Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

PubMed

Ferreira da Costa, Joana; Silva, David; Caamaño, Olga; Brea, José M; Loza, Maria Isabel; Munteanu, Cristian R; Pazos, Alejandro; García-Mera, Xerardo; González-Díaz, Humbert

2018-06-25

Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70-91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical-experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC 50 , EC 50 , K i , etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.

Phosphorus sorption on marine carbonate sediment: phosphonate as model organic compounds.

PubMed

Huang, Xiao-Lan; Zhang, Jia-Zhong

2011-11-01

Organophosphonate, characterized by the presence of a stable, covalent, carbon to phosphorus (C-P) bond, is a group of synthetic or biogenic organophosphorus compounds. The fate of these organic phosphorus compounds in the environment is not well studied. This study presents the first investigation on the sorption of phosphorus (P) in the presence of two model phosphonate compounds, 2-aminothylphosphonoic acid (2-AEP) and phosphonoformic acid (PFA), on marine carbonate sediments. In contrast to other organic P compounds, no significant inorganic phosphate exchange was observed in seawater. P was found to adsorb on the sediment only in the presence of PFA, not 2-AEP. This indicated that sorption of P from phosphonate on marine sediment was compound specific. Compared with inorganic phosphate sorption on the same sediments, P sorption from organic phosphorus is much less in the marine environment. Further study is needed to understand the potential role of the organophosphonate compounds in biogeochemical cycle of phosphorus in the environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)

PubMed Central

Myint, Kyaw Z.; Xie, Xiang-Qun

2015-01-01

This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In addition, the FANN-QSAR model was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds. We discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research. PMID:25502380

Selection of quantum chemical descriptors by chemometric methods in the study of antioxidant activity of flavonoid compounds

NASA Astrophysics Data System (ADS)

Weber, K. C.; Honório, K. M.; da Silva, S. L.; Mercadante, R.; da Silva, A. B. F.

In the present study, the aim was to select electronic properties responsible for free radical scavenging ability of a set of 25 flavonoid compounds employing chemometric methods. Electronic parameters were calculated using the AM1 semiempirical method, and chemometric methods (principal component analysis, hierarchical cluster analysis, and k-nearest neighbor) were used with the aim to build models able to find relationships between electronic features and the antioxidant activity presented by the compounds studied. According to these models, four electronic variables can be considered important to discriminate more and less antioxidant flavonoid compounds: polarizability (α), charge at carbon 3 (QC3), total charge at substituent 5 (QS5), and total charge at substituent 3' (QS3'). The features found as being responsible for the antioxidant activity of the flavonoid compounds studied are consistent with previous results found in the literature. The results obtained can also bring improvements in the search for better antioxidant flavonoid compounds.

Long-term transport behavior of psychoactive compounds in sewage-affected groundwater

NASA Astrophysics Data System (ADS)

Nham, Hang Thuy Thi; Greskowiak, Janek; Hamann, Enrico; Meffe, Raffaella; Hass, Ulrike; Massmann, Gudrun

2016-11-01

The present study provides a model-based characterization of the long-term transport behavior of five psychoactive compounds (meprobamate, pyrithyldione, primidone, phenobarbital and phenylethylmalonamide) introduced into groundwater via sewage irrigation in Berlin, Germany. Compounds are still present in the groundwater despite the sewage farm closure in the year 1980. Due to the limited information on (i) compound concentrations in the source water and (ii) substance properties, a total of 180 cross-sectional model realizations for each compound were carried out, covering a large range of possible parameter combinations. Results were compared with the present-day contamination patterns in the aquifer and the most likely scenarios were identified based on a number of model performance criteria. The simulation results show that (i) compounds are highly persistent under the present field conditions, and (ii) sorption is insignificant. Thus, back-diffusion from low permeability zones appears as the main reason for the compound retardation.

Measurement and Modeling of Setschenow Constants for Selected Hydrophilic Compounds in NaCl and CaCl2 Simulated Carbon Storage Brines.

PubMed

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

2017-06-20

Carbon capture, utilization, and storage (CCUS), a climate change mitigation strategy, along with unconventional oil and gas extraction, generates enormous volumes of produced water containing high salt concentrations and a litany of organic compounds. Understanding the aqueous solubility of organic compounds related to these operations is important for water treatment and reuse alternatives, as well as risk assessment purposes. The well-established Setschenow equation can be used to determine the effect of salts on aqueous solubility. However, there is a lack of reported Setschenow constants, especially for polar organic compounds. In this study, the Setschenow constants for selected hydrophilic organic compounds were experimentally determined, and linear free energy models for predicting the Setschenow constant of organic chemicals in concentrated brines were developed. Solid phase microextraction was employed to measure the salting-out behavior of six selected hydrophilic compounds up to 5 M NaCl and 2 M CaCl 2 and in Na-Ca-Cl brines. All compounds, which include phenol, p-cresol, hydroquinone, pyrrole, hexanoic acid, and 9-hydroxyfluorene, exhibited log-linear behavior up to these concentrations, meaning Setschenow constants previously measured at low salt concentrations can be extrapolated up to high salt concentrations for hydrophilic compounds. Setschenow constants measured in NaCl and CaCl 2 brines are additive for the compounds measured here; meaning Setschenow constants measured in single salt solutions can be used in multiple salt solutions. The hydrophilic compounds in this study were selected to elucidate differences in salting-out behavior based on their chemical structure. Using data from this study, as well as literature data, linear free energy relationships (LFERs) for prediction of NaCl, CaCl 2 , LiCl, and NaBr Setschenow constants were developed and validated. Two LFERs were improved. One LFER uses the Abraham solvation parameters, which include the index of refraction of the organic compound, organic compound's polarizability, hydrogen bonding acidity and basicity of the organic compound, and the molar volume of the compound. The other uses an octanol-water partitioning coefficient to predict NaCl Setschenow constants. Improved models from this study now include organic compounds that are structurally and chemically more diverse than the previous models. The CaCl 2 , LiCl, and NaBr single parameter LFERs use concepts from the Hofmeister series to predict new, respective Setschenow constants from NaCl Setschenow constants. The Setschenow constants determined here, as well as the LFERs developed, can be incorporated into CCUS reactive transport models to predict aqueous solubility and partitioning coefficients of organic compounds. This work also has implications for beneficial reuse of water from CCUS; this can aide in determining treatment technologies for produced waters.

VOLATILE ORGANIC COMPOUND EMISSIONS FROM LATEX PAINT-PART 2. TEST HOUSE STUDIES AND INDOOR AIR QUALITY (IAQ) MODELING

EPA Science Inventory

Emission models developed using small chamber data were combined with an Indoor Air Quality (IAQ) model to analyze the impact of volatile organic compound (VOC) emissions from latex paint on indoor environments. Test house experiments were conducted to verify the IAQ model's pred...

SOURCE APPORTIONMENT OF EXPOSURES TO VOLATILE ORGANIC COMPOUNDS: II. APPLICATION OF RECEPTOR MODELS TO TEAM STUDY DATA. (R826788)

EPA Science Inventory

Four receptor-oriented source apportionment models were applied to personal exposure measurements for toxic volatile organic compounds (VOCs). The measurements are from the total exposure assessment methodology studies conducted from 1980 to 1984 in New Jersey (NJ) and Califor...

Aegeline inspired synthesis of novel β3-AR agonist improves insulin sensitivity in vitro and in vivo models of insulin resistance.

PubMed

Rajan, Sujith; Satish, Sabbu; Shankar, Kripa; Pandeti, Sukanya; Varshney, Salil; Srivastava, Ankita; Kumar, Durgesh; Gupta, Abhishek; Gupta, Sanchita; Choudhary, Rakhi; Balaramnavar, Vishal M; Narender, Tadigoppula; Gaikwad, Anil N

2018-03-07

In our drug discovery program of natural product, earlier we have reported Aegeline that is N-acylated-1-amino-2- alcohol, which was isolated from the leaves of Aeglemarmelos showed anti-hyperlipidemic activity for which the QSAR studies predicted the compound to be the β3-AR agonist, but the mechanism of its action was not elucidated. In our present study, we have evaluated the β3-AR activity of novel N-acyl-1-amino-3-arylopropanol synthetic mimics of aegeline and its beneficial effect in insulin resistance. In this study, we have proposed the novel pharmacophore model using reported molecules for antihyperlipidemic activity. The reported pharmacophore features were also compared with the newly developed pharmacophore model for the observed biological activity. Based on 3D pharmacophore modeling of known β3AR agonist, we screened 20 synthetic derivatives of Aegeline from the literature. From these, the top scoring compound 10C was used for further studies. The in-slico result was further validated in HEK293T cells co-trransfected with human β3-AR and CRE-Luciferase reporter plasmid for β3-AR activity.The most active compound was selected and β3-AR activity was further validated in white and brown adipocytes differentiated from human mesenchymal stem cells (hMSCs). Insulin resistance model developed in hMSC derived adipocytes was used to study the insulin sensitizing property. 8 week HFD fed C57BL6 mice was given 50 mg/Kg of the selected compound and metabolic phenotyping was done to evaluate its anti-diabetic effect. As predicted by in-silico 3D pharmacophore modeling, the compound 10C was found to be the most active and specific β3-AR agonist with EC 50 value of 447 nM. The compound 10C activated β3AR pathway, induced lipolysis, fatty acid oxidation and increased oxygen consumption rate (OCR) in human adipocytes. Compound 10C induced expression of brown adipocytes specific markers and reverted chronic insulin induced insulin resistance in white adipocytes. The compound 10C also improved insulin sensitivity and glucose tolerance in 8 week HFD fed C57BL6 mice. This study enlightens the use of in vitro insulin resistance model close to human physiology to elucidates the insulin sensitizing activity of the compound 10C and edifies the use of β3AR agonist as therapeutic interventions for insulin resistance and type 2 diabetes. Copyright © 2018. Published by Elsevier Inc.

New consensus multivariate models based on PLS and ANN studies of sigma-1 receptor antagonists.

PubMed

Oliveira, Aline A; Lipinski, Célio F; Pereira, Estevão B; Honorio, Kathia M; Oliveira, Patrícia R; Weber, Karen C; Romero, Roseli A F; de Sousa, Alexsandro G; da Silva, Albérico B F

2017-10-02

The treatment of neuropathic pain is very complex and there are few drugs approved for this purpose. Among the studied compounds in the literature, sigma-1 receptor antagonists have shown to be promising. In order to develop QSAR studies applied to the compounds of 1-arylpyrazole derivatives, multivariate analyses have been performed in this work using partial least square (PLS) and artificial neural network (ANN) methods. A PLS model has been obtained and validated with 45 compounds in the training set and 13 compounds in the test set (r 2 training = 0.761, q 2 = 0.656, r 2 test = 0.746, MSE test = 0.132 and MAE test = 0.258). Additionally, multi-layer perceptron ANNs (MLP-ANNs) were employed in order to propose non-linear models trained by gradient descent with momentum backpropagation function. Based on MSE test values, the best MLP-ANN models were combined in a MLP-ANN consensus model (MLP-ANN-CM; r 2 test = 0.824, MSE test = 0.088 and MAE test = 0.197). In the end, a general consensus model (GCM) has been obtained using PLS and MLP-ANN-CM models (r 2 test = 0.811, MSE test = 0.100 and MAE test = 0.218). Besides, the selected descriptors (GGI6, Mor23m, SRW06, H7m, MLOGP, and μ) revealed important features that should be considered when one is planning new compounds of the 1-arylpyrazole class. The multivariate models proposed in this work are definitely a powerful tool for the rational drug design of new compounds for neuropathic pain treatment. Graphical abstract Main scaffold of the 1-arylpyrazole derivatives and the selected descriptors.

An acute rat in vivo screening model to predict compounds that alter blood glucose and/or insulin regulation.

PubMed

Brott, David A; Diamond, Melody; Campbell, Pam; Zuvich, Andy; Cheatham, Letitia; Bentley, Patricia; Gorko, Mary Ann; Fikes, James; Saye, JoAnne

2013-01-01

Drug-induced glucose dysregulation and insulin resistance have been associated with weight gain and potential induction and/or exacerbation of diabetes mellitus in the clinic suggesting they may be safety biomarkers when developing antipsychotics. Glucose and insulin have also been suggested as potential efficacy biomarkers for some oncology compounds. The objective of this study was to qualify a medium throughput rat in vivo acute Intravenous Glucose Tolerance Test (IVGTT) for predicting compounds that will induce altered blood glucose and/or insulin levels. Acute and sub-chronic studies were performed to qualify an acute IVGTT model. Double cannulated male rats (Han-Wistar and Sprague-Dawley) were administered vehicle, olanzapine, aripiprazole or other compounds at t=-44min for acute studies and at time=-44min on the last day of dosing for sub-chronic studies, treated with dextrose (time=0min; i.v.) and blood collected using an automated Culex® system for glucose and insulin analysis (time=-45, -1, 2, 10, 15, 30, 45, 60, 75, 90, 120, 150 and 180min). Olanzapine significantly increased glucose and insulin area under the curve (AUC) values while aripiprazole AUC values were similar to control, in both acute and sub-chronic studies. All atypical antipsychotics evaluated were consistent with literature references of clinical weight gain. As efficacy biomarkers, insulin AUC but not glucose AUC values were increased with a compound known to have insulin growth factor-1 (IGF-1) activity, compared to control treatment. These studies qualified the medium throughput acute IVGTT model to more quickly screen compounds for 1) safety - the potential to elicit glucose dysregulation and/or insulin resistance and 2) efficacy - as a surrogate for compounds affecting the glucose and/or insulin regulatory pathways. These data demonstrate that the same in vivo rat model and assays can be used to predict both clinical safety and efficacy of compounds. © 2013.

Competitive adsorption of furfural and phenolic compounds onto activated carbon in fixed bed column.

PubMed

Sulaymon, Abbas H; Ahmed, Kawther W

2008-01-15

For a multicomponent competitive adsorption of furfural and phenolic compounds, a mathematical model was builtto describe the mass transfer kinetics in a fixed bed column with activated carbon. The effects of competitive adsorption equilibrium constant, axial dispersion, external mass transfer, and intraparticle diffusion resistance on the breakthrough curve were studied for weakly adsorbed compound (furfural) and strongly adsorbed compounds (parachlorophenol and phenol). Experiments were carried out to remove the furfural and phenolic compound from aqueous solution. The equilibrium data and intraparticle diffusion coefficients obtained from separate experiments in a batch adsorber, by fitting the experimental data with theoretical model. The results show that the mathematical model includes external mass transfer and pore diffusion using nonlinear isotherms and provides a good description of the adsorption process for furfural and phenolic compounds in a fixed bed adsorber.

Potential Compounds for Oral Cancer Treatment: Resveratrol, Nimbolide, Lovastatin, Bortezomib, Vorinostat, Berberine, Pterostilbene, Deguelin, Andrographolide, and Colchicine

PubMed Central

Bundela, Saurabh; Sharma, Anjana; Bisen, Prakash S.

2015-01-01

Oral cancer is one of the main causes of cancer-related deaths in South-Asian countries. There are very limited treatment options available for oral cancer. Research endeavors focused on discovery and development of novel therapies for oral cancer, is necessary to control the ever rising oral cancer related mortalities. We mined the large pool of compounds from the publicly available compound databases, to identify potential therapeutic compounds for oral cancer. Over 84 million compounds were screened for the possible anti-cancer activity by custom build SVM classifier. The molecular targets of the predicted anti-cancer compounds were mined from reliable sources like experimental bioassays studies associated with the compound, and from protein-compound interaction databases. Therapeutic compounds from DrugBank, and a list of natural anti-cancer compounds derived from literature mining of published studies, were used for building partial least squares regression model. The regression model thus built, was used for the estimation of oral cancer specific weights based on the molecular targets. These weights were used to compute scores for screening the predicted anti-cancer compounds for their potential to treat oral cancer. The list of potential compounds was annotated with corresponding physicochemical properties, cancer specific bioactivity evidences, and literature evidences. In all, 288 compounds with the potential to treat oral cancer were identified in the current study. The majority of the compounds in this list are natural products, which are well-tolerated and have minimal side-effects compared to the synthetic counterparts. Some of the potential therapeutic compounds identified in the current study are resveratrol, nimbolide, lovastatin, bortezomib, vorinostat, berberine, pterostilbene, deguelin, andrographolide, and colchicine. PMID:26536350

Accelerated cure of phenol-formaldehyde resins : studies with model compounds

Treesearch

Anthony H. Conner; Linda F. Lorenz; Kolby C. Hirth

2002-01-01

2-Hydroxymethylphenol (2-HMP) and 4-hydroxymethylphenol (4-HMP) were used as model compounds to study the reactions that occur during cure of phenol-formaldehyde (PF) resin to which cure accelerators (ethyl formate, propylene carbonate, g-butyrolactone, and triacetin) have been added. The addition of cure accelerators significantly increased the rate of condensation...

A case study on the influences of long-range transport to Taiwan`s acid deposition using Taiwan air quality model

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

Ken-Hui Chang; Fu-Tien Jeng

1996-12-31

The long-range and transboundary transport of precursors of add deposition in East Asia became important due to the industrial development around this area. We started to develop Taiwan Air Quality Model (TAQM) system since 1992, which is based on regional Acid Deposition Model (RADM) system. A typical episode in Mei-Yu season has been selected to study. A case considering all emissions within simulated domain has been run as a reference case, and another perturbed case, not including Taiwan`s emission, has been also run for analyzing quantitatively the influence of long-range transport to Taiwan`s wet deposition during the episode are 31%more » and 24% for total sulfur compounds and total nitrogen compounds respectively; but for dry deposition, only 6% is contributed by long range transport for sulfur compounds and 29% for total nitrogen compounds. Therefore, the percentages of total acid deposition contributed by long-range transport are 27% and 25% for total sulfur compounds and total nitrogen compounds, respectively.« less

In silico study toward the identification of new and safe potential inhibitors of photosynthetic electron transport.

PubMed

Ribeiro, Taisa Pereira Piacentini; Manarin, Flávia Giovana; Borges de Melo, Eduardo

2018-05-30

To address the rising global demand for food, it is necessary to search for new herbicides that can control resistant weeds. We performed a 2D-quantitative structure-activity relationship (QSAR) study to predict compounds with photosynthesis-inhibitory activity. A data set of 44 compounds (quinolines and naphthalenes), which are described as photosynthetic electron transport (PET) inhibitors, was used. The obtained model was approved in internal and external validation tests. 2D Similarity-based virtual screening was performed and 64 compounds were selected from the ZINC database. By using the VEGA QSAR software, 48 compounds were shown to have potential toxic effects (mutagenicity and carcinogenicity). Therefore, the model was also tested using a set of 16 molecules obtained by a similarity search of the ZINC database. Six compounds showed good predicted inhibition of PET. The obtained model shows potential utility in the design of new PET inhibitors, and the hit compounds found by virtual screening are novel bicyclic scaffolds of this class. Copyright © 2018 Elsevier Inc. All rights reserved.

Selecting a Response in Task Switching: Testing a Model of Compound Cue Retrieval

ERIC Educational Resources Information Center

Schneider, Darryl W.; Logan, Gordon D.

2009-01-01

How can a task-appropriate response be selected for an ambiguous target stimulus in task-switching situations? One answer is to use compound cue retrieval, whereby stimuli serve as joint retrieval cues to select a response from long-term memory. In the present study, the authors tested how well a model of compound cue retrieval could account for a…

Hydrodeoxygenation of coal using organometallic catalyst precursors

NASA Astrophysics Data System (ADS)

Kirby, Stephen R.

2002-04-01

The objective of this dissertation was to determine the desirability of organometallic compounds for the hydrodeoxygenation (HDO) of coal during liquefaction. The primary focus of this study was the removal of phenol-like compounds from coal liquids for the production of a thermally stable jet fuel. Investigation of the HDO ability of an organometallic compound containing both cobalt and molybdenum (CoMo-T2) was achieved using a combination of model compound and coal experiments. Model compounds were chosen representing four oxygen functional groups present in a range of coals. Electron density and bond order calculations were performed for anthrone, dinaphthyl ether, xanthene, di-t-butylmethylphenol, and some of their derivatives to ascertain a potential order of hydrogenolysis and hydrogenation reactivity for these compounds. The four model compounds were then reacted with CoMo-T2, as well as ammonium tetrathiomolybdate (ATTM). Products of reaction were grouped as compounds that had undergone deoxygenation, those that had aromatic rings reduced, those that were products of both reaction pathways, and those produced through other routes. ATTM had an affinity for both reaction types. Its reaction order for the four model compounds with respect to deoxygenated compounds was the same as that estimated from electron density calculations for hydrogenolysis reactivity. CoMo-T2 appeared to show a preference toward hydrogenation, although deoxygenated products were still achieved in similar, or greater, yields, for almost all the model compounds. The reactivity order achieved for the four compounds with CoMo-T2 was similar to that estimated from bond order calculations for hydrogenation reactivity. Three coals were selected representing a range of coal ranks and oxygen contents. DECS-26 (Wyodak), DECS-24 (Illinois #6), and DECS-23 (Pittsburgh #8) were analyzed by CPMAS 13C NMR and pyrolysis-GC-MS to determine the functional groups comprising the oxygen content of these coals. Trends within the data were similar to those reported by other authors. Based on the conclusions from both the model compound studies and the coal analysis, predictions were made of the catalyst precursors' performance in the HDO of the three selected coals. It was concluded that CoMo-T2 is a desirable catalyst precursor for the HDO of coals (particularly low-rank coals), but that an optimum set of conditions must be determined to take full advantage of its HDO ability. (Abstract shortened by UMI.)

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

Imidazopyridine derivatives as potent and selective Polo-like kinase (PLK) inhibitors.

PubMed

Sato, Yoshiyuki; Onozaki, Yu; Sugimoto, Tetsuya; Kurihara, Hideki; Kamijo, Kaori; Kadowaki, Chie; Tsujino, Toshiaki; Watanabe, Akiko; Otsuki, Sachie; Mitsuya, Morihiro; Iida, Masato; Haze, Kyosuke; Machida, Takumitsu; Nakatsuru, Yoko; Komatani, Hideya; Kotani, Hidehito; Iwasawa, Yoshikazu

2009-08-15

A novel class of imidazopyridine derivatives was designed as PLK1 inhibitors. Extensive SAR studies supported by molecular modeling afforded a highly potent and selective compound 36. Compound 36 demonstrated good antitumor efficacy in xenograft nude rat model.

Design, synthesis, molecular modeling and biological evaluation of novel 2,3-dihydrophthalazine-1,4-dione derivatives as potential anticonvulsant agents

NASA Astrophysics Data System (ADS)

El-Helby, Abdel Ghany A.; Ayyad, Rezk R.; Sakr, Helmy M.; Abdelrahim, Adel S.; El-Adl, K.; Sherbiny, Farag S.; Eissa, Ibrahim H.; Khalifa, Mohamed M.

2017-02-01

In view of their expected anticonvulsant activity, some novel derivatives of 2,3-dihydrophthalazine-1,4-dione 4-22 were designed, synthesized and evaluated using pentylenetetrazole (PTZ) and picrotoxin as convulsion-inducing models. Moreover, the most active compounds were tested against electrical induced convulsion using maximal electroshock (MES) models of seizures. Most of the tested compounds showed considerable anticonvulsant activity in at least one of the anticonvulsant tests. Compounds 13 and 14g were proved to be the most potent compounds of this series with relatively low toxicity in the median lethal dose test when compared with the reference drug. Molecular modeling studies were done to verify the biological activity. The obtained results showed that the most potent compounds could be useful as a template for future design, optimization, and investigation to produce more active analogues.

Effects of gas-wall partitioning in Teflon tubing and instrumentation on time-resolved measurements of gas-phase organic compounds

NASA Astrophysics Data System (ADS)

Pagonis, Demetrios; Krechmer, Jordan E.; de Gouw, Joost; Jimenez, Jose L.; Ziemann, Paul J.

2017-12-01

Recent studies have demonstrated that organic compounds can partition from the gas phase to the walls in Teflon environmental chambers and that the process can be modeled as absorptive partitioning. Here these studies were extended to investigate gas-wall partitioning of organic compounds in Teflon tubing and inside a proton-transfer-reaction mass spectrometer (PTR-MS) used to monitor compound concentrations. Rapid partitioning of C8-C14 2-ketones and C11-C16 1-alkenes was observed for compounds with saturation concentrations (c∗) in the range of 3 × 104 to 1 × 107 µg m-3, causing delays in instrument response to step-function changes in the concentration of compounds being measured. These delays vary proportionally with tubing length and diameter and inversely with flow rate and c∗. The gas-wall partitioning process that occurs in tubing is similar to what occurs in a gas chromatography column, and the measured delay times (analogous to retention times) were accurately described using a linear chromatography model where the walls were treated as an equivalent absorbing mass that is consistent with values determined for Teflon environmental chambers. The effect of PTR-MS surfaces on delay times was also quantified and incorporated into the model. The model predicts delays of an hour or more for semivolatile compounds measured under commonly employed conditions. These results and the model can enable better quantitative design of sampling systems, in particular when fast response is needed, such as for rapid transients, aircraft, or eddy covariance measurements. They may also allow estimation of c∗ values for unidentified organic compounds detected by mass spectrometry and could be employed to introduce differences in time series of compounds for use with factor analysis methods. Best practices are suggested for sampling organic compounds through Teflon tubing.

A PHYSIOLOGICALLY BASED TOXICOKINETIC MODEL FOR DIETARY UPTAKE OF HYDROPHOBIC ORGANIC COMPOUNDS BY FISH: I. FEEDING STUDIES WITH 2,2',5,5'-TETRACHLOROBIPHENYL

EPA Science Inventory

A physiologically-based toxicokinetic (PBTK) model was developed to describe dietary uptake of hydrophobic organic compounds by fish. The gastrointestinal (GI) tract was modeled using four compartments corresponding to the stomach, pyloric ceca, upper intestine, and lower intesti...

