2016-08-02

We describe a tool, competitive fragmentation modeling for electron ionization (CFM-EI) that, given a chemical structure (e.g., in SMILES or InChI format), computationally predicts an electron ionization mass spectrum (EI-MS) (i.e., the type of mass spectrum commonly generated by gas chromatography mass spectrometry). The predicted spectra produced by this tool can be used for putative compound identification, complementing measured spectra in reference databases by expanding the range of compounds able to be considered when availability of measured spectra is limited. The tool extends CFM-ESI, a recently developed method for computational prediction of electrospray tandem mass spectra (ESI-MS/MS), but unlike CFM-ESI, CFM-EI can handle odd-electron ions and isotopes and incorporates an artificial neural network. Tests on EI-MS data from the NIST database demonstrate that CFM-EI is able to model fragmentation likelihoods in low-resolution EI-MS data, producing predicted spectra whose dot product scores are significantly better than full enumeration "bar-code" spectra. CFM-EI also outperformed previously reported results for MetFrag, MOLGEN-MS, and Mass Frontier on one compound identification task. It also outperformed MetFrag in a range of other compound identification tasks involving a much larger data set, containing both derivatized and nonderivatized compounds. While replicate EI-MS measurements of chemical standards are still a more accurate point of comparison, CFM-EI's predictions provide a much-needed alternative when no reference standard is available for measurement. CFM-EI is available at https://sourceforge.net/projects/cfm-id/ for download and http://cfmid.wishartlab.com as a web service.

Longitudinal trends and subgroup analysis in publication patterns for preclinical data of newly approved drugs.

PubMed

Köster, Ursula; Nolte, Ingo; Michel, Martin C

2016-02-01

Having observed a large variation in the number and type of original preclinical publications for newly registered drugs, we have explored whether longitudinal trends and/or factors specific for certain drugs or their manufacturers may explain such variation. Our analysis is based on 1954 articles related to 170 newly approved drugs. The number of preclinical publications per compound declined from a median of 10.5 in 1991 to 3 in 2011. A similar trend was observed for the number of in vivo studies in general, but not in the subset of in vivo studies in animal models of disease. The percentage of compounds with studies using isolated human cells or cell lines almost doubled over time from 37 to 72%. Number of publications did not exhibit major differences between compounds intended for human versus veterinary use, therapeutic areas, small molecules versus biologicals, or innovator versus follow-up compounds; however, some companies may publish fewer studies per compound than others. However, there were qualitative differences in the types of models being used depending on the therapeutic area; specifically, compounds for use in oncology very often used isolated cells and cell lines, often from human origin. We conclude that the large variation in number and type of reported preclinical data is not easily explained. We propose that pharmaceutical companies should consistently provide a comprehensive documentation of the preclinical data they generate as part of their development programs in the public domain to enable a better understanding of the drugs they intend to market.

Pro-osteogenic effects of fibrin glue in treatment of avascular necrosis of the femoral head in vivo by hepatocyte growth factor-transgenic mesenchymal stem cells

PubMed Central

2014-01-01

Background Autologous transplantation of modified mesenchymal stem cells (MSCs) is a promising candidate for the treatment of the refractory clinical disease, avascular necrosis of the femoral head (ANFH). Our previous attempts by compounding MSCs with medical fibrin glue to treat ANFH in animal model have achieved excellent effects. However, the underlying molecular mechanism is unclear, especially on the transgenic gene expression. Methods Rabbit MSCs were isolated and compounded with fibrin glue. Following degrading of fibrin glue, proliferation, viability, expression of transgenic hepatocyte growth factor gene as well as osteogenic differentiation of MSCs were evaluated together with that of uncompounded MSCs. Fibrin glue-compounded MSCs were transplanted into the lesion of ANFH model, and the therapeutic efficacy was compared with uncompounded MSCs. One-Way ANOVA was used to determine the statistical significance among treatment groups. Results Fibrin glue compounding will not affect molecular activities of MSCs, including hepatocyte growth factor (HGF) secretion, cell proliferation and viability, and osteogenic differentiation in vitro. When applying fibrin glue-compounded MSCs for the therapy of ANFH in vivo, fibrin glue functioned as a drug delivery system and provided a sustaining microenvironment for MSCs which helped the relatively long-term secretion of HGF in the femoral head lesion and resulted in improved therapeutic efficacy when compared with uncompounded MSCs as indicated by hematoxylin-eosin staining and immunohistochemistry of osteocalcin, CD105 and HGF. Conclusion Transplantation of fibrin glue-compounding MSCs is a promising novel method for ANFH therapy. PMID:24885252

Dissolution and sorption of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) and 2,4,6-trinitrotoluene (TNT) residues from detonated mineral surfaces.

PubMed

Jaramillo, Ashley M; Douglas, Thomas A; Walsh, Marianne E; Trainor, Thomas P

2011-08-01

Composition B (Comp B) is a commonly used military formulation composed of the toxic explosive compounds 2,4,6-trinitrotoluene (TNT), and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Numerous studies of the temporal fate of explosive compounds in soils, surface water and laboratory batch reactors have been conducted. However, most of these investigations relied on the application of explosive compounds to the media via aqueous addition and thus these studies do not provide information on the real world loading of explosive residues during detonation events. To address this we investigated the dissolution and sorption of TNT and RDX from Comp B residues loaded to pure mineral phases through controlled detonation. Mineral phases included nontronite, vermiculite, biotite and Ottawa sand (quartz with minor calcite). High Performance Liquid Chromatography and Attenuated Total Reflectance Fourier Transform Infrared spectroscopy were used to investigate the dissolution and sorption of TNT and RDX residues loaded onto the mineral surfaces. Detonation resulted in heterogeneous loading of TNT and RDX onto the mineral surfaces. Explosive compound residues dissolved rapidly (within 9 h) in all samples but maximum concentrations for TNT and RDX were not consistent over time due to precipitation from solution, sorption onto mineral surfaces, and/or chemical reactions between explosive compounds and mineral surfaces. We provide a conceptual model of the physical and chemical processes governing the fate of explosive compound residues in soil minerals controlled by sorption-desorption processes. Published by Elsevier Ltd.

Screening of synthetic and natural product databases: Identification of novel androgens and antiandrogens.

PubMed

Bobach, Claudia; Tennstedt, Stephanie; Palberg, Kristin; Denkert, Annika; Brandt, Wolfgang; de Meijere, Armin; Seliger, Barbara; Wessjohann, Ludger A

2015-01-27

The androgen receptor is an important pharmaceutical target for a variety of diseases. This paper presents an in silico/in vitro screening procedure to identify new androgen receptor ligands. The two-step virtual screening procedure uses a three-dimensional pharmacophore model and a docking/scoring routine. About 39,000 filtered compounds were docked with PLANTS and scored by Chemplp. Subsequent to virtual screening, 94 compounds, including 28 steroidal and 66 nonsteroidal compounds, were tested by an androgen receptor fluorescence polarization ligand displacement assay. As a result, 30 compounds were identified that show a relative binding affinity of more than 50% in comparison to 100 nM dihydrotestosterone and were classified as androgen receptor binders. For 11 androgen receptor binders of interest IC50 and Ki values were determined. The compound with the highest affinity exhibits a Ki value of 10.8 nM. Subsequent testing of the 11 compounds in a PC-3 and LNCaP multi readout proliferation assay provides insights into the potential mode of action. Further steroid receptor ligand displacement assays and docking studies on estrogen receptors α and β, glucocorticoid receptor, and progesterone receptor gave information about the specificity of the 11 most active compounds. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Phenolic Molding Compounds

NASA Astrophysics Data System (ADS)

Koizumi, Koji; Charles, Ted; de Keyser, Hendrik

Phenolic Molding Compounds continue to exhibit well balanced properties such as heat resistance, chemical resistance, dimensional stability, and creep resistance. They are widely applied in electrical, appliance, small engine, commutator, and automotive applications. As the focus of the automotive industry is weight reduction for greater fuel efficiency, phenolic molding compounds become appealing alternatives to metals. Current market volumes and trends, formulation components and its impact on properties, and a review of common manufacturing methods are presented. Molding processes as well as unique advanced techniques such as high temperature molding, live sprue, and injection/compression technique provide additional benefits in improving the performance characterisitics of phenolic molding compounds. Of special interest are descriptions of some of the latest innovations in automotive components, such as the phenolic intake manifold and valve block for dual clutch transmissions. The chapter also characterizes the most recent developments in new materials, including long glass phenolic molding compounds and carbon fiber reinforced phenolic molding compounds exhibiting a 10-20-fold increase in Charpy impact strength when compared to short fiber filled materials. The role of fatigue testing and fatigue fracture behavior presents some insight into long-term reliability and durability of glass-filled phenolic molding compounds. A section on new technology outlines the important factors to consider in modeling phenolic parts by finite element analysis and flow simulation.

Electronic structure and microscopic model of CoNb2O6

NASA Astrophysics Data System (ADS)

Molla, Kaimujjaman; Rahaman, Badiur

2018-05-01

We present the first principle density functional calculations to figure out the underlying spin model of CoNb2O6. The first principles calculations define the main paths of superexchange interaction between Co spins in this compound. We discuss the nature of the exchange paths and provide quantitative estimates of magnetic exchange couplings. A microscopic modeling based on analysis of the electronic structure of this system puts it in the interesting class of weakly couple geometrically frustrated isosceles triangular Ising antiferromagnet.

[Compounds modulating parathyroid hormone (PTH) secretion].

PubMed

Nagano, N; Iijima, H

2001-08-01

The control of parathyroid hormone (PTH) secretion is strictly regulated by the parathyroid Ca receptor (CaR). Calcimimetics and calcilytics selectively act on the parathyroid CaR to inhibit and enhance PTH secretion, respectively. According to the recent pharmacological two-state model, calcimimetics act on the CaR as allosteric agonists to stabilize an active conformation of CaR. Conversely, calcilytics act on the CaR as allosteric inverse agonists to stabilize an inactive conformation of CaR. These compounds that can alter circulating levels of PTH and bone turnover might provide novel treatments for adynamic bone disease in patients with chronic renal failure.

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.

Oxidation of aromatic contaminants coupled to microbial iron reduction

USGS Publications Warehouse

Lovley, D.R.; Baedecker, M.J.; Lonergan, D.J.; Cozzarelli, I.M.; Phillips, E.J.P.; Siegel, D.I.

1989-01-01

THE contamination of sub-surface water supplies with aromatic compounds is a significant environmental concern1,2. As these contaminated sub-surface environments are generally anaerobic, the microbial oxidation of aromatic compounds coupled to nitrate reduction, sulphate reduction and methane production has been studied intensively1-7. In addition, geochemical evidence suggests that Fe(III) can be an important electron acceptor for the oxidation of aromatic compounds in anaerobic groundwater. Until now, only abiological mechanisms for the oxidation of aromatic compounds with Fe(III) have been reported8-12. Here we show that in aquatic sediments, microbial activity is necessary for the oxidation of model aromatic compounds coupled to Fe(III) reduction. Furthermore, a pure culture of the Fe(III)-reducing bacterium GS-15 can obtain energy for growth by oxidizing benzoate, toluene, phenol or p-cresol with Fe(III) as the sole electron acceptor. These results extend the known physiological capabilities of Fe(III)-reducing organisms and provide the first example of an organism of any type which can oxidize an aromatic hydrocarbon anaerobically. ?? 1989 Nature Publishing Group.

Improved prediction of octanol-water partition coefficients from liquid-solute water solubilities and molar volumes

USGS Publications Warehouse

Chiou, C.T.; Schmedding, D.W.; Manes, M.

2005-01-01

A volume-fraction-based solvent-water partition model for dilute solutes, in which the partition coefficient shows a dependence on solute molar volume (V??), is adapted to predict the octanol-water partition coefficient (K ow) from the liquid or supercooled-liquid solute water solubility (Sw), or vice versa. The established correlation is tested for a wide range of industrial compounds and pesticides (e.g., halogenated aliphatic hydrocarbons, alkylbenzenes, halogenated benzenes, ethers, esters, PAHs, PCBs, organochlorines, organophosphates, carbamates, and amidesureas-triazines), which comprise a total of 215 test compounds spanning about 10 orders of magnitude in Sw and 8.5 orders of magnitude in Kow. Except for phenols and alcohols, which require special considerations of the Kow data, the correlation predicts the Kow within 0.1 log units for most compounds, much independent of the compound type or the magnitude in K ow. With reliable Sw and V data for compounds of interest, the correlation provides an effective means for either predicting the unavailable log Kow values or verifying the reliability of the reported log Kow data. ?? 2005 American Chemical Society.

Biomass Burning and Natural Emissions in the Amazon Rainforest: Impact on the Oxidative Capacity of the Atmosphere

NASA Astrophysics Data System (ADS)

dos Santos, F. C.; Guenther, A. B.; Longo, K.; Freitas, S. R.; Moreira, D. S.; Flávio, L.; Braz, R.; Brito, J.; Oram, D.; Forster, G.; Lee, J. D.; Bauguitte, S.

2015-12-01

Terrestrial vegetation, especially tropical forests, releases large amounts of biogenic volatile organic compounds (BVOC) into the atmosphere. The global emissions of BVOC (~1000 Tg C/year) are dominant in relation to anthropogenic volatile organic compounds (~100 Tg C/year), with biomass burning contributing close to 10 - 50 Tg C/year. Tropical trees cover about 18% of the global land surface but are estimated to be responsible for approximately 80% of terpenoid and 50% of other BVOCs emissions. Considering the importance of these emissions, the SAMBBA (South American Biomass Burning Analysis) experiment, which occurred during the dry season (September 2012) in the Amazon Rainforest, provided information about the chemical composition of the atmosphere through measurements on the aircraft FAAM BAE-146. Although primarily focused on biomass burning flights, the SAMBBA project carried out other flights providing indirect oxidative capacity data in different environments: natural emission dominated flights and biomass burning flights with fresh plumes (< 2 hours) and aged plumes (> 2 hours). Calculation of the [MVK+MACR]/[Isoprene] ratio enabled investigation of the impact of biomass burning on surface oxidation in comparison to the natural emission flights. During the morning (altitude < 500m), the [MVK+MACR]/[Isoprene] values for natural emission flights (1.0±0.4), fresh plume (1.9±0.6) and aged plume (1.4±0.6) suggest that biomass burning enhances BVOC oxidation in relation to the lifetime of the air mass. This study aims to improve the knowledge about the oxidative capacity of the atmosphere, which depends not only on chemical composition, but also other factors like the history of the air mass trajectories influencing the availability of these compounds, the NOx dependence of isoprene oxidation and whether the chemistry is dominated by OH or O3. A synergistic approach integrating observation and modeling, using 3D numerical model of chemical transport (CCATT-BRAMS) coupled with a natural emission model (MEGAN) has been applied to study the BVOC in the Amazon rainforest. The SAMBBA experiment provided a valuable database that is being included into a numerical model of air quality, developing a numerical model that incorporates the understanding needed to represent the observations.

A systematic study of mitochondrial toxicity of environmental chemicals using quantitative high throughput screening

PubMed Central

Attene-Ramos, Matias S.; Huang, Ruili; Sakamuru, Srilatha; Witt, Kristine L.; Beeson, Gyda C.; Shou, Louie; Schnellmann, Rick G.; Beeson, Craig C.; Tice, Raymond R.; Austin, Christopher P.; Xia, Menghang

2014-01-01

A goal of the Tox21 program is to transit toxicity testing from traditional in vivo models to in vitro assays that assess how chemicals affect cellular responses and toxicity pathways. A critical contribution of the NIH Chemical Genomics center (NCGC) to the Tox21 program is the implementation of a quantitative high throughput screening (qHTS) approach, using cell- and biochemical-based assays to generate toxicological profiles for thousands of environmental compounds. Here, we evaluated the effect of chemical compounds on mitochondrial membrane potential in HepG2 cells by screening a library of 1,408 compounds provided by the National Toxicology Program (NTP) in a qHTS platform. Compounds were screened over 14 concentrations, and results showed that 91 and 88 compounds disrupted mitochondrial membrane potential after treatment for one or five h, respectively. Seventy-six compounds active at both time points were clustered by structural similarity, producing 11 clusters and 23 singletons. Thirty-eight compounds covering most of the active chemical space were more extensively evaluated. Thirty-six of the 38 compounds were confirmed to disrupt mitochondrial membrane potential using a fluorescence plate reader and 35 were confirmed using a high content imaging approach. Among the 38 compounds, 4 and 6 induced LDH release, a measure of cytotoxicity, at 1 or 5 h, respectively. Compounds were further assessed for mechanism of action (MOA) by measuring changes in oxygen consumption rate, which enabled identification of 20 compounds as uncouplers. This comprehensive approach allows for evaluation of thousands of environmental chemicals for mitochondrial toxicity and identification of possible MOAs. PMID:23895456

MICROBIAL DEGRADATION OF NITROGEN, OXYGEN AND SULFUR HETEROCYCLIC COMPOUNDS UNDER ANAEROBIC CONDITIONS: STUDIES WITH AQUIFER SAMPLES

EPA Science Inventory

The potential for anaerobic biodegradation of 12 heterocyclic model compounds was studied. Nine of the model compounds were biotransformed in aquifer slurries under sulfate-reducing or methanogenic conditions. The nitrogen and oxygen heterocyclic compounds were more susceptible t...

Inhibition of growth of Zymomonas mobilis by model compounds found in lignocellulosic hydrolysates

PubMed Central

2013-01-01

Background During the pretreatment of biomass feedstocks and subsequent conditioning prior to saccharification, many toxic compounds are produced or introduced which inhibit microbial growth and in many cases, production of ethanol. An understanding of the toxic effects of compounds found in hydrolysate is critical to improving sugar utilization and ethanol yields in the fermentation process. In this study, we established a useful tool for surveying hydrolysate toxicity by measuring growth rates in the presence of toxic compounds, and examined the effects of selected model inhibitors of aldehydes, organic and inorganic acids (along with various cations), and alcohols on growth of Zymomonas mobilis 8b (a ZM4 derivative) using glucose or xylose as the carbon source. Results Toxicity strongly correlated to hydrophobicity in Z. mobilis, which has been observed in Escherichia coli and Saccharomyces cerevisiae for aldehydes and with some exceptions, organic acids. We observed Z. mobilis 8b to be more tolerant to organic acids than previously reported, although the carbon source and growth conditions play a role in tolerance. Growth in xylose was profoundly inhibited by monocarboxylic organic acids compared to growth in glucose, whereas dicarboxylic acids demonstrated little or no effects on growth rate in either substrate. Furthermore, cations can be ranked in order of their toxicity, Ca++ > > Na+ > NH4+ > K+. HMF (5-hydroxymethylfurfural), furfural and acetate, which were observed to contribute to inhibition of Z. mobilis growth in dilute acid pretreated corn stover hydrolysate, do not interact in a synergistic manner in combination. We provide further evidence that Z. mobilis 8b is capable of converting the aldehydes furfural, vanillin, 4-hydroxybenzaldehyde and to some extent syringaldehyde to their alcohol forms (furfuryl, vanillyl, 4-hydroxybenzyl and syringyl alcohol) during fermentation. Conclusions Several key findings in this report provide a mechanism for predicting toxic contributions of inhibitory components of hydrolysate and provide guidance for potential process development, along with potential future strain improvement and tolerance strategies. PMID:23837621

Neuroprotective Role of Novel Triazine Derivatives by Activating Wnt/β Catenin Signaling Pathway in Rodent Models of Alzheimer's Disease.

PubMed

Sinha, Anshuman; Tamboli, Riyaj S; Seth, Brashket; Kanhed, Ashish M; Tiwari, Shashi Kant; Agarwal, Swati; Nair, Saumya; Giridhar, Rajani; Chaturvedi, Rajnish Kumar; Yadav, Mange Ram

2015-08-01

It has been reported in the literature that cholinesterase inhibitors provide protection in Alzheimer's disease (AD). Recent reports have implicated triazine derivatives as cholinesterase inhibitors. These findings led us to investigate anti-cholinestrase property of some novel triazine derivatives synthesized in this laboratory. In vitro cholinesterase inhibition assay was performed using Ellman method. The potent compounds screened out from in vitro assay were further evaluated using scopolamine-induced amnesic mice model. Further, in vitro reactive oxygen species (ROS) scavenging and anti-apoptotic property of the potent compounds were demonstrated against Aβ1-42-induced neurotoxicity in rat hippocampal cells. Their neuroprotective role was assessed using Aβ1-42-induced Alzheimer's-like phenotype in rats. Further, the role of compounds on the activation of the Wnt/β-catenin pathway was studied. The results showed that the chosen compounds are having protective effect in Alzheimer's-like condition; the ex vivo results advocated their anti-cholinestrase and anti-oxidant activities. Treatment with TRZ-15 and TRZ-20 showed neuroprotective ability of the compounds as evidenced from the improved cognitive ability in the animals, and decrease in Aβ1-42 burden and cytochrome c and cleaved caspase-3 levels in the brain. This study also demonstrates positive involvement of the novel triazine derivatives in the Wnt/β-catenin pathway. Immunoblot and immunofluorescence data suggested that ratio of pGSK3/GSK3 and β-catenin got dramatically improved after treatment with TRZ-15 and TRZ-20. TRZ-15 and TRZ-20 showed neuroprotection in scopolamine-induced amnesic mice and Aβ1-42-induced Alzheimer's rat model and also activate the Wnt/β-catenin signaling pathway. These findings conclude that TRZ-15 and TRZ-20 could be a therapeutic approach to treat AD.

Basic studies on the pyrolysis of lignin compounds

Treesearch

Byung-ho Hwang

2003-01-01

By pyrolyzing lignin model compounds 1-lV at 315°C, an investigation was carried out with some results. In the pyrolysis of lignin model compound I and 11, 0.47 mol of guaiacol, 0.57 mol of dimethoxyphenol (DMP), and 0.12 and 0.23 mol of dimethoxyaceton ophenone (DMAP) were produced respectively. In the pyrolysis of lignin model compound lll and lV, 0.26 mol of...

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets.

PubMed

Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

PubMed Central

Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817

Density functional theory molecular modeling, chemical synthesis, and antimicrobial behaviour of selected benzimidazole derivatives

NASA Astrophysics Data System (ADS)

Marinescu, Maria; Tudorache, Diana Gabriela; Marton, George Iuliu; Zalaru, Christina-Marie; Popa, Marcela; Chifiriuc, Mariana-Carmen; Stavarache, Cristina-Elena; Constantinescu, Catalin

2017-02-01

Eco-friendly, one-pot, solvent-free synthesis of biologically active 2-substituted benzimidazoles is presented and discussed herein. Novel N-Mannich bases are synthesized from benzimidazoles, secondary amines and formaldehyde, and their structures are confirmed by 1H nuclear magnetic resonance (NMR), Fourier transform infrared (FTIR), and elemental analysis. All benzimidazole derivatives are evaluated by qualitative and quantitative methods against 9 bacterial strains. The largest microbicide and anti-biofilm effect is observed for the 2-(1-hydroxyethyl)-compounds. Density functional theory (DFT) modeling of the molecular structure and frontier molecular orbitals, i.e. highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO/LUMO), is accomplished by using the GAMESS 2012 software. Antimicrobial activity is correlated with the electronic parameters (chemical hardness, electronic chemical potential, global electrophilicity index), Mullikan atomic charges and geometric parameters of the benzimidazole compounds. The planarity of the compound, symmetry of the molecule, and the presence of a nucleophilic group, are advantages for a high antimicrobial activity. Finally, we briefly show that further accurate processing of such compounds into thin films and hybrid structures, e.g. by laser ablation matrix-assisted pulsed laser evaporation and/or laser-induced forward transfer, may indeed provide simple and environmental friendly, state-of-the-art solutions for antimicrobial coatings.

Models for liquid-liquid partition in the system dimethyl sulfoxide-organic solvent and their use for estimating descriptors for organic compounds.

PubMed

Karunasekara, Thushara; Poole, Colin F

2011-07-15

Partition coefficients for varied compounds were determined for the organic solvent-dimethyl sulfoxide biphasic partition system where the organic solvent is n-heptane or isopentyl ether. These partition coefficient databases are analyzed using the solvation parameter model facilitating a quantitative comparison of the dimethyl sulfoxide-based partition systems with other totally organic partition systems. Dimethyl sulfoxide is a moderately cohesive solvent, reasonably dipolar/polarizable and strongly hydrogen-bond basic. Although generally considered to be non-hydrogen-bond acidic, analysis of the partition coefficient database strongly supports reclassification as a weak hydrogen-bond acid in agreement with recent literature. The system constants for the n-heptane-dimethyl sulfoxide biphasic system provide an explanation of the mechanism for the selective isolation of polycyclic aromatic compounds from mixtures containing low-polarity hydrocarbons based on the capability of the polar interactions (dipolarity/polarizability and hydrogen-bonding) to overcome the opposing cohesive forces in dimethyl sulfoxide that are absent for the interactions with hydrocarbons of low polarity. In addition, dimethyl sulfoxide-organic solvent systems afford a complementary approach to other totally organic biphasic partition systems for descriptor measurements of compounds virtually insoluble in water. Copyright © 2011 Elsevier B.V. All rights reserved.