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.

Derivation of a human equivalent concentration for n-butanol using a physiologically based pharmacokinetic model for n-butyl acetate and metabolites n-butanol and n-butyric acid

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

Teeguarden, Justin G.; Deisinger, P. J.; Poet, Torka S.

2005-05-01

The metabolic series (family) approach for risk assessment uses a dosimetry-based analysis to develop toxicity information for a group of metabolically linked compounds using pharmacokinetic (PK) data for each compound and toxicity data for the parent compound. An initial physiologically-based pharmacokinetic (PBPK) model was developed to support the implementation of the metabolic series approach for n-butyl acetate and its subsequent metabolites, n-butanol, and n-butyric acid (the butyl series) (Barton et al. 2000). In conjunction with pilot pharmacokinetic studies, the model was used to design the definitive intravenous (i.v.) PK studies. Rats were implanted with dual indwelling cannulae and administered testmore » compounds by i.v. bolus dose, i.v. infusion, or by inhalation in a recirculating closed chamber. Hepatic, vascular and extravascular metabolic constants for metabolism were estimated by fitting the model to the blood time course data from these experiments. The respiratory bioavailability of n-butyl acetate and n-butanol was estimated from closed chamber inhalation studies and measured ventilation rates. The resulting butyl series PBPK model successfully reproduces the blood time course of these compounds following i.v. administration, and inhalation exposure to n-butyl acetate and n-butanol. A fully scaled human version of the model successfully reproduces arterial blood n-butanol kinetics following inhalation exposure to n-butanol. These validated i.v (rat) and inhalation route models (rat, butyl acetate, n-butanol; human, butanol only) can be used to support species and dose-route extrapolations required for risk assessment of butyl series family of compounds. Further, this work demonstrates the usefulness of i.v. kinetic data for parameterization of systemic metabolism and the value of collaboration between experimentalists and kineticists in the development of PBPK models. The product of this effort, validated rat and human PBPK models for the butyl series compounds, illustrates the effectiveness of broad multi-institutional public/private collaborations in the pursuit of developing state of the art tools for risk assessment.« less

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.

Reactivity of Cork Extracts with (+)-Catechin and Malvidin-3-O-glucoside in Wine Model Solutions: Identification of a New Family of Ellagitannin-Derived Compounds (Corklins).

PubMed

Azevedo, Joana; Fernandes, Ana; Oliveira, Joana; Brás, Natércia F; Reis, Sofia; Lopes, Paulo; Roseira, Isabel; Cabral, Miguel; Mateus, Nuno; de Freitas, Victor

2017-10-04

The aim of this study was to evaluate the reactivity of phenolic compounds extracted from cork stoppers to wine model solutions with two major wine components, namely, (+)-catechin and malvidin-3-O-glucoside. Besides the formation of some compounds already described in the literature, these reactions also yielded a new family of ellagitannin-derived compounds, named herein as corklins. This new family of compounds that were found to result from the interaction between ellagitannins in alcoholic solutions and (+)-catechin were structurally characterized by mass spectroscopy, nuclear magnetic resonance, and computational methods.

Selective CB2 receptor agonists. Part 2: Structure-activity relationship studies and optimization of proline-based compounds.

PubMed

Riether, Doris; Zindell, Renee; Wu, Lifen; Betageri, Raj; Jenkins, James E; Khor, Someina; Berry, Angela K; Hickey, Eugene R; Ermann, Monika; Albrecht, Claudia; Ceci, Angelo; Gemkow, Mark J; Nagaraja, Nelamangala V; Romig, Helmut; Sauer, Achim; Thomson, David S

2015-02-01

Through a ligand-based pharmacophore model (S)-proline based compounds were identified as potent cannabinoid receptor 2 (CB2) agonists with high selectivity over the cannabinoid receptor 1 (CB1). Structure-activity relationship investigations for this compound class lead to oxo-proline compounds 21 and 22 which combine an impressive CB1 selectivity profile with good pharmacokinetic properties. In a streptozotocin induced diabetic neuropathy model, 22 demonstrated a dose-dependent reversal of mechanical hyperalgesia. Copyright © 2014 Elsevier Ltd. All rights reserved.

Competition between the compound and the pre-compound emission processes in α-induced reactions at near astrophysical energy to well above it

NASA Astrophysics Data System (ADS)

Sharma, Manoj Kumar; Sharma, Vijay Raj; Yadav, Abhiskek; Singh, Pushpendra P.; Singh, B. P.; Prasad, R.

2016-04-01

The study of pre-compound emission in α-induced reactions, particularly at the low incident energies, is of considerable interest as the pre-compound emission is more likely to occur at higher energies. With a view to study the competition between the compound and the pre-compound emission processes in α-induced reactions at different energies and with different targets, a systematics for neutron emission channels in targets 51V, 55Mn, 93Nb, 121, 123Sb and 141Pr at energy ranging from astrophysical interest to well above it, has been developed. The off-line γ-ray-spectrometry based activation technique has been adopted to measure the excitation functions. The experimental excitation functions have been analysed within the framework of the compound nucleus mechanism based on the Weisskopf-Ewing model and the pre-compound emission calculations based on the geometry dependent hybrid model. The analysis of the data shows that experimental excitation functions could be reproduced only when the pre-compound emission, simulated theoretically, is taken into account. The strength of pre-compound emission process for each system has been obtained by deducing the pre-compound fraction. Analysis of data indicates that in α-induced reactions, the pre-compound emission process plays an important role, particularly at the low incident energies, where the pure compound nucleus process is likely to dominate.

MODELING OF MULTICOMPONENT PERVAPORATION FOR REMOVAL OF VOLATILE ORGANIC COMPOUNDS FROM WATER

EPA Science Inventory

A resistance-in-series model was used to study the pervaporation of multiple volatile organic compounds (VOCs)-water mixtures. Permeation experiments were carried out for four membranes: poly(dimethylsiloxane) (PDMS), polyether-block-polyamides (PEBA), polyurethane (PUR) and sil...

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.

Cross-Platform Toxicogenomics for the Prediction of Non-Genotoxic Hepatocarcinogenesis in Rat

PubMed Central

Metzger, Ute; Templin, Markus F.; Plummer, Simon; Ellinger-Ziegelbauer, Heidrun; Zell, Andreas

2014-01-01

In the area of omics profiling in toxicology, i.e. toxicogenomics, characteristic molecular profiles have previously been incorporated into prediction models for early assessment of a carcinogenic potential and mechanism-based classification of compounds. Traditionally, the biomarker signatures used for model construction were derived from individual high-throughput techniques, such as microarrays designed for monitoring global mRNA expression. In this study, we built predictive models by integrating omics data across complementary microarray platforms and introduced new concepts for modeling of pathway alterations and molecular interactions between multiple biological layers. We trained and evaluated diverse machine learning-based models, differing in the incorporated features and learning algorithms on a cross-omics dataset encompassing mRNA, miRNA, and protein expression profiles obtained from rat liver samples treated with a heterogeneous set of substances. Most of these compounds could be unambiguously classified as genotoxic carcinogens, non-genotoxic carcinogens, or non-hepatocarcinogens based on evidence from published studies. Since mixed characteristics were reported for the compounds Cyproterone acetate, Thioacetamide, and Wy-14643, we reclassified these compounds as either genotoxic or non-genotoxic carcinogens based on their molecular profiles. Evaluating our toxicogenomics models in a repeated external cross-validation procedure, we demonstrated that the prediction accuracy of our models could be increased by joining the biomarker signatures across multiple biological layers and by adding complex features derived from cross-platform integration of the omics data. Furthermore, we found that adding these features resulted in a better separation of the compound classes and a more confident reclassification of the three undefined compounds as non-genotoxic carcinogens. PMID:24830643

Understanding the mental lexicon through neglect dyslexia: a study on compound noun reading.

PubMed

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

2013-04-01

The present study employs neglect dyslexia (ND) as an experimental model to study compound-word processing; in particular, it investigates whether compound constituents are hierarchically organized at mental level and addresses the possibility of whole-word representation. Seven Italian-speaking patients suffering from ND participated in a word naming task. Both left-headed (pescespada, swordfish) and right-headed (astronave, spaceship) Italian compound nouns were used as stimuli. Non-existent compounds, which were generated by substituting the leftmost constituent of a compound with an orthographically similar word (e.g., *pestespada, *plaguesword), were also employed. A significant headedness effect emerged in the group analysis: patients read left-headed compounds better than right-headed compounds. A significant lexicality effect was also found: the participants read real compounds better than their non-existent compound pairs. Moreover, logit mixed-effects analyses indicated a left-hand constituent frequency effect. Results are discussed in terms of hierarchical representation of compounds and direct access to compound lemma nodes.

Oral LD50 toxicity modeling and prediction of per- and polyfluorinated chemicals on rat and mouse.

PubMed

Bhhatarai, Barun; Gramatica, Paola

2011-05-01

Quantitative structure-activity relationship (QSAR) analyses were performed using the LD(50) oral toxicity data of per- and polyfluorinated chemicals (PFCs) on rodents: rat and mouse. PFCs are studied under the EU project CADASTER which uses the available experimental data for prediction and prioritization of toxic chemicals for risk assessment by using the in silico tools. The methodology presented here applies chemometrical analysis on the existing experimental data and predicts the toxicity of new compounds. QSAR analyses were performed on the available 58 mouse and 50 rat LD(50) oral data using multiple linear regression (MLR) based on theoretical molecular descriptors selected by genetic algorithm (GA). Training and prediction sets were prepared a priori from available experimental datasets in terms of structure and response. These sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the models were verified on 376 per- and polyfluorinated chemicals including those in REACH preregistration list. The rat and mouse endpoints were predicted by each model for the studied compounds, and finally 30 compounds, all perfluorinated, were prioritized as most important for experimental toxicity analysis under the project. In addition, cumulative study on compounds within the AD of all four models, including two earlier published models on LC(50) rodent analysis was studied and the cumulative toxicity trend was observed using principal component analysis (PCA). The similarities and the differences observed in terms of descriptors and chemical/mechanistic meaning encoded by descriptors to prioritize the most toxic compounds are highlighted.

Modification of ginseng flavors by bitter compounds found in chocolate and coffee.

PubMed

Sook Chung, Hee; Lee, Soo-Yeun

2012-06-01

Ginseng is not widely accepted by U.S. consumers due to its unfamiliar flavors, despite its numerous health benefits. Previous studies have suggested that the bitter compounds in chocolate and coffee may mask the off-flavors of ginseng. The objectives of this study were to: (1) profile sensory characteristics of ginseng extract solution, caffeine solution, cyclo (L-Pro-L-Val) solution, theobromine solution, and 2 model solutions simulating chocolate bitterness; and (2) determine the changes in the sensory characteristics of ginseng extract solution by the addition of the bitter compounds found in chocolate and coffee. Thirteen solutions were prepared in concentrations similar to the levels of the bitter compounds found in coffee and chocolate products. Twelve panelists participated in a descriptive analysis panel which included time-intensity ratings. Ginseng extract was characterized as sweeter, starchier, and more green tea than the other sample solutions. Those characteristics of ginseng extract were effectively modified by the addition of caffeine, cyclo (L-Pro-L-Val), and 2 model solutions. A model solution simulating dark chocolate bitterness was the least influenced in intensities of bitterness by the addition of ginseng extract. Results from time-intensity ratings show that the addition of ginseng extract increased duration time in certain bitterness of the 2 model solutions. Bitter compounds found in dark chocolate could be proposed to effectively mask the unique flavors of ginseng. Future studies blending aroma compounds of chocolate and coffee into such model solutions may be conducted to investigate the influence on the perception of the unique flavors through the congruent flavors. © 2012 Institute of Food Technologists®

QSAR modeling of acute toxicity on mammals caused by aromatic compounds: the case study using oral LD50 for rats.

PubMed

Rasulev, Bakhtiyor; Kusić, Hrvoje; Leszczynska, Danuta; Leszczynski, Jerzy; Koprivanac, Natalija

2010-05-01

The goal of the study was to predict toxicity in vivo caused by aromatic compounds structured with a single benzene ring and the presence or absence of different substituent groups such as hydroxyl-, nitro-, amino-, methyl-, methoxy-, etc., by using QSAR/QSPR tools. A Genetic Algorithm and multiple regression analysis were applied to select the descriptors and to generate the correlation models. The most predictive model is shown to be the 3-variable model which also has a good ratio of the number of descriptors and their predictive ability to avoid overfitting. The main contributions to the toxicity were shown to be the polarizability weighted MATS2p and the number of certain groups C-026 descriptors. The GA-MLRA approach showed good results in this study, which allows the building of a simple, interpretable and transparent model that can be used for future studies of predicting toxicity of organic compounds to mammals.

Study of XAFS of some Fe compounds and determination of first shell radial distance

NASA Astrophysics Data System (ADS)

Parsai, Neetu; Mishra, Ashutosh

2017-05-01

X-ray absorption fine structure (XAFS) of some Fe compounds have been studied using the latest XAFS analysis software Demeter with Strawberry Perl. The processed XAFS data of the Fe compounds have been taken from available model compound library. The XAFS data have been processed to plot the µ(E) verses E spectra. These spectra have been converted into K-space, R-space and q-space. R-space spectra have been used to obtain first shell radial distance in Fe compounds. Structural parameters like first shell radial distance is useful in determination of bond length in Fe compounds. Hence the study play important role in biological applications.

Evaluation of a Silicone Membrane as an Alternative to Human Skin for Determining Skin Permeation Parameters of Chemical Compounds.

PubMed

Uchida, Takashi; Yakumaru, Masafumi; Nishioka, Keisuke; Higashi, Yoshihiro; Sano, Tomohiko; Todo, Hiroaki; Sugibayashi, Kenji

2016-01-01

We evaluated the effectiveness of a silicone membrane as an alternative to human skin using the skin permeation parameters of chemical compounds. An in vitro permeation study using 15 model compounds was conducted, and permeation parameters comprising permeability coefficient (P), diffusion parameter (DL(-2)), and partition parameter (KL) were calculated from each permeation profile. Significant correlations were obtained in log P, log DL(-2), and log KL values between the silicone membrane and human skin. DL(-2) values of model compounds, except flurbiprofen, in the silicone membrane were independent of the lipophilicity of the model compounds and were 100-fold higher than those in human skin. For antipyrine and caffeine, which are hydrophilic, KL values in the silicone membrane were 100-fold lower than those in human skin, and P values, calculated as the product of a DL(-2) and KL, were similar. For lipophilic compounds, such as n-butyl paraben and flurbiprofen, KL values for silicone were similar to or 10-fold higher than those in human skin, and P values for silicone were 100-fold higher than those in human skin. Furthermore, for amphiphilic compounds with log Ko/w values from 0.5 to 3.5, KL values in the silicone membrane were 10-fold lower than those in human skin, and P values for silicone were 10-fold higher than those in human skin. The silicone membrane was useful as a human skin alternative in an in vitro skin permeation study. However, depending on the lipophilicity of the model compounds, some parameters may be over- or underestimated.

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.

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.

Synthesis, biological evaluation and molecular modeling of novel series of pyridine derivatives as anticancer, anti-inflammatory and analgesic agents

NASA Astrophysics Data System (ADS)

Helal, M. H.; El-Awdan, S. A.; Salem, M. A.; Abd-elaziz, T. A.; Moahamed, Y. A.; El-Sherif, A. A.; Mohamed, G. A. M.

2015-01-01

This paper presents a combined synthesis; characterization, computational and biological activity studies of novel series of pyridines heterocyclic compounds. The compounds have been characterized by elemental analyses and spectral like IR, 1H NMR, 13C NMR and MS studies. Michael addition of substituted-2-methoxycarbonylacetanilide 2a,b on the α-substituted cinnamonitriles 3a-d gave the corresponding 2-pyridone derivatives 5-10. Structures of the titled compounds cited in this article were elucidated by spectrometric data (IR, 1H NMR, 13C NMR and MS). The molecular modeling of the synthesized compounds has been drawn and their molecular parameters were calculated. Also, valuable information is obtained from the calculation of molecular parameters including electronegativity, net dipole moment of the compounds, total energy, electronic energy, binding energy, HOMO and LUMO energy. Various in vitro antitumor as well as in vivo anti-inflammatory and analgesic activities of the synthesized compounds were investigated. Evaluation of anti-inflammatory activity of test compounds was performed using carrageenan induced paw edema in rats. All the tested compounds showed moderate to good activity. The SAR results indicate that all compounds showed moderate to good activity, among these 7 and 10 compounds having -N(CH3)2 group are most effective.

Pharmacokinetic parameters explain the therapeutic activity of antimicrobial agents in a silkworm infection model.

PubMed

Paudel, Atmika; Panthee, Suresh; Urai, Makoto; Hamamoto, Hiroshi; Ohwada, Tomohiko; Sekimizu, Kazuhisa

2018-01-25

Poor pharmacokinetic parameters are a major reason for the lack of therapeutic activity of some drug candidates. Determining the pharmacokinetic parameters of drug candidates at an early stage of development requires an inexpensive animal model with few associated ethical issues. In this study, we used the silkworm infection model to perform structure-activity relationship studies of an antimicrobial agent, GPI0039, a novel nitrofuran dichloro-benzyl ester, and successfully identified compound 5, a nitrothiophene dichloro-benzyl ester, as a potent antimicrobial agent with superior therapeutic activity in the silkworm infection model. Further, we compared the pharmacokinetic parameters of compound 5 with a nitrothiophene benzyl ester lacking chlorine, compound 7, that exerted similar antimicrobial activity but had less therapeutic activity in silkworms, and examined the metabolism of these antimicrobial agents in human liver fractions in vitro. Compound 5 had appropriate pharmacokinetic parameters, such as an adequate half-life, slow clearance, large area under the curve, low volume of distribution, and long mean residence time, compared with compound 7, and was slowly metabolized by human liver fractions. These findings suggest that the therapeutic effectiveness of an antimicrobial agent in the silkworms reflects appropriate pharmacokinetic properties.

Sensitivity of Aerosol Mass and Microphysics to varying treatments of Condensational Growth of Secondary Organic Compounds in a regional model

NASA Astrophysics Data System (ADS)

Lowe, Douglas; Topping, David; McFiggans, Gordon

2017-04-01

Gas to particle partitioning of atmospheric compounds occurs through disequilibrium mass transfer rather than through instantaneous equilibrium. However, it is common to treat only the inorganic compounds as partitioning dynamically whilst organic compounds, represented by the Volatility Basis Set (VBS), are partitioned instantaneously. In this study we implement a more realistic dynamic partitioning of organic compounds in a regional framework and assess impact on aerosol mass and microphysics. It is also common to assume condensed phase water is only associated with inorganic components. We thus also assess sensitivity to assuming all organics are hygroscopic according to their prescribed molecular weight. For this study we use WRF-Chem v3.4.1, focusing on anthropogenic dominated North-Western Europe. Gas-phase chemistry is represented using CBM-Z whilst aerosol dynamics are simulated using the 8-section MOSAIC scheme, including a 9-bin VBS treatment of organic aerosol. Results indicate that predicted mass loadings can vary significantly. Without gas phase ageing of higher volatility compounds, dynamic partitioning always results in lower mass loadings downwind of emission sources. The inclusion of condensed phase water in both partitioning models increases the predicted PM mass, resulting from a larger contribution from higher volatility organics, if present. If gas phase ageing of VBS compounds is allowed to occur in a dynamic model, this can often lead to higher predicted mass loadings, contrary to expected behaviour from a simple non-reactive gas phase box model. As descriptions of aerosol phase processes improve within regional models, the baseline descriptions of partitioning should retain the ability to treat dynamic partitioning of organics compounds. Using our simulations, we discuss whether derived sensitivities to aerosol processes in existing models may be inherently biased. This work was supported by the Natural Environment Research Council within the RONOCO (NE/F004656/1) and CCN-Vol (NE/L007827/1) projects.

Sensitivity of Aerosol Mass and Microphysics to Treatments of Condensational Growth of Secondary Organic Compounds in a Regional Model

NASA Astrophysics Data System (ADS)

Topping, D. O.; Lowe, D.; McFiggans, G.; Zaveri, R. A.

2016-12-01

Gas to particle partitioning of atmospheric compounds occurs through disequilibrium mass transfer rather than through instantaneous equilibrium. However, it is common to treat only the inorganic compounds as partitioning dynamically whilst organic compounds, represented by the Volatility Basis Set (VBS), are partitioned instantaneously. In this study we implement a more realistic dynamic partitioning of organic compounds in a regional framework and assess impact on aerosol mass and microphysics. It is also common to assume condensed phase water is only associated with inorganic components. We thus also assess sensitivity to assuming all organics are hygroscopic according to their prescribed molecular weight.For this study we use WRF-Chem v3.4.1, focusing on anthropogenic dominated North-Western Europe. Gas-phase chemistry is represented using CBM-Z whilst aerosol dynamics are simulated using the 8-section MOSAIC scheme, including a 9-bin volatility basis set (VBS) treatment of organic aerosol. Results indicate that predicted mass loadings can vary significantly. Without gas phase ageing of higher volatility compounds, dynamic partitioning always results in lower mass loadings downwind of emission sources. The inclusion of condensed phase water in both partitioning models increases the predicted PM mass, resulting from a larger contribution from higher volatility organics, if present. If gas phase ageing of VBS compounds is allowed to occur in a dynamic model, this can often lead to higher predicted mass loadings, contrary to expected behaviour from a simple non-reactive gas phase box model. As descriptions of aerosol phase processes improve within regional models, the baseline descriptions of partitioning should retain the ability to treat dynamic partitioning of organic compounds. Using our simulations, we discuss whether derived sensitivities to aerosol processes in existing models may be inherently biased.This work was supported by the Nature Environment Research Council within the RONOCO (NE/F004656/1) and CCN-Vol (NE/L007827/1) projects.

Predicting Age-appropriate Pharmacokinetics of Six Volatile Organic Compounds in the Rat Utilizing Physiologically-based Pharmacokinetic Modeling (T)

EPA Science Inventory

The capability of physiologically-based pharmacokinetic (PBPK) models to incorporate ageappropriate physiological and chemical-specific parameters was utilized in this study to predict changes in internal dosimetry for six volatile organic compounds (VOCs) across different ages o...

QSAR Modeling of Rat Acute Toxicity by Oral Exposure

PubMed Central

Zhu, Hao; Martin, Todd M.; Ye, Lin; Sedykh, Alexander; Young, Douglas M.; Tropsha, Alexander

2009-01-01

Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. In this study, a comprehensive dataset of 7,385 compounds with their most conservative lethal dose (LD50) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire dataset was selected that included all 3,472 compounds used in the TOPKAT’s training set. The remaining 3,913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R2 of linear regression between actual and predicted LD50 values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R2 ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD50 for every compound using all 5 models. The consensus models afforded higher prediction accuracy for the external validation dataset with the higher coverage as compared to individual constituent models. The validated consensus LD50 models developed in this study can be used as reliable computational predictors of in vivo acute toxicity. PMID:19845371

Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

PubMed

Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

2009-12-01

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

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.

Development of an in Silico Model of DPPH• Free Radical Scavenging Capacity: Prediction of Antioxidant Activity of Coumarin Type Compounds.

PubMed

Goya Jorge, Elizabeth; Rayar, Anita Maria; Barigye, Stephen J; Jorge Rodríguez, María Elisa; Sylla-Iyarreta Veitía, Maité

2016-06-07

A quantitative structure-activity relationship (QSAR) study of the 2,2-diphenyl-l-picrylhydrazyl (DPPH•) radical scavenging ability of 1373 chemical compounds, using DRAGON molecular descriptors (MD) and the neural network technique, a technique based on the multilayer multilayer perceptron (MLP), was developed. The built model demonstrated a satisfactory performance for the training ( R 2 = 0.713 ) and test set ( Q ext 2 = 0.654 ) , respectively. To gain greater insight on the relevance of the MD contained in the MLP model, sensitivity and principal component analyses were performed. Moreover, structural and mechanistic interpretation was carried out to comprehend the relationship of the variables in the model with the modeled property. The constructed MLP model was employed to predict the radical scavenging ability for a group of coumarin-type compounds. Finally, in order to validate the model's predictions, an in vitro assay for one of the compounds (4-hydroxycoumarin) was performed, showing a satisfactory proximity between the experimental and predicted pIC50 values.

Ultrasound-assisted synthesis, anticonvulsant activity, and docking study of indole-appended thiazolidin-4-ones.

PubMed

Nikalje, Anna Pratima G; Shaikh, Sameer I; Mulay, Abhineet; Khan, Firoz A K; Sangshetti, Jaiprakash N; Shaikh, Shoaib

2014-10-01

Two series of novel indolyl thiazolidin-4-one derivatives 4a-j and 5a-j were obtained by an ecofriendly synthetic protocol by treating a mixture of Schiff's bases (0.01 mol) with thioglycolic acid or thiolactic acid (0.01 mol) and anhydrous zinc chloride in catalytic amount in DMF as solvent under ultrasound irradiation, using an ultrasound synthesizer with a synthetic solid probe. The structures of the synthesized compounds were confirmed by IR, (1) H NMR, (13) C NMR, MS, and elemental analysis. The anticonvulsant activity and neurotoxicity of the newly synthesized compounds were established by MES and sc-PTZ model and by rotarod test, respectively, in vivo using mouse models. The actophotometer was used for the screening of behavioral activity. The compounds exhibited promising anticonvulsant activity; especially, the compounds showed maximum protection in the MES model at a dose of 100 mg/kg. Further, docking studies of the synthesized compounds were performed against the sodium channel receptor and showed good binding interactions with the receptor. A computational study was carried out to highlight the pharmacophore distance mapping, log p determination, and pharmacokinetic parameters. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

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

2009-01-01

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

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

PubMed

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

2009-01-01

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

Molecular Modeling and Experimental Investigations of Nonlinear Optical Compounds Monosubstituted Derivatives of Dicyanovinylbenzene

NASA Technical Reports Server (NTRS)

Timofeeva, Tatiana V.; Nesterov, Vladimir N.; Antipin, Mikhail Yu.; Clark, Ronald D.; Sanghadasa, Mohan; Cardelino, Beatriz H.; Moore, Craig E.; Frazier, Donald O.