Developing Hypothetical Inhibition Mechanism of Novel Urea Transporter B Inhibitor

NASA Astrophysics Data System (ADS)

Li, Min; Tou, Weng Ieong; Zhou, Hong; Li, Fei; Ren, Huiwen; Chen, Calvin Yu-Chian; Yang, Baoxue

2014-07-01

Urea transporter B (UT-B) is a membrane channel protein that specifically transports urea. UT-B null mouse exhibited urea selective urine concentrating ability deficiency, which suggests the potential clinical applications of the UT-B inhibitors as novel diuretics. Primary high-throughput virtual screening (HTVS) of 50000 small-molecular drug-like compounds identified 2319 hit compounds. These 2319 compounds were screened by high-throughput screening using an erythrocyte osmotic lysis assay. Based on the pharmacological data, putative UT-B binding sites were identified by structure-based drug design and validated by ligand-based and QSAR model. Additionally, UT-B structural and functional characteristics under inhibitors treated and untreated conditions were simulated by molecular dynamics (MD). As the result, we identified four classes of compounds with UT-B inhibitory activity and predicted a human UT-B model, based on which computative binding sites were identified and validated. A novel potential mechanism of UT-B inhibitory activity was discovered by comparing UT-B from different species. Results suggest residue PHE198 in rat and mouse UT-B might block the inhibitor migration pathway. Inhibitory mechanisms of UT-B inhibitors and the functions of key residues in UT-B were proposed. The binding site analysis provides a structural basis for lead identification and optimization of UT-B inhibitors.

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

Design, synthesis, antiviral bioactivity and three-dimensional quantitative structure-activity relationship study of novel ferulic acid ester derivatives containing quinazoline moiety.

PubMed

Wu, Zengxue; Zhang, Jian; Chen, Jixiang; Pan, Jianke; Zhao, Lei; Liu, Dengyue; Zhang, Awei; Chen, Jin; Hu, Deyu; Song, Baoan

2017-10-01

Ferulic acid and quinazoline derivatives possess good antiviral activities. In order to develop novel compounds with high antiviral activities, a series of ferulic acid ester derivatives containing quinazoline were synthesized and evaluated for their antiviral activities. Bioassays indicated that some of the compounds exhibited good antiviral activities in vivo against tobacco mosaic virus (TMV) and cucumber mosaic virus (CMV). One of the compounds demonstrated significant curative and protective activities against TMV and CMV, with EC 50 values of 162.14, 114.61 and 255.49, 138.81 mg L -1 , respectively, better than those of ningnanmycin (324.51, 168.84 and 373.88, 272.70 mg L -1 ). The values of q 2 and r 2 for comparative molecular field analysis and comparative molecular similarity index analysis in the TMV (0.508, 0.663 and 0.992, 0.930) and CMV (0.530, 0.626 and 0.997, 0.981) models presented good predictive abilities. Some of the title compounds demonstrated good antiviral activities. Three-dimensional quantitative structure-activity relationship models revealed that the antiviral activities depend on steric and electrostatic properties. These results could provide significant structural insights for the design of highly active ferulic acid derivatives. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Innovation leading the way: application of lean manufacturing to sample management.

PubMed

Allen, M; Wigglesworth, M J

2009-06-01

Historically, sample management successfully focused on providing compound quality and tracking distribution within a diverse geographic. However, if a competitive advantage is to be delivered in a changing environment of outsourcing, efficiency and customer service must now improve or face reconstruction. The authors have used discrete event simulation to model the compound process from chemistry to assay and applied lean manufacturing techniques to analyze and improve these processes. In doing so, they identified a value-adding process time of just 11 min within a procedure that took days. Modeling also allowed the analysis of equipment and human resources necessary to complete the expected demand in an acceptable cycle time. Layout and location of sample management and screening departments are key in allowing process integration, creating rapid flow of work, and delivering these efficiencies. Following this analysis and minor process changes, the authors have demonstrated for 2 programs that solid compounds can be converted to assay-ready plates in less than 4 h. In addition, it is now possible to deliver assay data from these compounds within the same working day, allowing chemistry teams more flexibility and more time to execute the next chemistry round. Additional application of lean manufacturing principles has the potential to further decrease cycle times while using fewer resources.

Real-space investigation of short-range magnetic correlations in fluoride pyrochlores NaCaCo 2F 7 and NaSrCo 2F 7 with magnetic pair distribution function analysis

DOE PAGES

Frandsen, Benjamin A.; Billinge, Simon J. L.; Ross, Kathryn A.; ...

2017-12-29

Here, we present time-of-flight neutron total scattering and polarized neutron scattering measurements of the magnetically frustrated compounds NaCaCo 2F 7 and NaSrCo 2F 7, which belong to a class of recently discovered pyrochlore compounds based on transition metals and fluorine. The magnetic pair distribution function (mPDF) technique is used to analyze and model the total scattering data in real space. We find that a previously-proposed model of short-range XY-like correlations with a length scale of 10-15 Å, combined with nearest-neighbor collinear antiferromagnetic correlations, accurately describes the mPDF data at low temperature, confirming the magnetic ground state in these materials. Thismore » model is further verified by the polarized neutron scattering data. From an analysis of the temperature dependence of the mPDF and polarized neutron scattering data, we find that short-range correlations persist on the nearest-neighbor length scale up to 200 K, approximately two orders of magnitude higher than the spin freezing temperatures of these compounds. These results highlight the opportunity presented by these new pyrochlore compounds to study the effects of geometric frustration at relatively high temperatures, while also advancing the mPDF technique and providing a novel opportunity to investigate a genuinely short-range-ordered magnetic ground state directly in real space.« less

Real-space investigation of short-range magnetic correlations in fluoride pyrochlores NaCaCo 2F 7 and NaSrCo 2F 7 with magnetic pair distribution function analysis

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

Frandsen, Benjamin A.; Billinge, Simon J. L.; Ross, Kathryn A.

Here, we present time-of-flight neutron total scattering and polarized neutron scattering measurements of the magnetically frustrated compounds NaCaCo 2F 7 and NaSrCo 2F 7, which belong to a class of recently discovered pyrochlore compounds based on transition metals and fluorine. The magnetic pair distribution function (mPDF) technique is used to analyze and model the total scattering data in real space. We find that a previously-proposed model of short-range XY-like correlations with a length scale of 10-15 Å, combined with nearest-neighbor collinear antiferromagnetic correlations, accurately describes the mPDF data at low temperature, confirming the magnetic ground state in these materials. Thismore » model is further verified by the polarized neutron scattering data. From an analysis of the temperature dependence of the mPDF and polarized neutron scattering data, we find that short-range correlations persist on the nearest-neighbor length scale up to 200 K, approximately two orders of magnitude higher than the spin freezing temperatures of these compounds. These results highlight the opportunity presented by these new pyrochlore compounds to study the effects of geometric frustration at relatively high temperatures, while also advancing the mPDF technique and providing a novel opportunity to investigate a genuinely short-range-ordered magnetic ground state directly in real space.« less

Hood entry coefficients of compound exhaust hoods.

PubMed

Figueroa, Crescente E

2011-12-01

A traditional method for assessing the flow rate in ventilation systems is based on multiple readings of velocity or velocity pressure (VP) (usually 10 or 20 points) taken in ductwork sections located away from fittings (> seven × diameters of straight duct). This study seeks to eliminate the need for a multiple-point evaluation and replace it with a simplified method that requires only a single measurement of hood static pressure (SP(h)) taken at a more accessible location (< three × diameters of straight duct from the hood entry). The SP(h) method is widely used for the assessment of flow rate in simple hoods. However, industrial applications quite often use compound hoods that are regularly of the slot/plenum type. For these hoods, a "compound coefficient of entry" has not been published, which makes the use of the hood static pressure method unfeasible. This study proposes a model for the computation of a "compound coefficient of entry" and validates the use of this model to assess flow rate in two systems of well-defined geometry (multi-slotted/plenum and single-slotted/tapered or "fish-tail" types). When using a conservative value of the slot loss factor (1.78), the proposed model yielded an estimate of the volumetric flow rate within 10% of that provided by a more comprehensive method of assessment. The simplicity of the hood static pressure method makes it very desirable, even in the upper range of experimental error found in this study.

Real-space investigation of short-range magnetic correlations in fluoride pyrochlores NaCaCo2F7 and NaSrCo2F7 with magnetic pair distribution function analysis

NASA Astrophysics Data System (ADS)

Frandsen, Benjamin A.; Ross, Kate A.; Krizan, Jason W.; Nilsen, Gøran J.; Wildes, Andrew R.; Cava, Robert J.; Birgeneau, Robert J.; Billinge, Simon J. L.

2017-12-01

We present time-of-flight neutron total scattering and polarized neutron scattering measurements of the magnetically frustrated compounds NaCaCo2F7 and NaSrCo2F7 , which belong to a class of recently discovered pyrochlore compounds based on transition metals and fluorine. The magnetic pair distribution function (mPDF) technique is used to analyze and model the total scattering data in real space. We find that a previously proposed model of short-range XY-like correlations with a length scale of 10-15 Å, combined with nearest-neighbor collinear antiferromagnetic correlations, accurately describes the mPDF data at low temperature, confirming the magnetic ground state in these materials. This model is further verified by the polarized neutron scattering data. From an analysis of the temperature dependence of the mPDF and polarized neutron scattering data, we find that short-range correlations persist on the nearest-neighbor length scale up to 200 K, approximately two orders of magnitude higher than the spin freezing temperatures of these compounds. These results highlight the opportunity presented by these new pyrochlore compounds to study the effects of geometric frustration at relatively high temperatures, while also advancing the mPDF technique and providing an opportunity to investigate a genuinely short-range-ordered magnetic ground state directly in real space.

Outdoor, Indoor, and Personal Exposure to VOCs in Children

PubMed Central

Adgate, John L.; Church, Timothy R.; Ryan, Andrew D.; Ramachandran, Gurumurthy; Fredrickson, Ann L.; Stock, Thomas H.; Morandi, Maria T.; Sexton, Ken

2004-01-01

We measured volatile organic compound (VOC) exposures in multiple locations for a diverse population of children who attended two inner-city schools in Minneapolis, Minnesota. Fifteen common VOCs were measured at four locations: outdoors (O), indoors at school (S), indoors at home (H), and in personal samples (P). Concentrations of most VOCs followed the general pattern O ≈ S < P ≤ H across the measured microenvironments. The S and O environments had the smallest and H the largest influence on personal exposure to most compounds. A time-weighted model of P exposure using all measured microenvironments and time–activity data provided little additional explanatory power beyond that provided by using the H measurement alone. Although H and P concentrations of most VOCs measured in this study were similar to or lower than levels measured in recent personal monitoring studies of adults and children in the United States, p-dichlorobenzene was the notable exception to this pattern, with upper-bound exposures more than 100 times greater than those found in other studies of children. Median and upper-bound H and P exposures were well above health benchmarks for several compounds, so outdoor measurements likely underestimate long-term health risks from children’s exposure to these compounds. PMID:15471730

Comparison of Adsorption/Desorption of Volatile Organic Compounds (VOCs) on Electrospun Nanofibers with Tenax TA for Potential Application in Sampling

PubMed Central

Chu, Lanling; Deng, Siwei; Zhao, Renshan; Deng, Jianjun; Kang, Xuejun

2016-01-01

The objective of this study was to compare the adsorption/desorption of target compounds on homemade electrospun nanofibers, polystyrene (PS) nanofibers, acrylic resin (AR) nanofibers and PS-AR composite nanofibers with Tenax TA. Ten volatile organic compounds (VOCs) were analyzed by preconcentration onto different sorbents followed by desorption (thermal and solvent orderly) and analysis by capillary gas chromatography. In comparison to Tenax TA, the electrospun nanofibers displayed a significant advantage in desorption efficiency and adsorption selectivity. Stability studies were conducted as a comparative experiment between PS-AR nanofibers and Tenax TA using toluene as the model compound. No stability problems were observed upon storage of toluene on both PS-AR nanofibers and Tenax TA over 60 hours period when maintained in an ultra-freezer (−80°C). The nanofibers provided slightly better stability for the adsorbed analytes than Tenax TA under other storage conditions. In addition, the nanofibers also provided slightly better precision than Tenax TA. The quantitative adsorption of PS-AR nanofibers exhibited a good linearity, as evidenced by the 0.988–0.999 range of regression coefficients (R). These results suggest that for VOCs sampling the electrospun nanofibers can be a potential ideal adsorbent. PMID:27776140

Energy efficient synthesis of boranes

DOEpatents

Thorn, David L [Los Alamos, NM; Tumas, William [Los Alamos, NM; Schwarz, Daniel E [Los Alamos, NM; Burrell, Anthony K [Los Alamos, NM

2012-01-24

The reaction of halo-boron compounds (B--X compounds, compounds having one or more boron-halogen bonds) with silanes provides boranes (B--H compounds, compounds having one or more B--H bonds) and halosilanes. Inorganic hydrides, such as surface-bound silane hydrides (Si--H) react with B--X compounds to form B--H compounds and surface-bound halosilanes. The surface bound halosilanes are converted back to surface-bound silanes electrochemically. Halo-boron compounds react with stannanes (tin compounds having a Sn--H bond) to form boranes and halostannanes (tin compounds having a Sn--X bond). The halostannanes are converted back to stannanes electrochemically or by the thermolysis of Sn-formate compounds. When the halo-boron compound is BCl.sub.3, the B--H compound is B.sub.2H.sub.6, and where the reducing potential is provided electrochemically or by the thermolysis of formate.

Energy efficient synthesis of boranes

DOEpatents

Thorn, David L.; Tumas, William; Schwarz, Daniel E.; Burrell, Anthony K.

2010-11-23

The reaction of halo-boron compounds (B--X compounds, compounds having one or more boron-halogen bonds) with silanes provides boranes (B--H compounds, compounds having one or more B--H bonds) and halosilanes. Inorganic hydrides, such as surface-bound silane hydrides (Si--H) react with B--X compounds to form B--H compounds and surface-bound halosilanes. The surface bound halosilanes are converted back to surface-bound silanes electrochemically. Halo-boron compounds react with stannanes (tin compounds having a Sn--H bond) to form boranes and halostannanes (tin compounds having a Sn--X bond). The halostannanes are converted back to stannanes electrochemically or by the thermolysis of Sn-formate compounds. When the halo-boron compound is BCl.sub.3, the B--H compound is B.sub.2H.sub.6, and where the reducing potential is provided electrochemically or by the thermolysis of formate.

Aerobic Toluene Degraders in the Rhizosphere of a Constructed Wetland Model Show Diurnal Polyhydroxyalkanoate Metabolism.

PubMed

Lünsmann, Vanessa; Kappelmeyer, Uwe; Taubert, Anja; Nijenhuis, Ivonne; von Bergen, Martin; Heipieper, Hermann J; Müller, Jochen A; Jehmlich, Nico

2016-07-15

Constructed wetlands (CWs) are successfully applied for the treatment of waters contaminated with aromatic compounds. In these systems, plants provide oxygen and root exudates to the rhizosphere and thereby stimulate microbial degradation processes. Root exudation of oxygen and organic compounds depends on photosynthetic activity and thus may show day-night fluctuations. While diurnal changes in CW effluent composition have been observed, information on respective fluctuations of bacterial activity are scarce. We investigated microbial processes in a CW model system treating toluene-contaminated water which showed diurnal oscillations of oxygen concentrations using metaproteomics. Quantitative real-time PCR was applied to assess diurnal expression patterns of genes involved in aerobic and anaerobic toluene degradation. We observed stable aerobic toluene turnover by Burkholderiales during the day and night. Polyhydroxyalkanoate synthesis was upregulated in these bacteria during the day, suggesting that they additionally feed on organic root exudates while reutilizing the stored carbon compounds during the night via the glyoxylate cycle. Although mRNA copies encoding the anaerobic enzyme benzylsuccinate synthase (bssA) were relatively abundant and increased slightly at night, the corresponding protein could not be detected in the CW model system. Our study provides insights into diurnal patterns of microbial processes occurring in the rhizosphere of an aquatic ecosystem. Constructed wetlands are a well-established and cost-efficient option for the bioremediation of contaminated waters. While it is commonly accepted knowledge that the function of CWs is determined by the interplay of plants and microorganisms, the detailed molecular processes are considered a black box. Here, we used a well-characterized CW model system treating toluene-contaminated water to investigate the microbial processes influenced by diurnal plant root exudation. Our results indicated stable aerobic toluene degradation by members of the Burkholderiales during the day and night. Polyhydroxyalkanoate synthesis in these bacteria was higher during the day, suggesting that they additionally fed on organic root exudates and reutilized the stored carbon compounds during the night. Our study illuminates microbial processes occurring in the rhizosphere of an aquatic ecosystem. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Aerobic Toluene Degraders in the Rhizosphere of a Constructed Wetland Model Show Diurnal Polyhydroxyalkanoate Metabolism

PubMed Central

Lünsmann, Vanessa; Kappelmeyer, Uwe; Taubert, Anja; Nijenhuis, Ivonne; von Bergen, Martin; Müller, Jochen A.; Jehmlich, Nico

2016-01-01

ABSTRACT Constructed wetlands (CWs) are successfully applied for the treatment of waters contaminated with aromatic compounds. In these systems, plants provide oxygen and root exudates to the rhizosphere and thereby stimulate microbial degradation processes. Root exudation of oxygen and organic compounds depends on photosynthetic activity and thus may show day-night fluctuations. While diurnal changes in CW effluent composition have been observed, information on respective fluctuations of bacterial activity are scarce. We investigated microbial processes in a CW model system treating toluene-contaminated water which showed diurnal oscillations of oxygen concentrations using metaproteomics. Quantitative real-time PCR was applied to assess diurnal expression patterns of genes involved in aerobic and anaerobic toluene degradation. We observed stable aerobic toluene turnover by Burkholderiales during the day and night. Polyhydroxyalkanoate synthesis was upregulated in these bacteria during the day, suggesting that they additionally feed on organic root exudates while reutilizing the stored carbon compounds during the night via the glyoxylate cycle. Although mRNA copies encoding the anaerobic enzyme benzylsuccinate synthase (bssA) were relatively abundant and increased slightly at night, the corresponding protein could not be detected in the CW model system. Our study provides insights into diurnal patterns of microbial processes occurring in the rhizosphere of an aquatic ecosystem. IMPORTANCE Constructed wetlands are a well-established and cost-efficient option for the bioremediation of contaminated waters. While it is commonly accepted knowledge that the function of CWs is determined by the interplay of plants and microorganisms, the detailed molecular processes are considered a black box. Here, we used a well-characterized CW model system treating toluene-contaminated water to investigate the microbial processes influenced by diurnal plant root exudation. Our results indicated stable aerobic toluene degradation by members of the Burkholderiales during the day and night. Polyhydroxyalkanoate synthesis in these bacteria was higher during the day, suggesting that they additionally fed on organic root exudates and reutilized the stored carbon compounds during the night. Our study illuminates microbial processes occurring in the rhizosphere of an aquatic ecosystem. PMID:27129963

Effect of missing data on multitask prediction methods.

PubMed

de la Vega de León, Antonio; Chen, Beining; Gillet, Valerie J

2018-05-22

There has been a growing interest in multitask prediction in chemoinformatics, helped by the increasing use of deep neural networks in this field. This technique is applied to multitarget data sets, where compounds have been tested against different targets, with the aim of developing models to predict a profile of biological activities for a given compound. However, multitarget data sets tend to be sparse; i.e., not all compound-target combinations have experimental values. There has been little research on the effect of missing data on the performance of multitask methods. We have used two complete data sets to simulate sparseness by removing data from the training set. Different models to remove the data were compared. These sparse sets were used to train two different multitask methods, deep neural networks and Macau, which is a Bayesian probabilistic matrix factorization technique. Results from both methods were remarkably similar and showed that the performance decrease because of missing data is at first small before accelerating after large amounts of data are removed. This work provides a first approximation to assess how much data is required to produce good performance in multitask prediction exercises.

The novel sigma-2 receptor ligand SW43 stabilizes pancreas cancer progression in combination with gemcitabine

PubMed Central

2010-01-01

Background Sigma-2 receptors are over-expressed in proliferating cancer cells, making an attractive target for the targeted treatment of pancreatic cancer. In this study, we investigated the role of the novel sigma-2 receptor ligand SW43 to induce apoptosis and augment standard chemotherapy. Results The binding affinity for sigma-2 ligands is high in pancreas cancer, and they induce apoptosis with a rank order of SV119 < SW43 < SRM in vitro. Combining these compounds with gemcitabine further increased apoptosis and decreased viability. Our in vivo model showed that sigma-2 ligand treatment decreased tumor volume to the same extent as gemcitabine. However, SW43 combination treatment with gemcitabine was superior to the other compounds and resulted in stabilization of tumor volume during treatment, with minimal toxicities. Conclusions This study shows that the sigma-2 ligand SW43 has the greatest capacity to augment gemcitabine in a pre-clinical model of pancreas cancer and has provided us with the rationale to move this compound forward with clinical investigations for patients with pancreatic cancer. PMID:21092190

Influence of the exchange and correlation functional on the structure of amorphous InSb and In{sub 3}SbTe{sub 2} compounds

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

Gabardi, Silvia; Caravati, Sebastiano; Bernasconi, Marco, E-mail: marco.bernasconi@mater.unimib.it

2016-05-28

We have investigated the structural, vibrational, and electronic properties of the amorphous phase of InSb and In{sub 3}SbTe{sub 2} compounds of interest for applications in phase change non-volatile memories. Models of the amorphous phase have been generated by quenching from the melt by molecular dynamics simulations based on density functional theory. In particular, we have studied the dependence of the structural properties on the choice of the exchange-correlation functional. It turns out that the use of the Becke-Lee-Yang-Parr functional provides models with a much larger fraction of In atoms in a tetrahedral bonding geometry with respect to previous results obtainedmore » with the most commonly used Perdew-Becke-Ernzerhof functional. This outcome is at odd with the properties of Ge{sub 2}Sb{sub 2}Te{sub 5} phase change compound for which the two exchange-correlation functionals yield very similar results on the structure of the amorphous phase.« less

Structure of Thermobifida fusca DyP-type peroxidase and activity towards Kraft lignin and lignin model compounds.

PubMed

Rahmanpour, Rahman; Rea, Dean; Jamshidi, Shirin; Fülöp, Vilmos; Bugg, Timothy D H

2016-03-15

A Dyp-type peroxidase enzyme from thermophilic cellulose degrader Thermobifida fusca (TfuDyP) was investigated for catalytic ability towards lignin oxidation. TfuDyP was characterised kinetically against a range of phenolic substrates, and a compound I reaction intermediate was observed via pre-steady state kinetic analysis at λmax 404 nm. TfuDyP showed reactivity towards Kraft lignin, and was found to oxidise a β-aryl ether lignin model compound, forming an oxidised dimer. A crystal structure of TfuDyP was determined, to 1.8 Å resolution, which was found to contain a diatomic oxygen ligand bound to the heme centre, positioned close to active site residues Asp-203 and Arg-315. The structure contains two channels providing access to the heme cofactor for organic substrates and hydrogen peroxide. Site-directed mutant D203A showed no activity towards phenolic substrates, but reduced activity towards ABTS, while mutant R315Q showed no activity towards phenolic substrates, nor ABTS. Copyright © 2016 Elsevier Inc. All rights reserved.

Virtual Ligand Screening Using PL-PatchSurfer2, a Molecular Surface-Based Protein-Ligand Docking Method.

PubMed

Shin, Woong-Hee; Kihara, Daisuke

2018-01-01

Virtual screening is a computational technique for predicting a potent binding compound for a receptor protein from a ligand library. It has been a widely used in the drug discovery field to reduce the efforts of medicinal chemists to find hit compounds by experiments.Here, we introduce our novel structure-based virtual screening program, PL-PatchSurfer, which uses molecular surface representation with the three-dimensional Zernike descriptors, which is an effective mathematical representation for identifying physicochemical complementarities between local surfaces of a target protein and a ligand. The advantage of the surface-patch description is its tolerance on a receptor and compound structure variation. PL-PatchSurfer2 achieves higher accuracy on apo form and computationally modeled receptor structures than conventional structure-based virtual screening programs. Thus, PL-PatchSurfer2 opens up an opportunity for targets that do not have their crystal structures. The program is provided as a stand-alone program at http://kiharalab.org/plps2 . We also provide files for two ligand libraries, ChEMBL and ZINC Drug-like.

SAR studies on truxillic acid mono esters as a new class of antinociceptive agents targeting fatty acid binding proteins.

PubMed

Yan, Su; Elmes, Matthew W; Tong, Simon; Hu, Kongzhen; Awwa, Monaf; Teng, Gary Y H; Jing, Yunrong; Freitag, Matthew; Gan, Qianwen; Clement, Timothy; Wei, Longfei; Sweeney, Joseph M; Joseph, Olivia M; Che, Joyce; Carbonetti, Gregory S; Wang, Liqun; Bogdan, Diane M; Falcone, Jerome; Smietalo, Norbert; Zhou, Yuchen; Ralph, Brian; Hsu, Hao-Chi; Li, Huilin; Rizzo, Robert C; Deutsch, Dale G; Kaczocha, Martin; Ojima, Iwao

2018-05-24

Fatty acid binding proteins (FABPs) serve as critical modulators of endocannabinoid signaling by facilitating the intracellular transport of anandamide and whose inhibition potentiates anandamide signaling. Our previous work has identified a novel small-molecule FABP inhibitor, α-truxillic acid 1-naphthyl monoester (SB-FI-26, 3) that has shown efficacy as an antinociceptive and anti-inflammatory agent in rodent models. In the present work, we have performed an extensive SAR study on a series of 3-analogs as novel FABP inhibitors based on computer-aided inhibitor drug design and docking analysis, chemical synthesis and biological evaluations. The prediction of binding affinity of these analogs to target FABP3, 5 and 7 isoforms was performed using the AutoDock 4.2 program, using the recently determined co-crystal structures of 3 with FABP5 and FABP7. The compounds with high docking scores were synthesized and evaluated for their activities using a fluorescence displacement assay against FABP3, 5 and 7. During lead optimization, compound 3l emerged as a promising compound with the Ki value of 0.21 μM for FABP 5, 4-fold more potent than 3 (Ki, 0.81 μM). Nine compounds exhibit similar or better binding affinity than 3, including compounds 4b (Ki, 0.55 μM) and 4e (Ki, 0.68 μM). Twelve compounds are selective for FABP5 and 7 with >10 μM Ki values for FABP3, indicating a safe profile to avoid potential cardiotoxicity concerns. Compounds 4f, 4j and 4k showed excellent selectivity for FABP5 and would serve as other new lead compounds. Compound 3a possessed high affinity and high selectivity for FABP7. Compounds with moderate to high affinity for FABP5 displayed antinociceptive effects in mice while compounds with low FABP5 affinity lacked in vivo efficacy. In vivo pain model studies in mice revealed that exceeding hydrophobicity significantly affects the efficacy. Thus, among the compounds with high affinity to FABP5 in vitro, the compounds with moderate hydrophobicity were identified as promising new lead compounds for the next round of optimization, including compounds 4b and 4j. For select cases, computational analysis of the observed SAR, especially the selectivity of new inhibitors to particular FABP isoforms, by comparing docking poses, interaction map, and docking energy scores has provided useful insights. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Selective cleavage of the C(α)-C(β) linkage in lignin model compounds via Baeyer-Villiger oxidation.

PubMed

Patil, Nikhil D; Yao, Soledad G; Meier, Mark S; Mobley, Justin K; Crocker, Mark

2015-03-21

Lignin is an amorphous aromatic polymer derived from plants and is a potential source of fuels and bulk chemicals. Herein, we present a survey of reagents for selective stepwise oxidation of lignin model compounds. Specifically, we have targeted the oxidative cleavage of Cα-Cβ bonds as a means to depolymerize lignin and obtain useful aromatic compounds. In this work, we prepared several lignin model compounds that possess structures, characteristic reactivity, and linkages closely related to the parent lignin polymer. We observed that selective oxidation of benzylic hydroxyl groups, followed by Baeyer-Villiger oxidation of the resulting ketones, successfully cleaves the Cα-Cβ linkage in these model compounds.

Relationship between soybean yield/quality and soil quality in a major soybean-producing area based on a 2D-QSAR model

NASA Astrophysics Data System (ADS)

Gao, Ming; Li, Shiwei

2017-05-01

Based on experimental data of the soybean yield and quality from 30 sampling points, a quantitative structure-activity relationship model (2D-QSAR) was established using the soil quality (elements, pH, organic matter content and cation exchange capacity) as independent variables and soybean yield or quality as the dependent variable, with SPSS software. During the modeling, the full data set (30 and 14 compounds) was divided into a training set (24 and 11 compounds) for model generation and a test set (6 and 3 compounds) for model validation. The R2 values of the resulting models and data were 0.826 and 0.808 for soybean yield and quality, respectively, and all regression coefficients were significant (P < 0.05). The correlation coefficient R2pred of observed values and predicted values of the soybean yield and soybean quality in the test set were 0.961 and 0.956, respectively, indicating that the models had a good predictive ability. Moreover, the Mo, Se, K, N and organic matter contents and the cation exchange capacity of soil had a positive effect on soybean production, and the B, Mo, Se, K and N contents and cation exchange coefficient had a positive effect on soybean quality. The results are instructive for enhancing soils to improve the yield and quality of soybean, and this method can also be used to study other crops or regions, providing a theoretical basis to improving the yield and quality of crops.

CANDO and the infinite drug discovery frontier

PubMed Central

Minie, Mark; Chopra, Gaurav; Sethi, Geetika; Horst, Jeremy; White, George; Roy, Ambrish; Hatti, Kaushik; Samudrala, Ram

2014-01-01

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound–proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12–25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 ‘high value’ predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering. PMID:24980786

Monitoring the apple polyphenol oxidase-modulated adduct formation of phenolic and amino compounds.

PubMed

Reinkensmeier, Annika; Steinbrenner, Katrin; Homann, Thomas; Bußler, Sara; Rohn, Sascha; Rawel, Hashadrai M

2016-03-01

Minimally processed fruit products such as smoothies are increasingly coming into demand. However, they are often combined with dairy ingredients. In this combination, phenolic compounds, polyphenoloxidases, and amino compounds could interact. In this work, a model approach is presented where apple serves as a source for a high polyphenoloxidase activity for modulating the reactions. The polyphenoloxidase activity ranged from 128 to 333nakt/mL in different apple varieties. From these, 'Braeburn' was found to provide the highest enzymatic activity. The formation and stability of resulting chromogenic conjugates was investigated. The results show that such adducts are not stable and possible degradation mechanisms leading to follow-up products formed are proposed. Finally, apple extracts were used to modify proteins and their functional properties characterized. There were retaining antioxidant properties inherent to phenolic compounds after adduct formation. Consequently, such interactions may also be utilized to improve the textural quality of food products. Copyright © 2015 Elsevier Ltd. All rights reserved.

3D-QSAR and docking studies on 1-hydroxypyridin-2-one compounds as mutant isocitrate dehydrogenase 1 inhibitors

NASA Astrophysics Data System (ADS)

Wang, Zhenya; Chang, Yiqun; Han, Yushui; Liu, Kangjia; Hou, Jinsong; Dai, Chengli; Zhai, Yuanhao; Guo, Jialiang; Sun, Pinghua; Lin, Jing; Chen, Weimin

2016-11-01

Mutation of isocitrate dehydrogenase 1 (IDH1) which is frequently found in certain cancers such as glioma, sarcoma and acute myeloid leukemia, has been proven to be a potent drug target for cancer therapy. In silico methodologies such as 3D-QSAR and molecular docking were performed to explore compounds with better mutant isocitrate dehydrogenase 1 (MIDH1) inhibitory activity using a series of 40 newly reported 1-hydroxypyridin-2-one compounds as MIDH1 inhibitors. The satisfactory CoMFA and CoMSIA models obtained after internal and external cross-validation gave q2 values of 0.691 and 0.535, r2 values of 0.984 and 0.936, respectively. 3D contour maps generated from CoMFA and CoMSIA along with the docking results provided information about the structural requirements for better MIDH1 inhibitory activity. Based on the structure-activity relationship, 17 new potent molecules with better predicted activity than the most active compound in the literature have been designed.

Structure-Based Design of Potent Bcl-2/Bcl-xL Inhibitors with Strong in Vivo Antitumor Activity

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

Zhou, Haibin; Aguilar, Angelo; Chen, Jianfang

Bcl-2 and Bcl-xL are key apoptosis regulators and attractive cancer therapeutic targets. We have designed and optimized a class of small-molecule inhibitors of Bcl-2 and Bcl-xL containing a 4,5-diphenyl-1H-pyrrole-3-carboxylic acid core structure. A 1.4 {angstrom} resolution crystal structure of a lead compound, 12, complexed with Bcl-xL has provided a basis for our optimization. The most potent compounds, 14 and 15, bind to Bcl-2 and Bcl-xL with subnanomolar K{sub i} values and are potent antagonists of Bcl-2 and Bcl-xL in functional assays. Compounds 14 and 15 inhibit cell growth with low nanomolar IC{sub 50} values in multiple small-cell lung cancer cellmore » lines and induce robust apoptosis in cancer cells at concentrations as low as 10 nM. Compound 14 also achieves strong antitumor activity in an animal model of human cancer.« less

Modification of PBDEs (BDE-15, BDE-47, BDE-85 and BDE-126) biological toxicity, bio-concentration, persistence and atmospheric long-range transport potential based on the pharmacophore modeling assistant with the full factor experimental design.

PubMed

Jiang, Long; Li, Yu

2016-04-15

In this study, the properties of AhR binding affinity, bio-concentration factor, half-life and vapor pressure were selected as the typical indicators of biological toxicity, bio-concentration, persistence and atmospheric long-range transport potential for polybrominated diphenyl ethers (PBDEs), respectively. A three-dimensional pharmacophore modeling assistant with a full factor experimental design for each property was used to reveal the significant pharmacophore features and the substituent effects to obtain reasonable modified schemes for the selected target PBDEs. Finally, the performances of the persistent organic pollutant (POP) properties, the synthesis feasibility and the fire resistance of the modified compounds were evaluated. The most influential pharmacophore feature for all POP properties was the hydrophobic group, especially the vinyl and propyl groups. Modified compounds with two additional hydrophobic groups exhibited a better regulatory performance. The average reduction in the proportions of the four POP properties for the modified compounds (except for 3-phenyl-BDE-15) was 70.60%, 52.44%, 47.04% and 70.88%. In addition, the energy and the C-Br bond dissociation enthalpy of the four typical PBDEs were higher than those of the modified compounds (except for 3-phenyl-BDE-15), indicating the synthesis feasibility and the lower energy barrier of the modified compounds to release Br free radicals to provide fire resistance. Copyright © 2015 Elsevier B.V. All rights reserved.

A topological substructural molecular design approach for predicting mutagenesis end-points of alpha, beta-unsaturated carbonyl compounds.

PubMed

Pérez-Garrido, Alfonso; Helguera, Aliuska Morales; López, Gabriel Caravaca; Cordeiro, M Natália D S; Escudero, Amalio Garrido

2010-01-31

Chemically reactive, alpha, beta-unsaturated carbonyl compounds are common environmental pollutants able to produce a wide range of adverse effects, including, e.g. mutagenicity. This toxic property can often be related to chemical structure, in particular to specific molecular substructures or fragments (alerts), which can then be used in specialized software or expert systems for predictive purposes. In the past, there have been many attempts to predict the mutagenicity of alpha, beta-unsaturated carbonyl compounds through quantitative structure activity relationships (QSAR) but considering only one exclusive endpoint: the Ames test. Besides, even though those studies give a comprehensive understanding of the phenomenon, they do not provide substructural information that could be useful forward improving expert systems based on structural alerts (SAs). This work reports an evaluation of classification models to probe the mutagenic activity of alpha, beta-unsaturated carbonyl compounds over two endpoints--the Ames and mammalian cell gene mutation tests--based on linear discriminant analysis along with the topological Substructure molecular design (TOPS-MODE) approach. The obtained results showed the better ability of the TOPS-MODE approach in flagging structural alerts for the mutagenicity of these compounds compared to the expert system TOXTREE. Thus, the application of the present QSAR models can aid toxicologists in risk assessment and in prioritizing testing, as well as in the improvement of expert systems, such as the TOXTREE software, where SAs are implemented. 2009 Elsevier Ireland Ltd. All rights reserved.

DEVELOPMENT AND VALIDATION OF AN AIR-TO-BEEF FOOD CHAIN MODEL FOR DIOXIN-LIKE COMPOUNDS

EPA Science Inventory

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 t...

Influence of mastication rate on dynamic flavour release analysed by combined model mouth/proton transfer reaction-mass spectrometry

NASA Astrophysics Data System (ADS)

van Ruth, Saskia M.; Buhr, Katja

2004-12-01

The influence of mastication rate on the dynamic release of seven volatile flavour compounds from sunflower oil was evaluated by combined model mouth/proton transfer reaction-mass spectrometry (PTR-MS). Air/oil partition coefficients were measured by static headspace gas chromatography. The dynamic release of the seven volatile flavour compounds from sunflower oil was significantly affected by the compounds' hydrophobicity and the mastication rate employed in the model mouth. The more hydrophobic compounds were released at a higher rate than their hydrophilic counterparts. Increase in mastication rate increased the maximum concentration measured by 36% on average, and the time to reach this maximum by 35% on average. Mastication affected particularly the release of the hydrophilic compounds. The maximum concentration of the compounds correlated significantly with the compounds' air/oil partition coefficients. The initial release rates over the first 15 s were affected by the type of compound, but not by the mastication rate. During the course of release, the proportions of the hydrophilic compounds to the overall flavour mixture in air decreased. The contribution of the hydrophobic compounds increased. Higher mastication rates, however, increased the proportions of the hydrophilic compounds and decreased those of the hydrophobic compounds.

Zebrafish is a predictive model for identifying compounds that protect against brain toxicity in severe acute organophosphorus intoxication.

PubMed

Faria, Melissa; Prats, Eva; Padrós, Francesc; Soares, Amadeu M V M; Raldúa, Demetrio

2017-04-01

Acute organophosphorus (OP) intoxication is a worldwide clinical and public health problem. In addition to cholinergic crisis, neurodegeneration and brain damage are hallmarks of the severe form of this toxidrome. Recently, we generated a chemical model of severe acute OP intoxication in zebrafish that is characterized by altered head morphology and brain degeneration. The pathophysiological pathways resulting in brain toxicity in this model are similar to those described in humans. The aim of this study was to assess the predictive power of this zebrafish model by testing the effect of a panel of drugs that provide protection in mammalian models. The selected drugs included "standard therapy" drugs (atropine and pralidoxime), reversible acetylcholinesterase inhibitors (huperzine A, galantamine, physostigmine and pyridostigmine), N-methyl-D-aspartate (NMDA) receptor antagonists (MK-801 and memantine), dual-function NMDA receptor and acetylcholine receptor antagonists (caramiphen and benactyzine) and anti-inflammatory drugs (dexamethasone and ibuprofen). The effects of these drugs on zebrafish survival and the prevalence of abnormal head morphology in the larvae exposed to 4 µM chlorpyrifos oxon [1 × median lethal concentration (LC 50 )] were determined. Moreover, the neuroprotective effects of pralidoxime, memantine, caramiphen and dexamethasone at the gross morphological level were confirmed by histopathological and transcriptional analyses. Our results demonstrated that the zebrafish model for severe acute OP intoxication has a high predictive value and can be used to identify new compounds that provide neuroprotection against severe acute OP intoxication.

Modeling the surface tension of complex, reactive organic-inorganic mixtures

NASA Astrophysics Data System (ADS)

Schwier, A. N.; Viglione, G. A.; Li, Z.; McNeill, V. F.

2013-01-01

Atmospheric aerosols can contain thousands of organic compounds which impact aerosol surface tension, affecting aerosol properties such as cloud condensation nuclei (CCN) ability. We present new experimental data for the surface tension of complex, reactive organic-inorganic aqueous mixtures mimicking tropospheric aerosols. Each solution contained 2-6 organic compounds, including methylglyoxal, glyoxal, formaldehyde, acetaldehyde, oxalic acid, succinic acid, leucine, alanine, glycine, and serine, with and without ammonium sulfate. We test two surface tension models and find that most reactive, complex, aqueous organic mixtures which do not contain salt are well-described by a weighted Szyszkowski-Langmuir (S-L) model which was first presented by Henning et al. (2005). Two approaches for modeling the effects of salt were tested: (1) the Tuckermann approach (an extension of the Henning model with an additional explicit salt term), and (2) a new implicit method proposed here which employs experimental surface tension data obtained for each organic species in the presence of salt used with the Henning model. We recommend the use of method (2) for surface tension modeling because the Henning model (using data obtained from organic-inorganic systems) and Tuckermann approach provide similar modeling fits and goodness of fit (χ2) values, yet the Henning model is a simpler and more physical approach to modeling the effects of salt, requiring less empirically determined parameters.

Thermodynamically Feasible Kinetic Models of Reaction Networks

PubMed Central

Ederer, Michael; Gilles, Ernst Dieter

2007-01-01

The dynamics of biological reaction networks are strongly constrained by thermodynamics. An holistic understanding of their behavior and regulation requires mathematical models that observe these constraints. However, kinetic models may easily violate the constraints imposed by the principle of detailed balance, if no special care is taken. Detailed balance demands that in thermodynamic equilibrium all fluxes vanish. We introduce a thermodynamic-kinetic modeling (TKM) formalism that adapts the concepts of potentials and forces from irreversible thermodynamics to kinetic modeling. In the proposed formalism, the thermokinetic potential of a compound is proportional to its concentration. The proportionality factor is a compound-specific parameter called capacity. The thermokinetic force of a reaction is a function of the potentials. Every reaction has a resistance that is the ratio of thermokinetic force and reaction rate. For mass-action type kinetics, the resistances are constant. Since it relies on the thermodynamic concept of potentials and forces, the TKM formalism structurally observes detailed balance for all values of capacities and resistances. Thus, it provides an easy way to formulate physically feasible, kinetic models of biological reaction networks. The TKM formalism is useful for modeling large biological networks that are subject to many detailed balance relations. PMID:17208985

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

NASA Astrophysics Data System (ADS)

Zhi, Hui; Zheng, Junxia; Chang, Yiqun; Li, Qingguo; Liao, Guochao; Wang, Qi; Sun, Pinghua

2015-10-01

Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q2 value of 0.792 and an r2 value of 0.985. The best CoMSIA model predicted a q2 value of 0.633 and an r2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients (rpred2) of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted.

Artificial neural networks to model formulation-property correlations in the process of inline-compounding on an injection moulding machine

NASA Astrophysics Data System (ADS)

Moritzer, Elmar; Müller, Ellen; Martin, Yannick; Kleeschulte, Rainer

2015-05-01

Today the global market poses great challenges for industrial product development. Complexity, diversity of variants, flexibility and individuality are just some of the features that products have to offer today. In addition, the product series have shorter lifetimes. Because of their high capacity for adaption, polymers are increasingly able to displace traditional materials such as wood, glass and metals from various fields of application. Polymers can only be used to substitute other materials, however, if they are optimally suited to the applications in question. Hence, product-specific material development is becoming increasingly important. Integrating the compounding step in the injection moulding process permits a more efficient and faster development process for a new polymer formulation, making it possible to create new product-specific materials. This process is called inline-compounding on an injection moulding machine. The entire process sequence is supported by software from Bayer Technology called Product Design Workbench (PDWB), which provides assistance in all the individual steps from data management, via analysis and model compilation, right through to the optimization of the formulation and the design of experiments. The software is based on artificial neural networks and can model the formulation-property correlations and thus enable different formulations to be optimized. In the study presented, the workflow and the modelling with the software are presented.

In Silico Analysis of the Association Relationship between Neuroprotection and Flavors of Traditional Chinese Medicine Based on the mGluRs

PubMed Central

Qiao, Liansheng; Chen, Yankun; Zhao, Bowen; Gu, Yu; Huo, Xiaoqian; Zhang, Yanling; Li, Gongyu

2018-01-01

The metabotropic glutamate receptors (mGluRs) are known as both synaptic receptors and taste receptors. This feature is highly similar to the Property and Flavor theory of Traditional Chinese medicine (TCM), which has the pharmacological effect and flavor. In this study, six ligand based pharmacophore (LBP) models, seven homology modeling models, and fourteen molecular docking models of mGluRs were built based on orthosteric and allosteric sites to screening potential compounds from Traditional Chinese Medicine Database (TCMD). Based on the Pharmacopoeia of the People’s Republic of China, TCMs of compounds and their flavors were traced and listed. According to the tracing result, we found that the TCMs of the compounds which bound to orthosteric sites of mGluRs are highly correlated to a sweet flavor, while the allosteric site corresponds to a bitter flavor. Meanwhile, the pharmacological effects of TCMs with highly frequent flavors were further analyzed. We found that those TCMs play a neuroprotective role through the efficiencies of detumescence, promoting blood circulation, analgesic effect, and so on. This study provides a guide for developing new neuroprotective drugs from TCMs which target mGluRs. Moreover, it is the first study to present a novel approach to discuss the association relationship between flavor and the neuroprotective mechanism of TCM based on mGluRs. PMID:29320397

Large Dataset of Acute Oral Toxicity Data Created for Testing ...

EPA Pesticide Factsheets

Acute toxicity data is a common requirement for substance registration in the US. Currently only data derived from animal tests are accepted by regulatory agencies, and the standard in vivo tests use lethality as the endpoint. Non-animal alternatives such as in silico models are being developed due to animal welfare and resource considerations. We compiled a large dataset of oral rat LD50 values to assess the predictive performance currently available in silico models. Our dataset combines LD50 values from five different sources: literature data provided by The Dow Chemical Company, REACH data from eChemportal, HSDB (Hazardous Substances Data Bank), RTECS data from Leadscope, and the training set underpinning TEST (Toxicity Estimation Software Tool). Combined these data sources yield 33848 chemical-LD50 pairs (data points), with 23475 unique data points covering 16439 compounds. The entire dataset was loaded into a chemical properties database. All of the compounds were registered in DSSTox and 59.5% have publically available structures. Compounds without a structure in DSSTox are currently having their structures registered. The structural data will be used to evaluate the predictive performance and applicable chemical domains of three QSAR models (TIMES, PROTOX, and TEST). Future work will combine the dataset with information from ToxCast assays, and using random forest modeling, assess whether ToxCast assays are useful in predicting acute oral toxicity. Pre

A quantum chemical study of molecular properties and QSPR modeling of oximes, amidoximes and hydroxamic acids with nucleophilic activity against toxic organophosphorus agents

NASA Astrophysics Data System (ADS)

Alencar Filho, Edilson B.; Santos, Aline A.; Oliveira, Boaz G.

2017-04-01

The proposal of this work includes the use of quantum chemical methods and cheminformatics strategies in order to understand the structural profile and reactivity of α-nucleophiles compounds such as oximes, amidoximes and hydroxamic acids, related to hydrolysis rate of organophosphates. Theoretical conformational study of 41 compounds were carried out through the PM3 semiempirical Hamiltonian, followed by the geometry optimization at the B3LYP/6-31+G(d,p) level of theory, complemented by Polarized Continuum Model (PCM) to simulate the aqueous environment. In line with the experimental hypothesis about hydrolytic power, the strength of the Intramolecular Hydrogen Bonds (IHBs) at light of the Bader's Quantum Theory of Atoms in Molecules (QTAIM) is related to the preferential conformations of α-nucleophiles. A set of E-Dragon descriptors (1,666) were submitted to a variable selection through Ordered Predictor Selection (OPS) algorithm. Five descriptors, including atomic charges obtained from the Natural Bond Orbitals (NBO) protocol jointly with a fragment index associated to the presence/absence of IHBs, provided a Quantitative Structure-Property Relationship (QSPR) model via Multiple Linear Regression (MLR). This model showed good validation parameters (R2 = 0.80, Qloo2 = 0.67 and Qext2 = 0.81) and allowed the identification of significant physicochemical features on the molecular scaffold in order to design compounds potentially more active against organophosphorus poisoning.

A Screenable In Vivo Assay for Mitochondrial Modulators Using Transgenic Bioluminescent Caenorhabditis elegans.

PubMed

Lagido, Cristina; McLaggan, Debbie; Glover, L Anne

2015-10-16

The multicellular model organism Caenorhabditis elegans is a small nematode of approximately 1 mm in size in adulthood that is genetically and experimentally tractable. It is economical and easy to culture and dispense in liquid medium which makes it well suited for medium-throughput screening. We have previously validated the use of transgenic luciferase expressing C. elegans strains to provide rapid in vivo assessment of the nematode's ATP levels.(1-3) Here we present the required materials and procedure to carry out bioassays with the bioluminescent C. elegans strains PE254 or PE255 (or any of their derivative strains). The protocol allows for in vivo detection of sublethal effects of drugs that may identify mitochondrial toxicity, as well as for in vivo detection of potential beneficial drug effects. Representative results are provided for the chemicals paraquat, rotenone, oxaloacetate and for four firefly luciferase inhibitory compounds. The methodology can be scaled up to provide a platform for screening drug libraries for compounds capable of modulating mitochondrial function. Pre-clinical evaluation of drug toxicity is often carried out on immortalized cancerous human cell lines which derive ATP mostly from glycolysis and are often tolerant of mitochondrial toxicants.(4,5) In contrast, C. elegans depends on oxidative phosphorylation to sustain development into adulthood, drawing a parallel with humans and providing a unique opportunity for compound evaluation in the physiological context of a whole live multicellular organism.

Method to improve lubricity of low-sulfur diesel and gasoline fuels

DOEpatents

Erdemir, Ali

2004-08-31

A method for providing lubricity in fuels and lubricants includes adding a boron compound to a fuel or lubricant to provide a boron-containing fuel or lubricant. The fuel or lubricant may contain a boron compound at a concentration between about 30 ppm and about 3,000 ppm and a sulfur concentration of less than about 500 ppm. A method of powering an engine to minimize wear, by burning a fuel containing boron compounds. The boron compounds include compound that provide boric acid and/or BO.sub.3 ions or monomers to the fuel or lubricant.

Chemical-specific screening criteria for interpretation of biomonitoring data for volatile organic compounds (VOCs)--application of steady-state PBPK model solutions.

PubMed

Aylward, Lesa L; Kirman, Chris R; Blount, Ben C; Hays, Sean M

2010-10-01

The National Health and Nutrition Examination Survey (NHANES) generates population-representative biomonitoring data for many chemicals including volatile organic compounds (VOCs) in blood. However, no health or risk-based screening values are available to evaluate these data from a health safety perspective or to use in prioritizing among chemicals for possible risk management actions. We gathered existing risk assessment-based chronic exposure reference values such as reference doses (RfDs), reference concentrations (RfCs), tolerable daily intakes (TDIs), cancer slope factors, etc. and key pharmacokinetic model parameters for 47 VOCs. Using steady-state solutions to a generic physiologically-based pharmacokinetic (PBPK) model structure, we estimated chemical-specific steady-state venous blood concentrations across chemicals associated with unit oral and inhalation exposure rates and with chronic exposure at the identified exposure reference values. The geometric means of the slopes relating modeled steady-state blood concentrations to steady-state exposure to a unit oral dose or unit inhalation concentration among 38 compounds with available pharmacokinetic parameters were 12.0 microg/L per mg/kg-d (geometric standard deviation [GSD] of 3.2) and 3.2 microg/L per mg/m(3) (GSD=1.7), respectively. Chemical-specific blood concentration screening values based on non-cancer reference values for both oral and inhalation exposure range from 0.0005 to 100 microg/L; blood concentrations associated with cancer risk-specific doses at the 1E-05 risk level ranged from 5E-06 to 6E-02 microg/L. The distribution of modeled steady-state blood concentrations associated with unit exposure levels across VOCs may provide a basis for estimating blood concentration screening values for VOCs that lack chemical-specific pharmacokinetic data. The screening blood concentrations presented here provide a tool for risk assessment-based evaluation of population biomonitoring data for VOCs and are most appropriately applied to central tendency estimates for such datasets. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Synthesis, Purification, and Characterization of a [mu]-(1,3-Propanedithiolato)-Hexacarbonyldiiron

ERIC Educational Resources Information Center

Works, Carmen F.