1999-01-01

A search for potential nonlinear optical compounds was performed using the Cambridge Structure Database and molecular modeling. We investigated a series of monosubstituted derivatives of dicyanovinylbenzene, since the nonlinear optical (NLO) properties of such derivatives (o-methoxy-dicyanovinylbenzene, DIVA) were studied earlier. The molecular geometry of these compounds was investigated with x-ray analysis and discussed along with the results of molecular mechanics and ab initio quantum chemical calculations. The influence of crystal packing on the planarity of the molecules of this series has been revealed. Two new compounds from the series studied, ortho-F and para-Cl-dicyanovinylbenzene, according to powder measurements, were found to be NLO compounds in the crystal state about 10 times more active than urea. The peculiarities of crystal structure formation in the framework of balance between van der Waals and electrostatic interactions have been discussed. The crystal shape of DIVA and two new NLO compounds have been calculated on the basis of the known crystal structure.

Molecular modeling and snake venom phospholipase A2 inhibition by phenolic compounds: Structure-activity relationship.

PubMed

Alam, Md Iqbal; Alam, Mohammed A; Alam, Ozair; Nargotra, Amit; Taneja, Subhash Chandra; Koul, Surrinder

2016-05-23

In our earlier study, we have reported that a phenolic compound 2-hydroxy-4-methoxybenzaldehyde from Janakia arayalpatra root extract was active against Viper and Cobra envenomations. Based on the structure of this natural product, libraries of synthetic structurally variant phenolic compounds were studied through molecular docking on the venom protein. To validate the activity of eight selected compounds, we have tested them in in vivo and in vitro models. The compound 21 (2-hydroxy-3-methoxy benzaldehyde), 22 (2-hydroxy-4-methoxybenzaldehyde) and 35 (2-hydroxy-3-methoxybenzylalcohol) were found to be active against venom-induced pathophysiological changes. The compounds 20, 15 and 35 displayed maximum anti-hemorrhagic, anti-lethal and PLA2 inhibitory activity respectively. In terms of SAR, the presence of a formyl group in conjunction with a phenolic group was seen as a significant contributor towards increasing the antivenom activity. The above observations confirmed the anti-venom activity of the phenolic compounds which needs to be further investigated for the development of new anti-snake venom leads. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

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.

Accounting for undetected compounds in statistical analyses of mass spectrometry 'omic studies.

PubMed

Taylor, Sandra L; Leiserowitz, Gary S; Kim, Kyoungmi

2013-12-01

Mass spectrometry is an important high-throughput technique for profiling small molecular compounds in biological samples and is widely used to identify potential diagnostic and prognostic compounds associated with disease. Commonly, this data generated by mass spectrometry has many missing values resulting when a compound is absent from a sample or is present but at a concentration below the detection limit. Several strategies are available for statistically analyzing data with missing values. The accelerated failure time (AFT) model assumes all missing values result from censoring below a detection limit. Under a mixture model, missing values can result from a combination of censoring and the absence of a compound. We compare power and estimation of a mixture model to an AFT model. Based on simulated data, we found the AFT model to have greater power to detect differences in means and point mass proportions between groups. However, the AFT model yielded biased estimates with the bias increasing as the proportion of observations in the point mass increased while estimates were unbiased with the mixture model except if all missing observations came from censoring. These findings suggest using the AFT model for hypothesis testing and mixture model for estimation. We demonstrated this approach through application to glycomics data of serum samples from women with ovarian cancer and matched controls.

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.

Synthesis, biological activity and molecular modeling of 4-fluoro-N-[ω-(1,2,3,4-tetrahydroacridin-9-ylamino)-alkyl]-benzamide derivatives as cholinesterase inhibitors.

PubMed

Szymański, P; Markowicz, M; Bajda, M; Malawska, B; Mikiciuk-Olasik, E

2012-12-01

The aim of this study was to synthesize and determine the biological activity of new derivatives of 4-fluorobenzoic acid and tetrahydroacridine towards inhibition of cholinesterases. Compounds were synthesized in condensation reaction between 9-aminoalkyl-tetrahydroacridines and the activated 4-fluorobenzoic acid. Properties towards inhibition of acetyl- and butyrylcholinesterase were estimated according to Ellman's spectrophotometric method. Among synthesized compounds the most active were compounds 4a and 4d. These compounds, in comparison with tacrine, were characterized by the similar values of IC50. Among all obtained compounds, 4d presented the highest selectivity towards inhibition of acetylcholinesterase. Molecular modeling studies revealed that all derivatives presented similar extended conformation in the gorge of acetylcholinesterase, however, there were 2 main conformations in the active center of butyrylcholinesterase: bent and extended conformation. © Georg Thieme Verlag KG Stuttgart · New York.

Development and validation of in silico models for estimating drug preformulation risk in PEG400/water and Tween80/water systems.

PubMed

Crivori, Patrizia; Morelli, Amedea; Pezzetta, Daniele; Rocchetti, Maurizio; Poggesi, Italo

2007-11-01

Solubility is one of the most important properties of drug candidates for achieving the targeted plasma concentrations following oral dosing. Furthermore, the formulations adopted in the in vivo preclinical studies, for both oral and intravenous administrations, are usually solutions. To formulate compounds sparingly soluble in water, pharmaceutically acceptable cosolvents or surfactants are typically employed to increase solubility. Compounds poorly soluble also in these systems will likely show severe formulation issues. In such cases, relatively high amount of compounds, rarely available in the early preclinical phases, are needed to identify the most appropriate dosing vehicles. Hence, the purpose of this study was to build two computational models which, on the basis of the molecular structure, are able to predict the compound solubility in two vehicle systems (40% PEG400/water and 10% Tween80/water) used in our company as screening tools for anticipating potential formulation issues. The two models were developed using the solubility data obtained from the analysis of approximately 2000 chemically diverse compounds. The structural diversity and the drug-like space covered by these molecules were investigated using the ChemGPS methodology. The compounds were classified (high/low preformulation risk) based on the experimental solubility value range. A combination of descriptors (i.e. logD at two different pH, E-state indices and other 2D structural descriptors) was correlated to these classes using partial least squares discriminant (PLSD) analysis. The overall accuracy of each PLSD model applied to independent sets of compounds was approximately 78%. The accuracy reached when the models were used in combination to identify molecules with low preformulation risk in both systems was 83%. The models appeared a valuable tool for predicting the preformulation risk of drug candidates and consequently for identifying the most appropriate dosing vehicles to be further investigated before the first in vivo preclinical studies. Since only a small number of 2D descriptors is need to evaluate the preformulation risk classes, the models resulted easy to use and characterized by high throughput.

Sulfur hexafluoride plasma surface modification of Gly-Ala and Ala-Gly as Bombyx mori silk model compounds: Mechanism investigations

NASA Astrophysics Data System (ADS)

Sangprasert, W.; Lee, V. S.; Boonyawan, D.; Tashiro, K.; Nimmanpipug, P.

2010-01-01

Low-pressure plasma has been used to improve the hydrophobicity of Thai silk. In this study, Glycine-Alanine (GA) and Alanine-Glycine (AG) were chosen to represent model compounds of Bombyx mori silk. Single crystals of the simplified model compounds were characterized by polarizing microscopy and X-ray diffraction. The space groups of P2 12 12 1 and P2 1 were found for AG and GA, respectively. The initial structures for calculation were obtained from the experimental crystal structures. Density functional theory at the BHandHLYP levels was used to investigate possible mechanisms of fluorine radicals reacting with AG and GA in the SF 6 plasma treatment. The results indicate that hydrogen atoms of silk model compounds were most likely to be abstracted from the alanine residue.

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors

PubMed Central

Ravikumar, Balaguru; Parri, Elina; Timonen, Sanna; Airola, Antti; Wennerberg, Krister

2017-01-01

Due to relatively high costs and labor required for experimental profiling of the full target space of chemical compounds, various machine learning models have been proposed as cost-effective means to advance this process in terms of predicting the most potent compound-target interactions for subsequent verification. However, most of the model predictions lack direct experimental validation in the laboratory, making their practical benefits for drug discovery or repurposing applications largely unknown. Here, we therefore introduce and carefully test a systematic computational-experimental framework for the prediction and pre-clinical verification of drug-target interactions using a well-established kernel-based regression algorithm as the prediction model. To evaluate its performance, we first predicted unmeasured binding affinities in a large-scale kinase inhibitor profiling study, and then experimentally tested 100 compound-kinase pairs. The relatively high correlation of 0.77 (p < 0.0001) between the predicted and measured bioactivities supports the potential of the model for filling the experimental gaps in existing compound-target interaction maps. Further, we subjected the model to a more challenging task of predicting target interactions for such a new candidate drug compound that lacks prior binding profile information. As a specific case study, we used tivozanib, an investigational VEGF receptor inhibitor with currently unknown off-target profile. Among 7 kinases with high predicted affinity, we experimentally validated 4 new off-targets of tivozanib, namely the Src-family kinases FRK and FYN A, the non-receptor tyrosine kinase ABL1, and the serine/threonine kinase SLK. Our sub-sequent experimental validation protocol effectively avoids any possible information leakage between the training and validation data, and therefore enables rigorous model validation for practical applications. These results demonstrate that the kernel-based modeling approach offers practical benefits for probing novel insights into the mode of action of investigational compounds, and for the identification of new target selectivities for drug repurposing applications. PMID:28787438

A Connectionist Model of Stimulus Class Formation with a Yes/No Procedure and Compound Stimuli

ERIC Educational Resources Information Center

Tovar, Angel E.; Chavez, Alvaro Torres

2012-01-01

We analyzed stimulus class formation in a human study and in a connectionist model (CM) with a yes/no procedure, using compound stimuli. In the human study, the participants were six female undergraduate students; the CM was a feed-forward back-propagation network. Two 3-member stimulus classes were trained with a similar procedure in both the…

Predicting chemical bioavailability using microarray gene expression data and regression modeling: A tale of three explosive compounds.

PubMed

Gong, Ping; Nan, Xiaofei; Barker, Natalie D; Boyd, Robert E; Chen, Yixin; Wilkins, Dawn E; Johnson, David R; Suedel, Burton C; Perkins, Edward J

2016-03-08

Chemical bioavailability is an important dose metric in environmental risk assessment. Although many approaches have been used to evaluate bioavailability, not a single approach is free from limitations. Previously, we developed a new genomics-based approach that integrated microarray technology and regression modeling for predicting bioavailability (tissue residue) of explosives compounds in exposed earthworms. In the present study, we further compared 18 different regression models and performed variable selection simultaneously with parameter estimation. This refined approach was applied to both previously collected and newly acquired earthworm microarray gene expression datasets for three explosive compounds. Our results demonstrate that a prediction accuracy of R(2) = 0.71-0.82 was achievable at a relatively low model complexity with as few as 3-10 predictor genes per model. These results are much more encouraging than our previous ones. This study has demonstrated that our approach is promising for bioavailability measurement, which warrants further studies of mixed contamination scenarios in field settings.

Viscoelastic Emulsion Improved the Bioaccessibility and Oral Bioavailability of Crystalline Compound: A Mechanistic Study Using in Vitro and in Vivo Models.

PubMed

Ting, Yuwen; Jiang, Yike; Lan, Yaqi; Xia, Chunxin; Lin, Zhenyu; Rogers, Michael A; Huang, Qingrong

2015-07-06

The oral bioavailability of hydrophobic compound is usually limited by the poor aqueous solubility in the gastrointestinal (GI) tract. Various oral formulations were developed to enhance the systemic concentration of such molecules. Moreover, compounds with high melting temperature that appear as insoluble crystals imposed a great challenge to the development of oral vehicle. Polymethoxyflavone, an emerging category of bioactive compounds with potent therapeutic efficacies, were characterized as having a hydrophobic and highly crystalline chemical structure. To enhance the oral dosing efficiency of polymethoxyflavone, a viscoelastic emulsion system with a high static viscosity was developed and optimized using tangeretin, one of the most abundant polymethoxyflavones found in natural sources, as a modeling compound. In the present study, different in vitro and in vivo models were used to mechanistically evaluate the effect of emulsification on oral bioavailability of tangeretin. In vitro lipolysis revealed that emulsified tangeretin was digested and became bioaccessible much faster than unprocessed tangeretin oil suspension. By simulating the entire human GI tract, TNO's gastrointestinal model (TIM-1) is a valuable tool to mechanistically study the effect of emulsification on the digestion events that lead to a better oral bioavailability of tangeretin. TIM-1 result indicated that tangeretin was absorbed in the upper GI tract. Thus, a higher oral bioavailability can be expected if the compound becomes bioaccessible in the intestinal lumen soon after dosing. In vivo pharmacokinetics analysis on mice again confirmed that the oral bioavailability of tangeretin increased 2.3 fold when incorporated in the viscoelastic emulsion than unformulated oil suspension. By using the combination of in vitro and in vivo models introduced in this work, the mechanism that underlie the effect of viscoelastic emulsion on the oral bioavailability of tangeretin was well-elucidated.

Animal models for testing anti-prion drugs.

PubMed

Fernández-Borges, Natalia; Elezgarai, Saioa R; Eraña, Hasier; Castilla, Joaquín

2013-01-01

Prion diseases belong to a group of fatal infectious diseases with no effective therapies available. Throughout the last 35 years, less than 50 different drugs have been tested in different experimental animal models without hopeful results. An important limitation when searching for new drugs is the existence of appropriate models of the disease. The three different possible origins of prion diseases require the existence of different animal models for testing anti-prion compounds. Wild type, over-expressing transgenic mice and other more sophisticated animal models have been used to evaluate a diversity of compounds which some of them were previously tested in different in vitro experimental models. The complexity of prion diseases will require more pre-screening studies, reliable sporadic (or spontaneous) animal models and accurate chemical modifications of the selected compounds before having an effective therapy against human prion diseases. This review is intended to put on display the more relevant animal models that have been used in the search of new antiprion therapies and describe some possible procedures when handling chemical compounds presumed to have anti-prion activity prior to testing them in animal models.

Emissions of organic compounds from produced water ponds II: Evaluation of flux chamber measurements with inverse-modeling techniques.

PubMed

Tran, Huy N Q; Lyman, Seth N; Mansfield, Marc L; O'Neil, Trevor; Bowers, Richard L; Smith, Ann P; Keslar, Cara

2018-07-01

In this study, the authors apply two different dispersion models to evaluate flux chamber measurements of emissions of 58 organic compounds, including C2-C11 hydrocarbons and methanol, ethanol, and isopropanol from oil- and gas-produced water ponds in the Uintah Basin. Field measurement campaigns using the flux chamber technique were performed at a limited number of produced water ponds in the basin throughout 2013-2016. Inverse-modeling results showed significantly higher emissions than were measured by the flux chamber. Discrepancies between the two methods vary across hydrocarbon compounds and are largest in alcohols due to their physical chemistries. This finding, in combination with findings in a related study using the WATER9 wastewater emission model, suggests that the flux chamber technique may underestimate organic compound emissions, especially alcohols, due to its limited coverage of the pond area and alteration of environmental conditions, especially wind speed. Comparisons of inverse-model estimations with flux chamber measurements varied significantly with the complexity of pond facilities and geometries. Both model results and flux chamber measurements suggest significant contributions from produced water ponds to total organic compound emission from oil and gas productions in the basin. This research is a component of an extensive study that showed significant amount of hydrocarbon emissions from produced water ponds in the Uintah Basin, Utah. Such findings have important meanings to air quality management agencies in developing control strategies for air pollution in oil and gas fields, especially for the Uintah Basin in which ozone pollutions frequently occurred in winter seasons.

Novel L-Dopa and dopamine prodrugs containing a 2-phenyl-imidazopyridine moiety.

PubMed

Denora, Nunzio; Laquintana, Valentino; Lopedota, Angela; Serra, Mariangela; Dazzi, Laura; Biggio, Giovanni; Pal, Dhananjay; Mitra, Ashim K; Latrofa, Andrea; Trapani, Giuseppe; Liso, Gaetano

2007-07-01

The aim of this study was to gain insight into the feasibility of enhancing the delivery of L-Dopa and dopamine to the brain by linking these neurotransmitters and L-Dopa ethyl ester to 2-phenyl-3-carboxymethyl-imidazopyridine compounds giving rise to the so-called Dopimid compounds. A number of Dopimid compounds were synthesized and both stability and binding studies to dopaminergic and benzodiazepine receptors were performed. To evaluate whether Dopimid compounds are P-gp substrates, [(3)H]ritonavir uptake experiments and bi-directional transport studies on confluent MDCKII-MDR1 monolayers were carried out. The brain penetration properties of Dopimid compounds were estimated by the Clark's computational model and evaluated by investigation of their transport across BBMECs monolayers. The dopamine levels following the intraperitoneal administration of the selected Dopimid compounds were measured in vivo by using brain microdialysis in rat. Tested compounds were adequately stable in solution buffered at pH 7.4 but undergo faster cleavage in dilute rat serum at 37 degrees C. Receptor binding studies showed that Dopimid compounds are essentially devoid of affinity for dopaminergic and benzodiazepine receptors. [(3)H]ritonavir uptake experiments indicated that selected Dopimid compounds, like L-Dopa and dopamine hydrochloride, are not substrates of P-gp and it was also confirmed by bi-directional transport experiments across MDCKII-MDR1 monolayers. By Clark's model a significant brain penetration was deduced for L-Dopa ethyl ester and dopamine derivatives. Transport studies involving BBMECs monolayers indicated that some of these compounds should be able to cross the BBB. Interestingly, the rank order of apparent permeability (P (app)) values observed in these assays parallels that calculated by the computational approach. Brain microdialysis experiments in rat showed that intraperitoneal acute administration of some Dopimid compounds induced a dose-dependent increase in cortical dopamine output. Based on these results, it may be concluded that some Dopimid compounds can be proposed as novel L-Dopa and dopamine prodrugs.

Parallel screening of drug-like natural compounds using Caco-2 cell permeability QSAR model with applicability domain, lipophilic ligand efficiency index and shape property: A case study of HIV-1 reverse transcriptase inhibitors

NASA Astrophysics Data System (ADS)

Patel, Rikin D.; Kumar, Sivakumar Prasanth; Patel, Chirag N.; Shankar, Shetty Shilpa; Pandya, Himanshu A.; Solanki, Hitesh A.

2017-10-01

The traditional drug design strategy centrally focuses on optimizing binding affinity with the receptor target and evaluates pharmacokinetic properties at a later stage which causes high rate of attrition in clinical trials. Alternatively, parallel screening allows evaluation of these properties and affinity simultaneously. In a case study to identify leads from natural compounds with experimental HIV-1 reverse transcriptase (RT) inhibition, we integrated various computational approaches including Caco-2 cell permeability QSAR model with applicability domain (AD) to recognize drug-like natural compounds, molecular docking to study HIV-1 RT interactions and shape similarity analysis with known crystal inhibitors having characteristic butterfly-like model. Further, the lipophilic properties of the compounds refined from the process with best scores were examined using lipophilic ligand efficiency (LLE) index. Seven natural compound hits viz. baicalien, (+)-calanolide A, mniopetal F, fagaronine chloride, 3,5,8-trihydroxy-4-quinolone methyl ether derivative, nitidine chloride and palmatine, were prioritized based on LLE score which demonstrated Caco-2 well absorption labeling, encompassment in AD structural coverage, better receptor affinity, shape adaptation and permissible AlogP value. We showed that this integrative approach is successful in lead exploration of natural compounds targeted against HIV-1 RT enzyme.

Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore-based virtual screening, molecular docking and molecular dynamics studies.

PubMed

Islam, Md Ataul; Pillay, Tahir S

2017-08-01

In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB. © 2017 John Wiley & Sons A/S.

Molecular Modeling and Experimental Study of Nonlinear Optical Compounds: Mono-Substituted Derivatives of Dicyanovinylbenzene

NASA Technical Reports Server (NTRS)

Timofeeva, Tatyana V.; Nesterov, Vladimir N.; Antipin, Mikhael Y.; Clark, R. D.; Sanghadasa, M.; Cardelino, B. H.; Moore, C. E.; Frazier, Donald O.

2000-01-01

A search for potential nonlinear optical (NLO) compounds has been performed using the Cambridge Structural Database and molecular modeling. We have studied a series of mono-substituted derivatives of dicyanovinylbenzene as the NLO properties of one of its derivatives (o-methoxy-dicyanovinylbenzene, DIVA) were described earlier. The molecular geometry in the series of the compounds studied was investigated with an X- ray analysis and discussed along with results of molecular mechanics and ab initio quantum chemical calculations. The influence of crystal packing on the molecular planarity has been revealed. Two new compounds from the series studied were found to be active for second harmonic generation (SHG) in the powder. The measurements of SHG efficiency have shown that the o-F- and p-Cl-derivatives of dicyanovinylbenzene are about 10 and 20- times more active than urea, respectively. The peculiarities of crystal structure formation in the framework of balance between the van der Waals and electrostatic interactions have been discussed. The crystal morphology of DIVA and two new SHG-active compounds have been calculated on the basis of their known crystal structures.

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.

Measurement of Setschenow constants for six hydrophobic compounds in simulated brines and use in predictive modeling for oil and gas systems.

PubMed

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

2016-02-01

Treatment and reuse of brines, produced from energy extraction activities, requires aqueous solubility data for organic compounds in saline solutions. The presence of salts decreases the aqueous solubility of organic compounds (i.e. salting-out effect) and can be modeled using the Setschenow Equation, the validity of which has not been assessed in high salt concentrations. In this study, we used solid-phase microextraction to determine Setschenow constants for selected organic compounds in aqueous solutions up to 2-5 M NaCl, 1.5-2 M CaCl2, and in Na-Ca binary electrolyte solutions to assess additivity of the constants. These compounds exhibited log-linear behavior up to these high NaCl concentrations. Log-linear decreases in solubility with increasing salt concentration were observed up to 1.5-2 M CaCl2 for all compounds, and added to a sparse database of CaCl2 Setschenow constants. Setschenow constants were additive in binary electrolyte mixtures. New models to predict CaCl2 and KCl Setschenow constants from NaCl Setschenow constants were developed, which successfully predicted the solubility of the compounds measured in this study. Overall, data show that the Setschenow Equation is valid for a wide range of salinity conditions typically found in energy-related technologies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Antidepressant-like and anxiolytic-like effects of cannabidiol: a chemical compound of Cannabis sativa.

PubMed

de Mello Schier, Alexandre R; de Oliveira Ribeiro, Natalia P; Coutinho, Danielle S; Machado, Sergio; Arias-Carrión, Oscar; Crippa, Jose A; Zuardi, Antonio W; Nardi, Antonio E; Silva, Adriana C

2014-01-01

Anxiety and depression are pathologies that affect human beings in many aspects of life, including social life, productivity and health. Cannabidiol (CBD) is a constituent non-psychotomimetic of Cannabis sativa with great psychiatric potential, including uses as an antidepressant-like and anxiolytic-like compound. The aim of this study is to review studies of animal models using CBD as an anxiolytic-like and antidepressant-like compound. Studies involving animal models, performing a variety of experiments on the above-mentioned disorders, such as the forced swimming test (FST), elevated plus maze (EPM) and Vogel conflict test (VCT), suggest that CBD exhibited an anti-anxiety and antidepressant effects in animal models discussed. Experiments with CBD demonstrated non-activation of neuroreceptors CB1 and CB2. Most of the studies demonstrated a good interaction between CBD and the 5-HT1A neuro-receptor.

REACTIONS OF FUEL NITROGEN COMPOUNDS UNDER CONDITIONS OF INERT PYROLYSIS

EPA Science Inventory

The paper describes the pyrolysis of fossil fuels and model nitrogen compounds in helium in a small quartz plow reactor, as part of a study of the chemical mechanisms involved in the conversion of fuel-nitrogen compounds to nitric oxide (NO) during combustion. Hydrogen cyanide (H...

DFT studies of the vibrational spectra of salicylic acid and related compounds

USDA-ARS?s Scientific Manuscript database

Compounds that exhibit intra- and intermolecular hydrogen bonds can have infrared and Raman spectra that show evidences of these hydrogen bonds. In modeling the vibrational spectra of such compounds, the addition of explicit hydrogen bonding species (e.g. solvent molecules) can often improve agreeme...

Bond-based bilinear indices for computational discovery of novel trypanosomicidal drug-like compounds through virtual screening.