2007-01-01

A project which exposes students to biologically important transition-metal chemistry is illustrated by taking an example of the iron-carbonyl compound, [mu]-(1,3-Propanedithiolaro)-hexa-carbonyldiiron as a structural model for an iron-only hydro-genase. The project provides the students with experience of Schlenk line techniques, purification,…

Human stem cells and drug screening: opportunities and challenges.

PubMed

Ebert, Allison D; Svendsen, Clive N

2010-05-01

High-throughput screening technologies are widely used in the early stages of drug discovery to rapidly evaluate the properties of thousands of compounds. However, they generally rely on testing compound libraries on highly proliferative immortalized or cancerous cell lines, which do not necessarily provide an accurate indication of the effects of compounds in normal human cells or the specific cell type under study. Recent advances in stem cell technology have the potential to allow production of a virtually limitless supply of normal human cells that can be differentiated into any specific cell type. Moreover, using induced pluripotent stem cell technology, they can also be generated from patients with specific disease traits, enabling more relevant modelling and drug screens. This article discusses the opportunities and challenges for the use of stem cells in drug screening with a focus on induced pluripotent stem cells.

Determination of the n-octanol/water partition coefficients of weakly ionizable basic compounds by reversed-phase high-performance liquid chromatography with neutral model compounds.

PubMed

Liang, Chao; Han, Shu-ying; Qiao, Jun-qin; Lian, Hong-zhen; Ge, Xin

2014-11-01

A strategy to utilize neutral model compounds for lipophilicity measurement of ionizable basic compounds by reversed-phase high-performance liquid chromatography is proposed in this paper. The applicability of the novel protocol was justified by theoretical derivation. Meanwhile, the linear relationships between logarithm of apparent n-octanol/water partition coefficients (logKow '') and logarithm of retention factors corresponding to the 100% aqueous fraction of mobile phase (logkw ) were established for a basic training set, a neutral training set and a mixed training set of these two. As proved in theory, the good linearity and external validation results indicated that the logKow ''-logkw relationships obtained from a neutral model training set were always reliable regardless of mobile phase pH. Afterwards, the above relationships were adopted to determine the logKow of harmaline, a weakly dissociable alkaloid. As far as we know, this is the first report on experimental logKow data for harmaline (logKow = 2.28 ± 0.08). Introducing neutral compounds into a basic model training set or using neutral model compounds alone is recommended to measure the lipophilicity of weakly ionizable basic compounds especially those with high hydrophobicity for the advantages of more suitable model compound choices and convenient mobile phase pH control. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electromembrane extraction of zwitterionic compounds as acid or base: comparison of extraction behavior at acidic and basic pHs.

PubMed

Nojavan, Saeed; Pourahadi, Ahmad; Hosseiny Davarani, Saied Saeed; Morteza-Najarian, Amin; Beigzadeh Abbassi, Mojtaba

2012-10-01

This study has performed on electromembrane extraction (EME) of some zwitterionic compounds based on their acidic and basic properties. High performance liquid chromatography (HPLC) equipped with UV detection was used for determination of model compounds. Cetirizine (CTZ) and mesalazine (MS) were chosen as model compounds, and each of them was extracted from acidic (as a cation) and basic (as an anion) sample solutions, separately. 1-Octanol and 2-nitrophenyl octylether (NPOE) were used as the common supported liquid membrane (SLM) solvents. EME parameters, such as extraction time, extraction voltage and pH of donor and acceptor solutions were studied in details for cationic and anionic forms of each model compound and obtained results for two ionic forms (cationic and anionic) of each compound were compared together. Results showed that zwitterionic compounds could be extracted in both cationic and anionic forms. Moreover, it was found that the extraction of anionic form of each model compound could be done in low voltages when 1-octanol was used as the SLM solvent. Results showed that charge type was not highly effective on the extraction efficiency of model compounds whereas the position of charge within the molecule was the key parameter. In optimized conditions, enrichment factors (EF) of 27-60 that corresponded to recoveries ranging from 39 to 86% were achieved. Copyright © 2012 Elsevier B.V. All rights reserved.

Predicting trace organic compound attenuation by ozone oxidation: Development of indicator and surrogate models.

PubMed

Park, Minkyu; Anumol, Tarun; Daniels, Kevin D; Wu, Shimin; Ziska, Austin D; Snyder, Shane A

2017-08-01

Ozone oxidation has been demonstrated to be an effective treatment process for the attenuation of trace organic compounds (TOrCs); however, predicting TOrC attenuation by ozone processes is challenging in wastewaters. Since ozone is rapidly consumed, determining the exposure times of ozone and hydroxyl radical proves to be difficult. As direct potable reuse schemes continue to gain traction, there is an increasing need for the development of real-time monitoring strategies for TOrC abatement in ozone oxidation processes. Hence, this study is primarily aimed at developing indicator and surrogate models for the prediction of TOrC attenuation by ozone oxidation. To this end, the second-order kinetic equations with a second-phase R ct value (ratio of hydroxyl radical exposure to molecular ozone exposure) were used to calculate comparative kinetics of TOrC attenuation and the reduction of indicator and spectroscopic surrogate parameters, including UV absorbance at 254 nm (UVA 254 ) and total fluorescence (TF). The developed indicator model using meprobamate as an indicator compound and the surrogate models with UVA 254 and TF exhibited good predictive power for the attenuation of 13 kinetically distinct TOrCs in five filtered and unfiltered wastewater effluents (R 2 values > 0.8). This study is intended to help provide a guideline for the implementation of indicator/surrogate models for real-time monitoring of TOrC abatement with ozone processes and integrate them into a regulatory framework in water reuse. Copyright © 2017 Elsevier Ltd. All rights reserved.

L-Arginyl-3,4-Spermidine is neuroprotective in several in vitro models of neurodegeneration and in vivo ischaemia without suppressing synaptic transmission

PubMed Central

Morrison, Barclay; Pringle, Ashley K; McManus, Terence; Ellard, John; Bradley, Mark; Signorelli, Francesco; Iannotti, Fausto; Sundstrom, Lars E

2002-01-01

Stroke is the third most common cause of death in the world, and there is a clear need to develop new therapeutics for the stroke victim. To address this need, we generated a combinatorial library of polyamine compounds based on sFTX-3.3 toxin from which L-Arginyl-3,4-Spermidine (L-Arg-3,4) emerged as a lead neuroprotective compound. In the present study, we have extended earlier results to examine the compound's neuroprotective actions in greater detail. In an in vitro ischaemia model, L-Arg-3,4 significantly reduced CA1 cell death when administered prior to induction of 60 min of ischaemia as well as when administered immediately after ischaemia. Surprisingly, L-Arg-3,4 continued to prevent cell death significantly when administration was delayed for as long as 60 min after ischaemia. L-Arg-3,4 significantly reduced cell death in excitotoxicity models mediated by glutamate, NMDA, AMPA, or kainate. Unlike glutamate receptor antagonists, 300 μM L-Arg-3,4 did not suppress synaptic transmission as measured by evoked responses in acute hippocampal slices. L-Arg-3,4 provided significant protection, in vitro, in a superoxide mediated injury model and prevented an increase of superoxide production after AMPA or NMDA stimulation. It also decreased nitric oxide production after in vitro ischaemia and NMDA stimulation, but did so without inhibiting nitric oxide synthase directly. Furthermore, L-Arg-3,4 was significantly neuroprotective in an in vivo model of global forebrain ischaemia, without any apparent neurological side-effects. Taken together, these results demonstrate that L-Arg-3,4 is protective in several models of neurodegeneration and may have potential as a new therapeutic compound for the treatment of stroke, trauma, and other neurodegenerative diseases. PMID:12466235

Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data.

PubMed

Kim, Marlene Thai; Huang, Ruili; Sedykh, Alexander; Wang, Wenyi; Xia, Menghang; Zhu, Hao

2016-05-01

Hepatotoxicity accounts for a substantial number of drugs being withdrawn from the market. Using traditional animal models to detect hepatotoxicity is expensive and time-consuming. Alternative in vitro methods, in particular cell-based high-throughput screening (HTS) studies, have provided the research community with a large amount of data from toxicity assays. Among the various assays used to screen potential toxicants is the antioxidant response element beta lactamase reporter gene assay (ARE-bla), which identifies chemicals that have the potential to induce oxidative stress and was used to test > 10,000 compounds from the Tox21 program. The ARE-bla computational model and HTS data from a big data source (PubChem) were used to profile environmental and pharmaceutical compounds with hepatotoxicity data. Quantitative structure-activity relationship (QSAR) models were developed based on ARE-bla data. The models predicted the potential oxidative stress response for known liver toxicants when no ARE-bla data were available. Liver toxicants were used as probe compounds to search PubChem Bioassay and generate a response profile, which contained thousands of bioassays (> 10 million data points). By ranking the in vitro-in vivo correlations (IVIVCs), the most relevant bioassay(s) related to hepatotoxicity were identified. The liver toxicants profile contained the ARE-bla and relevant PubChem assays. Potential toxicophores for well-known toxicants were created by identifying chemical features that existed only in compounds with high IVIVCs. Profiling chemical IVIVCs created an opportunity to fully explore the source-to-outcome continuum of modern experimental toxicology using cheminformatics approaches and big data sources. Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H. 2016. Mechanism profiling of hepatotoxicity caused by oxidative stress using antioxidant response element reporter gene assay models and big data. Environ Health Perspect 124:634-641; http://dx.doi.org/10.1289/ehp.1509763.

Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data

PubMed Central

Kim, Marlene Thai; Huang, Ruili; Sedykh, Alexander; Wang, Wenyi; Xia, Menghang; Zhu, Hao

2015-01-01

Background: Hepatotoxicity accounts for a substantial number of drugs being withdrawn from the market. Using traditional animal models to detect hepatotoxicity is expensive and time-consuming. Alternative in vitro methods, in particular cell-based high-throughput screening (HTS) studies, have provided the research community with a large amount of data from toxicity assays. Among the various assays used to screen potential toxicants is the antioxidant response element beta lactamase reporter gene assay (ARE-bla), which identifies chemicals that have the potential to induce oxidative stress and was used to test > 10,000 compounds from the Tox21 program. Objective: The ARE-bla computational model and HTS data from a big data source (PubChem) were used to profile environmental and pharmaceutical compounds with hepatotoxicity data. Methods: Quantitative structure–activity relationship (QSAR) models were developed based on ARE-bla data. The models predicted the potential oxidative stress response for known liver toxicants when no ARE-bla data were available. Liver toxicants were used as probe compounds to search PubChem Bioassay and generate a response profile, which contained thousands of bioassays (> 10 million data points). By ranking the in vitro–in vivo correlations (IVIVCs), the most relevant bioassay(s) related to hepatotoxicity were identified. Results: The liver toxicants profile contained the ARE-bla and relevant PubChem assays. Potential toxicophores for well-known toxicants were created by identifying chemical features that existed only in compounds with high IVIVCs. Conclusion: Profiling chemical IVIVCs created an opportunity to fully explore the source-to-outcome continuum of modern experimental toxicology using cheminformatics approaches and big data sources. Citation: Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H. 2016. Mechanism profiling of hepatotoxicity caused by oxidative stress using antioxidant response element reporter gene assay models and big data. Environ Health Perspect 124:634–641; http://dx.doi.org/10.1289/ehp.1509763 PMID:26383846

Finite Element Analysis of Walking Beam of a New Compound Adjustment Balance Pumping Unit

NASA Astrophysics Data System (ADS)

Wu, Jufei; Wang, Qian; Han, Yunfei

2017-12-01

In this paper, taking the designer of the new compound balance pumping unit beam as our research target, the three-dimensional model is established by Solid Works, the load and the constraint are determined. ANSYS Workbench is used to analyze the tail and the whole of the beam, the stress and deformation are obtained to meet the strength requirements. The finite element simulation and theoretical calculation of the moment of the center axis beam are carried out. The finite element simulation results are compared with the calculated results of the theoretical mechanics model to verify the correctness of the theoretical calculation. Finally, the finite element analysis is consistent with the theoretical calculation results. The theoretical calculation results are preferable, and the bending moment value provides the theoretical reference for the follow-up optimization and research design.

Roles of small laccases from Streptomyces in lignin degradation.

PubMed

Majumdar, Sudipta; Lukk, Tiit; Solbiati, Jose O; Bauer, Stefan; Nair, Satish K; Cronan, John E; Gerlt, John A

2014-06-24

Laccases (EC 1.10.3.2) are multicopper oxidases that can oxidize a range of substrates, including phenols, aromatic amines, and nonphenolic substrates. To investigate the involvement of the small Streptomyces laccases in lignin degradation, we generated acid-precipitable polymeric lignin obtained in the presence of wild-type Streptomyces coelicolor A3(2) (SCWT) and its laccase-less mutant (SCΔLAC) in the presence of Miscanthus x giganteus lignocellulose. The results showed that strain SCΔLAC was inefficient in degrading lignin compared to strain SCWT, thereby supporting the importance of laccase for lignin degradation by S. coelicolor A3(2). We also studied the lignin degradation activity of laccases from S. coelicolor A3(2), Streptomyces lividans TK24, Streptomyces viridosporus T7A, and Amycolatopsis sp. 75iv2 using both lignin model compounds and ethanosolv lignin. All four laccases degraded a phenolic model compound (LM-OH) but were able to oxidize a nonphenolic model compound only in the presence of redox mediators. Their activities are highest at pH 8.0 with a low krel/Kapp for LM-OH, suggesting that the enzymes’ natural substrates must be different in shape or chemical nature. Crystal structures of the laccases from S. viridosporus T7A (SVLAC) and Amycolatopsis sp. 75iv2 were determined both with and without bound substrate. This is the first report of a crystal structure for any laccase bound to a nonphenolic β-O-4 lignin model compound. An additional zinc metal binding site in SVLAC was also identified. The ability to oxidize and/or rearrange ethanosolv lignin provides further evidence of the utility of laccase activity for lignin degradation and/or modification.

Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

PubMed Central

Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

2014-01-01

Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

A Small-molecule Inhibitor, 5′-O-Tritylthymidine, targets FAK and Mdm-2 Interaction, and Blocks Breast and Colon Tumorigenesis in vivo

PubMed Central

Golubovskaya, Vita; Palma, Nadia L.; Zheng, Min; Ho, Baotran; Magis, Andrew; Ostrov, David; Cance, William G.

2013-01-01

Focal Adhesion Kinase (FAK) is overexpressed in many types of tumors and plays an important role in survival. We developed a novel approach, targeting FAK-protein interactions by computer modeling and screening of NCI small molecule drug database. In this report we targeted FAK and Mdm-2 protein interaction to decrease tumor growth. By macromolecular modeling we found a model of FAK and Mdm-2 interaction and performed screening of >200,000 small molecule compounds from NCI database with drug-like characteristics, targeting the FAK-Mdm-2 interaction. We identified 5′-O-Tritylthymidine, called M13 compound that significantly decreased viability in different cancer cells. M13 was docked into the pocket of FAK and Mdm-2 interaction and was directly bound to the FAK-N terminal domain by ForteBio Octet assay. In addition, M13 compound affected FAK and Mdm-2 levels and decreased complex of FAK and Mdm-2 proteins in breast and colon cancer cells. M13 re-activated p53 activity inhibited by FAK with Mdm-2 promoter. M13 decreased viability, clonogenicity, increased detachment and apoptosis in a dose-dependent manner in BT474 breast and in HCT116 colon cancer cells in vitro. M13 decreased FAK, activated p53 and caspase-8 in both cell lines. In addition, M13 decreased breast and colon tumor growth in vivo. M13 activated p53 and decreased FAK in tumor samples consistent with decreased tumor growth. The data demonstrate a novel approach for targeting FAK and Mdm-2 protein interaction, provide a model of FAK and Mdm-2 interaction, identify M13 compound targeting this interaction and decreasing tumor growth that is critical for future targeted therapeutics. PMID:22292771

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.

The uncertainty of biodegradation rate constants of emerging organic compounds in soil and groundwater - A compilation of literature values for 82 substances.

PubMed

Greskowiak, Janek; Hamann, Enrico; Burke, Victoria; Massmann, Gudrun

2017-12-01

The present study reports on biodegradation rate constants of emerging organic compounds (EOCs) in soil and groundwater available in the literature. The major aim of this compilation was to provide an assessment of the uncertainty of hydrological models with respect to the fate of EOCs. The literature search identified a total number of 82 EOCs for which 1st-order rate constants could be derived. It was found that for the majority of compounds degradation rate constants vary over more than three orders of magnitude. Correlation to factors that are well known to affect the degradation rate, such as temperature or redox condition was weak. No correlation at all was found with results from available quantitative structure-activity relationship models. This suggests that many unknown site specific or experimentally specific factors influence the degradation behavior of EOCs in the environment. Thus, local and catchment scale predictive models to estimate EOC concentration at receptors, e.g., receiving waters or drinking water wells, need to consider the large uncertainty in 1st-order rate constants. As a consequence, applying rate constants that were derived from one experiment or field site investigation to other experiments or field sites should be done with extreme caution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Design, synthesis, and protein crystallography of biaryltriazoles as potent tautomerase inhibitors of macrophage migration inhibitory factor.

PubMed

Dziedzic, Pawel; Cisneros, José A; Robertson, Michael J; Hare, Alissa A; Danford, Nadia E; Baxter, Richard H G; Jorgensen, William L

2015-03-04

Optimization is reported for biaryltriazoles as inhibitors of the tautomerase activity of human macrophage migration inhibitory factor (MIF), a proinflammatory cytokine associated with numerous inflammatory diseases and cancer. A combined approach was taken featuring organic synthesis, enzymatic assaying, crystallography, and modeling including free-energy perturbation (FEP) calculations. X-ray crystal structures for 3a and 3b bound to MIF are reported and provided a basis for the modeling efforts. The accommodation of the inhibitors in the binding site is striking with multiple hydrogen bonds and aryl-aryl interactions. Additional modeling encouraged pursuit of 5-phenoxyquinolinyl analogues, which led to the very potent compound 3s. Activity was further enhanced by addition of a fluorine atom adjacent to the phenolic hydroxyl group as in 3w, 3z, 3aa, and 3bb to strengthen a key hydrogen bond. It is also shown that physical properties of the compounds can be modulated by variation of solvent-exposed substituents. Several of the compounds are likely the most potent known MIF tautomerase inhibitors; the most active ones are more than 1000-fold more active than the well-studied (R)-ISO-1 and more than 200-fold more active than the chromen-4-one Orita-13.

A computationally identified compound antagonizes excess FGF-23 signaling in renal tubules and a mouse model of hypophosphatemia

DOE PAGES

Xiao, Zhousheng; Riccardi, Demian; Velazquez, Hector A.; ...

2016-11-22

Fibroblast growth factor–23 (FGF-23) interacts with a binary receptor complex composed of α-Klotho (α-KL) and FGF receptors (FGFRs) to regulate phosphate and vitamin D metabolism in the kidney. Excess FGF-23 production, which causes hypophosphatemia, is genetically inherited or occurs with chronic kidney disease. Among other symptoms, hypophosphatemia causes vitamin D deficiency and the bone-softening disorder rickets. Current therapeutics that target the receptor complex have limited utility clinically. In this paper, using a computationally driven, structure-based, ensemble docking and virtual high-throughput screening approach, we identified four novel compounds predicted to selectively inhibit FGF-23–induced activation of the FGFR/α-KL complex. Additional modeling andmore » functional analysis found that Zinc13407541 bound to FGF-23 and disrupted its interaction with the FGFR1/α-KL complex; experiments in a heterologous cell expression system showed that Zinc13407541 selectivity inhibited α-KL–dependent FGF-23 signaling. Zinc13407541 also inhibited FGF-23 signaling in isolated renal tubules ex vivo and partially reversed the hypophosphatemic effects of excess FGF-23 in a mouse model. Finally, these chemical probes provide a platform to develop lead compounds to treat disorders caused by excess FGF-23.« less

Catalytic pyrolysis of model compounds and waste cooking oil for production of light olefins over La/ZSM-5 catalysts

NASA Astrophysics Data System (ADS)

Li, F. W.; Ding, S. L.; Li, L.; Gao, C.; Zhong, Z.; Wang, S. X.; Li, Z. X.

2016-08-01

Waste cooking oil (WCO) and its model compounds (oleic acid and methyl laurate) are catalytically pyrolyzed in a fixed-bed reactor over La modified ZSM-5 catalysts (La/ZSM-5) aiming for production of C2-C4 light olefins. The LaO content in catalysts was set at 0, 2, 6, 10 and 14 wt%. The gas and liquid products are analyzed. The La/ZSM-5 catalyst with 6% LaO showed higher selectivity to light olefins when WCO and methyl laurate were pyrolyzed, and olefin content was 26% for WCO and 21% for methyl laurate. The catalyst with 10% LaO showed high selectivity to light olefins (28.5%) when oleic acid was pyrolyzed. The liquid products from WCO and model compounds mainly contain esters and aromatic hydrocarbons. More esters were observed in liquid products from methyl laurate and WCO pyrolysis, indicating that it is more difficult to pyrolyze esters and WCO than oleic acid. The coked catalysts were analyzed by temperature-programmed oxidation. The result shows that graphite is the main component of coke. The conversion of WCO to light olefins potentially provides an alternative and sustainable route for production of the key petrochemicals.

Electrochemical reductive dehalogenation of iodine-containing contrast agent pharmaceuticals: Examination of reactions of diatrizoate and iopamidol using the method of rotating ring-disc electrode (RRDE).

PubMed

Yan, Mingquan; Chen, Zhanghao; Li, Na; Zhou, Yuxuan; Zhang, Chenyang; Korshin, Gregory

2018-06-01

This study examined the electrochemical (EC) reduction of iodinated contrast media (ICM) exemplified by iopamidol and diatrizoate. The method of rotating ring-disc electrode (RRDE) was used to elucidate rates and mechanisms of the EC reactions of the selected ICMs. Experiments were carried at varying hydrodynamic conditions, concentrations of iopamidol, diatrizoate, natural organic matter (NOM) and model compounds (resorcinol, catechol, guaiacol) which were used to examine interactions between products of the EC reduction of ICMs and halogenation-active species. The data showed that iopamidol and diatrizoate were EC-reduced at potentials < -0.45 V vs. s.c.e. In the range of potentials -0.65 to -0.85 V their reduction was mass transfer-controlled. The presence of NOM and model compounds did not affect the EC reduction of iopamidol and diatrizoate but active iodine species formed as a result of the EC-induced transformations of these ICMs reacted readily with NOM and model compounds. These data provide more insight into the nature of generation of iodine-containing by-products in the case of reductive degradation of ICMs. Copyright © 2018 Elsevier Ltd. All rights reserved.

A computationally identified compound antagonizes excess FGF-23 signaling in renal tubules and a mouse model of hypophosphatemia.

PubMed

Xiao, Zhousheng; Riccardi, Demian; Velazquez, Hector A; Chin, Ai L; Yates, Charles R; Carrick, Jesse D; Smith, Jeremy C; Baudry, Jerome; Quarles, L Darryl

2016-11-22

Fibroblast growth factor-23 (FGF-23) interacts with a binary receptor complex composed of α-Klotho (α-KL) and FGF receptors (FGFRs) to regulate phosphate and vitamin D metabolism in the kidney. Excess FGF-23 production, which causes hypophosphatemia, is genetically inherited or occurs with chronic kidney disease. Among other symptoms, hypophosphatemia causes vitamin D deficiency and the bone-softening disorder rickets. Current therapeutics that target the receptor complex have limited utility clinically. Using a computationally driven, structure-based, ensemble docking and virtual high-throughput screening approach, we identified four novel compounds predicted to selectively inhibit FGF-23-induced activation of the FGFR/α-KL complex. Additional modeling and functional analysis found that Zinc13407541 bound to FGF-23 and disrupted its interaction with the FGFR1/α-KL complex; experiments in a heterologous cell expression system showed that Zinc13407541 selectivity inhibited α-KL-dependent FGF-23 signaling. Zinc13407541 also inhibited FGF-23 signaling in isolated renal tubules ex vivo and partially reversed the hypophosphatemic effects of excess FGF-23 in a mouse model. These chemical probes provide a platform to develop lead compounds to treat disorders caused by excess FGF-23. Copyright © 2016, American Association for the Advancement of Science.

A computationally identified compound antagonizes excess FGF-23 signaling in renal tubules and a mouse model of hypophosphatemia

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

Xiao, Zhousheng; Riccardi, Demian; Velazquez, Hector A.

Fibroblast growth factor–23 (FGF-23) interacts with a binary receptor complex composed of α-Klotho (α-KL) and FGF receptors (FGFRs) to regulate phosphate and vitamin D metabolism in the kidney. Excess FGF-23 production, which causes hypophosphatemia, is genetically inherited or occurs with chronic kidney disease. Among other symptoms, hypophosphatemia causes vitamin D deficiency and the bone-softening disorder rickets. Current therapeutics that target the receptor complex have limited utility clinically. In this paper, using a computationally driven, structure-based, ensemble docking and virtual high-throughput screening approach, we identified four novel compounds predicted to selectively inhibit FGF-23–induced activation of the FGFR/α-KL complex. Additional modeling andmore » functional analysis found that Zinc13407541 bound to FGF-23 and disrupted its interaction with the FGFR1/α-KL complex; experiments in a heterologous cell expression system showed that Zinc13407541 selectivity inhibited α-KL–dependent FGF-23 signaling. Zinc13407541 also inhibited FGF-23 signaling in isolated renal tubules ex vivo and partially reversed the hypophosphatemic effects of excess FGF-23 in a mouse model. Finally, these chemical probes provide a platform to develop lead compounds to treat disorders caused by excess FGF-23.« less

Design, Synthesis, and Protein Crystallography of Biaryltriazoles as Potent Tautomerase Inhibitors of Macrophage Migration Inhibitory Factor

DOE PAGES

Dziedzic, Pawel; Cisneros, José A.; Robertson, Michael J.; ...

2015-02-20

Optimization is reported for biaryltriazoles as inhibitors of the tautomerase activity of human macrophage migration inhibitory factor (MIF), a proinflammatory cytokine associated with numerous inflammatory diseases and cancer. A combined approach was taken featuring organic synthesis, enzymatic assaying, crystallography, and modeling including free-energy perturbation (FEP) calculations. X-ray crystal structures for 3a and 3b bound to MIF are reported and provided a basis for the modeling efforts. The accommodation of the inhibitors in the binding site is striking with multiple hydrogen bonds and aryl–aryl interactions. Additional modeling encouraged pursuit of 5-phenoxyquinolinyl analogues, which led to the very potent compound 3s. Activitymore » was further enhanced by addition of a fluorine atom adjacent to the phenolic hydroxyl group as in 3w, 3z, 3aa, and 3bb to strengthen a key hydrogen bond. We also show that physical properties of the compounds can be modulated by variation of solvent-exposed substituents. Several of the compounds are likely the most potent known MIF tautomerase inhibitors; the most active ones are more than 1000-fold more active than the well-studied (R)-ISO-1 and more than 200-fold more active than the chromen-4-one Orita-13.« less

Design and laboratory testing of a chamber device to measure total flux of volatile organic compounds from the unsaturated zone under natural conditions.

PubMed

Tillman, Fred D; Smith, James A

2004-11-01

To determine if an aquifer contaminated with volatile organic compounds (VOCs) has potential for natural remediation, all natural processes affecting the fate and transport of VOCs in the subsurface must be identified and quantified. This research addresses the quantification of air-phase volatile organic compounds (VOCs) leaving the unsaturated zone soil gas and entering the atmosphere-including the additional flux provided by advective soil-gas movement induced by barometric pumping. A simple and easy-to-use device for measuring VOC flux under natural conditions is presented. The vertical flux chamber (VFC) was designed using numerical simulations and evaluated in the laboratory. Mass-balance numerical simulations based on continuously stirred tank reactor equations (CSTR) provided information on flux measurement performance of several sampling configurations with the final chamber configuration measuring greater than 96% of model-simulated fluxes. A laboratory device was constructed to evaluate the flux chamber under both diffusion-only and advection-plus-diffusion transport conditions. The flux chamber measured an average of 82% of 15 diffusion-only fluxes and an average of 95% of 15 additional advection-plus-diffusion flux experiments. The vertical flux chamber has the capability of providing reliable measurement of VOC flux from the unsaturated zone under both diffusion and advection transport conditions.

SSCC TD: A Serial and Simultaneous Configural-Cue Compound Stimuli Representation for Temporal Difference Learning

PubMed Central

Mondragón, Esther; Gray, Jonathan; Alonso, Eduardo; Bonardi, Charlotte; Jennings, Dómhnall J.

2014-01-01

This paper presents a novel representational framework for the Temporal Difference (TD) model of learning, which allows the computation of configural stimuli – cumulative compounds of stimuli that generate perceptual emergents known as configural cues. This Simultaneous and Serial Configural-cue Compound Stimuli Temporal Difference model (SSCC TD) can model both simultaneous and serial stimulus compounds, as well as compounds including the experimental context. This modification significantly broadens the range of phenomena which the TD paradigm can explain, and allows it to predict phenomena which traditional TD solutions cannot, particularly effects that depend on compound stimuli functioning as a whole, such as pattern learning and serial structural discriminations, and context-related effects. PMID:25054799

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

Charge-dependent many-body exchange and dispersion interactions in combined QM/MM simulations

NASA Astrophysics Data System (ADS)

Kuechler, Erich R.; Giese, Timothy J.; York, Darrin M.

2015-12-01

Accurate modeling of the molecular environment is critical in condensed phase simulations of chemical reactions. Conventional quantum mechanical/molecular mechanical (QM/MM) simulations traditionally model non-electrostatic non-bonded interactions through an empirical Lennard-Jones (LJ) potential which, in violation of intuitive chemical principles, is bereft of any explicit coupling to an atom's local electronic structure. This oversight results in a model whereby short-ranged exchange-repulsion and long-ranged dispersion interactions are invariant to changes in the local atomic charge, leading to accuracy limitations for chemical reactions where significant atomic charge transfer can occur along the reaction coordinate. The present work presents a variational, charge-dependent exchange-repulsion and dispersion model, referred to as the charge-dependent exchange and dispersion (QXD) model, for hybrid QM/MM simulations. Analytic expressions for the energy and gradients are provided, as well as a description of the integration of the model into existing QM/MM frameworks, allowing QXD to replace traditional LJ interactions in simulations of reactive condensed phase systems. After initial validation against QM data, the method is demonstrated by capturing the solvation free energies of a series of small, chlorine-containing compounds that have varying charge on the chlorine atom. The model is further tested on the SN2 attack of a chloride anion on methylchloride. Results suggest that the QXD model, unlike the traditional LJ model, is able to simultaneously obtain accurate solvation free energies for a range of compounds while at the same time closely reproducing the experimental reaction free energy barrier. The QXD interaction model allows explicit coupling of atomic charge with many-body exchange and dispersion interactions that are related to atomic size and provides a more accurate and robust representation of non-electrostatic non-bonded QM/MM interactions.

Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis.

PubMed

Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X

2016-09-01

The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

Genome-scale metabolic modeling to provide insight into the production of storage compounds during feast-famine cycles of activated sludge.

PubMed

Tajparast, Mohammad; Frigon, Dominic

2013-01-01

Studying storage metabolism during feast-famine cycles of activated sludge treatment systems provides profound insight in terms of both operational issues (e.g., foaming and bulking) and process optimization for the production of value added by-products (e.g., bioplastics). We examined the storage metabolism (including poly-β-hydroxybutyrate [PHB], glycogen, and triacylglycerols [TAGs]) during feast-famine cycles using two genome-scale metabolic models: Rhodococcus jostii RHA1 (iMT1174) and Escherichia coli K-12 (iAF1260) for growth on glucose, acetate, and succinate. The goal was to develop the proper objective function (OF) for the prediction of the main storage compound produced in activated sludge for given feast-famine cycle conditions. For the flux balance analysis, combinations of three OFs were tested. For all of them, the main OF was to maximize growth rates. Two additional sub-OFs were used: (1) minimization of biochemical fluxes, and (2) minimization of metabolic adjustments (MoMA) between the feast and famine periods. All (sub-)OFs predicted identical substrate-storage associations for the feast-famine growth of the above-mentioned metabolic models on a given substrate when glucose and acetate were set as sole carbon sources (i.e., glucose-glycogen and acetate-PHB), in agreement with experimental observations. However, in the case of succinate as substrate, the predictions depended on the network structure of the metabolic models such that the E. coli model predicted glycogen accumulation and the R. jostii model predicted PHB accumulation. While the accumulation of both PHB and glycogen was observed experimentally, PHB showed higher dynamics during an activated sludge feast-famine growth cycle with succinate as substrate. These results suggest that new modeling insights between metabolic predictions and population ecology will be necessary to properly predict metabolisms likely to emerge within the niches of activated sludge communities. Nonetheless, we believe that the development of this approach will help guide the optimization of the production of storage compounds as valuable by-products of wastewater treatment.

Global detection and analysis of volatile components from sun-dried and sulfur-fumigated herbal medicine by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry.

PubMed

Cao, Gang; Cai, Hao; Cong, Xiaodong; Liu, Xiao; Ma, Xiaoqing; Lou, Yajing; Qin, Kunming; Cai, Baochang

2012-08-21

The sulfur-fumigation process can induce changes in the contents of volatile compounds and the chemical transformation of herbal medicines. Although literature has reported many methods for analyzing volatile target compounds from herbal medicine, all of them are largely limited to target compounds and sun-dried samples. This study provides a comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC×GC-TOF/MS) method based on a chemical profiling approach to identify non-target and target volatile compounds from sun-dried and sulfur-fumigated herbal medicine. Using Chrysanthemum morifolium as a model herbal medicine, the combined power of this approach is illustrated by the identification of 209 and 111 volatile compounds with match quality >80% from sun-dried and sulfur-fumigated Chrysanthemum morifolium, respectively. The study has also shown that sulfur-fumigated samples showed a significant loss of the main active compounds and a more destructive fingerprint profile compared to the sun-dried ones. 50 volatile compounds were lost in the sulfur-fumigated Chrysanthemum morifolium sample. The approach and methodology reported in this paper would be useful for identifying complicated target and non-target components from various complex mixtures such as herbal medicine and its preparations, biological and environmental samples. Furthermore, it can be applied for the intrinsic quality control of herbal medicine and its preparations.

Car-Parrinello molecular dynamics study of the charge-discharge cycle in lithium-ion battery materials

NASA Astrophysics Data System (ADS)

Kung, Y. F.; Jia, C. J.; Gent, W. E.; Lee, I.; Moritz, B.; Devereaux, T. P.

Lithium-ion transition metal oxide compounds have shown great potential for use as battery electrodes. However, the underlying structural modifications which accompany delithiation during battery charging remain less well understood. Formation of peroxide-like species and cation migration between layers comprise two promising candidates for describing numerous experimental observations. Taking Li2RuO3 as a model system, we use Car-Parrinello molecular dynamics to examine the structural changes that occur during delithiation and lithiation. We compare our results to existing experimental observations in other compounds and provide guidance for future experiments, including resonant inelastic x-ray scattering (RIXS).

Modeling and design of challenge tests: Inflammatory and metabolic biomarker study examples.

PubMed

Gabrielsson, Johan; Hjorth, Stephan; Vogg, Barbara; Harlfinger, Stephanie; Gutierrez, Pablo Morentin; Peletier, Lambertus; Pehrson, Rikard; Davidsson, Pia

2015-01-25

Given the complexity of pharmacological challenge experiments, it is perhaps not surprising that design and analysis, and in turn interpretation and communication of results from a quantitative point of view, is often suboptimal. Here we report an inventory of common designs sampled from anti-inflammatory, respiratory and metabolic disease drug discovery studies, all of which are based on animal models of disease involving pharmacological and/or patho/physiological interaction challenges. The corresponding data are modeled and analyzed quantitatively, the merits of the respective approach discussed and inferences made with respect to future design improvements. Although our analysis is limited to these disease model examples, the challenge approach is generally applicable to the vast majority of pharmacological intervention studies. In the present five Case Studies results from pharmacodynamic effect models from different therapeutic areas were explored and analyzed according to five typical designs. Plasma exposures of test compounds were assayed by either liquid chromatography/mass spectrometry or ligand binding assays. To describe how drug intervention can regulate diverse processes, turnover models of test compound-challenger interaction, transduction processes, and biophase time courses were applied for biomarker response in eosinophil count, IL6 response, paw-swelling, TNFα response and glucose turnover in vivo. Case Study 1 shows results from intratracheal administration of Sephadex, which is a glucocorticoid-sensitive model of airway inflammation in rats. Eosinophils in bronchoalveolar fluid were obtained at different time points via destructive sampling and then regressed by the mixed-effects modeling. A biophase function of the Sephadex time course was inferred from the modeled eosinophil time courses. In Case Study 2, a mouse model showed that the time course of cytokine-induced IL1β challenge was altered with or without drug intervention. Anakinra reversed the IL1β induced cytokine IL6 response in a dose-dependent manner. This Case Study contained time courses of test compound (drug), challenger (IL1β) and cytokine response (IL6), which resulted in high parameter precision. Case Study 3 illustrates collagen-induced arthritis progression in the rat. Swelling scores (based on severity of hind paw swelling) were used to describe arthritis progression after the challenge and the inhibitory effect of two doses of an orally administered test compound. In Case Study 4, a cynomolgus monkey model for lipopolysaccharide LPS-induced TNFα synthesis and/or release was investigated. This model provides integrated information on pharmacokinetics and in vivo potency of the test compounds. Case Study 5 contains data from an oral glucose tolerance test in rats, where the challenger is the same as the pharmacodynamic response biomarker (glucose). It is therefore convenient to model the extra input of glucose simultaneously with baseline data and during intervention of a glucose-lowering compound at different dose levels. Typically time-series analyses of challenger- and biomarker-time data are necessary if an accurate and precise estimate of the pharmacodynamic properties of a test compound is sought. Erosion of data, resulting in the single-point assessment of drug action after a challenge test, should generally be avoided. This is particularly relevant for situations where one expects time-curve shifts, tolerance/rebound, impact of disease, or hormetic concentration-response relationships to occur. Copyright © 2014 Elsevier B.V. All rights reserved.

Insights into Aqueous-phase processing through Comparison of the Organic Chemical Composition of Atmospheric Particles and Cloud Water in the Southeast United States

NASA Astrophysics Data System (ADS)

Boone, E.; Laskin, J.; Laskin, A.; Wirth, C.; Shepson, P. B.; Stirm, B. H.; Pratt, K.

2014-12-01

Organic compounds comprise a significant mass fraction of submicron atmospheric particles with considerable contribution from secondary organic aerosol (SOA), a large fraction of which is formed from the oxidation of biogenic volatile organic compounds. Aqueous-phase reactions in particles and cloud droplets are suggested to increase SOA mass and change the chemical composition the particles following cloud evaporation. Aqueous-phase processing may also explain discrepancies between measurements and models. To gain a better understanding of these processes, cloud water and below-cloud atmospheric particles were collected onboard a research aircraft during the Southeast Oxidants and Aerosol Study (SOAS) over Alabama in June 2013. Nanospray desorption electrospray ionization (nano-DESI) and direct electrospray ionization (ESI) coupled with high resolution mass spectrometry were utilized to compare the organic molecular composition of the particle and cloud water samples, respectively. Several hundred unique compounds have been identified in the particle and cloud water samples, allowing possible aqueous-phase reactions to be examined. Hydrolysis of organosulfate compounds, aqueous-phase formation of nitrogen-containing compounds, and possible fragmentation of oligomeric compounds will be discussed, with comparisons to previous laboratory studies. This study provides insights into aqueous-phase reactions in ambient cloud droplets.

Synthesis and biological evaluation of 3-thiazolocoumarinyl Schiff-base derivatives as cholinesterase inhibitors.

PubMed

Raza, Rabia; Saeed, Aamer; Arif, Mubeen; Mahmood, Shamsul; Muddassar, Muhammad; Raza, Ahsan; Iqbal, Jamshed

2012-10-01

On the basis of the observed biological activity of the coumarins, a new set of 3-thiazolocoumarinyl Schiff-base derivatives with chlorine, hydroxy and methoxy functional group substitutions were designed and synthesized. These compounds were tested against acetylcholinesterase from Electrophorus electricus and butyrylcholinesterase from horse serum and their structure-activity relationship was established. Studies revealed them as the potential inhibitors of cholinesterase (acetylcholinesterase and butyrylcholinesterase). The 3f was found to be most potent against acetylcholinesterase with K(i) value of 1.05 ± 0.3 μM and 3l showed excellent inhibitory action against butyrylcholinesterase with K(i) value of 0.041 ± 0.002 μM. The synthesized compounds were also docked into the active sites of the homology models of acetylcholinesterase and butyrylcholinesterase to predict the binding modes of these compounds. It was predicted that most of the compounds have similar binding modes with reasonable binding affinities. Our docking studies have also shown that these synthesized compounds have better interaction patterns with butyrylcholinesterase over acetylcholinesterase. The main objective of the study was to develop new potent and selective compounds, which might be further optimized to prevent the progression of the Alzheimer's disease and could provide symptomatic treatment. © 2012 John Wiley & Sons A/S.

Open innovation for phenotypic drug discovery: The PD2 assay panel.

PubMed

Lee, Jonathan A; Chu, Shaoyou; Willard, Francis S; Cox, Karen L; Sells Galvin, Rachelle J; Peery, Robert B; Oliver, Sarah E; Oler, Jennifer; Meredith, Tamika D; Heidler, Steven A; Gough, Wendy H; Husain, Saba; Palkowitz, Alan D; Moxham, Christopher M

2011-07-01

Phenotypic lead generation strategies seek to identify compounds that modulate complex, physiologically relevant systems, an approach that is complementary to traditional, target-directed strategies. Unlike gene-specific assays, phenotypic assays interrogate multiple molecular targets and signaling pathways in a target "agnostic" fashion, which may reveal novel functions for well-studied proteins and discover new pathways of therapeutic value. Significantly, existing compound libraries may not have sufficient chemical diversity to fully leverage a phenotypic strategy. To address this issue, Eli Lilly and Company launched the Phenotypic Drug Discovery Initiative (PD(2)), a model of open innovation whereby external research groups can submit compounds for testing in a panel of Lilly phenotypic assays. This communication describes the statistical validation, operations, and initial screening results from the first PD(2) assay panel. Analysis of PD(2) submissions indicates that chemical diversity from open source collaborations complements internal sources. Screening results for the first 4691 compounds submitted to PD(2) have confirmed hit rates from 1.6% to 10%, with the majority of active compounds exhibiting acceptable potency and selectivity. Phenotypic lead generation strategies, in conjunction with novel chemical diversity obtained via open-source initiatives such as PD(2), may provide a means to identify compounds that modulate biology by novel mechanisms and expand the innovation potential of drug discovery.

VAPOR PRESSURES AND HEATS OF VAPORIZATION OF PRIMARY COAL TARS

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

Eric M. Suuberg; Vahur Oja

1997-07-01

This project had as its main focus the determination of vapor pressures of coal pyrolysis tars. It involved performing measurements of these vapor pressures and from them, developing vapor pressure correlations suitable for use in advanced pyrolysis models (those models which explicitly account for mass transport limitations). This report is divided into five main chapters. Each chapter is a relatively stand-alone section. Chapter A reviews the general nature of coal tars and gives a summary of existing vapor pressure correlations for coal tars and model compounds. Chapter B summarizes the main experimental approaches for coal tar preparation and characterization whichmore » have been used throughout the project. Chapter C is concerned with the selection of the model compounds for coal pyrolysis tars and reviews the data available to us on the vapor pressures of high boiling point aromatic compounds. This chapter also deals with the question of identifying factors that govern the vapor pressures of coal tar model materials and their mixtures. Chapter D covers the vapor pressures and heats of vaporization of primary cellulose tars. Chapter E discusses the results of the main focus of this study. In summary, this work provides improved understanding of the volatility of coal and cellulose pyrolysis tars. It has resulted in new experimentally verified vapor pressure correlations for use in pyrolysis models. Further research on this topic should aim at developing general vapor pressure correlations for all coal tars, based on their molecular weight together with certain specific chemical characteristics i.e. hydroxyl group content.« less

Predicting physical properties of emerging compounds with limited physical and chemical data: QSAR model uncertainty and applicability to military munitions.

PubMed

Bennett, Erin R; Clausen, Jay; Linkov, Eugene; Linkov, Igor

2009-11-01

Reliable, up-front information on physical and biological properties of emerging materials is essential before making a decision and investment to formulate, synthesize, scale-up, test, and manufacture a new material for use in both military and civilian applications. Multiple quantitative structure-activity relationships (QSARs) software tools are available for predicting a material's physical/chemical properties and environmental effects. Even though information on emerging materials is often limited, QSAR software output is treated without sufficient uncertainty analysis. We hypothesize that uncertainty and variability in material properties and uncertainty in model prediction can be too large to provide meaningful results. To test this hypothesis, we predicted octanol water partitioning coefficients (logP) for multiple, similar compounds with limited physical-chemical properties using six different commercial logP calculators (KOWWIN, MarvinSketch, ACD/Labs, ALogP, CLogP, SPARC). Analysis was done for materials with largely uncertain properties that were similar, based on molecular formula, to military compounds (RDX, BTTN, TNT) and pharmaceuticals (Carbamazepine, Gemfibrizol). We have also compared QSAR modeling results for a well-studied pesticide and pesticide breakdown product (Atrazine, DDE). Our analysis shows variability due to structural variations of the emerging chemicals may be several orders of magnitude. The model uncertainty across six software packages was very high (10 orders of magnitude) for emerging materials while it was low for traditional chemicals (e.g. Atrazine). Thus the use of QSAR models for emerging materials screening requires extensive model validation and coupling QSAR output with available empirical data and other relevant information.

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.

Nerve agent analogues that produce authentic soman, sarin, tabun, and cyclohexyl methylphosphonate-modified human butyrylcholinesterase.

PubMed

Gilley, Cynthia; MacDonald, Mary; Nachon, Florian; Schopfer, Lawrence M; Zhang, Jun; Cashman, John R; Lockridge, Oksana

2009-10-01

The goal was to test 14 nerve agent model compounds of soman, sarin, tabun, and cyclohexyl methylphosphonofluoridate (GF) for their suitability as substitutes for true nerve agents. We wanted to know whether the model compounds would form the identical covalent adduct with human butyrylcholinesterase that is produced by reaction with true nerve agents. Nerve agent model compounds containing thiocholine or thiomethyl in place of fluorine or cyanide were synthesized as Sp and Rp stereoisomers. Purified human butyrylcholinesterase was treated with a 45-fold molar excess of nerve agent analogue at pH 7.4 for 17 h at 21 degrees C. The protein was denatured by boiling and was digested with trypsin. Aged and nonaged active site peptide adducts were quantified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry of the tryptic digest mixture. The active site peptides were isolated by HPLC and analyzed by MALDI-TOF-TOF mass spectrometry. Serine 198 of butyrylcholinesterase was covalently modified by all 14 compounds. Thiocholine was the leaving group in all compounds that had thiocholine in place of fluorine or cyanide. Thiomethyl was the leaving group in the GF thiomethyl compounds. However, sarin thiomethyl compounds released either thiomethyl or isopropyl, while soman thiomethyl compounds released either thiomethyl or pinacolyl. Thiocholine compounds reacted more rapidly with butyrylcholinesterase than thiomethyl compounds. Labeling with the model compounds resulted in aged adducts that had lost the O-alkyl group (O-ethyl for tabun, O-cyclohexyl for GF, isopropyl for sarin, and pinacolyl for soman) in addition to the thiocholine or thiomethyl group. The nerve agent model compounds containing thiocholine and the GF thiomethyl analogue were found to be suitable substitutes for true soman, sarin, tabun, and GF in terms of the adduct that they produced with human butyrylcholinesterase. However, the soman and sarin thiomethyl compounds yielded two types of adducts, one of which was thiomethyl phosphonate, a modification not found after treatment with authentic soman and sarin.

Multi-instrument comparison and compilation of non-methane organic gas emissions from biomass burning and implications for smoke-derived secondary organic aerosol precursors

NASA Astrophysics Data System (ADS)

Hatch, Lindsay E.; Yokelson, Robert J.; Stockwell, Chelsea E.; Veres, Patrick R.; Simpson, Isobel J.; Blake, Donald R.; Orlando, John J.; Barsanti, Kelley C.

2017-01-01

Multiple trace-gas instruments were deployed during the fourth Fire Lab at Missoula Experiment (FLAME-4), including the first application of proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOFMS) and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) for laboratory biomass burning (BB) measurements. Open-path Fourier transform infrared spectroscopy (OP-FTIR) was also deployed, as well as whole-air sampling (WAS) with one-dimensional gas chromatography-mass spectrometry (GC-MS) analysis. This combination of instruments provided an unprecedented level of detection and chemical speciation. The chemical composition and emission factors (EFs) determined by these four analytical techniques were compared for four representative fuels. The results demonstrate that the instruments are highly complementary, with each covering some unique and important ranges of compositional space, thus demonstrating the need for multi-instrument approaches to adequately characterize BB smoke emissions. Emission factors for overlapping compounds generally compared within experimental uncertainty, despite some outliers, including monoterpenes. Data from all measurements were synthesized into a single EF database that includes over 500 non-methane organic gases (NMOGs) to provide a comprehensive picture of speciated, gaseous BB emissions. The identified compounds were assessed as a function of volatility; 6-11 % of the total NMOG EF was associated with intermediate-volatility organic compounds (IVOCs). These atmospherically relevant compounds historically have been unresolved in BB smoke measurements and thus are largely missing from emission inventories. Additionally, the identified compounds were screened for published secondary organic aerosol (SOA) yields. Of the total reactive carbon (defined as EF scaled by the OH rate constant and carbon number of each compound) in the BB emissions, 55-77 % was associated with compounds for which SOA yields are unknown or understudied. The best candidates for future smog chamber experiments were identified based on the relative abundance and ubiquity of the understudied compounds, and they included furfural, 2-methyl furan, 2-furan methanol, and 1,3-cyclopentadiene. Laboratory study of these compounds will facilitate future modeling efforts.