PubMed

Castillo-Garit, Juan Alberto; del Toro-Cortés, Oremia; Vega, Maria C; Rolón, Miriam; Rojas de Arias, Antonieta; Casañola-Martin, Gerardo M; Escario, José A; Gómez-Barrio, Alicia; Marrero-Ponce, Yovani; Torrens, Francisco; Abad, Concepción

2015-01-01

Two-dimensional bond-based bilinear indices and linear discriminant analysis are used in this report to perform a quantitative structure-activity relationship study to identify new trypanosomicidal compounds. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop the theoretical models. Two discriminant models, computed using bond-based bilinear indices, are developed and both show accuracies higher than 86% for training and test sets. The stochastic model correctly indentifies nine out of eleven compounds of a set of organic chemicals obtained from our synthetic collaborators. The in vitro antitrypanosomal activity of this set against epimastigote forms of Trypanosoma cruzi is assayed. Both models show a good agreement between theoretical predictions and experimental results. Three compounds showed IC50 values for epimastigote elimination (AE) lower than 50 μM, while for the benznidazole the IC50 = 54.7 μM which was used as reference compound. The value of IC50 for cytotoxicity of these compounds is at least 5 times greater than their value of IC50 for AE. Finally, we can say that, the present algorithm constitutes a step forward in the search for efficient ways of discovering new antitrypanosomal compounds. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Mechanistic Physiologically Based Pharmacokinetic Modeling of the Dissolution and Food Effect of a Biopharmaceutics Classification System IV Compound-The Venetoclax Story.

PubMed

Emami Riedmaier, Arian; Lindley, David J; Hall, Jeffrey A; Castleberry, Steven; Slade, Russell T; Stuart, Patricia; Carr, Robert A; Borchardt, Thomas B; Bow, Daniel A J; Nijsen, Marjoleen

2018-01-01

Venetoclax, a selective B-cell lymphoma-2 inhibitor, is a biopharmaceutics classification system class IV compound. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to mechanistically describe absorption and disposition of an amorphous solid dispersion formulation of venetoclax in humans. A mechanistic PBPK model was developed incorporating measured amorphous solubility, dissolution, metabolism, and plasma protein binding. A middle-out approach was used to define permeability. Model predictions of oral venetoclax pharmacokinetics were verified against clinical studies of fed and fasted healthy volunteers, and clinical drug interaction studies with strong CYP3A inhibitor (ketoconazole) and inducer (rifampicin). Model verification demonstrated accurate prediction of the observed food effect following a low-fat diet. Ratios of predicted versus observed C max and area under the curve of venetoclax were within 0.8- to 1.25-fold of observed ratios for strong CYP3A inhibitor and inducer interactions, indicating that the venetoclax elimination pathway was correctly specified. The verified venetoclax PBPK model is one of the first examples mechanistically capturing absorption, food effect, and exposure of an amorphous solid dispersion formulated compound. This model allows evaluation of untested drug-drug interactions, especially those primarily occurring in the intestine, and paves the way for future modeling of biopharmaceutics classification system IV compounds. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

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.

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.

In silico-based combinatorial pharmacophore modelling and docking studies of GSK-3β and GK inhibitors of Hippophae.

PubMed

Middha, Sushil Kumar; Goyal, Arvind Kumar; Faizan, Syed Ahmed; Sanghamitra, Nethramurthy; Basistha, Bharat Chandra; Usha, Talambedu

2013-11-01

Type 2 diabetes is an inevitably progressive disease, with irreversible beta cell failure. Glycogen synthase kinase and Glukokinase, two important enzymes with diverse biological actions in carbohydrate metabolism, are promising targets for developing novel antidiabetic drugs. A combinatorial structure-based molecular docking and pharmacophore modelling study was performed with the compounds of Hippophae salicifolia and H. rhamnoides as inhibitors. Docking with Discovery Studio 3.5 revealed that two compounds from H. salicifolia, viz Lutein D and an analogue of Zeaxanthin, and two compounds from H. rhamnoides, viz Isorhamnetin-3-rhamnoside and Isorhamnetin-7-glucoside, bind significantly to the GSK-3 beta receptor and play a role in its inhibition; whereas in the case of Glucokinase, only one compound from both the plants, i.e. vitamin C, had good binding characteristics capable of activation. The results help to understand the type of interactions that occur between the ligands and the receptors. Toxicity predictions revealed that none of the compounds had hepatotoxic effects and had good absorption as well as solubility characteristics. The compounds did not possess plasma protein-binding, crossing blood-brain barrier ability. Further, in vivo and in vitro studies need to be performed to prove that these compounds can be used effectively as antidiabetic drugs.

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

PubMed Central

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

2015-01-01

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

A MIXTURE OF SEVEN ANTIANDROGENIC COMPOUNDS ELICITS ADDITIVE EFFECTS ON THE MALE RAT REPRODUCTIVE TRACT THAT CORRESPOND TO MODELED PREDICTIONS

EPA Science Inventory

The main objectives of this study were to: (1) determine whether dissimilar antiandrogenic compounds display additive effects when present in combination and (2) to assess the ability of modelling approaches to accurately predict these mixture effects based on data from single ch...

CRITICAL EVALUATION OF THE DIFFUSION HYPOTHESIS IN THE THEORY OF POROUS MEDIA VOLATILE ORGANIC COMPOUND (VOC) SOURCES AND SINKS

EPA Science Inventory

The paper proposes three alternative, diffusion-limited mathematical models to account for volatile organic compound (VOC) interactions with indoor sinks, using the linear isotherm model as a reference point. (NOTE: Recent reports by both the U.S. EPA and a study committee of the...

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

PubMed

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

2011-08-11

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

2, 5-Disubstituted phthalimides: design, synthesis and anticonvulsant activity in scPTZ and MES models.

PubMed

Saadabadi, Atefeh; Kohen, Babak; Irandoust, Maryam; Shafaroudi, Hamed; Mohammadpour, Tara; Rezayat, Mahdi; Davood, Asghar

2018-05-15

In this study, fifteenth new 2,5-disubstituted analgouges of phthalimide were designed and synthesized using the appropriate synthetic route to evaluate anticonvulsant activity against the maximal electroshock (MES) and subcutaneous pentylenetetrazole (scPTZ) compare to phenytoin as a positive control. The structures of the synthesized compounds were confirmed by FT-IR, H-NMR, C-NMR and MASS spectroscopy. All the tested compounds were found to be effective in the PTZ model at the dose of 60 mg/kg and most of the compounds showed protection against MES test indicative of their ability to inhibit the seizure spread at the all dose ranges. Compound 3 has illustrated the best efficacy among all compounds and showed more potency than phenytoin in clonic seizure and was potent as phenytoin in tonic seizure. Using a model of the Na channel, these derivatives were docked in the active site. Docking studies displayed that all synthesized compounds have more negative binding energy compare to reference drug and inhibition-constant less than phenytoin that means they can block the receptor more efficiently and usually form hydrophobic interactions or hydrogen binding interaction frequently with the domains I, II, III and rarely with domain IV. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A method to predict different mechanisms for blood-brain barrier permeability of CNS activity compounds in Chinese herbs using support vector machine.

PubMed

Jiang, Ludi; Chen, Jiahua; He, Yusu; Zhang, Yanling; Li, Gongyu

2016-02-01

The blood-brain barrier (BBB), a highly selective barrier between central nervous system (CNS) and the blood stream, restricts and regulates the penetration of compounds from the blood into the brain. Drugs that affect the CNS interact with the BBB prior to their target site, so the prediction research on BBB permeability is a fundamental and significant research direction in neuropharmacology. In this study, we combed through the available data and then with the help of support vector machine (SVM), we established an experiment process for discovering potential CNS compounds and investigating the mechanisms of BBB permeability of them to advance the research in this field four types of prediction models, referring to CNS activity, BBB permeability, passive diffusion and efflux transport, were obtained in the experiment process. The first two models were used to discover compounds which may have CNS activity and also cross the BBB at the same time; the latter two were used to elucidate the mechanism of BBB permeability of those compounds. Three optimization parameter methods, Grid Search, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), were used to optimize the SVM models. Then, four optimal models were selected with excellent evaluation indexes (the accuracy, sensitivity and specificity of each model were all above 85%). Furthermore, discrimination models were utilized to study the BBB properties of the known CNS activity compounds in Chinese herbs and this may guide the CNS drug development. With the relatively systematic and quick approach, the application rationality of traditional Chinese medicines for treating nervous system disease in the clinical practice will be improved.

De Novo Design of Bioactive Small Molecules by Artificial Intelligence

PubMed Central

Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca

2018-01-01

Abstract Generative artificial intelligence offers a fresh view on molecular design. We present the first‐time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine‐tuned on recognizing retinoid X and peroxisome proliferator‐activated receptor agonists. We synthesized five top‐ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low‐micromolar receptor modulatory activity in cell‐based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. PMID:29319225

The proposal of architecture for chemical splitting to optimize QSAR models for aquatic toxicity.

PubMed

Colombo, Andrea; Benfenati, Emilio; Karelson, Mati; Maran, Uko

2008-06-01

One of the challenges in the field of quantitative structure-activity relationship (QSAR) analysis is the correct classification of a chemical compound to an appropriate model for the prediction of activity. Thus, in previous studies, compounds have been divided into distinct groups according to their mode of action or chemical class. In the current study, theoretical molecular descriptors were used to divide 568 organic substances into subsets with toxicity measured for the 96-h lethal median concentration for the Fathead minnow (Pimephales promelas). Simple constitutional descriptors such as the number of aliphatic and aromatic rings and a quantum chemical descriptor, maximum bond order of a carbon atom divide compounds into nine subsets. For each subset of compounds the automatic forward selection of descriptors was applied to construct QSAR models. Significant correlations were achieved for each subset of chemicals and all models were validated with the leave-one-out internal validation procedure (R(2)(cv) approximately 0.80). The results encourage to consider this alternative way for the prediction of toxicity using QSAR subset models without direct reference to the mechanism of toxic action or the traditional chemical classification.

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

PubMed

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

2010-02-26

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

Predictive ecotoxicity of MoA 1 of organic chemicals using in silico approaches.

PubMed

de Morais E Silva, Luana; Alves, Mateus Feitosa; Scotti, Luciana; Lopes, Wilton Silva; Scotti, Marcus Tullius

2018-05-30

Persistent organic products are compounds used for various purposes, such as personal care products, surfactants, colorants, industrial additives, food, pesticides and pharmaceuticals. These substances are constantly introduced into the environment and many of these pollutants are difficult to degrade. Toxic compounds classified as MoA 1 (Mode of Action 1) are low toxicity compounds that comprise nonreactive chemicals. In silico methods such as Quantitative Structure-Activity Relationships (QSARs) have been used to develop important models for prediction in several areas of science, as well as aquatic toxicity studies. The aim of the present study was to build a QSAR model-based set of theoretical Volsurf molecular descriptors using the fish acute toxicity values of compounds defined as MoA 1 to identify the molecular properties related to this mechanism. The selected Partial Least Squares (PLS) results based on the values of cross-validation coefficients of determination (Q cv 2 ) show the following values: Q cv 2 = 0.793, coefficient of determination (R 2 ) = 0.823, explained variance in external prediction (Q ext 2 ) = 0.87. From the selected descriptors, not only the hydrophobicity is related to the toxicity as already mentioned in previously published studies but other physicochemical properties combined contribute to the activity of these compounds. The symmetric distribution of the hydrophobic moieties in the structure of the compounds as well as the shape, as branched chains, are important features that are related to the toxicity. This information from the model can be useful in predicting so as to minimize the toxicity of organic compounds. Copyright © 2018. Published by Elsevier Inc.

Simulating the Effects of Semivolatile Compounds on Cloud Processing of Aerosol

NASA Astrophysics Data System (ADS)

Kokkola, H.; Kudzotsa, I.; Tonttila, J.; Raatikainen, T.; Romakkaniemi, S.

2017-12-01

Aerosol removal processes largely dictate how well aerosol is transported in the atmosphere and thus the aerosol load over remote regions depends on how effectively aerosol is removed during its transport from the source regions. This means that in order to model the global distribution aerosol, both in vertical and horizontal, wet deposition processes have to be properly modelled. However, in large scale models, the description of wet removal and the vertical redistribution of aerosol by cloud processes is often extremely simplified.Here we present a novel aerosol-cloud model SALSA, where the aerosol properties are tracked through different cloud processes. These processes include: cloud droplet activation, precipitation formation, ice nucleation, melting, and evaporation. It is a sectional model that includes separate size sections for non-activated aerosol, cloud droplets, precipitation droplets, and ice crystals. The aerosol-cloud model was coupled to a large eddy model UCLALES which simulates the boundary-layer dynamics. In this study, the model has been applied in studying the wet removal as well as interactions between aerosol, clouds, and semi-volatile compounds, ammonia and nitric acid. These semi-volative compounds are special in the sense that they co-condense together with water during cloud activation and have been suggested to form droplets that can be considered cloud-droplet-like already in subsaturated conditions. In our model, we calculate the kinetic partitioning of ammonia and sulfate thus explicitly taking into account the effect of ammonia and nitric acid in the cloud formation. Our simulations indicate that especially in polluted conditions, these compounds significantly affect the properties of cloud droplets thus significantly affecting the lifecycle of different aerosol compounds.

Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species.

PubMed

Fourches, Denis; Barnes, Julie C; Day, Nicola C; Bradley, Paul; Reed, Jane Z; Tropsha, Alexander

2010-01-01

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automated text mining with limited manual curation, opening up new opportunities for generating and modeling chemical toxicology data.

Calibration and validation of toxicokinetic-toxicodynamic models for three neonicotinoids and some aquatic macroinvertebrates.

PubMed

Focks, Andreas; Belgers, Dick; Boerwinkel, Marie-Claire; Buijse, Laura; Roessink, Ivo; Van den Brink, Paul J

2018-05-01

Exposure patterns in ecotoxicological experiments often do not match the exposure profiles for which a risk assessment needs to be performed. This limitation can be overcome by using toxicokinetic-toxicodynamic (TKTD) models for the prediction of effects under time-variable exposure. For the use of TKTD models in the environmental risk assessment of chemicals, it is required to calibrate and validate the model for specific compound-species combinations. In this study, the survival of macroinvertebrates after exposure to the neonicotinoid insecticide was modelled using TKTD models from the General Unified Threshold models of Survival (GUTS) framework. The models were calibrated on existing survival data from acute or chronic tests under static exposure regime. Validation experiments were performed for two sets of species-compound combinations: one set focussed on multiple species sensitivity to a single compound: imidacloprid, and the other set on the effects of multiple compounds for a single species, i.e., the three neonicotinoid compounds imidacloprid, thiacloprid and thiamethoxam, on the survival of the mayfly Cloeon dipterum. The calibrated models were used to predict survival over time, including uncertainty ranges, for the different time-variable exposure profiles used in the validation experiments. From the comparison between observed and predicted survival, it appeared that the accuracy of the model predictions was acceptable for four of five tested species in the multiple species data set. For compounds such as neonicotinoids, which are known to have the potential to show increased toxicity under prolonged exposure, the calibration and validation of TKTD models for survival needs to be performed ideally by considering calibration data from both acute and chronic tests.

Structural basis for the enhanced stability of protein model compounds and peptide backbone unit in ammonium ionic liquids.

PubMed

Vasantha, T; Attri, Pankaj; Venkatesu, Pannuru; Devi, R S Rama

2012-10-04

Protein folding/unfolding is a fascinating study in the presence of cosolvents, which protect/disrupt the native structure of protein, respectively. The structure and stability of proteins and their functional groups may be modulated by the addition of cosolvents. Ionic liquids (ILs) are finding a vast array of applications as novel cosolvents for a wide variety of biochemical processes that include protein folding. Here, the systematic and quantitative apparent transfer free energies (ΔG'(tr)) of protein model compounds from water to ILs through solubility measurements as a function of IL concentration at 25 °C have been exploited to quantify and interpret biomolecular interactions between model compounds of glycine peptides (GPs) with ammonium based ILs. The investigated aqueous systems consist of zwitterionic glycine peptides: glycine (Gly), diglycine (Gly(2)), triglycine (Gly(3)), tetraglycine (Gly(4)), and cyclic glycylglycine (c(GG)) in the presence of six ILs such as diethylammonium acetate (DEAA), diethylammonium hydrogen sulfate (DEAS), triethylammonium acetate (TEAA), triethylammonium hydrogen sulfate (TEAS), triethylammonium dihydrogen phosphate (TEAP), and trimethylammonium acetate (TMAA). We have observed positive values of ΔG'(tr) for GPs from water to ILs, indicating that interactions between ILs and GPs are unfavorable, which leads to stabilization of the structure of model protein compounds. Moreover, our experimental data ΔG'(tr) is used to obtain transfer free energies (Δg'(tr)) of the peptide backbone unit (or glycyl unit) (-CH(2)C═ONH-), which is the most numerous group in globular proteins, from water to IL solutions. To obtain the mechanism events of the ILs' role in enhancing the stability of the model compounds, we have further obtained m-values for GPs from solubility limits. These results explicitly elucidate that all alkyl ammonium ILs act as stabilizers for model compounds through the exclusion of ILs from model compounds of proteins and also reflect the effect of alkyl chain on the stability of protein model compounds.

Systems for the Storage of Molecular Oxygen - A Study.

DTIC Science & Technology

1980-11-25

form adducts with certain chemical compounds . This process, which will be called chemical absorption, generally uses a transition metal coordination... compound as the absorber. The study of oxygen binding to metal complexes has become of great interest over the past three decades (21), and some...for iron, most notably cobalt (33-35) manganese (36,37) and ruthenium (38), usually to serve as model compounds for biologically important heme

Mouse Models Applied to the Research of Pharmacological Treatments in Asthma.

PubMed

Marqués-García, Fernando; Marcos-Vadillo, Elena

2016-01-01

Models developed for the study of asthma mechanisms can be used to investigate new compounds with pharmacological activity against this disease. The increasing number of compounds requires a preclinical evaluation before starting the application in humans. Preclinical evaluation in animal models reduces the number of clinical trials positively impacting in the cost and in safety. In this chapter, three protocols for the study of drugs are shown: a model to investigate corticoids as a classical treatment of asthma; a protocol to test the effects of retinoic acid (RA) on asthma; and a mouse model to test new therapies in asthma as monoclonal antibodies.

The Involvement of Morphological Information in the Memorization of Chinese Compound Words: Evidence from Memory Errors.

PubMed

Liu, Duo

2016-02-01

The processing of morphological information during Chinese word memorization was investigated in the present study. Participants were asked to study words presented to them on a computer screen in the studying phase and then judge whether presented words were old or new in the test phase. In addition to parent words (i.e. the words studied in the study phase), the test phase also included conjunction lures (constructed out of morphemes in the parent words) and new words (constructed out of entirely new morphemes). Three kinds of words (i.e. subordinate compounds, coordinative compounds, and single-morpheme words) were involved. In both two experiments, performance on lures worsened when both parent words and lures were coordinative compounds, compared to the condition when both were subordinate compounds. The different performance between compounds with different compounding structures in the test phase suggests the involvement of morphological information in the memorization of Chinese compound words. The spreading activation theory for memory and the interactive activation model for the processing of morphologically complex words were referred to for interpreting the results.

Preclinical Torsades-de-Pointes screens: advantages and limitations of surrogate and direct approaches in evaluating proarrhythmic risk.

PubMed

Gintant, Gary A

2008-08-01

The successful development of novel drugs requires the ability to detect (and avoid) compounds that may provoke Torsades-de-Pointes (TdeP) arrhythmia while endorsing those compounds with minimal torsadogenic risk. As TdeP is a rare arrhythmia not readily observed during clinical or post-marketing studies, numerous preclinical models are employed to assess delayed or altered ventricular repolarization (surrogate markers linked to enhanced proarrhythmic risk). This review evaluates the advantages and limitations of selected preclinical models (ranging from the simplest cellular hERG current assay to the more complex in vitro perfused ventricular wedge and Langendorff heart preparations and in vivo chronic atrio-ventricular (AV)-node block model). Specific attention is paid to the utility of concentration-response relationships and "risk signatures" derived from these studies, with the intention of moving beyond predicting clinical QT prolongation and towards prediction of TdeP risk. While the more complex proarrhythmia models may be suited to addressing questionable or conflicting proarrhythmic signals obtained with simpler preclinical assays, further benchmarking of proarrhythmia models is required for their use in the robust evaluation of safety margins. In the future, these models may be able to reduce unwarranted attrition of evolving compounds while becoming pivotal in the balanced integrated risk assessment of advancing compounds.

Role of Electrostatic Interactions on the Transport of Druglike Molecules in Hydrogel-Based Articular Cartilage Mimics: Implications for Drug Delivery.

PubMed

Ye, Fengbin; Baldursdottir, Stefania; Hvidt, Søren; Jensen, Henrik; Larsen, Susan W; Yaghmur, Anan; Larsen, Claus; Østergaard, Jesper

2016-03-07

In the field of drug delivery to the articular cartilage, it is advantageous to apply artificial tissue models as surrogates of cartilage for investigating drug transport and release properties. In this study, artificial cartilage models consisting of 0.5% (w/v) agarose gel containing 0.5% (w/v) chondroitin sulfate or 0.5% (w/v) hyaluronic acid were developed, and their rheological and morphological properties were characterized. UV imaging was utilized to quantify the transport properties of the following four model compounds in the agarose gel and in the developed artificial cartilage models: H-Ala-β-naphthylamide, H-Lys-Lys-β-naphthylamide, lysozyme, and α-lactalbumin. The obtained results showed that the incorporation of the polyelectrolytes chondroitin sulfate or hyaluronic acid into agarose gel induced a significant reduction in the apparent diffusivities of the cationic model compounds as compared to the pure agarose gel. The decrease in apparent diffusivity of the cationic compounds was not caused by a change in the gel structure since a similar reduction in apparent diffusivity was not observed for the net negatively charged protein α-lactalbumin. The apparent diffusivity of the cationic compounds in the negatively charged hydrogels was highly dependent on the ionic strength, pointing out the importance of electrostatic interactions between the diffusant and the polyelectrolytes. Solution based affinity studies between the model compounds and the two investigated polyelectrolytes further confirmed the electrostatic nature of their interactions. The results obtained from the UV imaging diffusion studies are important for understanding the effect of drug physicochemical properties on the transport in articular cartilage. The extracted information may be useful in the development of hydrogels for in vitro release testing having features resembling the articular cartilage.

Virtual screening of B-Raf kinase inhibitors: A combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy calculation studies.

PubMed

Zhang, Wen; Qiu, Kai-Xiong; Yu, Fang; Xie, Xiao-Guang; Zhang, Shu-Qun; Chen, Ya-Juan; Xie, Hui-Ding

2017-10-01

B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG bind ) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines. In the result, five hit compounds show good biological activities (IC 50 <50μM). The present method of virtual screening can be applied to find structurally diverse inhibitors, and the obtained five structurally diverse compounds are expected to develop novel BRIs. Copyright © 2017. Published by Elsevier Ltd.

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.

Temperature Responses of Soil Organic Matter Components With Varying Recalcitrance

NASA Astrophysics Data System (ADS)

Simpson, M. J.; Feng, X.

2007-12-01

The response of soil organic matter (SOM) to global warming remains unclear partly due to the chemical heterogeneity of SOM composition. In this study, the decomposition of SOM from two grassland soils was investigated in a one-year laboratory incubation at six different temperatures. SOM was separated into solvent- extractable compounds, suberin- and cutin-derived compounds, and lignin monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components had distinct chemical structures and recalcitrance, and their decomposition was fitted by a two-pool exponential decay model. The stability of SOM components was assessed using geochemical parameters and kinetic parameters derived from model fitting. Lignin monomers exhibited much lower decay rates than solvent-extractable compounds and a relatively low percentage of lignin monomers partitioned into the labile SOM pool, which confirmed the generally accepted recalcitrance of lignin compounds. Suberin- and cutin-derived compounds had a poor fitting for the exponential decay model, and their recalcitrance was shown by the geochemical degradation parameter which stabilized during the incubation. The aliphatic components of suberin degraded faster than cutin-derived compounds, suggesting that cutin-derived compounds in the soil may be at a higher stage of degradation than suberin- derived compounds. The temperature sensitivity of decomposition, expressed as Q10, was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of the recalcitrant lignin monomers had much higher Q10 values than soil respiration or the solvent-extractable compounds decomposition. Our study shows that the decomposition of recalcitrant SOM is highly sensitive to temperature, more so than bulk soil mineralization. This observation suggests a potential acceleration in the degradation of the recalcitrant SOM pool with global warming.

Novel multi-targeted agents for Alzheimer's disease: Synthesis, biological evaluation, and molecular modeling of novel 2-[4-(4-substitutedpiperazin-1-yl)phenyl]benzimidazoles.

PubMed

Ozadali-Sari, Keriman; Tüylü Küçükkılınç, Tuba; Ayazgok, Beyza; Balkan, Ayla; Unsal-Tan, Oya

2017-06-01

The present study describes the synthesis, pharmacological evaluation (BChE/AChE inhibition, Aβ antiaggregation, and neuroprotective effects), and molecular modeling studies of novel 2-[4-(4-substitutedpiperazin-1-yl)phenyl]benzimidazole derivatives. The alkyl-substituted derivatives exhibited selective inhibition on BChE with varying efficiency. Compounds 3b and 3d were found to be the most potent inhibitors of BChE with IC 50 values of 5.18 and 5.22μM, respectively. The kinetic studies revealed that 3b is a partial non-competitive BChE inhibitor. Molecular modeling studies also showed that the alkyl-substituted derivatives were able to reach the catalytic anionic site of the BChE. The compounds with an inhibitory effect on BChE were subsequently screened for their Aβ antiaggregating and neuroprotective activities. Compounds 3a and 3b exerted a potential neuroprotective effect against H 2 O 2 and Aβ-induced cytotoxicity in SH-SY5Y cells. Collectively, 3b was found as the most promising compound for the development of multi-target directed ligands against Alzheimer's disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Ex vivo inhibition of Clostridium botulinum neurotoxin types B, C, E, and F by small molecular weight inhibitors.