Evolution of Bromoform in a Global Chemistry and Transport Model

NASA Technical Reports Server (NTRS)

Douglass, Anne R.; Pierson, J. M.; Douglass, Anne R.; Einaudi, Franco (Technical Monitor)

2000-01-01

It is well known that many chlorine and bromine compounds that are inert in the troposphere are destroyed in the stratosphere and contribute to the stratospheric burden of reactive chlorine and bromine species. But the contribution from those chlorine and bromine compounds which are reactive in the troposphere is less certain because it is not known whether convection can transport these gases to the upper troposphere rapidly enough to overcome their short tropospheric lifetimes. We examine this issue using a three-dimensional chemistry and transport model to simulate the evolution of three gases which have surface sources, bromoform (CHBr3), methyl chloroform (CH3CCl3), and carbon dioxide (CO2). Our objective is to determine if CHBr3 might enhance the lower stratospheric burden of reactive bromine. The other two gases provide tests of the quality of the simulation. Both CHBr3 and CH3CCl3 are destroyed in the troposphere by reaction with hydroxyl (OH), whose latitudinal and monthly variation is provided by a two-dimensional model and upon which a diurnal variation is imposed. Comparison of the lifetime of CH3CCl3 computed from observations (5 years) with the lifetime computed from the simulation provides an integrated test of the model's transport and photochemistry. Observations also show that CO2 exhibits a strong seasonal cycle in the northern hemisphere troposphere that is not propagated directly across the tropopause into the lower stratosphere. Thus, maintenance of the observed troposphere-stratosphere distinctness of CO2 in the presence of convection is a critical benchmark for meeting our objective.

Characterization of commercial inactive dry yeast preparations for enological use based on their ability to release soluble compounds and their behavior toward aroma compounds in model wines.

PubMed

Pozo-Bayón, Maria Angeles; Andujar-Ortiz, Inmaculada; Alcaide-Hidalgo, Juan María; Martín-Alvarez, Pedro J; Moreno-Arribas, M Victoria

2009-11-25

The characterization of commercial enological inactive dry yeast (IDY) with different applications in wine production has been carried out. This study was based on the yeast's ability to release soluble compounds (high molecular weight nitrogen, free amino nitrogen, peptidic nitrogen, free amino acids, and polysaccharides) into model wines and on its behavior toward the volatility of seven wine aroma compounds. Important differences in soluble compounds released into the model wines supplemented with commercial IDY were found, with the free amino acids being among the most released. The volatility of most of the aroma compounds was affected by the addition of IDY preparations at a concentration usually employed during winemaking. The extent of this effect was dependent on the physicochemical characteristics of the aroma compound and on the length of time the IDY preparations remained in contact with the model wines. Whereas shorter contact times (2, 4, and 6 days) mainly promoted a "salting-out" effect, longer exposure (9 and 13 days) provoked a retention effect, with the consequent reduction of aroma compounds in the headspace. The use of different commercial preparations also promoted different effects toward the aroma compounds that may be at least in part due to differences in their ability to release soluble compounds of yeast origin into the wines.

A novel simplified model for torsional vibration analysis of a series-parallel hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Tang, Xiaolin; Yang, Wei; Hu, Xiaosong; Zhang, Dejiu

2017-02-01

In this study, based on our previous work, a novel simplified torsional vibration dynamic model is established to study the torsional vibration characteristics of a compound planetary hybrid propulsion system. The main frequencies of the hybrid driveline are determined. In contrast to vibration characteristics of the previous 16-degree of freedom model, the simplified model can be used to accurately describe the low-frequency vibration property of this hybrid powertrain. This study provides a basis for further vibration control of the hybrid powertrain during the process of engine start/stop.

Development of Monopole Interaction Models for Ionic Compounds. Part I: Estimation of Aqueous Henry’s Law Constants for Ions and Gas Phase pKa Values for Acidic Compounds

EPA Science Inventory

The SPARC (SPARC Performs Automated Reasoning in Chemistry) physicochemical mechanistic models for neutral compounds have been extended to estimate Henry’s Law Constant (HLC) for charged species by incorporating ionic electrostatic interaction models. Combinations of absolute aq...

Stereoregularity of poly (lactic acid) and their model compounds as studied by NMR and quantum chemical calculations

USDA-ARS?s Scientific Manuscript database

In order to understand the origin of the tacticity splitting in the NMR spectrum of poly(lactic acid), monomer model compound and dimer model compounds (both isotactic and syndiotactic) were synthesized and their 1H and 13C NMR chemical shifts observed. Two energetically stable conformations were o...

Encapsulation of a model compound in pectin delays its release from a biobased polymeric material

USDA-ARS?s Scientific Manuscript database

A model compound was encapsulated in pectin and then extruded with thermoplastic starch to form a composite. The intended product was a food-contact tray made of biobased polymers infused with an anti-microbial agent; however, caffeine was used as the model compound in the preliminary work. The mode...

Pyrolysis reaction networks for lignin model compounds: unraveling thermal deconstruction of β-O-4 and α-O-4 compounds

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

Choi, Yong S.; Singh, Rahul; Zhang, Jing

2016-01-01

Although lignin is one of the main components of biomass, its pyrolysis chemistry is not well understood due to complex heterogeneity. To gain insights into this chemistry, the pyrolysis of seven lignin model compounds (five ..beta..-O-4 and two ..alpha..-O-4 linked molecules) was investigated in a micropyrolyzer connected to GC-MS/FID. According to quantitative product mole balance for the reaction networks, concerted retro-ene fragmentation and homolytic dissociation were strongly suggested as the initial reaction step for ..beta..-O-4 compounds and ..alpha..-O-4 compounds, respectively. The difference in reaction pathway between compounds with different linkages was believed to result from thermodynamics of the radical initiation.more » The rate constants for the different reaction pathways were predicted from ab initio density functional theory calculations and pre-exponential literature values. The computational findings were consistent with the experiment results, further supporting the different pyrolysis mechanisms for the ..beta..-ether linked and ..alpha..-ether linked compounds. A combination of the two pathways from the dimeric model compounds was able to describe qualitatively the pyrolysis of a trimeric lignin model compound containing both ..beta..-O-4 and ..alpha..-O-4 linkages.« less

Evaluation of adamantane hydroxamates as botulinum neurotoxin inhibitors: synthesis, crystallography, modeling, kinetic and cellular based studies.

PubMed

Šilhár, Peter; Silvaggi, Nicholas R; Pellett, Sabine; Čapková, Kateřina; Johnson, Eric A; Allen, Karen N; Janda, Kim D

2013-03-01

Botulinum neurotoxins (BoNTs) are the most lethal biotoxins known to mankind and are responsible for the neuroparalytic disease botulism. Current treatments for botulinum poisoning are all protein based and thus have a limited window of treatment opportunity. Inhibition of the BoNT light chain protease (LC) has emerged as a therapeutic strategy for the treatment of botulism as it may provide an effective post exposure remedy. Using a combination of crystallographic and modeling studies a series of hydroxamates derived from 1-adamantylacetohydroxamic acid (3a) were prepared. From this group of compounds, an improved potency of about 17-fold was observed for two derivatives. Detailed mechanistic studies on these structures revealed a competitive inhibition model, with a K(i)=27 nM, which makes these compounds some of the most potent small molecule, non-peptidic BoNT/A LC inhibitors reported to date. Copyright © 2012 Elsevier Ltd. All rights reserved.

iFly: The eye of the fruit fly as a model to study autophagy and related trafficking pathways.

PubMed

Lőrincz, Péter; Takáts, Szabolcs; Kárpáti, Manuéla; Juhász, Gábor

2016-03-01

Autophagy is a process by which eukaryotic cells degrade and recycle their intracellular components within lysosomes. Autophagy is induced by starvation to ensure survival of individual cells, and it has evolved to fulfill numerous additional roles in animals. Autophagy not only provides nutrient supply through breakdown products during starvation, but it is also required for the elimination of damaged or surplus organelles, toxic proteins, aggregates, and pathogens, and is essential for normal organelle turnover. Because of these roles, defects in autophagy have pathological consequences. Here we summarize the current knowledge of autophagy and related trafficking pathways in a convenient model: the compound eye of the fruit fly Drosophila melanogaster. In our review, we present a general introduction of the development and structure of the compound eye. This is followed by a discussion of various neurodegeneration models including retinopathies, with special emphasis on the protective role of autophagy against these diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prediction of Mutagenicity of Chemicals from Their Calculated Molecular Descriptors: A Case Study with Structurally Homogeneous versus Diverse Datasets.

PubMed

Basak, Subhash C; Majumdar, Subhabrata

2015-01-01

Variation in high-dimensional data is often caused by a few latent factors, and hence dimension reduction or variable selection techniques are often useful in gathering useful information from the data. In this paper we consider two such recent methods: Interrelated two-way clustering and envelope models. We couple these methods with traditional statistical procedures like ridge regression and linear discriminant analysis, and apply them on two data sets which have more predictors than samples (i.e. n < p scenario) and several types of molecular descriptors. One of these datasets consists of a congeneric group of Amines while the other has a much diverse collection compounds. The difference of prediction results between these two datasets for both the methods supports the hypothesis that for a congeneric set of compounds, descriptors of a certain type are enough to provide good QSAR models, but as the data set grows diverse including a variety of descriptors can improve model quality considerably.

Deposition and transport of linezolid mediated by a synthetic surfactant Synsurf® within a pressurized metered dose inhaler: a Calu-3 model

PubMed Central

van Rensburg, Lyné; van Zyl, Johann M; Smith, Johan

2018-01-01

Background Previous studies in our laboratory demonstrated that a synthetic peptide containing lung surfactant enhances the permeability of chemical compounds through bronchial epithelium. The purpose of this study was to test two formulations of Synsurf® combined with linezolid as respirable compounds using a pressurized metered dose inhaler (pMDI). Methods Aerosolization efficiency of the surfactant-drug microparticles onto Calu-3 monolayers as an air interface culture was analyzed using a Next Generation Impactor™. Results The delivered particles and drug dose showed a high dependency from the preparation that was aerosolized. Scanning electron microscopy imaging allowed for visualization of the deposited particles, establishing them as liposomal-type structures (diameter 500 nm to 2 μm) with filamentous features. Conclusion The different surfactant drug combinations allow for an evaluation of the significance of the experimental model system, as well as assessment of the formulations providing a possible noninvasive, site-specific, delivery model via pMDI. PMID:29765201

Ion binding compounds, radionuclide complexes, methods of making radionuclide complexes, methods of extracting radionuclides, and methods of delivering radionuclides to target locations

DOEpatents

Chen, Xiaoyuan; Wai, Chien M.; Fisher, Darrell R.

2000-01-01

The invention pertains to compounds for binding lanthanide ions and actinide ions. The invention further pertains to compounds for binding radionuclides, and to methods of making radionuclide complexes. Also, the invention pertains to methods of extracting radionuclides. Additionally, the invention pertains to methods of delivering radionuclides to target locations. In one aspect, the invention includes a compound comprising: a) a calix[n]arene group, wherein n is an integer greater than 3, the calix[n]arene group comprising an upper rim and a lower rim; b) at least one ionizable group attached to the lower rim; and c) an ion selected from the group consisting of lanthanide and actinide elements bound to the ionizable group. In another aspect, the invention includes a method of extracting a radionuclide, comprising: a) providing a sample comprising a radionuclide; b) providing a calix[n]arene compound in contact with the sample, wherein n is an integer greater than 3; and c) extracting radionuclide from the sample into the calix[n]arene compound. In yet another aspect, the invention includes a method of delivering a radionuclide to a target location, comprising: a) providing a calix[n]arene compound, wherein n is an integer greater than 3, the calix[n]arene compound comprising at least one ionizable group; b) providing a radionuclide bound to the calix[n]arene compound; and c) providing an antibody attached to the calix[n]arene compound, the antibody being specific for a material found at the target location.

Boron containing amino acid compounds and methods for their use

DOEpatents

Glass, John D.; Coderre, Jeffrey A.

2000-01-01

The present invention provides new boron containing amino acid compounds and methods for making these compounds by contacting melphalan or another nitrogen mustard derivative and sodium borocaptate. The present invention also provides a method of treating a mammal having a tumor by administering to the mammal a therapeutically effective amount of the new boron containing amino acid compounds.

Mastering tricyclic ring systems for desirable functional cannabinoid activity

PubMed Central

Petrov, Ravil R.; Knight, Lindsay; Chen, Shao-Rui; Wager-Miller, Jim; McDaniel, Steven W.; Diaz, Fanny; Barth, Francis; Pan, Hui-Lin; Mackie, Ken; Cavasotto, Claudio N.; Diaz, Philippe

2013-01-01

There is growing interest in using cannabinoid receptor 2 (CB2) agonists for the treatment of neuropathic pain and other indications. In continuation of our ongoing program aiming for the development of new small molecule cannabinoid ligands, we have synthesized a novel series of carbazole and γ-carboline derivatives. The affinities of the newly synthesized compounds were determined by a competitive radioligand displacement assay for human CB2 cannabinoid receptor and rat CB1 cannabinoid receptor. Functional activity and selectivity at human CB1 and CB2 receptors were characterized using receptor internalization and [35S]GTP-γ-S assays. The structure-activity relationship and optimization studies of the carbazole series have led to the discovery of a non-selective CB1 and CB2 agonist, compound 4. Our subsequent research efforts to increase CB2 selectivity of this lead compound have led to the discovery of CB2 selective compound 64, which robustly internalized CB2 receptors. Compound 64 had potent inhibitory effects on pain hypersensitivity in a rat model of neuropathic pain. Other potent and CB2 receptor–selective compounds, including compounds 63 and 68, and a selective CB1 agonist, compound 74 were also discovered. In addition, we identified the CB2 ligand 35 which failed to promote CB2 receptor internalization and inhibited compound CP55,940-induced CB2 internalization despite a high CB2 receptor affinity. The present study provides novel tricyclic series as a starting point for further investigations of CB2 pharmacology and pain treatment. PMID:24125850

Review of the Toxicity of the Metallic Compounds Proposed for Use in the New Green Missile Formulation

NASA Technical Reports Server (NTRS)

Major, Michael A.

2000-01-01

In an effort to modernize and minimize hazards posed by the toxic components of missile propellant, the USACHPPM has been tasked to provide a comparison of the toxicity of compounds currently in use as missile propellants and the suite of compounds proposed to replace them. This report deals with the portion of this work concerning the toxicity of the organometallic compounds used in these formulations. Toxicity assessments of the organic compounds used in these formulations are published elsewhere. In general, toxicity data were available for all the metal compounds of concern or for closely related compounds that can serve as surrogates for the assessment of toxicity. We have high confidence in the reliability of these comparisons. This report is organized by element to provide the reader with an in-depth assessment with a minimum of redundancy. The narrative will first describe general concepts about the toxicity of each metal and then provide a summary of the toxicological information available for the specific compound.

Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets.

PubMed

Sun, Jiangming; Carlsson, Lars; Ahlberg, Ernst; Norinder, Ulf; Engkvist, Ola; Chen, Hongming

2017-07-24

Conformal prediction has been proposed as a more rigorous way to define prediction confidence compared to other application domain concepts that have earlier been used for QSAR modeling. One main advantage of such a method is that it provides a prediction region potentially with multiple predicted labels, which contrasts to the single valued (regression) or single label (classification) output predictions by standard QSAR modeling algorithms. Standard conformal prediction might not be suitable for imbalanced data sets. Therefore, Mondrian cross-conformal prediction (MCCP) which combines the Mondrian inductive conformal prediction with cross-fold calibration sets has been introduced. In this study, the MCCP method was applied to 18 publicly available data sets that have various imbalance levels varying from 1:10 to 1:1000 (ratio of active/inactive compounds). Our results show that MCCP in general performed well on bioactivity data sets with various imbalance levels. More importantly, the method not only provides confidence of prediction and prediction regions compared to standard machine learning methods but also produces valid predictions for the minority class. In addition, a compound similarity based nonconformity measure was investigated. Our results demonstrate that although it gives valid predictions, its efficiency is much worse than that of model dependent metrics.

Hepatoprotective and Anti-fibrotic Agents: It's Time to Take the Next Step

PubMed Central

Weiskirchen, Ralf

2016-01-01

Hepatic fibrosis and cirrhosis cause strong human suffering and necessitate a monetary burden worldwide. Therefore, there is an urgent need for the development of therapies. Pre-clinical animal models are indispensable in the drug discovery and development of new anti-fibrotic compounds and are immensely valuable for understanding and proofing the mode of their proposed action. In fibrosis research, inbreed mice and rats are by far the most used species for testing drug efficacy. During the last decades, several hundred or even a thousand different drugs that reproducibly evolve beneficial effects on liver health in respective disease models were identified. However, there are only a few compounds (e.g., GR-MD-02, GM-CT-01) that were translated from bench to bedside. In contrast, the large number of drugs successfully tested in animal studies is repeatedly tested over and over engender findings with similar or identical outcome. This circumstance undermines the 3R (Replacement, Refinement, Reduction) principle of Russell and Burch that was introduced to minimize the suffering of laboratory animals. This ethical framework, however, represents the basis of the new animal welfare regulations in the member states of the European Union. Consequently, the legal authorities in the different countries are halted to foreclose testing of drugs in animals that were successfully tested before. This review provides a synopsis on anti-fibrotic compounds that were tested in classical rodent models. Their mode of action, potential sources and the observed beneficial effects on liver health are discussed. This review attempts to provide a reference compilation for all those involved in the testing of drugs or in the design of new clinical trials targeting hepatic fibrosis. PMID:26779021

Enolate-Forming Phloretin Pharmacophores: Hepatoprotection in an Experimental Model of Drug-Induced Toxicity.

PubMed

Geohagen, Brian C; Vydyanathan, Amaresh; Kosharskyy, Boleslav; Shaparin, Naum; Gavin, Terrence; LoPachin, Richard M

2016-06-01

Drug-induced toxicity is often mediated by electrophilic metabolites, such as bioactivation of acetaminophen (APAP) to N-acetyl-p-benzoquinone imine (NAPQI). We have shown that APAP hepatotoxicity can be prevented by 2-acetylcyclopentanone (2-ACP). This 1,3-dicarbonyl compound ionizes to form an enolate nucleophile that scavenges NAPQI and other electrophilic intermediates. In this study, we expanded our investigation of enolate-forming compounds to include analyses of the phloretin pharmacophores, 2',4',6'-trihydroxyacetophenone (THA) and phloroglucinol (PG). Studies in a mouse model of APAP overdose showed that THA provided hepatoprotection when given either by intraperitoneal injection or oral administration, whereas PG was hepatoprotective only when given intraperitoneally. Corroborative research characterized the molecular pharmacology (efficacy, potency) of 2-ACP, THA, and PG in APAP-exposed isolated mouse hepatocytes. For comparative purposes, N-acetylcysteine (NAC) cytoprotection was also evaluated. Measurements of multiple cell parameters (e.g., cell viability, mitochondrial membrane depolarization) indicated that THA and, to a lesser extent, PG provided concentration-dependent protection against APAP toxicity, which exceeded that of 2-ACP or NAC. The enolate-forming compounds and NAC truncated ongoing APAP exposure and thereby returned intoxicated hepatocytes toward normal viability. The superior ability of THA to protect is related to multifaceted modes of action that include metal ion chelation, free radical trapping, and scavenging of NAPQI and other soft electrophiles involved in oxidative stress. The rank order of potency for the tested cytoprotectants was consistent with that determined in a parallel mouse model. These data suggest that THA or a derivative might be useful in treating drug-induced toxicities and other conditions that involve electrophile-mediated pathogenesis. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

Enolate-Forming Phloretin Pharmacophores: Hepatoprotection in an Experimental Model of Drug-Induced Toxicity

PubMed Central

Geohagen, Brian C.; Vydyanathan, Amaresh; Kosharskyy, Boleslav; Shaparin, Naum; Gavin, Terrence

2016-01-01

Drug-induced toxicity is often mediated by electrophilic metabolites, such as bioactivation of acetaminophen (APAP) to N-acetyl-p-benzoquinone imine (NAPQI). We have shown that APAP hepatotoxicity can be prevented by 2-acetylcyclopentanone (2-ACP). This 1,3-dicarbonyl compound ionizes to form an enolate nucleophile that scavenges NAPQI and other electrophilic intermediates. In this study, we expanded our investigation of enolate-forming compounds to include analyses of the phloretin pharmacophores, 2′,4′,6′-trihydroxyacetophenone (THA) and phloroglucinol (PG). Studies in a mouse model of APAP overdose showed that THA provided hepatoprotection when given either by intraperitoneal injection or oral administration, whereas PG was hepatoprotective only when given intraperitoneally. Corroborative research characterized the molecular pharmacology (efficacy, potency) of 2-ACP, THA, and PG in APAP-exposed isolated mouse hepatocytes. For comparative purposes, N-acetylcysteine (NAC) cytoprotection was also evaluated. Measurements of multiple cell parameters (e.g., cell viability, mitochondrial membrane depolarization) indicated that THA and, to a lesser extent, PG provided concentration-dependent protection against APAP toxicity, which exceeded that of 2-ACP or NAC. The enolate-forming compounds and NAC truncated ongoing APAP exposure and thereby returned intoxicated hepatocytes toward normal viability. The superior ability of THA to protect is related to multifaceted modes of action that include metal ion chelation, free radical trapping, and scavenging of NAPQI and other soft electrophiles involved in oxidative stress. The rank order of potency for the tested cytoprotectants was consistent with that determined in a parallel mouse model. These data suggest that THA or a derivative might be useful in treating drug-induced toxicities and other conditions that involve electrophile-mediated pathogenesis. PMID:27029584

Optimization of the Caco-2 permeability assay to screen drug compounds for intestinal absorption and efflux.

PubMed

Press, Barry

2011-01-01

In vitro permeability assays are a valuable tool for scientists during lead compound optimization. As a majority of discovery projects are focused on the development of orally bioavailable drugs, correlation of in vitro permeability data to in vivo absorption results is critical for understanding the structural-physicochemical relationship (SPR) of drugs exhibiting low levels of absorption. For more than a decade, the Caco-2 screening assay has remained a popular, in vitro system to test compounds for both intestinal permeability and efflux liability. Despite advances in artificial membrane technology and in silico modeling systems, drug compounds still benefit from testing in cell-based epithelial monolayer assays for lead optimization. This chapter provides technical information for performing and optimizing the Caco-2 assay. In addition, techniques are discussed for dealing with some of the most pressing issues surrounding in vitro permeability assays (i.e., low aqueous solubility of test compounds and low postassay recovery). Insights are offered to help researchers avoid common pitfalls in the interpretation of in vitro permeability data, which can often lead to the perception of misleading results for correlation to in vivo data.

Developing Enhanced Blood–Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling

PubMed Central

Wang, Wenyi; Kim, Marlene T.; Sedykh, Alexander

2015-01-01

Purpose Experimental Blood–Brain Barrier (BBB) permeability models for drug molecules are expensive and time-consuming. As alternative methods, several traditional Quantitative Structure-Activity Relationship (QSAR) models have been developed previously. In this study, we aimed to improve the predictivity of traditional QSAR BBB permeability models by employing relevant public bio-assay data in the modeling process. Methods We compiled a BBB permeability database consisting of 439 unique compounds from various resources. The database was split into a modeling set of 341 compounds and a validation set of 98 compounds. Consensus QSAR modeling workflow was employed on the modeling set to develop various QSAR models. A five-fold cross-validation approach was used to validate the developed models, and the resulting models were used to predict the external validation set compounds. Furthermore, we used previously published membrane transporter models to generate relevant transporter profiles for target compounds. The transporter profiles were used as additional biological descriptors to develop hybrid QSAR BBB models. Results The consensus QSAR models have R2=0.638 for fivefold cross-validation and R2=0.504 for external validation. The consensus model developed by pooling chemical and transporter descriptors showed better predictivity (R2=0.646 for five-fold cross-validation and R2=0.526 for external validation). Moreover, several external bio-assays that correlate with BBB permeability were identified using our automatic profiling tool. Conclusions The BBB permeability models developed in this study can be useful for early evaluation of new compounds (e.g., new drug candidates). The combination of chemical and biological descriptors shows a promising direction to improve the current traditional QSAR models. PMID:25862462

The classification of almonds (Prunus dulcis) by country and variety using UHPLC-HRMS-based untargeted metabolomics.

PubMed

Gil Solsona, R; Boix, C; Ibáñez, M; Sancho, J V

2018-03-01

The aim of this study was to use an untargeted UHPLC-HRMS-based metabolomics approach allowing discrimination between almonds based on their origin and variety. Samples were homogenised, extracted with ACN:H 2 O (80:20) containing 0.1% HCOOH and injected in a UHPLC-QTOF instrument in both positive and negative ionisation modes. Principal component analysis (PCA) was performed to ensure the absence of outliers. Partial least squares - discriminant analysis (PLS-DA) was employed to create and validate the models for country (with five different compounds) and variety (with 20 features), showing more than 95% accuracy. Additional samples were injected and the model was evaluated with blind samples, with more than 95% of samples being correctly classified using both models. MS/MS experiments were carried out to tentatively elucidate the highlighted marker compounds (pyranosides, peptides or amino acids, among others). This study has shown the potential of high-resolution mass spectrometry to perform and validate classification models, also providing information concerning the identification of the unexpected biomarkers which showed the highest discriminant power.

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment.

PubMed

Minovski, Nikola; Perdih, Andrej; Solmajer, Tom

2012-05-01

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.

Bioremediation of nanomaterials

DOEpatents

Chen, Frank Fanqing; Keasling, Jay D; Tang, Yinjie J

2013-05-14

The present invention provides a method comprising the use of microorganisms for nanotoxicity study and bioremediation. In some embodiment, the microorganisms are bacterial organisms such as Gram negative bacteria, which are used as model organisms to study the nanotoxicity of the fullerene compounds: E. coli W3110, a human related enterobacterium and Shewanella oneidensis MR-1, an environmentally important bacterium with versatile metabolism.