PubMed

Montgomery, Vicki A; Ahmed, S Ashraf; Olson, Mark A; Mizanur, Rahman M; Stafford, Robert G; Roxas-Duncan, Virginia I; Smith, Leonard A

2015-05-01

Two small molecular weight inhibitors, compounds CB7969312 and CB7967495, that displayed inhibition of botulinum neurotoxin serotype A in a previous study, were evaluated for inhibition of botulinum neurotoxin serotypes B, C, E, and F. The small molecular weight inhibitors were assessed by molecular modeling, UPLC-based peptide cleavage assay; and an ex vivo assay, the mouse phrenic nerve - hemidiaphragm assay (MPNHDA). While both compounds were inhibitors of botulinum neurotoxin (BoNT) serotypes B, C, and F in the MPNHDA, compound CB7969312 was effective at lower molar concentrations than compound CB7967495. However, compound CB7967495 was significantly more effective at preventing BoNTE intoxication than compound CB7969312. In the UPLC-based peptide cleavage assay, CB7969312 was also more effective against LcC. Both compounds inhibited BoNTE, but not BoNTF, LcE, or LcF in the UPLC-based peptide cleavage assay. Molecular modeling studies predicted that both compounds would be effective inhibitors of BoNTs B, C, E, and F. But CB7967495 was predicted to be a more effective inhibitor of the four serotypes (B, C, E, and F) than CB7969312. This is the first report of a small molecular weight compound that inhibits serotypes B, C, E, and F in the ex vivo assay. Published by Elsevier Ltd.

Isolation and Quantification of Ginsenoside Rh23, a New Anti-Melanogenic Compound from the Leaves of Panax ginseng.

PubMed

Lee, Dae Young; Kim, Hyoung-Geun; Lee, Yeong-Geun; Kim, Jin Hee; Lee, Jae Won; Choi, Bo-Ram; Jang, In-Bae; Kim, Geum-Soog; Baek, Nam-In

2018-01-29

A new ginsenoside, named ginsenoside Rh23 ( 1 ), and 20- O -β-d-glucopyranosyl-3β,6α,12β,20β,25-pentahydroxydammar-23-ene ( 2 ) were isolated from the leaves of hydroponic Panax ginseng . Compounds were isolated by various column chromatography and their structures were determined based on spectroscopic methods, including high resolution quadrupole/time of flight mass spectrometry (HR-QTOF/MS), nuclear magnetic resonance (NMR) spectroscopy, and infrared (IR) spectroscopy. To determine anti-melanogenic activity, the change in the melanin content in melan-a cells treated with identified compounds was tested. Additionally, we investigated the melanin inhibitory effects of ginsenoside Rh23 on pigmentation in a zebrafish in vivo model. Compound 1 inhibited potent melanogenesis in melan-a cells with 37.0% melanogenesis inhibition at 80 µM and also presented inhibition on the body pigmentation in zebrafish model. Although compound 2 showed slightly lower inhibitory activity than compound 1 , it also showed significantly decreased melanogenesis in melan-a cell and in zebrafish model. These results indicated that compounds isolated from hydroponic P. ginseng may be used as new skin whitening compound through the in vitro and in vivo systems. Furthermore, this study demonstrated the utility of MS-based compound 1 for the quantitative analysis. Ginsenoside Rh23 ( 1 ) was found at a level of 0.31 mg/g in leaves of hydroponic P. ginseng .

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.

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.

[Studies on bioactive constituents of whole herbs of Vernonia cinerea].

PubMed

Zhu, Hua-xu; Tang, Yu-ping; Pan, Lin-mei; Min, Zhi-da

2008-08-01

To study the constituents of the whole herbs of Vernonia cinerea. by bio-activity guided isolation with PC-12 model. The constituents were separated by column chromatography and the structures were elucidated by spectroscopic methods. Four compounds were identified to be (+)-lirioresinol B (1), stigmasterol (2), stigmasterol-3-O-beta-D-glucoside (3), 4-sulfo-benzocyclobutene (4), and their NGF inducing activity were also investigated. Compounds 1, 3, 4 were isolated from this genus for the first time, and compound 4 was identified as a new natural product. Compounds 1, 3, 4 showed cytotoxicity on PC-12, and compounds 2, 3, 4 showed inhibition activity. Compound 4 showed a specific effect on the survival of TrkA fibroblasts, and resulted in the inducing NGF activity.

Biodegradation of coal-related model compounds

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

Campbell, J.A.; Stewart, D.L.; McCulloch, M.

1988-06-01

We have studied the reactions of model compounds having coal-related functionalities (ester linkages, ether linkages, PAH) with the intact organism, cell-free filtrate, and cell-free enzyme of C. versicolor to better understand the process of biosolubilization. Many of the degradation products have been identified by gas chromatography/mass spectroscopy (GC/MS). Results indicate that the two compounds tested with the intact fungal organism were completely degraded. Complete degradation refers to no recovery of model compound. We can probably assume that the other two would also be totally degraded, since we have not yet found a simple compound that will survive long-term exposure tomore » the intact fungus. The ease of degradation with the cell-free filtrate appears to be in the order: phenylbenzoate > benzylbenzoate > benzyl ether > methoxybenzophenone. Esters and ethers that are activated by aromatic rings appear to be susceptible to the fungal extract; however, aromatic ketones are not affected by the extract. From the limited results we have obtained from the isolated enzyme, it appears that the activity may parallel the cell-free filtrate. When the cell-free extract was tested with the model compounds indole, dibenzothiophene, and bibenzyl, no degradation with the enzyme was noted: however, exposure of these compounds to the intact organism resulted in complete degradation. Analysis of the controls indicated no degradation. 8 refs., 1 fig., 1 tab.« less

Identification of Ideal Multi-targeting Bioactive Compounds Against Mur Ligases of Enterobacter aerogenes and Its Binding Mechanism in Comparison with Chemical Inhibitors.

PubMed

Chakkyarath, Vijina; Natarajan, Jeyakumar

2017-10-31

Enterobacter aerogenes have been reported as important opportunistic and multi-resistant bacterial pathogens for humans during the last three decades in hospital wards. The emergence of drug-resistant E. aerogenes demands the need for developing new drugs. Peptidoglycan is an important component of the cell wall of bacteria and the peptidoglycan biochemical pathway is considered as the best source of antibacterial targets. Within this pathway, four Mur ligases MurC, MurD, MurE, and MurF are responsible for the successive additions of L-alanine and suitable targets for developing novel antibacterial drugs. As an inference from this fact, we modeled the three-dimensional structure of above Mur ligases using best template structures available in PDB and analyzed its common binding features. Structural refinement and energy minimization of the predicted Mur ligases models is also being done using molecular dynamics studies. The models of Mur ligases were further investigated for in silico docking studies using bioactive plant compounds from the literature. Interestingly, these results indicate that four plant compounds Isojuripidine, Atroviolacegenin, Porrigenin B, and Nummularogenin showing better docking results in terms of binding energy and number of hydrogen bonds. All these four compounds are spirostan-based compounds with differences in side chains and the amino acid such as ASN, LYS, THR, HIS, ARG (polar) and PHE, GLY, VAL, ALA, MET (non-polar) playing active role in binding site of all four Mur ligases. Overall, in the predicted model, the four plant compounds with its binding features could pave way to design novel multi-targeted antibacterial plant-based bioactive compounds specific to Mur ligases for the treatment of Enterobacter infections.

Modeling concentration patterns of agricultural and urban micropollutants in surface waters in catchment of mixed land use

NASA Astrophysics Data System (ADS)

Stamm, C.; Scheidegger, R.; Bader, H. P.

2012-04-01

Organic micropollutants detected in surface waters can originate from agricultural and urban sources. Depending on the use of the compounds, the temporal loss patterns vary substantially. Therefore models that simulate water quality in watersheds of mixed land use have to account for all relevant sources. We present here simulation results of a transport model that describes the dynamic of several biocidal compounds as well as the behaviour of human pharmaceuticals. The model consists of the sub-model Rexpo simulating the transfer of the compounds from the point of application to the stream in semi-lumped manner. The river sub-model, which is programmed in the Aquasim software, describes the fate of the compounds in the stream. Both sub-models are process-based. The Rexpo sub-model was calibrated at the scale of a small catchment of 25 km2, which is inhabited by about 12'000 people. Based on the resulting model parameters the loss dynamics of two herbicides (atrazine, isoproturon) and a compound of mixed urban and agricultural use (diuron) were predicted for two nested catchment of 212 and 1696 km2, respectively. The model output was compared to observed time-series of concentrations and loads obtained for the entire year 2009. Additionally, the fate of two pharmaceuticals with constant input (carbamazepine, diclofenac) was simulated for improving the understanding of possible degradation processes. The simulated loads and concentrations of the biocidal compounds differed by a factor of 2 to 3 from the observations. In general, the seasonal patterns were well captured by the model. However, a detailed analysis of the seasonality revealed substantial input uncertainty for the application of the compounds. The model results also demonstrated that for the dynamics of rain-driven losses of biocidal compounds the semi-lumped approach of the Rexpo sub-model was sufficient. Only for simulating the photolytic degradation of diclofenac in the stream the detailed representation of the routing in the stream was essential. Overall, the study demonstrated that the simulation of micropollutants at the watershed scale can be strongly hampered by input uncertainty regarding the use of the chemicals. Under such conditions the level of process-representation in the Rexpo sub-models is superfluous. For practical applications, one should address the question how to simply the approach while still maintaining the essential parts.

Biodegradation of coal-related model compounds. [C. versicolor

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

Campbell, J.A.; Stewart, D.L.; McCulloch, M.

1988-01-01

The details of the specific reactions of lignin biodegradation, and the biochemistry involved, have been primarily based on the use of low molecular weight compounds representing specific substructures rather than the complex, polymeric lignin material. The authors have studied the reactions of model compounds having coal-related functionalities (ester linkages, ether linkages, PAH) with the intact organisms, cell-free filtrate, and cell-free enzyme of C. versicolor to better understand the process of biosolubilization. Many of the degradation products have been identified by gas chromatography/mass spectrometry (GC/MS). Results are discussed.

Effect of composition of simulated intestinal media on the solubility of poorly soluble compounds investigated by design of experiments.

PubMed

Madsen, Cecilie Maria; Feng, Kung-I; Leithead, Andrew; Canfield, Nicole; Jørgensen, Søren Astrup; Müllertz, Anette; Rades, Thomas

2018-01-01

The composition of the human intestinal fluids varies both intra- and inter-individually. This will influence the solubility of orally administered drug compounds, and hence, the absorption and efficacy of compounds displaying solubility limited absorption. The purpose of this study was to assess the influence of simulated intestinal fluid (SIF) composition on the solubility of poorly soluble compounds. Using a Design of Experiments (DoE) approach, a set of 24 SIF was defined within the known compositions of human fasted state intestinal fluid. The SIF were composed of phospholipid, bile salt, and different pH, buffer capacities and osmolarities. On a small scale semi-robotic system, the solubility of 6 compounds (aprepitant, carvedilol, felodipine, fenofibrate, probucol, and zafirlukast) was determined in the 24 SIF. Compound specific models, describing key factors influencing the solubility of each compound, were identified. Although all models were different, the level of phospholipid and bile salt, the pH, and the interactions between these, had the biggest influences on solubility overall. Thus, a reduction of the DoE from five to three factors was possible (11-13 media), making DoE solubility studies feasible compared to single SIF solubility studies. Applying this DoE approach will lead to a better understanding of the impact of intestinal fluid composition on the solubility of a given drug compound. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Effects of Digested Onion Extracts on Intestinal Gene Expression: An Interspecies Comparison Using Different Intestine Models

PubMed Central

Govers, Coen; van der Meulen, Jan; van Hoef, Angeline; Stoopen, Geert; Hamers, Astrid; Hoekman, Arjan; de Vos, Ric; Bovee, Toine F. H.; Smits, Mari; Mes, Jurriaan J.

2016-01-01

Human intestinal tissue samples are barely accessible to study potential health benefits of nutritional compounds. Numbers of animals used in animal trials, however, need to be minimalized. Therefore, we explored the applicability of in vitro (human Caco-2 cells) and ex vivo intestine models (rat precision cut intestine slices and the pig in-situ small intestinal segment perfusion (SISP) technique) to study the effect of food compounds. In vitro digested yellow (YOd) and white onion extracts (WOd) were used as model food compounds and transcriptomics was applied to obtain more insight into which extent mode of actions depend on the model. The three intestine models shared 9,140 genes which were used to compare the responses to digested onions between the models. Unsupervised clustering analysis showed that genes up- or down-regulated by WOd in human Caco-2 cells and rat intestine slices were similarly regulated by YOd, indicating comparable modes of action for the two onion species. Highly variable responses to onion were found in the pig SISP model. By focussing only on genes with significant differential expression, in combination with a fold change > 1.5, 15 genes showed similar onion-induced expression in human Caco-2 cells and rat intestine slices and 2 overlapping genes were found between the human Caco-2 and pig SISP model. Pathway analyses revealed that mainly processes related to oxidative stress, and especially the Keap1-Nrf2 pathway, were affected by onions in all three models. Our data fit with previous in vivo studies showing that the beneficial effects of onions are mostly linked to their antioxidant properties. Taken together, our data indicate that each of the in vitro and ex vivo intestine models used in this study, taking into account their limitations, can be used to determine modes of action of nutritional compounds and can thereby reduce the number of animals used in conventional nutritional intervention studies. PMID:27631494

Effects of Digested Onion Extracts on Intestinal Gene Expression: An Interspecies Comparison Using Different Intestine Models.

PubMed

de Wit, Nicole J W; Hulst, Marcel; Govers, Coen; van der Meulen, Jan; van Hoef, Angeline; Stoopen, Geert; Hamers, Astrid; Hoekman, Arjan; de Vos, Ric; Bovee, Toine F H; Smits, Mari; Mes, Jurriaan J; Hendriksen, Peter J M

2016-01-01

Human intestinal tissue samples are barely accessible to study potential health benefits of nutritional compounds. Numbers of animals used in animal trials, however, need to be minimalized. Therefore, we explored the applicability of in vitro (human Caco-2 cells) and ex vivo intestine models (rat precision cut intestine slices and the pig in-situ small intestinal segment perfusion (SISP) technique) to study the effect of food compounds. In vitro digested yellow (YOd) and white onion extracts (WOd) were used as model food compounds and transcriptomics was applied to obtain more insight into which extent mode of actions depend on the model. The three intestine models shared 9,140 genes which were used to compare the responses to digested onions between the models. Unsupervised clustering analysis showed that genes up- or down-regulated by WOd in human Caco-2 cells and rat intestine slices were similarly regulated by YOd, indicating comparable modes of action for the two onion species. Highly variable responses to onion were found in the pig SISP model. By focussing only on genes with significant differential expression, in combination with a fold change > 1.5, 15 genes showed similar onion-induced expression in human Caco-2 cells and rat intestine slices and 2 overlapping genes were found between the human Caco-2 and pig SISP model. Pathway analyses revealed that mainly processes related to oxidative stress, and especially the Keap1-Nrf2 pathway, were affected by onions in all three models. Our data fit with previous in vivo studies showing that the beneficial effects of onions are mostly linked to their antioxidant properties. Taken together, our data indicate that each of the in vitro and ex vivo intestine models used in this study, taking into account their limitations, can be used to determine modes of action of nutritional compounds and can thereby reduce the number of animals used in conventional nutritional intervention studies.

Docking-based Screening of Ficus religiosa Phytochemicals as Inhibitors of Human Histamine H2 Receptor.

PubMed

Chaudhary, Amit; Yadav, Birendra Singh; Singh, Swati; Maurya, Pramod Kumar; Mishra, Alok; Srivastva, Shweta; Varadwaj, Pritish Kumar; Singh, Nand Kumar; Mani, Ashutosh

2017-10-01

Ficus religiosa L. is generally known as Peepal and belongs to family Moraceae . The tree is a source of many compounds having high medicinal value. In gastrointestinal tract, histamine H2 receptors have key role in histamine-stimulated gastric acid secretion. Their over stimulation causes its excessive production which is responsible for gastric ulcer. This study aims to screen the range of phytochemicals present in F. religiosa for binding with human histamine H2 and identify therapeutics for a gastric ulcer from the plant. In this work, a 3D-structure of human histamine H2 receptor was modeled by using homology modeling and the predicted model was validated using PROCHECK. Docking studies were also performed to assess binding affinities between modeled receptor and 34 compounds. Molecular dynamics simulations were done to identify most stable receptor-ligand complexes. Absorption, distribution, metabolism, excretion, and screening was done to evaluate pharmacokinetic properties of compounds. The results suggest that seven ligands, namely, germacrene, bergaptol, lanosterol, Ergost-5-en-3beta-ol, α-amyrin acetate, bergapten, and γ-cadinene showed better binding affinities. Among seven phytochemicals, lanosterol and α-amyrin acetate were found to have greater stability during simulation studies. These two compounds may be a suitable therapeutic agent against histamine H2 receptor. This study was performed to screen antiulcer compounds from F. religiosa . Molecular modeling, molecular docking and MD simulation studies were performed with selected phytochemicals from F. religiosa . The analysis suggests that Lanosterol and α-amyrin may be a suitable therapeutic agent against histamine H2 receptor. This study facilitates initiation of the herbal drug discovery process for the antiulcer activity. Abbreviations used: ADMET: Absorption, distribution, metabolism, excretion and toxicity, DOPE: Discrete Optimized Potential Energy, OPLS: Optimized potential for liquid simulations, RMSD: Root-mean-square deviation, HOA: Human oral absorption, MW: Molecular weight, SP: Standard-precision, XP: Extra-precision, GPCRs: G protein-coupled receptors, SASA: Solvent accessible surface area, Rg: Radius of gyration, NHB: Number of hydrogen bond.

Magnetism in S = 1 / 2 Double Perovskites with Strong Spin-Orbit Interactions

NASA Astrophysics Data System (ADS)

Ishizuka, Hiroaki; Balents, Leon

2015-03-01

Motivated by recent studies on heavy-element double-perovskite (DP) compounds, we theoretically studied spin models on a FCC lattice with anisotropic interactions. In these systems, competition/cooperation of spin, orbital, and the lattice degrees of freedoms in the presence of the strong-spin orbit coupling is of particular interest. In a previous theoretical study, the magnetic phase diagrams of DP compounds with 5d1 electron configuration was studied using a model with four-fold degenerated single-ion state. On the other hand, a recent experiment on a DP material, Ba2Na2OsO6, reported that the compound is likely to be an effective S = 1 / 2 magnet. Inspired by the experimental observation, we considered spin models with symmetry-allowed anisotropic nearest-neighbor interactions. By a combination of various analytical and numerical techniques, we present the magnetic phase diagram of the model and the effect of thermal and quantum fluctuations. In particular, we show that fluctuations induce < 110 > anisotropy of magnetic moments. We also discuss a possible ``nematic'' phase driven by spin-phonon couplings.

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.

Preliminary characterization of wild lactic acid bacteria and their abilities to produce flavour compounds in ripened model cheese system.

PubMed

Randazzo, C L; De Luca, S; Todaro, A; Restuccia, C; Lanza, C M; Spagna, G; Caggia, C

2007-08-01

The aim of this work was to preliminary characterize wild lactic acid bacteria (LAB), previously isolated during artisanal Pecorino Siciliano (PS) cheese-making for technological and flavour formation abilities in a model cheese system. Twelve LAB were studied for the ability to grow at 10 and 45 degrees C, to coagulate and acidify both reconstituted skim milk and ewe's milk. Moreover, the capacity of the strains to generate aroma compounds was evaluated in a model cheese system at 30- and 60-day ripening. Flavour compounds were screened by sensory analysis and throughout gas chromatography (GC)-mass spectrometry (MS). Most of the strains were able to grow both at 10 and 45 degrees C and exhibited high ability to acidify and coagulate ewes' milk. Sensory evaluation revealed that the wild strains produced more significant flavour attributes than commercial strains in the 60-day-old model cheese system. GC-MS data confirmed the results of sensory evaluations and showed the ability of wild lactobacilli to generate key volatile compounds. Particularly, three wild lactobacilli strains, belonging to Lactobacillus casei, Lb. rhamnosus and Lb. plantarum species, generated both in 60- and 30-day-old model cheeses system, the 3-methyl butan(al)(ol) compound, which is associated with fruity taste. The present work preliminarily demonstrated that the technological and flavour formation abilities of the wild strains are strain-specific and that wild lactobacilli, which produced key flavour compounds during ripening, could be used as tailor-made starters. This study reports the technological characterization and flavour formation ability of wild LAB strains isolated from artisanal Pecorino cheese and highlights that the catabolic activities were highly strain dependent. Hence, wild lactobacilli could be selected as tailor-made starter cultures for the PS cheese manufacture.

Structure-activity models of oral clearance, cytotoxicity, and LD50: a screen for promising anticancer compounds

PubMed Central

Boik, John C; Newman, Robert A

2008-01-01

Background Quantitative structure-activity relationship (QSAR) models have become popular tools to help identify promising lead compounds in anticancer drug development. Few QSAR studies have investigated multitask learning, however. Multitask learning is an approach that allows distinct but related data sets to be used in training. In this paper, a suite of three QSAR models is developed to identify compounds that are likely to (a) exhibit cytotoxic behavior against cancer cells, (b) exhibit high rat LD50 values (low systemic toxicity), and (c) exhibit low to modest human oral clearance (favorable pharmacokinetic characteristics). Models were constructed using Kernel Multitask Latent Analysis (KMLA), an approach that can effectively handle a large number of correlated data features, nonlinear relationships between features and responses, and multitask learning. Multitask learning is particularly useful when the number of available training records is small relative to the number of features, as was the case with the oral clearance data. Results Multitask learning modestly but significantly improved the classification precision for the oral clearance model. For the cytotoxicity model, which was constructed using a large number of records, multitask learning did not affect precision but did reduce computation time. The models developed here were used to predict activities for 115,000 natural compounds. Hundreds of natural compounds, particularly in the anthraquinone and flavonoids groups, were predicted to be cytotoxic, have high LD50 values, and have low to moderate oral clearance. Conclusion Multitask learning can be useful in some QSAR models. A suite of QSAR models was constructed and used to screen a large drug library for compounds likely to be cytotoxic to multiple cancer cell lines in vitro, have low systemic toxicity in rats, and have favorable pharmacokinetic properties in humans. PMID:18554402

Structure-activity models of oral clearance, cytotoxicity, and LD50: a screen for promising anticancer compounds.

PubMed

Boik, John C; Newman, Robert A

2008-06-13

Quantitative structure-activity relationship (QSAR) models have become popular tools to help identify promising lead compounds in anticancer drug development. Few QSAR studies have investigated multitask learning, however. Multitask learning is an approach that allows distinct but related data sets to be used in training. In this paper, a suite of three QSAR models is developed to identify compounds that are likely to (a) exhibit cytotoxic behavior against cancer cells, (b) exhibit high rat LD50 values (low systemic toxicity), and (c) exhibit low to modest human oral clearance (favorable pharmacokinetic characteristics). Models were constructed using Kernel Multitask Latent Analysis (KMLA), an approach that can effectively handle a large number of correlated data features, nonlinear relationships between features and responses, and multitask learning. Multitask learning is particularly useful when the number of available training records is small relative to the number of features, as was the case with the oral clearance data. Multitask learning modestly but significantly improved the classification precision for the oral clearance model. For the cytotoxicity model, which was constructed using a large number of records, multitask learning did not affect precision but did reduce computation time. The models developed here were used to predict activities for 115,000 natural compounds. Hundreds of natural compounds, particularly in the anthraquinone and flavonoids groups, were predicted to be cytotoxic, have high LD50 values, and have low to moderate oral clearance. Multitask learning can be useful in some QSAR models. A suite of QSAR models was constructed and used to screen a large drug library for compounds likely to be cytotoxic to multiple cancer cell lines in vitro, have low systemic toxicity in rats, and have favorable pharmacokinetic properties in humans.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

PubMed

Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

Application of Artificial Neural Network and Support Vector Machines in Predicting Metabolizable Energy in Compound Feeds for Pigs.

PubMed

Ahmadi, Hamed; Rodehutscord, Markus

2017-01-01

In the nutrition literature, there are several reports on the use of artificial neural network (ANN) and multiple linear regression (MLR) approaches for predicting feed composition and nutritive value, while the use of support vector machines (SVM) method as a new alternative approach to MLR and ANN models is still not fully investigated. The MLR, ANN, and SVM models were developed to predict metabolizable energy (ME) content of compound feeds for pigs based on the German energy evaluation system from analyzed contents of crude protein (CP), ether extract (EE), crude fiber (CF), and starch. A total of 290 datasets from standardized digestibility studies with compound feeds was provided from several institutions and published papers, and ME was calculated thereon. Accuracy and precision of developed models were evaluated, given their produced prediction values. The results revealed that the developed ANN [ R 2  = 0.95; root mean square error (RMSE) = 0.19 MJ/kg of dry matter] and SVM ( R 2  = 0.95; RMSE = 0.21 MJ/kg of dry matter) models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR ( R 2  = 0.89; RMSE = 0.27 MJ/kg of dry matter). The developed ANN and SVM models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR; however, there were not obvious differences between performance of ANN and SVM models. Thus, SVM model may also be considered as a promising tool for modeling the relationship between chemical composition and ME of compound feeds for pigs. To provide the readers and nutritionist with the easy and rapid tool, an Excel ® calculator, namely, SVM_ME_pig, was created to predict the metabolizable energy values in compound feeds for pigs using developed support vector machine model.

Rational design of bioactive, modularly assembled aminoglycosides targeting the RNA that causes myotonic dystrophy type 1.

PubMed

Childs-Disney, Jessica L; Parkesh, Raman; Nakamori, Masayuki; Thornton, Charles A; Disney, Matthew D

2012-12-21

Myotonic dystrophy type 1 (DM1) is caused when an expanded r(CUG) repeat (r(CUG)(exp)) binds the RNA splicing regulator muscleblind-like 1 protein (MBNL1) as well as other proteins. Previously, we reported that modularly assembled small molecules displaying a 6'-N-5-hexynoate kanamycin A RNA-binding module (K) on a peptoid backbone potently inhibit the binding of MBNL1 to r(CUG)(exp). However, these parent compounds are not appreciably active in cell-based models of DM1. The lack of potency was traced to suboptimal cellular permeability and localization. To improve these properties, second-generation compounds that are conjugated to a d-Arg(9) molecular transporter were synthesized. These modified compounds enter cells in higher concentrations than the parent compounds and are efficacious in cell-based DM1 model systems at low micromolar concentrations. In particular, they improve three defects that are the hallmarks of DM1: a translational defect due to nuclear retention of transcripts containing r(CUG)(exp); pre-mRNA splicing defects due to inactivation of MBNL1; and the formation of nuclear foci. The best compound in cell-based studies was tested in a mouse model of DM1. Modest improvement of pre-mRNA splicing defects was observed. These studies suggest that a modular assembly approach can afford bioactive compounds that target RNA.

Rational Design of Bioactive, Modularly Assembled Aminoglycosides Targeting the RNA that Causes Myotonic Dystrophy Type 1

PubMed Central

Childs-Disney, Jessica L.; Parkesh, Raman; Nakamori, Masayuki; Thornton, Charles A.; Disney, Matthew D.

2012-01-01

Myotonic dystrophy type 1 (DM1) is caused when an expanded r(CUG) repeat (r(CUG)exp) binds the RNA splicing regulator muscleblind-like 1 protein (MBNL1) as well as other proteins. Previously, we reported that modularly assembled small molecules displaying a 6′-N-5-hexynoate kanamycin A RNA-binding module (K) on a peptoid backbone potently inhibit the binding of MBNL1 to r(CUG)exp. However, these parent compounds are not appreciably active in cell-based models of DM1. The lack of potency was traced to suboptimal cellular permeability and localization. To improve these properties, second-generation compounds that are conjugated to a D-Arg9 molecular transporter were synthesized. These modified compounds enter cells in higher concentrations than the parent compounds and are efficacious in cell-based DM1 model systems at low micromolar concentrations. In particular, they improve three defects that are the hallmarks of DM1: a translational defect due to nuclear retention of transcripts containing r(CUG)exp; pre-mRNA splicing defects due to inactivation of MBNL1; and the formation of nuclear foci. The best compound in cell-based studies was tested in a mouse model of DM1. Modest improvement of pre-mRNA splicing defects was observed. These studies suggest that a modular assembly approach can afford bioactive compounds that target RNA. PMID:23130637

Potential grape-derived contributions to volatile ester concentrations in wine.

PubMed

Boss, Paul K; Pearce, Anthony D; Zhao, Yanjia; Nicholson, Emily L; Dennis, Eric G; Jeffery, David W

2015-04-29

Grape composition affects wine flavour and aroma not only through varietal compounds, but also by influencing the production of volatile compounds by yeast. C9 and C12 compounds that potentially influence ethyl ester synthesis during fermentation were studied using a model grape juice medium. It was shown that the addition of free fatty acids, their methyl esters or acyl-carnitine and acyl-amino acid conjugates can increase ethyl ester production in fermentations. The stimulation of ethyl ester production above that of the control was apparent when lower concentrations of the C9 compounds were added to the model musts compared to the C12 compounds. Four amino acids, which are involved in CoA biosynthesis, were also added to model grape juice medium in the absence of pantothenate to test their ability to influence ethyl and acetate ester production. β-Alanine was the only one shown to increase the production of ethyl esters, free fatty acids and acetate esters. The addition of 1 mg∙L(-1) β-alanine was enough to stimulate production of these compounds and addition of up to 100 mg∙L(-1) β-alanine had no greater effect. The endogenous concentrations of β-alanine in fifty Cabernet Sauvignon grape samples exceeded the 1 mg∙L(-1) required for the stimulatory effect on ethyl and acetate ester production observed in this study.

Low cost biosorbent "banana peel" for the removal of phenolic compounds from olive mill wastewater: kinetic and equilibrium studies.

PubMed

Achak, M; Hafidi, A; Ouazzani, N; Sayadi, S; Mandi, L

2009-07-15

The aim of this work is to determine the potential of application of banana peel as a biosorbent for removing phenolic compounds from olive mill wastewaters. The effect of adsorbent dosage, pH and contact time were investigated. The results showed that the increase in the banana peel dosage from 10 to 30 g/L significantly increased the phenolic compounds adsorption rates from 60 to 88%. Increase in the pH to above neutrality resulted in the increase in the phenolic compounds adsorption capacity. The adsorption process was fast, and it reached equilibrium in 3-h contact time. The Freundlich and Langmuir adsorption models were used for mathematical description of the adsorption equilibrium and it was found that experimental data fitted very well to both Freundlich and Langmuir models. Batch adsorption models, based on the assumption of the pseudo-first-order, pseudo-second-order and intraparticle diffusion mechanism, showed that kinetic data follow closely the pseudo-second-order than the pseudo-first-order and intraparticle diffusion. Desorption studies showed that low pH value was efficient for desorption of phenolic compounds. These results indicate clearly the efficiency of banana peel as a low-cost solution for olive mill wastewaters treatment and give some preliminary elements for the comprehension of the interactions between banana peel as a bioadsorbent and the very polluting compounds from the olive oil industry.

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 ).

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

Radiation chemistry of salicylic and methyl substituted salicylic acids: Models for the radiation chemistry of pharmaceutical compounds

NASA Astrophysics Data System (ADS)

Ayatollahi, Shakiba; Kalnina, Daina; Song, Weihua; Turks, Maris; Cooper, William J.

2013-11-01

Salicylic acid and its derivatives are components of many medications and moieties found in numerous pharmaceutical compounds. They have been used as models for various pharmaceutical compounds in pharmacological studies, for the treatment of pharmaceuticals and personal care products (PPCPs), and, reactions with natural organic matter (NOM). In this study, the radiation chemistry of benzoic acid, salicylic acid and four methyl substituted salicylic acids (MSA) is reported. The absolute bimolecular reaction rate constants for hydroxyl radical reaction with benzoic and salicylic acids as well as 3-methyl-, 4-methyl-, 5-methyl-, and 6-methyl-salicylic acid were determined (5.86±0.54)×109, (1.07±0.07)×1010, (7.48±0.17)×109, (7.31±0.29)×109, (5.47±0.25)×109, (6.94±0.10)×109 (M-1 s-1), respectively. The hydrated electron reaction rate constants were measured (3.02±0.10)×109, (8.98±0.27)×109, (5.39±0.21)×109, (4.33±0.17)×109, (4.72±0.15)×109, (1.42±0.02)×109 (M-1 s-1), respectively. The transient absorption spectra for the six model compounds were examined and their role as model compounds for the radiation chemistry of pharmaceuticals investigated.

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.

Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity

PubMed Central

Zhu, Hao; Rusyn, Ivan; Richard, Ann; Tropsha, Alexander

2008-01-01

Background To develop efficient approaches for rapid evaluation of chemical toxicity and human health risk of environmental compounds, the National Toxicology Program (NTP) in collaboration with the National Center for Chemical Genomics has initiated a project on high-throughput screening (HTS) of environmental chemicals. The first HTS results for a set of 1,408 compounds tested for their effects on cell viability in six different cell lines have recently become available via PubChem. Objectives We have explored these data in terms of their utility for predicting adverse health effects of the environmental agents. Methods and results Initially, the classification k nearest neighbor (kNN) quantitative structure–activity relationship (QSAR) modeling method was applied to the HTS data only, for a curated data set of 384 compounds. The resulting models had prediction accuracies for training, test (containing 275 compounds together), and external validation (109 compounds) sets as high as 89%, 71%, and 74%, respectively. We then asked if HTS results could be of value in predicting rodent carcinogenicity. We identified 383 compounds for which data were available from both the Berkeley Carcinogenic Potency Database and NTP–HTS studies. We found that compounds classified by HTS as “actives” in at least one cell line were likely to be rodent carcinogens (sensitivity 77%); however, HTS “inactives” were far less informative (specificity 46%). Using chemical descriptors only, kNN QSAR modeling resulted in 62.3% prediction accuracy for rodent carcinogenicity applied to this data set. Importantly, the prediction accuracy of the model was significantly improved (72.7%) when chemical descriptors were augmented by HTS data, which were regarded as biological descriptors. Conclusions Our studies suggest that combining NTP–HTS profiles with conventional chemical descriptors could considerably improve the predictive power of computational approaches in toxicology. PMID:18414635

Validation of visualized transgenic zebrafish as a high throughput model to assay bradycardia related cardio toxicity risk candidates.

PubMed

Wen, Dingsheng; Liu, Aiming; Chen, Feng; Yang, Julin; Dai, Renke

2012-10-01

Drug-induced QT prolongation usually leads to torsade de pointes (TdP), thus for drugs in the early phase of development this risk should be evaluated. In the present study, we demonstrated a visualized transgenic zebrafish as an in vivo high-throughput model to assay the risk of drug-induced QT prolongation. Zebrafish larvae 48 h post-fertilization expressing green fluorescent protein in myocardium were incubated with compounds reported to induce QT prolongation or block the human ether-a-go-go-related gene (hERG) K⁺ current. The compounds sotalol, indapaminde, erythromycin, ofoxacin, levofloxacin, sparfloxacin and roxithromycin were additionally administrated by microinjection into the larvae yolk sac. The ventricle heart rate was recorded using the automatic monitoring system after incubation or microinjection. As a result, 14 out of 16 compounds inducing dog QT prolongation caused bradycardia in zebrafish. A similar result was observed with 21 out of 26 compounds which block hERG current. Among the 30 compounds which induced human QT prolongation, 25 caused bradycardia in this model. Thus, the risk of compounds causing bradycardia in this transgenic zebrafish correlated with that causing QT prolongation and hERG K⁺ current blockage in established models. The tendency that high logP values lead to high risk of QT prolongation in this model was indicated, and non-sensitivity of this model to antibacterial agents was revealed. These data suggest application of this transgenic zebrafish as a high-throughput model to screen QT prolongation-related cardio toxicity of the drug candidates. Copyright © 2012 John Wiley & Sons, Ltd.

Bioactivity Studies of β-Lactam Derived Polycyclic Fused Pyrroli-Dine/Pyrrolizidine Derivatives in Dentistry: In Vitro, In Vivo and In Silico Studies

PubMed Central

Winfred, Sofi Beaula; Mannivanan, Bhavani; Bhoopalan, Hemadev; Shankar, Venkatesh; Sekar, Sathiya; Venkatachalam, Deepa Parvathi; Pitani, Ravishankar; Nagendrababu, Venkateshbabu; Thaiman, Malini; Devivanayagam, Kandaswamy; Jayaraman, Jeyakanthan; Ragavachary, Raghunathan; Venkatraman, Ganesh

2015-01-01

The antibacterial activity of β-lactam derived polycyclic fused pyrrolidine/pyrrolizidine derivatives synthesized by 1, 3-dipolar cycloaddition reaction was evaluated against microbes involved in dental infection. Fifteen compounds were screened; among them compound 3 showed efficient antibacterial activity in an ex vivo dentinal tubule model and in vivo mice infectious model. In silico docking studies showed greater affinity to penicillin binding protein. Cell damage was observed under Scanning Electron Microscopy (SEM) which was further proved by Confocal Laser Scanning Microscope (CLSM) and quantified using Flow Cytometry by PI up-take. Compound 3 treated E. faecalis showed ROS generation and loss of membrane integrity was quantified by flow cytometry. Compound 3 was also found to be active against resistant E. faecalis strains isolated from failed root canal treatment cases. Further, compound 3 was found to be hemocompatible, not cytotoxic to normal mammalian NIH 3T3 cells and non mutagenic. It was concluded that β-lactam compound 3 exhibited promising antibacterial activity against E. faecalis involved in root canal infections and the mechanism of action was deciphered. The results of this research can be further implicated in the development of potent antibacterial medicaments with applications in dentistry. PMID:26185985

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.

Norisoprenoids, sesquiterpenes and terpenoids content of Valpolicella wines during ageing: investigating aroma potential in relationship to evolution of tobacco and balsamic aroma in aged wine

NASA Astrophysics Data System (ADS)

Slaghenaufi, Davide; Ugliano, Maurizio

2018-03-01

During wine ageing, tobacco and balsamic aroma notes appear. In this paper, volatile compounds directly or potentially related to those aromas have been investigated in Corvina and Corvinone wines during aging. Corvina and Corvinone are two northern-Italy autochthonous red grape varieties, used to produce Valpolicella Classico and Amarone wines, both characterized by tobacco and balsamic aroma notes. Wines were analysed shortly after bottling or following model ageing at 60 °C for 48, 72, and 168 hours. Volatile compounds were analysed by HS-SPME-GC-MS. Results showed that compounds related to tobacco aroma (β-damascenone, 3-oxo-α-ionol, (E)-1-(2,3,6-Trimethylphenyl)-buta-1,3-diene (TPB) and megastigmatrienones) increased in relationship to storage time with different patterns. β-Damascenone and 3-oxo-α-ionol rapidly increased to reach a plateau in the first 48-72 hours of model ageing. Instead, TPB and megastigmatrienones concentration showed a linear correlation with ageing time. During model ageing, several cyclic terpenes tended to increase. Among them 1,8-cineole and 1,4-cineole, previously reported to contribute to red wine eucalyptus notes increased proportionally to storage time, and this behavior was clearly associated with reactions involving α-terpineol, limonene and terpinolene, as confirmed by studies with model wine solutions. Among other relevant volatile compounds, sesquiterpenes appear to contribute potentially balsamic and spicy aroma notes. In this study, linear sesquiterpenes (nerolidol, farnesol) underwent acid hydrolysis during long wine ageing, while cyclic sesquiterpenes seemed to increase with time. The chemical pathways associated with evolution of some of the compounds investigated have been studied in model wine.

De Novo Design of Bioactive Small Molecules by Artificial Intelligence.

PubMed

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

2018-01-01

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

Regioselectivity of enzymatic and photochemical single electron transfer promoted carbon-carbon bond fragmentation reactions of tetrameric lignin model compounds.

PubMed

Cho, Dae Won; Latham, John A; Park, Hea Jung; Yoon, Ung Chan; Langan, Paul; Dunaway-Mariano, Debra; Mariano, Patrick S

2011-04-15

New types of tetrameric lignin model compounds, which contain the common β-O-4 and β-1 structural subunits found in natural lignins, have been prepared and carbon-carbon bond fragmentation reactions of their cation radicals, formed by photochemical (9,10-dicyanoanthracene) and enzymatic (lignin peroxidase) SET-promoted methods, have been explored. The results show that cation radical intermediates generated from the tetrameric model compounds undergo highly regioselective C-C bond cleavage in their β-1 subunits. The outcomes of these processes suggest that, independent of positive charge and odd-electron distributions, cation radicals of lignins formed by SET to excited states of sensitizers or heme-iron centers in enzymes degrade selectively through bond cleavage reactions in β-1 vs β-O-4 moieties. In addition, the findings made in the enzymatic studies demonstrate that the sterically large tetrameric lignin model compounds undergo lignin peroxidase-catalyzed cleavage via a mechanism involving preliminary formation of an enzyme-substrate complex.

Understanding the polypharmacological anticancer effects of Xiao Chai Hu Tang via a computational pharmacological model

PubMed Central

ZHENG, CHUN-SONG; WU, YIN-SHENG; BAO, HONG-JUAN; XU, XIAO-JIE; CHEN, XING-QIANG; YE, HONG-ZHI; WU, GUANG-WEN; XU, HUI-FENG; LI, XI-HAI; CHEN, JIA-SHOU; LIU, XIAN-XIANG

2014-01-01

Xiao Chai Hu Tang (XCHT), a traditional herbal formula, is widely administered as a cancer treatment. However, the underlying molecular mechanisms of its anticancer effects are not fully understood. In the present study, a computational pharmacological model that combined chemical space mapping, molecular docking and network analysis was employed to predict which chemical compounds in XCHT are potential inhibitors of cancer-associated targets, and to establish a compound-target (C-T) network and compound-compound (C-C) association network. The identified compounds from XCHT demonstrated diversity in chemical space. Furthermore, they occupied regions of chemical space that were the same, or close to, those occupied by drug or drug-like compounds that are associated with cancer, according to the Therapeutic Targets Database. The analysis of the molecular docking and the C-T network demonstrated that the potential inhibitors possessed the properties of promiscuous drugs and combination therapies. The C-C network was classified into four clusters and the different clusters contained various multi-compound combinations that acted on different targets. The study indicated that XCHT has a polypharmacological role in treating cancer and the potential inhibitory components of XCHT require further investigation as potential therapeutic strategies for cancer patients. PMID:24926384

Behavior of platinum(iv) complexes in models of tumor hypoxia: cytotoxicity, compound distribution and accumulation.

PubMed

Schreiber-Brynzak, Ekaterina; Pichler, Verena; Heffeter, Petra; Hanson, Buck; Theiner, Sarah; Lichtscheidl-Schultz, Irene; Kornauth, Christoph; Bamonti, Luca; Dhery, Vineet; Groza, Diana; Berry, David; Berger, Walter; Galanski, Markus; Jakupec, Michael A; Keppler, Bernhard K

2016-04-01

Hypoxia in solid tumors remains a challenge for conventional cancer therapeutics. As a source for resistance, metastasis development and drug bioprocessing, it influences treatment results and disease outcome. Bioreductive platinum(iv) prodrugs might be advantageous over conventional metal-based therapeutics, as biotransformation in a reductive milieu, such as under hypoxia, is required for drug activation. This study deals with a two-step screening of experimental platinum(iv) prodrugs with different rates of reduction and lipophilicity with the aim of identifying the most appropriate compounds for further investigations. In the first step, the cytotoxicity of all compounds was compared in hypoxic multicellular spheroids and monolayer culture using a set of cancer cell lines with different sensitivities to platinum(ii) compounds. Secondly, two selected compounds were tested in hypoxic xenografts in SCID mouse models in comparison to satraplatin, and, additionally, (LA)-ICP-MS-based accumulation and distribution studies were performed for these compounds in hypoxic spheroids and xenografts. Our findings suggest that, while cellular uptake and cytotoxicity strongly correlate with lipophilicity, cytotoxicity under hypoxia compared to non-hypoxic conditions and antitumor activity of platinum(iv) prodrugs are dependent on their rate of reduction.

Development of a model for predicting reaction rate constants of organic chemicals with ozone at different temperatures.

PubMed

Li, Xuehua; Zhao, Wenxing; Li, Jing; Jiang, Jingqiu; Chen, Jianji; Chen, Jingwen

2013-08-01

To assess the persistence and fate of volatile organic compounds in the troposphere, the rate constants for the reaction with ozone (kO3) are needed. As kO3 values are only available for hundreds of compounds, and experimental determination of kO3 is costly and time-consuming, it is of importance to develop predictive models on kO3. In this study, a total of 379 logkO3 values at different temperatures were used to develop and validate a model for the prediction of kO3, based on quantum chemical descriptors, Dragon descriptors and structural fragments. Molecular descriptors were screened by stepwise multiple linear regression, and the model was constructed by partial least-squares regression. The cross validation coefficient QCUM(2) of the model is 0.836, and the external validation coefficient Qext(2) is 0.811, indicating that the model has high robustness and good predictive performance. The most significant descriptor explaining logkO3 is the BELm2 descriptor with connectivity information weighted atomic masses. kO3 increases with increasing BELm2, and decreases with increasing ionization potential. The applicability domain of the proposed model was visualized by the Williams plot. The developed model can be used to predict kO3 at different temperatures for a wide range of organic chemicals, including alkenes, cycloalkenes, haloalkenes, alkynes, oxygen-containing compounds, nitrogen-containing compounds (except primary amines) and aromatic compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2009-03-01

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

Synthesis, Structural Studies and Biological Evaluation of Connections of Thiosemicarbazide, 1,2,4-Triazole and 1,3,4-Thiadiazole with Palmitic Acid.

PubMed

Jóźwiak, Michał; Stępień, Karolina; Wrzosek, Małgorzata; Olejarz, Wioletta; Kubiak-Tomaszewska, Grażyna; Filipowska, Anna; Filipowski, Wojciech; Struga, Marta

2018-04-03

Thirty new derivatives of palmitic acid were efficiently synthesized. All obtained compounds can be divided into three groups of derivatives: Thiosemicarbazides (compounds 1 - 10 ), 1,2,4-triazoles (compounds 1a - 10a ) and 1,3,4-thiadiazoles (compounds 1b - 10b ) moieties. ¹H-NMR, 13 C-NMR and MS methods were used to confirm the structure of derivatives. All obtained compounds were tested in vitro against a number of microorganisms, including Gram-positive cocci, Gram-negative rods and Candida albicans . Compounds 4 , 5 , 6 , 8 showed significant inhibition against C. albicans . The range of MIC values was 50-1.56 μg/mL. The halogen atom, especially at the 3rd position of the phenyl group was significantly important for antifungal activity. The biological activity against Candida albicans and selected molecular descriptors were used as a basis for QSAR models, that have been determined by means of multiple linear regression. The models have been validated by means of the Leave-One-Out Cross Validation. The obtained QSAR models were characterized by high determination coefficients and good prediction power.

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.

Microwave-assisted chemical pre-treatment of waste sorghum leaves: Process optimization and development of an intelligent model for determination of volatile compound fractions.

PubMed

Rorke, Daneal C S; Suinyuy, Terence N; Gueguim Kana, E B

2017-01-01

This study reports the profiling of volatile compounds generated during microwave-assisted chemical pre-treatment of sorghum leaves. Compounds including acetic acid (0-186.26ng/g SL), furfural (0-240.80ng/g SL), 5-hydroxymethylfurfural (HMF) (0-19.20ng/g SL) and phenol (0-7.76ng/g SL) were detected. The reducing sugar production was optimized. An intelligent model based on Artificial Neural Networks (ANNs) was developed and validated to predict a profile of 21 volatile compounds under novel pre-treatment conditions. This model gave R 2 -values of up to 0.93. Knowledge extraction revealed furfural and phenol exhibited high sensitivity to acid- and alkali concentration and S:L ratio, while phenol showed high sensitivity to microwave duration and intensity. Furthermore, furfural production was majorly dependent on acid concentration and fit a dosage-response relationship model with a 2.5% HCl threshold. Significant non-linearities were observed between pre-treatment conditions and the profile of various compounds. This tool reduces analytical costs through virtual analytical instrumentation, improving process economics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mathematical modeling of atmospheric fine particle-associated primary organic compound concentrations

NASA Astrophysics Data System (ADS)

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

1996-08-01

An atmospheric transport model has been used to explore the relationship between source emissions and ambient air quality for individual particle phase organic compounds present in primary aerosol source emissions. An inventory of fine particulate organic compound emissions was assembled for the Los Angeles area in the year 1982. Sources characterized included noncatalyst- and catalyst-equipped autos, diesel trucks, paved road dust, tire wear, brake lining dust, meat cooking operations, industrial oil-fired boilers, roofing tar pots, natural gas combustion in residential homes, cigarette smoke, fireplaces burning oak and pine wood, and plant leaf abrasion products. These primary fine particle source emissions were supplied to a computer-based model that simulates atmospheric transport, dispersion, and dry deposition based on the time series of hourly wind observations and mixing depths. Monthly average fine particle organic compound concentrations that would prevail if the primary organic aerosol were transported without chemical reaction were computed for more than 100 organic compounds within an 80 km × 80 km modeling area centered over Los Angeles. The monthly average compound concentrations predicted by the transport model were compared to atmospheric measurements made at monitoring sites within the study area during 1982. The predicted seasonal variation and absolute values of the concentrations of the more stable compounds are found to be in reasonable agreement with the ambient observations. While model predictions for the higher molecular weight polycyclic aromatic hydrocarbons (PAH) are in agreement with ambient observations, lower molecular weight PAH show much higher predicted than measured atmospheric concentrations in the particle phase, indicating atmospheric decay by chemical reactions or evaporation from the particle phase. The atmospheric concentrations of dicarboxylic acids and aromatic polycarboxylic acids greatly exceed the contributions that are due to direct emissions from primary sources, confirming that these compounds are principally formed by atmospheric chemical reactions.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities

NASA Astrophysics Data System (ADS)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

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.

Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease.

PubMed

Iqbal, Saleem; Anantha Krishnan, Dhanabalan; Gunasekaran, Krishnasamy

2017-12-13

Protein kinases are ubiquitously expressed as Serine/Threonine kinases, and play a crucial role in cellular activities. Protein kinases have evolved through stringent regulation mechanisms. Protein kinases are also involved in tauopathy, thus are important targets for developing Anti-Alzheimer's disease compounds. Structures with an indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors for human protein kinase C, here we report the generation of four point 3D geometric featured pharmacophore model. In order to identify novel and potent PKCθ inhibitors, the pharmacophore model was screened against 80,000,00 compounds from various chemical databases such as., ZINC, SPEC, ASINEX, which resulted in 127 compound hits, and were taken for molecular docking filters (HTVS, XP docking). After in-depth analysis of binding patterns, induced fit docking (flexible) was employed for six compounds along with the cocrystallized inhibitor. Molecular docking study reveals that compound 6F found to be tight binder at the active site of PKCθ as compared to the cocrystal and has occupancy of 90 percentile. MM-GBSA also confirmed the potency of the compound 6F as better than cocrystal. Molecular dynamics results suggest that compound 6F showed good binding stability of active sites residues similar to cocrystal 7G compound. Present study corroborates the pharmacophore-based virtual screening, and finds the compound 6F as a potent Inhibitor of PKC, having therapeutic potential for Alzheimer's disease. Worldwide, 46.8 million people are believed to be living with Alzheimer's disease. When elderly population increases rapidly and neurodegenerative burden also increases in parallel, we project the findings from this study will be useful for drug developing efforts targeting Alzheimer's disease.