Potential for brain accessibility and analysis of stability of selected flavonoids in relation to neuroprotection in vitro.

PubMed

Pogačnik, Lea; Pirc, Katja; Palmela, Inês; Skrt, Mihaela; Kim, Kwang S; Brites, Dora; Brito, Maria Alexandra; Ulrih, Nataša Poklar; Silva, Rui F M

2016-11-15

Natural food sources constitute a promising source of new compounds with neuroprotective properties, once they have the ability to reach the brain. Our aim was to evaluate the brain accessibility of quercetin, epigallocatechin gallate (EGCG) and cyanidin-3-glucoside (C3G) in relation to their neuroprotective capability. Primary cortical neuron cultures were exposed to oxidative insult in the absence and presence of the selected compounds, and neuroprotection was assessed through evaluation of apoptotic-like and necrotic-like cell death. The brain accessibility of selected compounds was assessed using an optimised human blood-brain barrier model. The blood-brain barrier model was crossed rapidly by EGCG and more slowly by C3G, but not by quercetin. EGCG protected against oxidation-induced neuronal necrotic-like cell death by ~40%, and apoptosis by ~30%. Both quercetin and C3G were less effective, since only the lowest quercetin concentration was protective, and C3G only prevented necrosis by ~37%. Quercetin, EGCG and C3G effectively inhibited α-synuclein fibrillation over the relevant timescale applied here. Overall, EGCG seems to be the most promising neuroprotective compound. Thus, inclusion of this polyphenol in the diet might provide an affordable means to reduce the impact of neurodegenerative diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Use of biopartitioning micellar chromatography and RP-HPLC for the determination of blood-brain barrier penetration of α-adrenergic/imidazoline receptor ligands, and QSPR analysis.

PubMed

Vucicevic, J; Popovic, M; Nikolic, K; Filipic, S; Obradovic, D; Agbaba, D

2017-03-01

For this study, 31 compounds, including 16 imidazoline/α-adrenergic receptor (IRs/α-ARs) ligands and 15 central nervous system (CNS) drugs, were characterized in terms of the retention factors (k) obtained using biopartitioning micellar and classical reversed phase chromatography (log k BMC and log k wRP , respectively). Based on the retention factor (log k wRP ) and slope of the linear curve (S) the isocratic parameter (φ 0 ) was calculated. Obtained retention factors were correlated with experimental log BB values for the group of examined compounds. High correlations were obtained between logarithm of biopartitioning micellar chromatography (BMC) retention factor and effective permeability (r(log k BMC /log BB): 0.77), while for RP-HPLC system the correlations were lower (r(log k wRP /log BB): 0.58; r(S/log BB): -0.50; r(φ 0 /P e ): 0.61). Based on the log k BMC retention data and calculated molecular parameters of the examined compounds, quantitative structure-permeability relationship (QSPR) models were developed using partial least squares, stepwise multiple linear regression, support vector machine and artificial neural network methodologies. A high degree of structural diversity of the analysed IRs/α-ARs ligands and CNS drugs provides wide applicability domain of the QSPR models for estimation of blood-brain barrier penetration of the related compounds.

Comparison of the Solubilization Properties of Polysorbate 80 and Isopropanol/Water Solvent Systems for Organic Compounds Extracted from Three Pharmaceutical Packaging Configurations.

PubMed

Zdravkovic, Steven A

2016-10-10

It has been reported that the presence of polysorbate 80 in a pharmaceutical product's formulation may increase the number and/or amount of impurities leached from materials used during its manufacture, storage, and/or administration. However, it is uncertain if/how the solubilization properties of this surfactant compare to non-surfactant solvent systems. The goal of this study is to provide insight into this area of uncertainty by comparing the solubilization properties of polysorbate 80 to those of isopropanol/water solutions while in contact with a plasticized polyvinylchloride parenteral delivery bag, a single-use type manufacturing bag, and a polypropylene bottle. These properties were determined via a binding experiment, in which a set of model compounds was introduced into the solutions, and via an extraction experiment, in which compounds were extracted from the packaging material by the solutions. In both experiments, the amount of each compound present at equilibrium was assayed to determine the extent they were solubilized by the solution from the packaging material. Results from these experiments illustrate differences in the magnitude of solubilization obtained from solutions containing polysorbate 80 as compared to those composed of isopropanol/water. However, it was also demonstrated that their solubilization properties can be linked via a mathematical model. Copyright © 2016 Elsevier B.V. All rights reserved.

Priming of plant resistance by natural compounds. Hexanoic acid as a model

PubMed Central

Aranega-Bou, Paz; de la O Leyva, Maria; Finiti, Ivan; García-Agustín, Pilar; González-Bosch, Carmen

2014-01-01

Some alternative control strategies of currently emerging plant diseases are based on the use of resistance inducers. This review highlights the recent advances made in the characterization of natural compounds that induce resistance by a priming mechanism. These include vitamins, chitosans, oligogalacturonides, volatile organic compounds, azelaic and pipecolic acid, among others. Overall, other than providing novel disease control strategies that meet environmental regulations, natural priming agents are valuable tools to help unravel the complex mechanisms underlying the induced resistance (IR) phenomenon. The data presented in this review reflect the novel contributions made from studying these natural plant inducers, with special emphasis placed on hexanoic acid (Hx), proposed herein as a model tool for this research field. Hx is a potent natural priming agent of proven efficiency in a wide range of host plants and pathogens. It can early activate broad-spectrum defenses by inducing callose deposition and the salicylic acid (SA) and jasmonic acid (JA) pathways. Later it can prime pathogen-specific responses according to the pathogen’s lifestyle. Interestingly, Hx primes redox-related genes to produce an anti-oxidant protective effect, which might be critical for limiting the infection of necrotrophs. Our Hx-IR findings also strongly suggest that it is an attractive tool for the molecular characterization of the plant alarmed state, with the added advantage of it being a natural compound. PMID:25324848

Release kinetics of volatile organic compounds from roasted and ground coffee: online measurements by PTR-MS and mathematical modeling.

PubMed

Mateus, Maria-L; Lindinger, Christian; Gumy, Jean-C; Liardon, Remy

2007-12-12

The present work shows the possibilities and limitations in modeling release kinetics of volatile organic compounds (VOCs) from roasted and ground coffee by applying physical and empirical models such as the diffusion and Weibull models. The release kinetics of VOCs were measured online by proton transfer reaction-mass spectrometry (PTR-MS). Compounds were identified by GC-MS, and the contribution of the individual compounds to different mass fragments was elucidated by GC/PTR-MS. Coffee samples roasted to different roasting degrees and ground to different particle sizes were studied under dry and wet stripping conditions. To investigate the accuracy of modeling the VOC release kinetics recorded using PTR-MS, online kinetics were compared with kinetics reconstituted from purge and trap samplings. Results showed that uncertainties in ion intensities due to the presence of isobaric species may prevent the development of a robust mathematical model. Of the 20 identified compounds, 5 were affected to a lower extent as their contribution to specific m/z intensity varied by <15% over the stripping time. The kinetics of these compounds were fitted using physical and statistical models, respectively, the diffusion and Weibull models, which helped to identify the underlying release mechanisms. For dry stripping, the diffusion model allowed a good representation of the release kinetics, whereas for wet stripping conditions, release patterns were very complex and almost specific for each compound analyzed. In the case of prewetted coffee, varying particle size (approximately 400-1200 microm) had no significant effect on the VOC release rate, whereas for dry coffee, the release was faster for smaller particles. The absence of particle size effect in wet coffee was attributed to the increase of opened porosity and compound diffusivity by solubilization and matrix relaxation. To conclude, the accurate modeling of VOC release kinetics from coffee allowed small variations in compound release to be discriminated. Furthermore, it evidenced the different aroma compositions that may be obtained depending on the time when VOCs are recovered.

Hepatic 3D spheroid models for the detection and study of compounds with cholestatic liability

PubMed Central

Hendriks, Delilah F. G.; Fredriksson Puigvert, Lisa; Messner, Simon; Mortiz, Wolfgang; Ingelman-Sundberg, Magnus

2016-01-01

Drug-induced cholestasis (DIC) is poorly understood and its preclinical prediction is mainly limited to assessing the compound’s potential to inhibit the bile salt export pump (BSEP). Here, we evaluated two 3D spheroid models, one from primary human hepatocytes (PHH) and one from HepaRG cells, for the detection of compounds with cholestatic liability. By repeatedly co-exposing both models to a set of compounds with different mechanisms of hepatotoxicity and a non-toxic concentrated bile acid (BA) mixture for 8 days we observed a selective synergistic toxicity of compounds known to cause cholestatic or mixed cholestatic/hepatocellular toxicity and the BA mixture compared to exposure to the compounds alone, a phenomenon that was more pronounced after extending the exposure time to 14 days. In contrast, no such synergism was observed after both 8 and 14 days of exposure to the BA mixture for compounds that cause non-cholestatic hepatotoxicity. Mechanisms behind the toxicity of the cholestatic compound chlorpromazine were accurately detected in both spheroid models, including intracellular BA accumulation, inhibition of ABCB11 expression and disruption of the F-actin cytoskeleton. Furthermore, the observed synergistic toxicity of chlorpromazine and BA was associated with increased oxidative stress and modulation of death receptor signalling. Combined, our results demonstrate that the hepatic spheroid models presented here can be used to detect and study compounds with cholestatic liability. PMID:27759057

An insect-tapeworm model as a proxy for anthelminthic effects in the mammalian host.

PubMed

Woolsey, Ian David; Fredensborg, Brian L; Jensen, Per M; Kapel, Christian M O; Meyling, Nicolai V

2015-07-01

Invertebrate models provide several important advantages over their vertebrate counterparts including fewer legislative stipulations and faster, more cost-effective experimental procedures. Furthermore, various similarities between insect and mammalian systems have been highlighted. To obtain maximum use of invertebrate models in pharmacology, their fidelity as analogues of vertebrate systems requires verification. We utilised a flour beetle (Tenebrio molitor)-tapeworm (Hymenolepis diminuta) model to evaluate the efficacy of known anthelmintic compounds, praziquantel, mebendazole and levamisole against H. diminuta cysticercoid larvae in vitro. Inhibition of cysticercoid activity during the excystation procedure was used as a proxy for worm removal. The effects of the three compounds mirrored their relative efficacy in treatment against adult worms in mammalian systems; however, further study is required to determine the fidelity of this model in relation to dose administered. The model precludes comparison of consecutive daily administration of pharmaceuticals in mammals due to cysticercoids not surviving outside of the host for multiple days. Treatment of beetles in vivo, followed by excystation of cysticercoids postdissection could potentially allow for such comparisons. Further model validation will include analysis of pharmaceutical efficacy in varying H. diminuta isolates and pharmaceutical dilution in solvents other than water. Notwithstanding, our results demonstrate that this model holds promise as a method to efficiently identify promising new cestocidal candidates.

The reactivity of phenolic and non-phenolic residual kraft lignin model compounds with Mn(II)-peroxidase from Lentinula edodes.

PubMed

Crestini, C; D'Annibale, A; Sermanni, G G; Saladino, R

2000-02-01

Three phenolic model compounds representing bonding patterns of residual kraft lignin were incubated with manganese peroxidase from Lentinula edodes. Extensive degradation of all the phenolic models, mainly occurring via side-chain benzylic oxidation, was observed. Among the tested model compounds the diphenylmethane alpha-5 phenolic model was found to be the most reactive, yielding several products showing oxidation and fragmentation at the bridging position. The non-phenolic 5-5' biphenyl and 5-5' diphenylmethane models were found unreactive.

Modelling the contribution of biogenic VOCs to new particle formation in the Jülich plant atmosphere chamber

NASA Astrophysics Data System (ADS)

Liao, L.; Dal Maso, M.; Mogensen, D.; Roldin, P.; Rusanen, A.; Kerminen, V.-M.; Mentel, T. F.; Wildt, J.; Kleist, E.; Kiendler-Scharr, A.; Tillmann, R.; Ehn, M.; Kulmala, M.; Boy, M.

2014-11-01

We used the MALTE-BOX model including near-explicit air chemistry and detailed aerosol dynamics to study the mechanisms of observed new particle formation events in the Jülich Plant Atmosphere Chamber. The modelled and measured H2SO4 (sulfuric acid) concentrations agreed within a factor of two. The modelled total monoterpene concentration was in line with PTR-MS observations, and we provided the distributions of individual isomers of terpenes, when no measurements were available. The aerosol dynamic results supported the hypothesis that H2SO4 is one of the critical compounds in the nucleation process. However, compared to kinetic H2SO4 nucleation, nucleation involving OH oxidation products of monoterpenes showed a better agreement with the measurements, with R2 up to 0.97 between modelled and measured total particle number concentrations. The nucleation coefficient for kinetic H2SO4 nucleation was 2.1 × 10-11 cm3 s-1, while the organic nucleation coefficient was 9.0 × 10-14 cm3 s-1. We classified the VOC oxidation products into two sub-groups including extremely low-volatility organic compounds (ELVOCs) and semi-volatile organic compounds (SVOCs). These ELVOCs and SVOCs contributed approximately equally to the particle volume production, whereas only ELVOCs made the smallest particles to grow in size. The model simulations revealed that the chamber walls constitute a major net sink of SVOCs on the first experiment day. However, the net wall SVOC uptake was gradually reduced because of SVOC desorption during the following days. Thus, in order to capture the observed temporal evolution of the particle number size distribution, the model needs to consider reversible gas-wall partitioning.

Modeling of Arylamide Helix Mimetics in the p53 Peptide Binding Site of hDM2 Suggests Parallel and Anti-Parallel Conformations Are Both Stable

PubMed Central

Fuller, Jonathan C.; Jackson, Richard M.; Edwards, Thomas A.; Wilson, Andrew J.; Shirts, Michael R.

2012-01-01

The design of novel α-helix mimetic inhibitors of protein-protein interactions is of interest to pharmaceuticals and chemical genetics researchers as these inhibitors provide a chemical scaffold presenting side chains in the same geometry as an α-helix. This conformational arrangement allows the design of high affinity inhibitors mimicking known peptide sequences binding specific protein substrates. We show that GAFF and AutoDock potentials do not properly capture the conformational preferences of α-helix mimetics based on arylamide oligomers and identify alternate parameters matching solution NMR data and suitable for molecular dynamics simulation of arylamide compounds. Results from both docking and molecular dynamics simulations are consistent with the arylamides binding in the p53 peptide binding pocket. Simulations of arylamides in the p53 binding pocket of hDM2 are consistent with binding, exhibiting similar structural dynamics in the pocket as simulations of known hDM2 binders Nutlin-2 and a benzodiazepinedione compound. Arylamide conformations converge towards the same region of the binding pocket on the 20 ns time scale, and most, though not all dihedrals in the binding pocket are well sampled on this timescale. We show that there are two putative classes of binding modes for arylamide compounds supported equally by the modeling evidence. In the first, the arylamide compound lies parallel to the observed p53 helix. In the second class, not previously identified or proposed, the arylamide compound lies anti-parallel to the p53 helix. PMID:22916232

Misfit layer compounds and ferecrystals: Model systems for thermoelectric nanocomposites

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

Merrill, Devin R.; Moore, Daniel B.; Bauers, Sage R.

A basic summary of thermoelectric principles is presented in a historical context, following the evolution of the field from initial discovery to modern day high-zT materials. A specific focus is placed on nanocomposite materials as a means to solve the challenges presented by the contradictory material requirements necessary for efficient thermal energy harvest. Misfit layer compounds are highlighted as an example of a highly ordered anisotropic nanocomposite system. Their layered structure provides the opportunity to use multiple constituents for improved thermoelectric performance, through both enhanced phonon scattering at interfaces and through electronic interactions between the constituents. Recently, a class ofmore » metastable, turbostratically-disordered misfit layer compounds has been synthesized using a kinetically controlled approach with low reaction temperatures. The kinetically stabilized structures can be prepared with a variety of constituent ratios and layering schemes, providing an avenue to systematically understand structure-function relationships not possible in the thermodynamic compounds. We summarize the work that has been done to date on these materials. The observed turbostratic disorder has been shown to result in extremely low cross plane thermal conductivity and in plane thermal conductivities that are also very small, suggesting the structural motif could be attractive as thermoelectric materials if the power factor could be improved. The first 10 compounds in the [(PbSe) 1+δ] m(TiSe₂) n family (m, n ≤ 3) are reported as a case study. As n increases, the magnitude of the Seebeck coefficient is significantly increased without a simultaneous decrease in the in-plane electrical conductivity, resulting in an improved thermoelectric power factor.« less

Misfit layer compounds and ferecrystals: Model systems for thermoelectric nanocomposites

DOE PAGES

Merrill, Devin R.; Moore, Daniel B.; Bauers, Sage R.; ...

2015-04-22

A basic summary of thermoelectric principles is presented in a historical context, following the evolution of the field from initial discovery to modern day high-zT materials. A specific focus is placed on nanocomposite materials as a means to solve the challenges presented by the contradictory material requirements necessary for efficient thermal energy harvest. Misfit layer compounds are highlighted as an example of a highly ordered anisotropic nanocomposite system. Their layered structure provides the opportunity to use multiple constituents for improved thermoelectric performance, through both enhanced phonon scattering at interfaces and through electronic interactions between the constituents. Recently, a class ofmore » metastable, turbostratically-disordered misfit layer compounds has been synthesized using a kinetically controlled approach with low reaction temperatures. The kinetically stabilized structures can be prepared with a variety of constituent ratios and layering schemes, providing an avenue to systematically understand structure-function relationships not possible in the thermodynamic compounds. We summarize the work that has been done to date on these materials. The observed turbostratic disorder has been shown to result in extremely low cross plane thermal conductivity and in plane thermal conductivities that are also very small, suggesting the structural motif could be attractive as thermoelectric materials if the power factor could be improved. The first 10 compounds in the [(PbSe) 1+δ] m(TiSe₂) n family (m, n ≤ 3) are reported as a case study. As n increases, the magnitude of the Seebeck coefficient is significantly increased without a simultaneous decrease in the in-plane electrical conductivity, resulting in an improved thermoelectric power factor.« less

Eu(2+)-Activated Alkaline-Earth Halophosphates, M5(PO4)3X:Eu(2+) (M = Ca, Sr, Ba; X = F, Cl, Br) for NUV-LEDs: Site-Selective Crystal Field Effect.

PubMed

Kim, Donghyeon; Kim, Sung-Chul; Bae, Jong-Seong; Kim, Sungyun; Kim, Seung-Joo; Park, Jung-Chul

2016-09-06

Eu(2+)-activated M5(PO4)3X (M = Ca, Sr, Ba; X = F, Cl, Br) compounds providing different alkaline-earth metal and halide ions were successfully synthesized and characterized. The emission peak maxima of the M5(PO4)3Cl:Eu(2+) (M = Ca, Sr, Ba) compounds were blue-shifted from Ca to Ba (454 nm for Ca, 444 nm for Sr, and 434 nm for Ba), and those of the Sr5(PO4)3X:Eu(2+) (X = F, Cl, Br) compounds were red-shifted along the series of halides, F → Cl → Br (437 nm for F, 444 nm for Cl, and 448 nm for Br). The site selectivity and occupancy of the activator ions (Eu(2+)) in the M5(PO4)3X:Eu(2+) (M = Ca, Sr, Ba; X = F, Cl, Br) crystal lattices were estimated based on theoretical calculation of the 5d → 4f transition energies of Eu(2+) using LCAO. In combination with the photoluminescence measurements and theoretical calculation, it was elucidated that the Eu(2+) ions preferably enter the fully oxygen-coordinated sites in the M5(PO4)3X:Eu(2+) (M = Ca, Sr, Ba; X = F, Cl, Br) compounds. This trend can be well explained by "Pauling's rules". These compounds may provide a platform for modeling a new phosphor and application in the solid-state lighting field.

Misfit Layer Compounds and Ferecrystals: Model Systems for Thermoelectric Nanocomposites

PubMed Central

Merrill, Devin R.; Moore, Daniel B.; Bauers, Sage R.; Falmbigl, Matthias; Johnson, David C.

2015-01-01

A basic summary of thermoelectric principles is presented in a historical context, following the evolution of the field from initial discovery to modern day high-zT materials. A specific focus is placed on nanocomposite materials as a means to solve the challenges presented by the contradictory material requirements necessary for efficient thermal energy harvest. Misfit layer compounds are highlighted as an example of a highly ordered anisotropic nanocomposite system. Their layered structure provides the opportunity to use multiple constituents for improved thermoelectric performance, through both enhanced phonon scattering at interfaces and through electronic interactions between the constituents. Recently, a class of metastable, turbostratically-disordered misfit layer compounds has been synthesized using a kinetically controlled approach with low reaction temperatures. The kinetically stabilized structures can be prepared with a variety of constituent ratios and layering schemes, providing an avenue to systematically understand structure-function relationships not possible in the thermodynamic compounds. We summarize the work that has been done to date on these materials. The observed turbostratic disorder has been shown to result in extremely low cross plane thermal conductivity and in plane thermal conductivities that are also very small, suggesting the structural motif could be attractive as thermoelectric materials if the power factor could be improved. The first 10 compounds in the [(PbSe)1+δ]m(TiSe2)n family (m, n ≤ 3) are reported as a case study. As n increases, the magnitude of the Seebeck coefficient is significantly increased without a simultaneous decrease in the in-plane electrical conductivity, resulting in an improved thermoelectric power factor. PMID:28788045

Chemical screening identifies filastatin, a small molecule inhibitor of Candida albicans adhesion, morphogenesis, and pathogenesis.

PubMed

Fazly, Ahmed; Jain, Charu; Dehner, Amie C; Issi, Luca; Lilly, Elizabeth A; Ali, Akbar; Cao, Hong; Fidel, Paul L; Rao, Reeta P; Kaufman, Paul D

2013-08-13

Infection by pathogenic fungi, such as Candida albicans, begins with adhesion to host cells or implanted medical devices followed by biofilm formation. By high-throughput phenotypic screening of small molecules, we identified compounds that inhibit adhesion of C. albicans to polystyrene. Our lead candidate compound also inhibits binding of C. albicans to cultured human epithelial cells, the yeast-to-hyphal morphological transition, induction of the hyphal-specific HWP1 promoter, biofilm formation on silicone elastomers, and pathogenesis in a nematode infection model as well as alters fungal morphology in a mouse mucosal infection assay. We term this compound filastatin based on its strong inhibition of filamentation, and we use chemical genetic experiments to show that it acts downstream of multiple signaling pathways. These studies show that high-throughput functional assays targeting fungal adhesion can provide chemical probes for study of multiple aspects of fungal pathogenesis.

Chemical screening identifies filastatin, a small molecule inhibitor of Candida albicans adhesion, morphogenesis, and pathogenesis

PubMed Central

Fazly, Ahmed; Jain, Charu; Dehner, Amie C.; Issi, Luca; Lilly, Elizabeth A.; Ali, Akbar; Cao, Hong; Fidel, Paul L.; P. Rao, Reeta; Kaufman, Paul D.

2013-01-01

Infection by pathogenic fungi, such as Candida albicans, begins with adhesion to host cells or implanted medical devices followed by biofilm formation. By high-throughput phenotypic screening of small molecules, we identified compounds that inhibit adhesion of C. albicans to polystyrene. Our lead candidate compound also inhibits binding of C. albicans to cultured human epithelial cells, the yeast-to-hyphal morphological transition, induction of the hyphal-specific HWP1 promoter, biofilm formation on silicone elastomers, and pathogenesis in a nematode infection model as well as alters fungal morphology in a mouse mucosal infection assay. We term this compound filastatin based on its strong inhibition of filamentation, and we use chemical genetic experiments to show that it acts downstream of multiple signaling pathways. These studies show that high-throughput functional assays targeting fungal adhesion can provide chemical probes for study of multiple aspects of fungal pathogenesis. PMID:23904484

Arylazolyl(azinyl)thioacetanilides. Part 16: Structure-based bioisosterism design, synthesis and biological evaluation of novel pyrimidinylthioacetanilides as potent HIV-1 inhibitors.

PubMed

Li, Xiao; Lu, Xueyi; Chen, Wenmin; Liu, Huiqing; Zhan, Peng; Pannecouque, Christophe; Balzarini, Jan; De Clercq, Erik; Liu, Xinyong

2014-10-01

A series of novel pyrimidinylthioacetanilides were designed, synthesized, and evaluated for their biological activity as potent HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs). Most of the tested compounds were proved to be effective in inhibiting HIV-1 (IIIB) replication with EC50 ranging from 0.15 μM to 24.2 μM, thereinto compound 15 was the most active lead with favorable inhibitory activity against HIV-1 (IIIB) (EC50=0.15 μM, SI=684). Besides, compound 6 displayed moderate inhibition against the double-mutated HIV-1 strain (K103N/Y181C) (EC50=3.9 μM). Preliminary structure-activity relationships (SARs), structure-cytotoxicity relationships (SCRs) data, and molecular modeling studies were discussed as well, which may provide valuable insights for further optimizations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Electron-ion dissociative recombination rate constants relevant to the Titan atmosphere and the Interstellar Medium

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

Osborne, David; Lawson, Patrick; Adams, Nigel, E-mail: ngadams@uga.edu

Following the arrival of Cassini at Titan in 2004, the Titan atmosphere has been shown to contain large complex polycyclic-aromatic hydrocarbons. Since Cassini has provided a great deal of data, there exists a need for kinetic rate data to help with modeling this atmosphere. One type of kinetic data needed is electron-ion dissociative recombination (e-IDR) rate constants. These data are not readily available for larger compounds, such as naphthalene, or oxygen containing compounds, such as 1,4 dioxane or furan. Here, the rate constants for naphthalene, 1,4 dioxane, and furan have been measured and their temperature dependencies are determined when possible,more » using the University of Georgia's Variable Temperature Flowing Afterglow. The rate constants are compared with those previously published for other compounds; these show trends which illustrate the effects which multi-rings and oxygen heteroatoms substitutions have upon e-IDR rate constants.« less

Electron-ion dissociative recombination rate constants relevant to the Titan atmosphere and the Interstellar Medium

NASA Astrophysics Data System (ADS)

Osborne, David; Lawson, Patrick; Adams, Nigel

2014-01-01

Following the arrival of Cassini at Titan in 2004, the Titan atmosphere has been shown to contain large complex polycyclic-aromatic hydrocarbons. Since Cassini has provided a great deal of data, there exists a need for kinetic rate data to help with modeling this atmosphere. One type of kinetic data needed is electron-ion dissociative recombination (e-IDR) rate constants. These data are not readily available for larger compounds, such as naphthalene, or oxygen containing compounds, such as 1,4 dioxane or furan. Here, the rate constants for naphthalene, 1,4 dioxane, and furan have been measured and their temperature dependencies are determined when possible, using the University of Georgia's Variable Temperature Flowing Afterglow. The rate constants are compared with those previously published for other compounds; these show trends which illustrate the effects which multi-rings and oxygen heteroatoms substitutions have upon e-IDR rate constants.

Removal of basic nitrogen compounds from hydrocarbon liquids

DOEpatents

Givens, Edwin N.; Hoover, David S.

1985-01-01

A method is provided for reducing the concentration of basic nitrogen compounds in hydrocarbonaceous feedstock fluids used in the refining industry by providing a solid particulate carbonaceous adsorbent/fuel material such as coal having active basic nitrogen complexing sites on the surface thereof and the coal with a hydrocarbonaceous feedstock containing basic nitrogen compounds to facilitate attraction of the basic nitrogen compounds to the complexing sites and the formation of complexes thereof on the surface of the coal. The adsorbent coal material and the complexes formed thereon are from the feedstock fluid to provide a hydrocarbonaceous fluid of reduced basic nitrogen compound concentration. The coal can then be used as fuel for boilers and the like.

Integrating in Silico and in Vitro Approaches To Predict Drug Accessibility to the Central Nervous System.

PubMed

Zhang, Yan-Yan; Liu, Houfu; Summerfield, Scott G; Luscombe, Christopher N; Sahi, Jasminder

2016-05-02

Estimation of uptake across the blood-brain barrier (BBB) is key to designing central nervous system (CNS) therapeutics. In silico approaches ranging from physicochemical rules to quantitative structure-activity relationship (QSAR) models are utilized to predict potential for CNS penetration of new chemical entities. However, there are still gaps in our knowledge of (1) the relationship between marketed human drug derived CNS-accessible chemical space and preclinical neuropharmacokinetic (neuroPK) data, (2) interpretability of the selected physicochemical descriptors, and (3) correlation of the in vitro human P-glycoprotein (P-gp) efflux ratio (ER) and in vivo rodent unbound brain-to-blood ratio (Kp,uu), as these are assays routinely used to predict clinical CNS exposure, during drug discovery. To close these gaps, we explored the CNS druglike property boundaries of 920 market oral drugs (315 CNS and 605 non-CNS) and 846 compounds (54 CNS drugs and 792 proprietary GlaxoSmithKline compounds) with available rat Kp,uu data. The exact permeability coefficient (Pexact) and P-gp ER were determined for 176 compounds from the rat Kp,uu data set. Receiver operating characteristic curves were performed to evaluate the predictive power of human P-gp ER for rat Kp,uu. Our data demonstrates that simple physicochemical rules (most acidic pKa ≥ 9.5 and TPSA < 100) in combination with P-gp ER < 1.5 provide mechanistic insights for filtering BBB permeable compounds. For comparison, six classification modeling methods were investigated using multiple sets of in silico molecular descriptors. We present a random forest model with excellent predictive power (∼0.75 overall accuracy) using the rat neuroPK data set. We also observed good concordance between the structural interpretation results and physicochemical descriptor importance from the Kp,uu classification QSAR model. In summary, we propose a novel, hybrid in silico/in vitro approach and an in silico screening model for the effective development of chemical series with the potential to achieve optimal CNS exposure.

Chiral mercaptoacetamides display enantioselective inhibition of histone deacetylase 6 and exhibit neuroprotection in cortical neuron models of oxidative stress.

PubMed

Kalin, Jay H; Zhang, Hankun; Gaudrel-Grosay, Sophie; Vistoli, Giulio; Kozikowski, Alan P

2012-03-05

Mercaptoacetamide-based ligands have been designed as a new class of histone deacetylase (HDAC) inhibitors for possible use in the treatment of neurodegenerative diseases. The thiol group of these compounds provides a key binding element for interaction with the catalytic zinc ion, and thus differs from the more typically employed hydroxamic acid based zinc binding groups. Herein we disclose the chemistry and biology of some substituted mercaptoacetamides with the intention of increasing HDAC6 isoform selectivity while maintaining potency similar to their hydroxamic acid analogues. The introduction of a stereocenter α to the thiol group was found to have a considerable impact on HDAC inhibitor potency. These new compounds were also profiled for their therapeutic potential in an in vitro model of stress-induced neuronal injury and were found to act as nontoxic neuroprotective agents. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Radicals and molecular products from the gas-phase pyrolysis of lignin model compounds. Cinnamyl alcohol

PubMed Central

Khachatryan, Lavrent; Xu, Meng-xia; Wu, Ang-jian; Pechagin, Mikhail; Asatryan, Rubik

2016-01-01

The experimental results on detection and identification of intermediate radicals and molecular products from gas-phase pyrolysis of cinnamyl alcohol (CnA), the simplest non-phenolic lignin model compound, over the temperature range of 400–800 °C are reported. The low temperature matrix isolation – electron paramagnetic resonance (LTMI-EPR) experiments along with the theoretical calculations, provided evidences on the generation of the intermediate carbon and oxygen centered as well as oxygen-linked, conjugated radicals. A mechanistic analysis is performed based on density functional theory to explain formation of the major products from CnA pyrolysis; cinnamaldehyde, indene, styrene, benzaldehyde, 1-propynyl benzene, and 2-propenyl benzene. The evaluated bond dissociation patterns and unimolecular decomposition pathways involve dehydrogenation, dehydration, 1,3-sigmatropic H-migration, 1,2-hydrogen shift, C—O and C—C bond cleavage processes. PMID:28344372

Reaction pathways of model compounds of biomass-derived oxygenates on Fe/Ni bimetallic surfaces

NASA Astrophysics Data System (ADS)

Yu, Weiting; Chen, Jingguang G.

2015-10-01

Controlling the activity and selectivity of converting biomass-derivatives to fuels and valuable chemicals is critical for the utilization of biomass feedstocks. There are primarily three classes of non-food competing biomass, cellulose, hemicellulose and lignin. In the current work, glycolaldehyde, furfural and acetaldehyde are studied as model compounds of the three classes of biomass-derivatives. Monometallic Ni(111) and monolayer (ML) Fe/Ni(111) bimetallic surfaces are studied for the reaction pathways of the three biomass surrogates. The ML Fe/Ni(111) surface is identified as an efficient surface for the conversion of biomass-derivatives from the combined results of density functional theory (DFT) calculations and temperature programmed desorption (TPD) experiments. A correlation is also established between the optimized adsorption geometry and experimental reaction pathways. These results should provide helpful insights in catalyst design for the upgrading and conversion of biomass.

Magnetically induced phonon splitting in A Cr 2 O 4 spinels from first principles

DOE PAGES

Wysocki, Aleksander L.; Birol, Turan

2016-04-22

We study the magnetically-induced phonon splitting in cubic ACr 2O 4 (A=Mg, Zn, Cd) spinels from first principles and demonstrate that the sign of the splitting, which is experimentally observed to be opposite in CdCr 2O 4 compared to ZnCr 2O 4 and MgCr 2O 4, is determined solely by the particular magnetic ordering pattern observed in these compounds. We further show that this interaction between magnetism and phonon frequencies can be fully described by the previously proposed spin-phonon coupling model [C. J. Fennie and K. M. Rabe, Phys. Rev. Lett. 96, 205505 (2006)] that includes only the nearest neighbormore » exchange. In conclusion, using this model with materials specific parameters calculated from first principles, we provide additional insights into the physics of spin-phonon coupling in this intriguing family of compounds.« less

Semiclassical Calculation of Reaction Rate Constants for Homolytical Dissociations

NASA Technical Reports Server (NTRS)

Cardelino, Beatriz H.

2002-01-01

There is growing interest in extending organometallic chemical vapor deposition (OMCVD) to III-V materials that exhibit large thermal decomposition at their optimum growth temperature, such as indium nitride. The group III nitrides are candidate materials for light-emitting diodes and semiconductor lasers operating into the blue and ultraviolet regions. To overcome decomposition of the deposited compound, the reaction must be conducted at high pressures, which causes problems of uniformity. Microgravity may provide the venue for maintaining conditions of laminar flow under high pressure. Since the selection of optimized parameters becomes crucial when performing experiments in microgravity, efforts are presently geared to the development of computational OMCVD models that will couple the reactor fluid dynamics with its chemical kinetics. In the present study, we developed a method to calculate reaction rate constants for the homolytic dissociation of III-V compounds for modeling OMCVD. The method is validated by comparing calculations with experimental reaction rate constants.

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

PubMed

Bian, Yuemin; Xie, Xiang-Qun Sean

2018-04-09

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

Vitamin E and breast cancer prevention: current status and future potential.

PubMed

Kline, Kimberly; Lawson, Karla A; Yu, Weiping; Sanders, Bob G

2003-01-01

Vitamin E is a collective term used to refer to a number of structurally and functionally different compounds. Although some vitamin E compounds are popular supplements marketed for their potential beneficial antioxidant effects for a number of chronic diseases including various forms of cancer, a recent report by the National Academy of Sciences Food and Nutrition Board concluded that too little is known at present to provide definitive answers regarding whether taking larger doses of dietary antioxidants will help prevent chronic diseases. Recent reviews of epidemiological data suggest that dietary source vitamin E may provide some protection against breast cancer, while vitamin E supplements do not. A majority of studies investigating the protective effects of certain types of vitamin E in animal models of mammary cancer prevention conclude that there is little or no effect. The study of vitamin E is complex, and the vitamin E field faces many scientific challenges.

Bis(morpholino-1,3,5-triazine) derivatives: potent adenosine 5'-triphosphate competitive phosphatidylinositol-3-kinase/mammalian target of rapamycin inhibitors: discovery of compound 26 (PKI-587), a highly efficacious dual inhibitor.

PubMed

Venkatesan, Aranapakam M; Dehnhardt, Christoph M; Delos Santos, Efren; Chen, Zecheng; Dos Santos, Osvaldo; Ayral-Kaloustian, Semiramis; Khafizova, Gulnaz; Brooijmans, Natasja; Mallon, Robert; Hollander, Irwin; Feldberg, Larry; Lucas, Judy; Yu, Ker; Gibbons, James; Abraham, Robert T; Chaudhary, Inder; Mansour, Tarek S

2010-03-25

The PI3K/Akt signaling pathway is a key pathway in cell proliferation, growth, survival, protein synthesis, and glucose metabolism. It has been recognized recently that inhibiting this pathway might provide a viable therapy for cancer. A series of bis(morpholino-1,3,5-triazine) derivatives were prepared and optimized to provide the highly efficacious PI3K/mTOR inhibitor 1-(4-{[4-(dimethylamino)piperidin-1-yl]carbonyl}phenyl)-3-[4-(4,6-dimorpholin-4-yl-1,3,5-triazin-2-yl)phenyl]urea 26 (PKI-587). Compound 26 has shown excellent activity in vitro and in vivo, with antitumor efficacy in both subcutaneous and orthotopic xenograft tumor models when administered intravenously. The structure-activity relationships and the in vitro and in vivo activity of analogues in this series are described.

Optimal choice of pH for toxicity and bioaccumulation studies of ionizing organic chemicals.

PubMed

Rendal, Cecilie; Kusk, Kresten Ole; Trapp, Stefan

2011-11-01

It is recognized that the pH of exposure solutions can influence the toxicity and bioaccumulation of ionizing compounds. The present study investigates whether it can be considered a general rule that an ionizable compound is more toxic and more bioaccumulative when in the neutral state. Three processes were identified to explain the behavior of ionizing compounds with changing pH: the change in lipophilicity when a neutral compound becomes ionized, electrical attraction, and the ion trap. The literature was screened for bioaccumulation and toxicity tests of ionizing organic compounds performed at multiple pH levels. Toxicity and bioconcentration factors (BCFs) were higher for acids at lower pH values, whereas the opposite was true for bases. The effect of pH was most pronounced when pH - pK(a) was in the range of -1 to 3 for acids, and -3 to 1 for bases. The factor by which toxicity and BCF changed with pH was correlated with the lipophilicity of the compound (log K(OW) of the neutral compound). For both acids and bases, the correlation was positive, but it was significant only for acids. Because experimental data in the literature were limited, results were supplemented with model simulations using a dynamic flux model based on the Fick-Nernst-Planck diffusion equation known as the cell model. The cell model predicts that bases with delocalized charges may in some cases show declining bioaccumulation with increasing pH. Little information is available for amphoteric and zwitterionic compounds; however, based on simulations with the cell model, it is expected that the highest toxicity and bioaccumulation of these compounds will be found where the compounds are most neutral, at the isoelectric point. Copyright © 2011 SETAC.

Selective field evaporation in field-ion microscopy for ordered alloys

NASA Astrophysics Data System (ADS)

Ge, Xi-jin; Chen, Nan-xian; Zhang, Wen-qing; Zhu, Feng-wu

1999-04-01

Semiempirical pair potentials, obtained by applying the Chen-inversion technique to a cohesion equation of Rose et al. [Phys. Rev. B 29, 2963 (1984)], are employed to assess the bonding energies of surface atoms of intermetallic compounds. This provides a new calculational model of selective field evaporation in field-ion microscopy (FIM). Based on this model, a successful interpretation of FIM image contrasts for Fe3Al, PtCo, Pt3Co, Ni4Mo, Ni3Al, and Ni3Fe is given.

Computational Models of the Representation of Bangla Compound Words in the Mental Lexicon.

PubMed

Dasgupta, Tirthankar; Sinha, Manjira; Basu, Anupam

2016-08-01

In this paper we aim to model the organization and processing of Bangla compound words in the mental lexicon. Our objective is to determine whether the mental lexicon access a Bangla compound word as a whole or decomposes the whole word into its constituent morphemes and then recognize them accordingly. To address this issue, we adopted two different strategies. First, we conduct a cross-modal priming experiment over a number of native speakers. Analysis of reaction time (RT) and error rates indicates that in general, Bangla compound words are accessed via partial decomposition process. That is some word follows full-listing mode of representation and some words follow the decomposition route of representation. Next, based on the collected RT data we have developed a computational model that can explain the processing phenomena of the access and representation of Bangla compound words. In order to achieve this, we first explored the individual roles of head word position, morphological complexity, orthographic transparency and semantic compositionality between the constituents and the whole compound word. Accordingly, we have developed a complexity based model by combining these features together. To a large extent we have successfully explained the possible processing phenomena of most of the Bangla compound words. Our proposed model shows an accuracy of around 83 %.

Modeling the surface tension of complex, reactive organic-inorganic mixtures

NASA Astrophysics Data System (ADS)

Schwier, A. N.; Viglione, G. A.; Li, Z.; McNeill, V. Faye

2013-11-01

Atmospheric aerosols can contain thousands of organic compounds which impact aerosol surface tension, affecting aerosol properties such as heterogeneous reactivity, ice nucleation, and cloud droplet formation. We present new experimental data for the surface tension of complex, reactive organic-inorganic aqueous mixtures mimicking tropospheric aerosols. Each solution contained 2-6 organic compounds, including methylglyoxal, glyoxal, formaldehyde, acetaldehyde, oxalic acid, succinic acid, leucine, alanine, glycine, and serine, with and without ammonium sulfate. We test two semi-empirical surface tension models and find that most reactive, complex, aqueous organic mixtures which do not contain salt are well described by a weighted Szyszkowski-Langmuir (S-L) model which was first presented by Henning et al. (2005). Two approaches for modeling the effects of salt were tested: (1) the Tuckermann approach (an extension of the Henning model with an additional explicit salt term), and (2) a new implicit method proposed here which employs experimental surface tension data obtained for each organic species in the presence of salt used with the Henning model. We recommend the use of method (2) for surface tension modeling of aerosol systems because the Henning model (using data obtained from organic-inorganic systems) and Tuckermann approach provide similar modeling results and goodness-of-fit (χ2) values, yet the Henning model is a simpler and more physical approach to modeling the effects of salt, requiring less empirically determined parameters.

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.

Modeling interactions between a β-O-4 type lignin model compound and 1-allyl-3-methylimidazolium chloride ionic liquid.

PubMed

Zhu, Youtao; Yan, Jing; Liu, Chengbu; Zhang, Dongju

2017-08-01

Aiming at understanding the molecular mechanism of the lignin dissolution in imidazolium-based ionic liquids (ILs), this work presents a combined quantum chemistry (QC) calculation and molecular dynamics (MD) simulation study on the interaction of the lignin model compound, veratrylglycerol-β-guaiacyl ether (VG) with 1-allyl-3-methylimidazolium chloride ([Amim]Cl). The monomer of VG is shown to feature a strong intramolecular hydrogen bond, and its dimer is indicated to present important π-π stacking and intermolecular hydrogen bonding interactions. The interactions of both the cation and anion of [Amim]Cl with VG are shown to be stronger than that between the two monomers, indicating that [Amim]Cl is capable of dissolving lignin. While Cl - anion forms a hydrogen-bonded complex with VG, the imidazolium cation interacts with VG via both the π-π stacking and intermolecular hydrogen bonding. The calculated interaction energies between VG and the IL or its components (the cation, anion, and ion pair) indicate the anion plays a more important role than the cation for the dissolution of lignin in the IL. Theoretical results provide help for understanding the molecular mechanism of lignin dissolution in imidazolium-based IL. The theoretical calculations on the interaction between the lignin model compound and [Amim]Cl ionic liquid indicate that the anion of [Amim]Cl plays a more important role for lignin dissolution although the cation also makes a substantial contribution. © 2017 Wiley Periodicals, Inc.

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).

Reverse Osmosis Processing of Organic Model Compounds and Fermentation Broths

DTIC Science & Technology

2006-04-01

AFRL-ML-TY-TP-2007-4545 POSTPRINT REVERSE OSMOSIS PROCESSING OF ORGANIC MODEL COMPOUNDS AND FERMENTATION BROTHS Robert Diltz...TELEPHONE NUMBER (Include area code) Bioresource Technology 98 (2007) 686–695Reverse osmosis processing of organic model compounds and fermentation broths...December 2005; accepted 31 January 2006 Available online 4 April 2006Abstract Post-treatment of an anaerobic fermentation broth was evaluated using a 150

[Biopharmaceutics classification and absorption mechanisms primary study on four kinds of flavonoids].

PubMed

Li, Hui-Fang; Zhang, Dong; Qu, Wen-Jun; Wang, Hai-Lin; Liu, Yang; Borjigdai, Almaz; Cui, Jian; Dong, Zheng-Qi

2016-04-01

The solubility and permeability on four kinds of flavonoids (kaempferol, hesperidin, apigenin, genistein) were test according to the theory of biopharmaceutics classification system (BCS), and their absorption mechanism. The solubility was investigated by the method in determination of solubility of "Chinese Pharmacopoeia 2010". To detect appearance permeability of compounds mentioned above, the appropriate concentrations were selected by the MTT method in cell transfer experiments in Caco-2 cell model, which established by in vitro cell culture method. Therefore, these compounds were classified with BCS according to solubility and permeability. In addition, to explore absorption mechanisms, the experiments in three different concentrations of compounds in high, medium and low in bidirectional transformation methods in Caco-2 cell model contacted. The study indicated that all of kaempferol, hesperidin, apigenin, genistein have the characteristics in low solubility and high permeability, which belong to BCSⅡ, and the absorption mechanism of kaempferol was active transportation. Whereas, hesperidin, apigenin, genistein were passive transportation. In this study, it carried out initial explorations on establishment of determination for solubility and permeability in flavonoids, and provided theoretical reference for further research on BCS in traditional Chinese medicine. Copyright© by the Chinese Pharmaceutical Association.

Automatically updating predictive modeling workflows support decision-making in drug design.

PubMed

Muegge, Ingo; Bentzien, Jörg; Mukherjee, Prasenjit; Hughes, Robert O

2016-09-01

Using predictive models for early decision-making in drug discovery has become standard practice. We suggest that model building needs to be automated with minimum input and low technical maintenance requirements. Models perform best when tailored to answering specific compound optimization related questions. If qualitative answers are required, 2-bin classification models are preferred. Integrating predictive modeling results with structural information stimulates better decision making. For in silico models supporting rapid structure-activity relationship cycles the performance deteriorates within weeks. Frequent automated updates of predictive models ensure best predictions. Consensus between multiple modeling approaches increases the prediction confidence. Combining qualified and nonqualified data optimally uses all available information. Dose predictions provide a holistic alternative to multiple individual property predictions for reaching complex decisions.

Structure- and ligand-based structure-activity relationships for a series of inhibitors of aldolase.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2012-12-01

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r²=0.98 and q²=0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pKi values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.

Structure prediction and analysis of MxaF from obligate, facultative and restricted facultative methylobacterium.

PubMed

Singh, Raghvendra Pratap; Singh, Ram Nageena; Srivastava, Manish K; Srivastava, Alok Kumar; Kumar, Sudheer; Dubey, Ramesh Chandra; Sharma, Arun Kumar

2012-01-01

Methylobacteria are ubiquitous in the biosphere which are capable of growing on C1 compounds such as formate, formaldehyde, methanol and methylamine as well as on a wide range of multi-carbon growth substrates such as C2, C3 and C4 compounds due to the methylotrophic enzymes methanol dehydrogenase (MDH). MDH is performing these functions with the help of a key protein mxaF. Unfortunately, detailed structural analysis and homology modeling of mxaF is remains undefined. Hence, the objective of this research is the characterization and three dimensional modeling of mxaF protein from three different methylotrophs by using I-TASSER server. The predicted model were further optimize and validate by Profile 3D, Errat, Verifiy3-D and PROCHECK server. Predicted and best evaluated models have been successfully deposited to PMDB database with PMDB ID PM0077505, PM0077506 and PM0077507. Active site identification revealed 11, 13 and 14 putative functional site residues in respected models. It may play a major role during protein-protein, and protein-cofactor interactions. This study can provide us an ab-initio and detail information to understand the structure, mechanism of action and regulation of mxaF protein.

Structure prediction and analysis of MxaF from obligate, facultative and restricted facultative methylobacterium

PubMed Central

Singh, Raghvendra Pratap; Singh, Ram Nageena; Srivastava, Manish K; Srivastava, Alok Kumar; Kumar, Sudheer; Dubey, Ramesh Chandra; Sharma, Arun Kumar

2012-01-01

Methylobacteria are ubiquitous in the biosphere which are capable of growing on C1 compounds such as formate, formaldehyde, methanol and methylamine as well as on a wide range of multi-carbon growth substrates such as C2, C3 and C4 compounds due to the methylotrophic enzymes methanol dehydrogenase (MDH). MDH is performing these functions with the help of a key protein mxaF. Unfortunately, detailed structural analysis and homology modeling of mxaF is remains undefined. Hence, the objective of this research is the characterization and three dimensional modeling of mxaF protein from three different methylotrophs by using I-TASSER server. The predicted model were further optimize and validate by Profile 3D, Errat, Verifiy3-D and PROCHECK server. Predicted and best evaluated models have been successfully deposited to PMDB database with PMDB ID PM0077505, PM0077506 and PM0077507. Active site identification revealed 11, 13 and 14 putative functional site residues in respected models. It may play a major role during protein-protein, and protein-cofactor interactions. This study can provide us an ab-initio and detail information to understand the structure, mechanism of action and regulation of mxaF protein. PMID:23275704

Predicting acute contact toxicity of pesticides in honeybees (Apis mellifera) through a k-nearest neighbor model.

PubMed

Como, F; Carnesecchi, E; Volani, S; Dorne, J L; Richardson, J; Bassan, A; Pavan, M; Benfenati, E

2017-01-01

Ecological risk assessment of plant protection products (PPPs) requires an understanding of both the toxicity and the extent of exposure to assess risks for a range of taxa of ecological importance including target and non-target species. Non-target species such as honey bees (Apis mellifera), solitary bees and bumble bees are of utmost importance because of their vital ecological services as pollinators of wild plants and crops. To improve risk assessment of PPPs in bee species, computational models predicting the acute and chronic toxicity of a range of PPPs and contaminants can play a major role in providing structural and physico-chemical properties for the prioritisation of compounds of concern and future risk assessments. Over the last three decades, scientific advisory bodies and the research community have developed toxicological databases and quantitative structure-activity relationship (QSAR) models that are proving invaluable to predict toxicity using historical data and reduce animal testing. This paper describes the development and validation of a k-Nearest Neighbor (k-NN) model using in-house software for the prediction of acute contact toxicity of pesticides on honey bees. Acute contact toxicity data were collected from different sources for 256 pesticides, which were divided into training and test sets. The k-NN models were validated with good prediction, with an accuracy of 70% for all compounds and of 65% for highly toxic compounds, suggesting that they might reliably predict the toxicity of structurally diverse pesticides and could be used to screen and prioritise new pesticides. Copyright © 2016 Elsevier Ltd. All rights reserved.