Modeling prescribed burning experiments and assessing the fire impacts on local to regional air quality

NASA Astrophysics Data System (ADS)

Zhou, L.; Baker, K. R.; Napelenok, S. L.; Elleman, R. A.; Urbanski, S. P.

2016-12-01

Biomass burning, including wildfires and prescribed burns, strongly impact the global carbon cycle and are of increasing concern due to the potential impacts on ambient air quality. This modelling study focuses on the evolution of carbonaceous compounds during a prescribed burning experiment and assesses the impacts of burning on local to regional air quality. The Community Multiscale Air Quality (CMAQ) model is used to conduct 4 and 2 km grid resolution simulations of prescribed burning experiments in southeast Washington state and western Idaho state in summer 2013. The ground and airborne measurements from the field experiment are used to evaluate the model performance in capturing surface and aloft impacts from the burning events. Phase partitioning of organic compounds in the plume are studied as it is a crucial step towards understanding the fate of carbonaceous compounds. The sensitivities of ambient concentrations and deposition to emissions are conducted for organic carbon, elemental carbon and ozone to estimate the impacts of fire on air quality.

Artificial neural networks and the study of the psychoactivity of cannabinoid compounds.

PubMed

Honório, Káthia M; de Lima, Emmanuela F; Quiles, Marcos G; Romero, Roseli A F; Molfetta, Fábio A; da Silva, Albérico B F

2010-06-01

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher's weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

An uncertainty and sensitivity analysis applied to the prioritisation of pharmaceuticals as surface water contaminants from wastewater treatment plant direct emissions.

PubMed

Morais, Sérgio Alberto; Delerue-Matos, Cristina; Gabarrell, Xavier

2014-08-15

In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results. Copyright © 2014. Published by Elsevier B.V.

Caenorhabditis elegans as Model System in Pharmacology and Toxicology: Effects of Flavonoids on Redox-Sensitive Signalling Pathways and Ageing

PubMed Central

Koch, Karoline; Havermann, Susannah; Büchter, Christian

2014-01-01

Flavonoids are secondary plant compounds that mediate diverse biological activities, for example, by scavenging free radicals and modulating intracellular signalling pathways. It has been shown in various studies that distinct flavonoid compounds enhance stress resistance and even prolong the life span of organisms. In the last years the model organism C. elegans has gained increasing importance in pharmacological and toxicological sciences due to the availability of various genetically modified nematode strains, the simplicity of modulating genes by RNAi, and the relatively short life span. Several studies have been performed demonstrating that secondary plant compounds influence ageing, stress resistance, and distinct signalling pathways in the nematode. Here we present an overview of the modulating effects of different flavonoids on oxidative stress, redox-sensitive signalling pathways, and life span in C. elegans introducing the usability of this model system for pharmacological and toxicological research. PMID:24895670

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.

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.

Chemometric studies on potential larvicidal compounds against Aedes aegypti.

PubMed

Scotti, Luciana; Scotti, Marcus Tullius; Silva, Viviane Barros; Santos, Sandra Regina Lima; Cavalcanti, Sócrates C H; Mendonça, Francisco J B

2014-03-01

The mosquito Aedes aegypti (Diptera, Culicidae) is the vector of yellow and dengue fever. In this study, chemometric tools, such as, Principal Component Analysis (PCA), Consensus PCA (CPCA), and Partial Least Squares Regression (PLS), were applied to a set of fifty five active compounds against Ae. aegypti larvae, which includes terpenes, cyclic alcohols, phenolic compounds, and their synthetic derivatives. The calculations were performed using the VolSurf+ program. CPCA analysis suggests that the higher weight blocks of descriptors were SIZE/SHAPE, DRY, and H2O. The PCA was generated with 48 descriptors selected from the previous blocks. The scores plot showed good separation between more and less potent compounds. The first two PCs accounted for over 60% of the data variance. The best model obtained in PLS, after validation leave-one-out, exhibited q(2) = 0.679 and r(2) = 0.714. External prediction model was R(2) = 0.623. The independent variables having a hydrophobic profile were strongly correlated to the biological data. The interaction maps generated with the GRID force field showed that the most active compounds exhibit more interaction with the DRY probe.

Optimization of a Small Tropomyosin-related Kinase B (TrkB) Agonist 7,8-Dihydroxyflavone Active in Mouse Models of Depression

PubMed Central

Liu, Xia; Chan, Chi-Bun; Qi, Qi; Xiao, Ge; Luo, Hongbo R.; He, Xiaolin; Ye, Keqiang

2012-01-01

Structure-activity relationship study shows that the catechol group in 7,8-dihdyroxyflavone, a selective small TrkB receptor agonist, is critical for the agonistic activity. To improve the poor pharmacokinetic profiles intrinsic to catechol-containing molecules and elevate the agonistic effect of the lead compound, we initiated the lead optimization campaign by synthesizing various bioisosteric derivatives. Here we show that the optimized 2-methyl-8-(4′-(pyrrolidin-1-yl)phenyl)chromeno[7,8-d]imidazol-6(1H)-one derivative possesses the enhanced TrkB stimulatory activity. Chronic oral administration of this compound significantly reduces the immobility in forced swim test and tail suspension test, two classical antidepressant behavioral animal models, which is accompanied by robust TrkB activation in hippocampus of mouse brain. Further, in vitro ADMET studies demonstrate that this compound possesses the improved features compared to the previous lead compound. Hence, this optimized compound may act as a promising lead candidate for in-depth drug development for treating various neurological disorders including depression. PMID:22984948

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.

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.

A PHARMACOKINETIC MODEL FOR ESTIMATING ...

EPA Pesticide Factsheets

Empirical evidence suggests that exposure of Americans to dioxin-like compounds was low during the early decades of the 20th century, then increased during the 1940s and 1950s reaching a peak in the 1960s and 1970s, and progressively decreased to lower levels in the 1980s and 1990s. Such evidence includes dioxin analysis of carbon-dated sediment cores of lakes and rivers, preserved meat samples from different decades of the 20th century, and limited body burden measurements of dioxin-like compounds. Pinsky and Lorber (1998) summarized studies measuring 2,3,7,8-TCDD in blood and adipose tissue finding a range of 10-20 pg/g (ppt) lipid during the 1970s, and 2-10 ppt lipid during the 1980s. This study reviews body burdens of dioxin toxic equivalents, TEQs, to find a range from about 50-80 ppt lipid during the 1970s, 30-50 ppt lipid during the 1980s, and 10-20 ppt lipid during the 1990s (TEQs comprised of the 17 dioxin and furan congeners only). Pinsky and Lorber (1998) investigated historical exposure trends for 2,3,7,8-TCDD by using a single-compartment, first-order pharmacokinetic model. The current study extends this prior effort by modeling dioxin TEQs instead of the single compound, 2,3,7,8-TCDD. TEQs are modeled as though they are a single compound, in contrast to an approach where the individual dioxin and furan congeners are modeled separately. It was found that body burdens of TEQs during the 1970s, 80s, and 90s could be modeled by assuming a histor

Emissions and fate of brominated flame retardants in the indoor environment: a critical review of modelling approaches.

PubMed

Liagkouridis, Ioannis; Cousins, Ian T; Cousins, Anna Palm

2014-09-01

This review explores the existing understanding and the available approaches to estimating the emissions and fate of semi-volatile organic compounds (SVOCs) and in particular focuses on the brominated flame retardants (BFRs). Volatilisation, an important emission mechanism for the more volatile compounds can be well described using current emission models. More research is needed, however, to better characterise alternative release mechanisms such as direct material-particle partitioning and material abrasion. These two particle-mediated emissions are likely to result in an increased chemical release from the source than can be accounted for by volatilisation, especially for low volatile compounds, and emission models need to be updated in order to account for these. Air-surface partitioning is an important fate process for SVOCs such as BFRs however it is still not well characterised indoors. In addition, the assumption of an instantaneous air-particle equilibrium adopted by current indoor fate models might not be valid for high-molecular weight, strongly sorbing compounds. A better description of indoor particle dynamics is required to assess the effect of particle-associated transport as this will control the fate of low volatile BFRs. We suggest further research steps that will improve modelling precision and increase our understanding of the factors that govern the indoor fate of a wide range of SVOCs. It is also considered that the appropriateness of the selected model for a given study relies on the individual characteristics of the study environment and scope of the study. Copyright © 2014 Elsevier B.V. All rights reserved.

Toxico-Cheminformatics and QSPR Modeling of the Carcinogenic Potency Database

EPA Science Inventory

Report on the development of a tiered, confirmatory scheme for prediction of chemical carcinogenicity based on QSAR studies of compounds with available mutagenic and carcinogenic data. For 693 such compounds from the Carcinogenic Potency Database characterized molecular topologic...

Effects of membrane composition on release of model hydrophilic compound from osmotic delivery systems.

PubMed

Ozdemir, N; Ozalp, Y; Ozkan, Y

2000-01-01

In this study, the effects of surface-active agents in different types and concentrations, added into the coating solution, on release of model hydrophilic compound have been examined. For this purpose, the tablets, prepared with the use of methylene blue as a model substance, were coated by spray coating technique with cellulose acetate solution containing polyethylene glycol 400 as a plasticizer. In addition, cetylpyridinium chloride as cationic surface-active agent and sodium lauryl sulphate as anionic surface-active agent were added into coating solution in different concentrations. After creating a delivery orifice by a microdrill on the tablets, release of model hydrophilic compound was tested by the USP paddle method. The data obtained were evaluated according to the different kinetics and the mechanism of release from the preparations was examined. The surface properties of the coating material were investigated by scanning electron microscope taken before and after the contact with medium fluid, as well as the mechanical properties by tensile tests. In conclusion, it has been found that the cationic surface active agent, cetylpyridinium chloride reduced the lag time, observed during the release of model hydrophilic compound, as a result of its enhancing effect on wettability of tablets by reducing the contact angle between the medium fluid and the coating material. On the other hand, the anionic surface active agent, sodium lauryl sulphate has been inactivated possibly due to the interaction with model hydrophilic compound that has cationic properties and/or substances contained in membrane composition; thus, the lag time has not decreased and furthermore, a significant decrease in the delivery rate of model hydrophilic compound has been observed.

Synthesis and pharmacological evaluation of polyfunctional benzimidazole-NSAID chimeric molecules combining anti-inflammatory, immunomodulatory and antioxidant activities.

PubMed

Bansal, Yogita; Silakari, Om

2014-11-01

Polyfunctional compounds comprise a novel class of therapeutic agents for treatment of multifactorial diseases. The present study reports a series of benzimidazole-non-steroidal anti-inflammatory drugs (NSAIDs) conjugates (1-10) as novel polyfunctional compounds synthesized in the presence of orthophosphoric acid. The compounds were evaluated for anti-inflammatory (carageenan-induced paw edema model), immunomodulatory (direct haemagglutination test and carbon clearance index models), antioxidant (in vitro and in vivo) and for ulcerogenic effects. Each of the compound has retained the anti-inflammatory activity of the corresponding parent NSAID while exhibiting significantly reduced gastric ulcers. Additionally, the compounds are found to possess potent immunostimulatory and antioxidant activities. The compound 8 was maximally potent (antibody titre value 358.4 ± 140.21, carbon clearance index 0.053 ± 0.002 and antioxidant EC50 value 0.03 ± 0.006). These compounds, exhibiting such multiple pharmacological activities, can be taken as lead for the development of potent drugs for the treatment of chronic multifactorial diseases involving inflammation, immune system modulation and oxidative stress such as cancers. The Lipinski's parameters suggested the compounds to be bear drug like properties.

Computational investigation of the selectivity of salen and tetrahydrosalen compounds towards the tumor-associated hCA XII isozyme.

PubMed

Akdemir, Atilla; De Monte, Celeste; Carradori, Simone; Supuran, Claudiu T

2015-02-01

In previous work, 14 salen and tetrahydrosalen compounds have been synthesized and tested in enzyme inhibition assays against cytosolic human carbonic anhydrase isozymes I and II (hCA I and II) and tumor-associated isozymes IX and XII (hCA IX and XII). These compounds show selectivity against hCA XII over hCA I, II and IX. In this study, molecular modeling and docking studies were applied to understand this preference of the compounds for hCA XII. Most likely, the compounds can displace the zinc-bound water molecule of hCA XII to form a direct interaction with the Zn(2+) ion. In the other isozymes, the compounds might not be able to displace the water molecule nor are they expected to interact with the Zn(2+) ion.

A modification of the Hammett equation for predicting ionisation constants of p-vinyl phenols.

PubMed

Sipilä, Julius; Nurmi, Harri; Kaukonen, Ann Marie; Hirvonen, Jouni; Taskinen, Jyrki; Yli-Kauhaluoma, Jari

2005-01-01

Currently there are several compounds used as drugs or studied as new chemical entities, which have an electron withdrawing group connected to a vinylic double bond in a phenolic or catecholic core structure. These compounds share a common feature--current computational methods utilizing the Hammett type equation for the prediction of ionisation constants fail to give accurate prediction of pK(a)'s for compounds containing the vinylic moiety. The hypothesis was that the effect of electron-withdrawing substituents on the pK(a) of p-vinyl phenols is due to the delocalized electronic structure of these compounds. Thus, this effect should be additive for multiple substituents attached to the vinylic double bond and quantifiable by LFER-based methods. The aim of this study was to produce an improved equation with a reduced tendency to underestimate the effect of the double bond on the ionisation of the phenolic hydroxyl. To this end a set of 19 para-substituted vinyl phenols was used. The ionisation constants were measured potentiometrically, and a training set of 10 compounds was selected to build a regression model (r2 = 0.987 and S.E. = 0.09). The average error with an external test set of six compounds was 0.19 for our model and 1.27 for the ACD-labs 7.0. Thus, we have been able to significantly improve the existing model for prediction of the ionisation constants of substituted p-vinyl phenols.

Correlation between octanol/water and liposome/water distribution coefficients and drug absorption of a set of pharmacologically active compounds.

PubMed

Esteves, Freddy; Moutinho, Carla; Matos, Carla

2013-06-01

Absorption and consequent therapeutic action are key issues in the development of new drugs by the pharmaceutical industry. In this sense, different models can be used to simulate biological membranes to predict the absorption of a drug. This work compared the octanol/water and the liposome/water models. The parameters used to relate the two models were the distribution coefficients between liposomes and water and octanol and water and the fraction of drug orally absorbed. For this study, 66 drugs were collected from literature sources and divided into four groups according to charge and ionization degree: neutral; positively charged; negatively charged; and partially ionized/zwitterionic. The results show a satisfactory linear correlation between the octanol and liposome systems for the neutral (R²= 0.9324) and partially ionized compounds (R²= 0.9367), contrary to the positive (R²= 0.4684) and negatively charged compounds (R²= 0.1487). In the case of neutral drugs, results were similar in both models because of the high fraction orally absorbed. However, for the charged drugs (positively, negatively, and partially ionized/zwitterionic), the liposomal model has a more-appropriate correlation with absorption than the octanol model. These results show that the neutral compounds only interact with membranes through hydrophobic bonds, whereas charged drugs favor electrostatic interactions established with the liposomes. With this work, we concluded that liposomes may be a more-appropriate biomembrane model than octanol for charged compounds.

Investigation of biological effects of some Mannich Bases containing Bis-1,2,4- Triazole.

PubMed

Parlak, A E; Celik, S; Karatepe, M; Turkoglu, S; Alayunt, N O; Dastan, S D; Ulas, M; Sandal, S; Tekin, S; Koparir, M

2016-06-30

In this study, the effects of Mannich bases containing bis-1,2,4-triazole on the levels of in vivo malondialdehyde (MDA) and antioxidant vitamins (A, E, C) were examined in serum, livers and kidneys of rats. DA and vitamin (A, E, C) levels were determined by high performance liquid chromatography (HPLC). Antioxidant effect was investigated by determining the MDA levels in Saccharomyces cerevisiae cells as in vitro. Furthermore, the antitumor effects of compounds were investigated against MCF-7 human breast cancer cells. Interrelations of results among control and compound groups were evaluated using SPSS statistical software package. As a result, some of the compounds showed effective biological activity when compared to control conditions. The test compounds used in this study may be effective for utilization in the selection and design of model compounds for further studies.

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

PubMed

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

2012-01-01

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

A generic biokinetic model for carbon-14 labelled compounds

NASA Astrophysics Data System (ADS)

Manger, Ryan Paul

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

Design, synthesis and molecular modeling studies of novel thiazolidine-2,4-dione derivatives as potential anti-cancer agents

NASA Astrophysics Data System (ADS)

Asati, Vivek; Bharti, Sanjay Kumar

2018-02-01

A series of novel thiazolidine-2,4-dione derivatives 4a-x have been designed, synthesized and evaluated for potential anti-cancer activity. The anti-cancer activity of synthesized compounds 4a-x were evaluated against selected human cancer cell line of breast (MCF-7) using sulforhodamine B (SRB) method. Among the synthesized compounds, 4x having 2-cyano phenyl group showed significant cytotoxic activity which is comparable to that of adriamycin as standard anti-cancer drug. The SAR study revealed that the substituted phenyl group on oxadiazole ring attached to thiazolidine-2,4-dione moiety showed significant growth inhibitory activity against MCF-7 cell line. The result of molecular modeling studies showed that compounds 4f, 4o and 4x having similar structural alignment as crystal ligand of protein.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

PubMed

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

2014-05-01

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

A compound memristive synapse model for statistical learning through STDP in spiking neural networks

PubMed Central

Bill, Johannes; Legenstein, Robert

2014-01-01

Memristors have recently emerged as promising circuit elements to mimic the function of biological synapses in neuromorphic computing. The fabrication of reliable nanoscale memristive synapses, that feature continuous conductance changes based on the timing of pre- and postsynaptic spikes, has however turned out to be challenging. In this article, we propose an alternative approach, the compound memristive synapse, that circumvents this problem by the use of memristors with binary memristive states. A compound memristive synapse employs multiple bistable memristors in parallel to jointly form one synapse, thereby providing a spectrum of synaptic efficacies. We investigate the computational implications of synaptic plasticity in the compound synapse by integrating the recently observed phenomenon of stochastic filament formation into an abstract model of stochastic switching. Using this abstract model, we first show how standard pulsing schemes give rise to spike-timing dependent plasticity (STDP) with a stabilizing weight dependence in compound synapses. In a next step, we study unsupervised learning with compound synapses in networks of spiking neurons organized in a winner-take-all architecture. Our theoretical analysis reveals that compound-synapse STDP implements generalized Expectation-Maximization in the spiking network. Specifically, the emergent synapse configuration represents the most salient features of the input distribution in a Mixture-of-Gaussians generative model. Furthermore, the network's spike response to spiking input streams approximates a well-defined Bayesian posterior distribution. We show in computer simulations how such networks learn to represent high-dimensional distributions over images of handwritten digits with high fidelity even in presence of substantial device variations and under severe noise conditions. Therefore, the compound memristive synapse may provide a synaptic design principle for future neuromorphic architectures. PMID:25565943

Role of physicochemical properties in the activation of peroxisome proliferator-activated receptor δ.

PubMed

Maltarollo, Vinícius G; Homem-de-Mello, Paula; Honorio, Káthia M

2011-10-01

Current researches on treatments for metabolic diseases involve a class of biological receptors called peroxisome proliferator-activated receptors (PPARs), which control the metabolism of carbohydrates and lipids. A subclass of these receptors, PPARδ, regulates several metabolic processes, and the substances that activate them are being studied as new drug candidates for the treatment of diabetes mellitus and metabolic syndrome. In this study, several PPARδ agonists with experimental biological activity were selected for a structural and chemical study. Electronic, stereochemical, lipophilic and topological descriptors were calculated for the selected compounds using various theoretical methods, such as density functional theory (DFT). Fisher's weight and principal components analysis (PCA) methods were employed to select the most relevant variables for this study. The partial least squares (PLS) method was used to construct the multivariate statistical model, and the best model obtained had 4 PCs, q ( 2 ) = 0.80 and r ( 2 ) = 0.90, indicating a good internal consistency. The prediction residues calculated for the compounds in the test set had low values, indicating the good predictive capability of our PLS model. The model obtained in this study is reliable and can be used to predict the biological activity of new untested compounds. Docking studies have also confirmed the importance of the molecular descriptors selected for this system.

Investigating the reactivity of pMDI with wood cell walls using high-resolution solution-state NMR spectroscopy

Treesearch

Daniel J. Yelle; John Ralph; Charles R. Frihart

2009-01-01

The objectives of this study are the following: (1) Use solution-state NMR to assign contours in HSQC spectra of the reaction products between pMDI model compounds and: (a) lignin model compounds, (b) milled-wood lignin, (c) ball-milled wood, (d) microtomed loblolly pine; (2) Determine where and to what degree urethane formation occurs with loblolly pine cell wall...

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

Development of a convenient ex vivo model for the study of the transcorneal permeation of drugs: histological and permeability evaluation.

PubMed

Pescina, Silvia; Govoni, Paolo; Potenza, Arianna; Padula, Cristina; Santi, Patrizia; Nicoli, Sara

2015-01-01

In this paper, an ex vivo model for the study of the transcorneal permeation of drugs, based on porcine tissues, was evaluated. The setup is characterized by ease of realization, absence of O₂ and CO₂ bubbling and low cost; additionally, the large availability of porcine tissue permits a high throughput. Histological images showed the comparability between porcine and human corneas and confirmed the effectiveness of the isolation procedure. A new de-epithelization procedure based on a thermal approach was also set up to simulate cornea permeability in pathological conditions. The procedure did not affect the integrity of the underlying layers and allowed the characterization of the barrier properties of epithelium and stroma. Six compounds with different physicochemical properties were tested: fluorescein, atenolol, propranolol, diclofenac, ganciclovir and lidocaine. The model highlighted the barrier function played by epithelium toward the diffusion of hydrophilic compounds and the permselectivity with regard to more lipophilic molecules. In particular, positively charged compounds showed a significantly higher transcorneal permeability than negatively charged compounds. The comparability of results with literature data supports the goodness and the robustness of the model, especially taking into account the behavior of fluorescein, which is generally considered a marker of tissue integrity. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

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

Development of Matrix Metalloproteinase-2 Inhibitors for Cardioprotection

PubMed Central

Bencsik, Péter; Kupai, Krisztina; Görbe, Anikó; Kenyeres, Éva; Varga, Zoltán V.; Pálóczi, János; Gáspár, Renáta; Kovács, László; Weber, Lutz; Takács, Ferenc; Hajdú, István; Fabó, Gabriella; Cseh, Sándor; Barna, László; Csont, Tamás; Csonka, Csaba; Dormán, György; Ferdinandy, Péter

2018-01-01

The objective of our present study is to develop novel inhibitors for MMP-2 for acute cardioprotection. In a series of pilot studies, novel substituted carboxylic acid derivatives were synthesized based on imidazole and thiazole scaffolds and then tested in a screeening cascade for MMP inhibition. We found that the MMP-inhibiting effects of imidazole and thiazole carboxylic acid-based compounds are superior in efficacy in comparison to the conventional hydroxamic acid derivatives of the same molecules. Based on these results, a 568-membered focused library of imidazole and thiazole compounds was generated in silico and then the library members were docked to the 3D model of MMP-2 followed by an in vitro medium throughput screening (MTS) based on a fluorescent assay employing MMP-2 catalytic domain. Altogether 45 compounds showed a docking score of >70, from which 30 compounds were successfully synthesized. Based on the MMP-2 inhibitory tests using gelatin zymography, 7 compounds were then selected and tested in neonatal rat cardiac myocytes subjected to simulated I/R injury. Six compounds showed significant cardio-cytoprotecion and the most effective compound (MMPI-1154) significantly decreased infarct size when applied at 1 μM in an ex vivo model for acute myocardial infarction. This is the first demonstration that imidazole and thiazole carboxylic acid-based compounds are more efficacious MMP-2 inhibitor than their hydroxamic acid derivatives. MMPI-1154 is a promising novel cardio-cytoprotective imidazole-carboxylic acid MMP-2 inhibitor lead candidate for the treatment of acute myocardial infarction. PMID:29674965

Evaluation of the intestinal permeability of rosemary (Rosmarinus officinalis L.) extract polyphenols and terpenoids in Caco-2 cell monolayers.

PubMed

Pérez-Sánchez, Almudena; Borrás-Linares, Isabel; Barrajón-Catalán, Enrique; Arráez-Román, David; González-Álvarez, Isabel; Ibáñez, Elena; Segura-Carretero, Antonio; Bermejo, Marival; Micol, Vicente

2017-01-01

Rosemary (Rosmarinus officinalis) is grown throughout the world and is widely used as a medicinal herb and to season and preserve food. Rosemary polyphenols and terpenoids have attracted great interest due to their potential health benefits. However, complete information regarding their absorption and bioavailability in Caco-2 cell model is scarce. The permeation properties of the bioactive compounds (flavonoids, diterpenes, triterpenes and phenylpropanoids) of a rosemary extract (RE), obtained by supercritical fluid extraction, was studied in Caco-2 cell monolayer model, both in a free form or liposomed. Compounds were identified and quantitated by liquid chromatography coupled to quadrupole time-of-flight with electrospray ionization mass spectrometry analysis (HPLC-ESI-QTOF-MS), and the apparent permeability values (Papp) were determined, for the first time in the extract, for 24 compounds in both directions across cell monolayer. For some compounds, such as triterpenoids and some flavonoids, Papp values found were reported for the first time in Caco-2 cells.Our results indicate that most compounds are scarcely absorbed, and passive diffusion is suggested to be the primary mechanism of absorption. The use of liposomes to vehiculize the extract resulted in reduced permeability for most compounds. Finally, the biopharmaceutical classification (BCS) of all the compounds was achieved according to their permeability and solubility data for bioequivalence purposes. BCS study reveal that most of the RE compounds could be classified as classes III and IV (low permeability); therefore, RE itself should also be classified into this category.

MICROBIAL VOLATILE ORGANIC COMPOUND EMISSION RATES AND EXPOSURE MODEL

EPA Science Inventory

This paper presents the results from a study that examined microbial volatile organic compound (MVOC) emissions from six fungi and one bacterial species (Streptomyces spp.) commonly found in indoor environments. Data are presented on peak emission rates from inoculated agar plate...

Bioactive Molecule from Streptomyces sp. Mitigates MDR Klebsiella pneumoniae in Zebrafish Infection Model

PubMed Central

Cheepurupalli, Lalitha; Raman, Thiagarajan; Rathore, Sudarshan S.; Ramakrishnan, Jayapradha

2017-01-01

The emergence and spread of multi-drug resistant (MDR) especially carbapenem-resistant Klebsiella pneumoniae is a major emerging threat to public health, leading to excess in mortality rate as high as 50–86%. MDR K. pneumoniae manifests all broad mechanisms of drug resistance, hence development of new drugs to treat MDR K. pneumoniae infection has become a more relevant question in the scientific community. In the present study a potential Streptomyces sp. ASK2 was isolated from rhizosphere soil of medicinal plant. The multistep HPLC purification identified the active principle exhibiting antagonistic activity against MDR K. pneumoniae. The purified compound was found to be an aromatic compound with aliphatic side chain molecule having a molecular weight of 444.43 Da. FT-IR showed the presence of OH and C=O as functional groups. The bioactive compound was further evaluated for drug induced toxicity and efficacy in adult zebrafish infection model. As this is the first study on K. pneumoniae – zebrafish model, the infectious doses to manifest sub-clinical and clinical infection were optimized. Furthermore, the virulence of K. pneumoniae in planktonic and biofilm state was studied in zebrafish. The MTT assay of ex vivo culture of zebrafish liver reveals non-toxic nature of the proposed ASK2 compound at an effective dose. Moreover, significant increase in survival rate of infected zebrafish suggests that ASK2 compound from a new strain of Streptomyces sp. was potent in mitigating MDR K. pneumoniae infection. PMID:28446900

Antimycobacterial drug discovery using Mycobacteria-infected amoebae identifies anti-infectives and new molecular targets.

PubMed

Trofimov, Valentin; Kicka, Sébastien; Mucaria, Sabrina; Hanna, Nabil; Ramon-Olayo, Fernando; Del Peral, Laura Vela-Gonzalez; Lelièvre, Joël; Ballell, Lluís; Scapozza, Leonardo; Besra, Gurdyal S; Cox, Jonathan A G; Soldati, Thierry

2018-03-02

Tuberculosis remains a serious threat to human health world-wide, and improved efficiency of medical treatment requires a better understanding of the pathogenesis and the discovery of new drugs. In the present study, we performed a whole-cell based screen in order to complete the characterization of 168 compounds from the GlaxoSmithKline TB-set. We have established and utilized novel previously unexplored host-model systems to characterize the GSK compounds, i.e. the amoeboid organisms D. discoideum and A. castellanii, as well as a microglial phagocytic cell line, BV2. We infected these host cells with Mycobacterium marinum to monitor and characterize the anti-infective activity of the compounds with quantitative fluorescence measurements and high-content microscopy. In summary, 88.1% of the compounds were confirmed as antibiotics against M. marinum, 11.3% and 4.8% displayed strong anti-infective activity in, respectively, the mammalian and protozoan infection models. Additionally, in the two systems, 13-14% of the compounds displayed pro-infective activity. Our studies underline the relevance of using evolutionarily distant pathogen and host models in order to reveal conserved mechanisms of virulence and defence, respectively, which are potential "universal" targets for intervention. Subsequent mechanism of action studies based on generation of over-expresser M. bovis BCG strains, generation of spontaneous resistant mutants and whole genome sequencing revealed four new molecular targets, including FbpA, MurC, MmpL3 and GlpK.

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.

Formulation Studies of InhA inhibitors and Combination therapy to improve efficacy against Mycobacterium tuberculosis

PubMed Central

Knudson, Susan E.; Cummings, Jason E.; Bommineni, Gopal R.; Pan, Pan; Tonge, Peter J.; Slayden, Richard A.

2016-01-01

Summary Previously, structure-based drug design was used to develop substituted diphenyl ethers with potency against the Mycobacterium tuberculosis (Mtb) enoyl-ACP reductase (InhA), however, the highly lipophilic centroid compound, SB-PT004, lacked sufficient efficacy in the acute murine Mtb infection model. A next generation series of compounds were designed with improved specificity, potency against InhA, and reduced cytotoxicity in vitro, but these compounds also had limited solubility. Accordingly, solubility and pharmacokinetics studies were performed to develop formulations for this class and other experimental drug candidates with high logP values often encountered in drug discovery. Lead diphenyl ethers were formulated in co-solvent and Self-Dispersing Lipid Formulations (SDLFs) and evaluated in a rapid murine Mtb infection model that assesses dissemination to and bacterial burden in the spleen. In vitro synergy studies were performed with the lead diphenyl ether compounds, SB-PT070 and SB-PT091, and rifampin (RIF), which demonstrated an additive effect, and that guided the in vivo studies. Combinatorial therapy in vivo studies with these compounds delivered in our Self-Micro Emulsifying Drug Delivery System (SMEDDS) resulted in an additional 1.4 log10 CFU reduction in the spleen of animals co-treated with SB-PT091 and RIF and an additional 1.7 log10 reduction in the spleen with animals treated with both SB-PT070 and RIF. PMID:27865404

Mechanistic Insights into the Specificity of Human Cytosolic Sulfotransferase 2A1 (hSULT2A1) for Hydroxylated Polychlorinated Biphenyls Through the Use of Fluoro-tagged Probes

PubMed Central

Ekuase, E.J.; van ’t Erve, T.J.; Rahaman, A.; Robertson, L.W.; Duffel, M.W.; Luthe, G.

2015-01-01

Determining the relationships between the structures of substrates and inhibitors and their interactions with drug-metabolizing enzymes is of prime importance in predicting the toxic potential of new and legacy xenobiotics. Traditionally, quantitative structure activity relationship (QSAR) studies are performed with many distinct compounds. Based on the chemical properties of the tested compounds, complex relationships can be established so that models can be developed to predict toxicity of novel compounds. In this study, the use of fluorinated analogues as supplemental QSAR compounds was investigated. Substituting fluorine induces changes in electronic and steric properties of the substrate without substantially changing the chemical backbone of the substrate. In vitro assays were performed using purified human cytosolic sulfotransferase hSULT2A1 as a model enzyme. A mono-hydroxylated polychlorinated biphenyl (4-OH PCB 14) and its four possible mono-fluoro analogues were used as test compounds. Remarkable similarities were found between this approach and previously published QSAR studies for hSULT2A1. Both studies implicate the importance of dipole moment and dihedral angle as being important to PCB structure in respect to being substrates for hSULT2A1. We conclude that mono-fluorinated analogues of a target substrate can be a useful tool to study the structure activity relationships for enzyme specificity. PMID:26165989

Multi-Phase Equilibrium and Solubilities of Aromatic Compounds and Inorganic Compounds in Sub- and Supercritical Water: A Review.

PubMed

Liu, Qinli; Ding, Xin; Du, Bowen; Fang, Tao

2017-11-02

Supercritical water oxidation (SCWO), as a novel and efficient technology, has been applied to wastewater treatment processes. The use of phase equilibrium data to optimize process parameters can offer a theoretical guidance for designing SCWO processes and reducing the equipment and operating costs. In this work, high-pressure phase equilibrium data for aromatic compounds+water systems and inorganic compounds+water systems are given. Moreover, thermodynamic models, equations of state (EOS) and empirical and semi-empirical approaches are summarized and evaluated. This paper also lists the existing problems of multi-phase equilibria and solubility studies on aromatic compounds and inorganic compounds in sub- and supercritical water.

Insight into the structural requirements of proton pump inhibitors based on CoMFA and CoMSIA studies.

PubMed

Nayana, M Ravi Shashi; Sekhar, Y Nataraja; Nandyala, Haritha; Muttineni, Ravikumar; Bairy, Santosh Kumar; Singh, Kriti; Mahmood, S K

2008-10-01

In the present study, a series of 179 quinoline and quinazoline heterocyclic analogues exhibiting inhibitory activity against Gastric (H+/K+)-ATPase were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q(2) of 0.777, 0.744 and conventional cross-validation coefficient, r(2) of 0.927, 0.914 respectively. The predictive ability of generated models was tested on a set of 52 compounds having broad range of activity. CoMFA and CoMSIA yielded predicted activities for test set compounds with r(pred)(2) of 0.893 and 0.917 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r(pred)(2) based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel peptic-ulcer inhibitors prior to their synthesis.

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

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

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

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

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

Perfluoroalkyl phosphonic and phosphinic acids as proton conductors for anhydrous proton-exchange membranes.

PubMed

Herath, Mahesha B; Creager, Stephen E; Kitaygorodskiy, Alex; DesMarteau, Darryl D

2010-09-10

A study of proton-transport rates and mechanisms under anhydrous conditions using a series of acid model compounds, analogous to comb-branch perfluorinated ionomers functionalized with phosphonic, phosphinic, sulfonic, and carboxylic acid protogenic groups, is reported. Model compounds are characterized with respect to proton conductivity, viscosity, proton, and anion (conjugate base) self-diffusion coefficients, and Hammett acidity. The highest conductivities, and also the highest viscosities, are observed for the phosphonic and phosphinic acid model compounds. Arrhenius analysis of conductivity and viscosity for these two acids reveals much lower activation energies for ion transport than for viscous flow. Additionally, the proton self-diffusion coefficients are much higher than the conjugate-base self-diffusion coefficients for these two acids. Taken together, these data suggest that anhydrous proton transport in the phosphonic and phosphinic acid model compounds occurs primarily by a structure-diffusion, hopping-based mechanism rather than a vehicle mechanism. Further analysis of ionic conductivity and ion self-diffusion rates by using the Nernst-Einstein equation reveals that the phosphonic and phosphinic acid model compounds are relatively highly dissociated even under anhydrous conditions. In contrast, sulfonic and carboxylic acid-based systems exhibit relatively low degrees of dissociation under anhydrous conditions. These findings suggest that fluoroalkyl phosphonic and phosphinic acids are good candidates for further development as anhydrous, high-temperature proton conductors.

Prediction of octanol-water partition coefficients of organic compounds by multiple linear regression, partial least squares, and artificial neural network.

PubMed

Golmohammadi, Hassan

2009-11-30

A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol-water partition coefficients (log P(o/w)). A genetic algorithm was applied as a variable selection tool. Modeling of log P(o/w) of these compounds as a function of theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS), and artificial neural network (ANN). The best selected descriptors that appear in the models are: atomic charge weighted partial positively charged surface area (PPSA-3), fractional atomic charge weighted partial positive surface area (FPSA-3), minimum atomic partial charge (Qmin), molecular volume (MV), total dipole moment of molecule (mu), maximum antibonding contribution of a molecule orbital in the molecule (MAC), and maximum free valency of a C atom in the molecule (MFV). The result obtained showed the ability of developed artificial neural network to prediction of partition coefficients of organic compounds. Also, the results revealed the superiority of ANN over the MLR and PLS models. Copyright 2009 Wiley Periodicals, Inc.

Lead optimization of antimalarial propafenone analogues.

PubMed

Lowes, David; Pradhan, Anupam; Iyer, Lalitha V; Parman, Toufan; Gow, Jason; Zhu, Fangyi; Furimsky, Anna; Lemoff, Andrew; Guiguemde, W Armand; Sigal, Martina; Clark, Julie A; Wilson, Emily; Tang, Liang; Connelly, Michele C; Derisi, Joseph L; Kyle, Dennis E; Mirsalis, Jon; Guy, R Kiplin

2012-07-12

Previously reported studies identified analogues of propafenone that had potent antimalarial activity, reduced cardiac ion channel activity, and properties that suggested the potential for clinical development for malaria. Careful examination of the bioavailability, pharmacokinetics, toxicology, and efficacy of this series of compounds using rodent models revealed orally bioavailable compounds that are nontoxic and suppress parasitemia in vivo. Although these compounds possess potential for further preclinical development, they also carry some significant challenges.

Consensus QSAR model for identifying novel H5N1 inhibitors.

PubMed

Sharma, Nitin; Yap, Chun Wei

2012-08-01

Due to the importance of neuraminidase in the pathogenesis of influenza virus infection, it has been regarded as the most important drug target for the treatment of influenza. Resistance to currently available drugs and new findings related to structure of the protein requires novel neuraminidase 1 (N1) inhibitors. In this study, a consensus QSAR model with defined applicability domain (AD) was developed using published N1 inhibitors. The consensus model was validated using an external validation set. The model achieved high sensitivity, specificity, and overall accuracy along with low false positive rate (FPR) and false discovery rate (FDR). The performance of model on the external validation set and training set were comparable, thus it was unlikely to be overfitted. The low FPR and low FDR will increase its accuracy in screening large chemical libraries. Screening of ZINC library resulted in 64,772 compounds as probable N1 inhibitors, while 173,674 compounds were defined to be outside the AD of the consensus model. The advantage of the current model is that it was developed using a large and diverse dataset and has a defined AD which prevents its use on compounds that it is not capable of predicting. The consensus model developed in this study is made available via the free software, PaDEL-DDPredictor.

Numerical and Experimental Study on the Residual Stresses in the Nitrided Steel

NASA Astrophysics Data System (ADS)

Song, X.; Zhang, Zhi-Qian; Narayanaswamy, S.; Huang, Y. Z.; Zarinejad, M.

2016-09-01

In the present work, residual stresses distribution in the gas nitrided AISI 4140 sample has been studied using finite element (FE) simulation. The nitrogen concentration profile is obtained from the diffusion-controlled compound layer growth model, and nitrogen concentration controls the material volume change through phase transformation and lattice interstitials which results in residual stresses. Such model is validated through residual stress measurement technique—micro-ring-core method, which is applied to the nitriding process to obtain the residual stresses profiles in both the compound and diffusion layer. The numerical and experimental results are in good agreement with each other; they both indicate significant stress variation in the compound layer, which was not captured in previous research works due to the resolution limit of the traditional methods.

Characterization of chemical ingredients and anticonvulsant activity of American skullcap (Scutellaria lateriflora).

PubMed

Zhang, Zhizhen; Lian, Xiao-yuan; Li, Shiyou; Stringer, Janet L

2009-05-01

American skullcap (the aerial part of Scutellaria lateriflora L.) has been traditionally used by Native Americans and Europeans as a nerve tonic, sedative, and anticonvulsant. However, despite some previous studies, the quality and safety, the bioactive ingredients, and the pharmacological properties of American skullcap are not fully understood. The aims of this study were to characterize the chemical ingredients of American skullcap and to evaluate its anticonvulsant activity. Twelve phenolic compounds including 10 flavonoids and two phenylethanoid glycosides were isolated and identified from American skullcap and used as marker compounds. An HPLC analytic method for analyzing these marker compounds in commercial American skullcap products from different sources was established and validated. The anticonvulsant activity of American skullcap was determined in rat models of acute seizures induced by pilocarpine and pentylenetetrazol. The results from this study indicate that (1) phenolic compounds, especially flavonoids, are the predominant constituents in American skullcap; (2) American skullcap products have similar constituents, but the content and relative proportions of the individual constituents varies widely; and (3) American skullcap has anticonvulsant activity in rodent models of acute seizures.

Predicting total organic halide formation from drinking water chlorination using quantitative structure-property relationships.

PubMed

Luilo, G B; Cabaniss, S E

2011-10-01

Chlorinating water which contains dissolved organic matter (DOM) produces disinfection byproducts, the majority of unknown structure. Hence, the total organic halide (TOX) measurement is used as a surrogate for toxic disinfection byproducts. This work derives a robust quantitative structure-property relationship (QSPR) for predicting the TOX formation potential of model compounds. Literature data for 49 compounds were used to train the QSPR in moles of chlorine per mole of compound (Cp) (mol-Cl/mol-Cp). The resulting QSPR has four descriptors, calibration [Formula: see text] of 0.72 and standard deviation of estimation of 0.43 mol-Cl/mol-Cp. Internal and external validation indicate that the QSPR has good predictive power and low bias (‰<‰1%). Applying this QSPR to predict TOX formation by DOM surrogates - tannic acid, two model fulvic acids and two agent-based model assemblages - gave a predicted TOX range of 136-184 µg-Cl/mg-C, consistent with experimental data for DOM, which ranged from 78 to 192 µg-Cl/mg-C. However, the limited structural variation in the training data may limit QSPR applicability; studies of more sulfur-containing compounds, heterocyclic compounds and high molecular weight compounds could lead to a more widely applicable QSPR.

[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.

Solid-phase cadmium speciation in soil using L3-edge XANES spectroscopy with partial least-squares regression.

PubMed

Siebers, Nina; Kruse, Jens; Eckhardt, Kai-Uwe; Hu, Yongfeng; Leinweber, Peter

2012-07-01

Cadmium (Cd) has a high toxicity and resolving its speciation in soil is challenging but essential for estimating the environmental risk. In this study partial least-square (PLS) regression was tested for its capability to deconvolute Cd L(3)-edge X-ray absorption near-edge structure (XANES) spectra of multi-compound mixtures. For this, a library of Cd reference compound spectra and a spectrum of a soil sample were acquired. A good coefficient of determination (R(2)) of Cd compounds in mixtures was obtained for the PLS model using binary and ternary mixtures of various Cd reference compounds proving the validity of this approach. In order to describe complex systems like soil, multi-compound mixtures of a variety of Cd compounds must be included in the PLS model. The obtained PLS regression model was then applied to a highly Cd-contaminated soil revealing Cd(3)(PO(4))(2) (36.1%), Cd(NO(3))(2)·4H(2)O (24.5%), Cd(OH)(2) (21.7%), CdCO(3) (17.1%) and CdCl(2) (0.4%). These preliminary results proved that PLS regression is a promising approach for a direct determination of Cd speciation in the solid phase of a soil sample.

Insights from depth-averaged numerical simulation of flow at bridge abutments in compound channels.

DOT National Transportation Integrated Search

2011-07-01

Two-dimensional, depth-averaged flow models are used to study the distribution of flow around spill-through abutments situated on floodplains in compound channels and rectangular channels (flow on very wide floodplains may be treated as rectangular c...

Triaryl Benzimidazoles as a New Class of Antibacterial Agents against Resistant Pathogenic Microorganisms.

PubMed

Picconi, Pietro; Hind, Charlotte; Jamshidi, Shirin; Nahar, Kazi; Clifford, Melanie; Wand, Matthew E; Sutton, J Mark; Rahman, Khondaker Miraz

2017-07-27

A new class of nontoxic triaryl benzimidazole compounds, derived from existing classes of DNA minor groove binders, were designed, synthesized, and evaluated for their antibacterial activity against multidrug resistant (MDR) Gram-positive and Gram-negative species. Molecular modeling experiments suggest that the newly synthesized class cannot be accommodated within the minor groove of DNA due to a change in the shape of the molecules. Compounds 8, 13, and 14 were found to be the most active of the series, with MICs in the range of 0.5-4 μg/mL against the MDR Staphylococci and Enterococci species. Compound 13 showed moderate activity against the MDR Gram-negative strains, with MICs in the range of 16-32 μg/mL. Active compounds showed a bactericidal mode of action, and a mechanistic study suggested the inhibition of bacterial gyrase as the mechanism of action (MOA) of this chemical class. The MOA was further supported by the molecular modeling study.

Identification of novel peroxisome proliferator-activated receptor-gamma (PPARγ) agonists using molecular modeling method

NASA Astrophysics Data System (ADS)

Gee, Veronica M. W.; Wong, Fiona S. L.; Ramachandran, Lalitha; Sethi, Gautam; Kumar, Alan Prem; Yap, Chun Wei

2014-11-01

Peroxisome proliferator-activated receptor-gamma (PPARγ) plays a critical role in lipid and glucose homeostasis. It is the target of many drug discovery studies, because of its role in various disease states including diabetes and cancer. Thiazolidinediones, a synthetic class of agents that work by activation of PPARγ, have been used extensively as insulin-sensitizers for the management of type 2 diabetes. In this study, a combination of QSAR and docking methods were utilised to perform virtual screening of more than 25 million compounds in the ZINC library. The QSAR model was developed using 1,517 compounds and it identified 42,378 potential PPARγ agonists from the ZINC library, and 10,000 of these were selected for docking with PPARγ based on their diversity. Several steps were used to refine the docking results, and finally 30 potentially highly active ligands were identified. Four compounds were subsequently tested for their in vitro activity, and one compound was found to have a K i values of <5 μM.

Kinetic and Isotherm Modelling of the Adsorption of
Phenolic Compounds from Olive Mill Wastewater onto Activated Carbon

PubMed Central

Casazza, Alessandro A.; Perego, Patrizia

2015-01-01

Summary The adsorption of phenolic compounds from olive oil wastewater by commercial activated carbon was studied as a function of adsorbent quantity and temperature. The sorption kinetics and the equilibrium isotherms were evaluated. Under optimum conditions (8 g of activated carbon per 100 mL), the maximum sorption capacity of activated carbon expressed as mg of caffeic acid equivalent per g of activated carbon was 35.8 at 10 °C, 35.4 at 25 °C and 36.1 at 40 °C. The pseudo-second-order model was considered as the most suitable for kinetic results, and Langmuir isotherm was chosen to better describe the sorption system. The results confirmed the efficiency of activated carbon to remove almost all phenolic compound fractions from olive mill effluent. The preliminary results obtained will be used in future studies. The carbohydrate fraction of this upgraded residue could be employed to produce bioethanol, and adsorbed phenolic compounds can be recovered and used in different industries. PMID:27904350

Modelling the contribution of biogenic volatile organic compounds to new particle formation in the Jülich plant atmosphere chamber

NASA Astrophysics Data System (ADS)

Roldin, P.; Liao, L.; Mogensen, D.; Dal Maso, M.; Rusanen, A.; Kerminen, V.-M.; Mentel, T. F.; Wildt, J.; Kleist, E.; Kiendler-Scharr, A.; Tillmann, R.; Ehn, M.; Kulmala, M.; Boy, M.

2015-09-01

We used the Aerosol Dynamics gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM) to simulate the contribution of BVOC plant emissions to the observed new particle formation during photooxidation experiments performed in the Jülich Plant-Atmosphere Chamber and to evaluate how well smog chamber experiments can mimic the atmospheric conditions during new particle formation events. ADCHAM couples the detailed gas-phase chemistry from Master Chemical Mechanism with a novel aerosol dynamics and particle phase chemistry module. Our model simulations reveal that the observed particle growth may have either been controlled by the formation rate of semi- and low-volatility organic compounds in the gas phase or by acid catalysed heterogeneous reactions between semi-volatility organic compounds in the particle surface layer (e.g. peroxyhemiacetal dimer formation). The contribution of extremely low-volatility organic gas-phase compounds to the particle formation and growth was suppressed because of their rapid and irreversible wall losses, which decreased their contribution to the nano-CN formation and growth compared to the atmospheric situation. The best agreement between the modelled and measured total particle number concentration (R2 > 0.95) was achieved if the nano-CN was formed by kinetic nucleation involving both sulphuric acid and organic compounds formed from OH oxidation of BVOCs.

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

PubMed

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

2015-09-01

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

From Omics to Drug Metabolism and High Content Screen of Natural Product in Zebrafish: A New Model for Discovery of Neuroactive Compound

PubMed Central

Hung, Ming Wai; Zhang, Zai Jun; Li, Shang; Lei, Benson; Yuan, Shuai; Cui, Guo Zhen; Man Hoi, Pui; Chan, Kelvin; Lee, Simon Ming Yuen

2012-01-01

The zebrafish (Danio rerio) has recently become a common model in the fields of genetics, environmental science, toxicology, and especially drug screening. Zebrafish has emerged as a biomedically relevant model for in vivo high content drug screening and the simultaneous determination of multiple efficacy parameters, including behaviour, selectivity, and toxicity in the content of the whole organism. A zebrafish behavioural assay has been demonstrated as a novel, rapid, and high-throughput approach to the discovery of neuroactive, psychoactive, and memory-modulating compounds. Recent studies found a functional similarity of drug metabolism systems in zebrafish and mammals, providing a clue with why some compounds are active in zebrafish in vivo but not in vitro, as well as providing grounds for the rationales supporting the use of a zebrafish screen to identify prodrugs. Here, we discuss the advantages of the zebrafish model for evaluating drug metabolism and the mode of pharmacological action with the emerging omics approaches. Why this model is suitable for identifying lead compounds from natural products for therapy of disorders with multifactorial etiopathogenesis and imbalance of angiogenesis, such as Parkinson's disease, epilepsy, cardiotoxicity, cerebral hemorrhage, dyslipidemia, and hyperlipidemia, is addressed. PMID:22919414

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.

Temperature responses of individual soil organic matter components

NASA Astrophysics Data System (ADS)

Feng, Xiaojuan; Simpson, Myrna J.

2008-09-01

Temperature responses of soil organic matter (SOM) remain unclear partly due to its chemical and compositional heterogeneity. In this study, the decomposition of SOM from two grassland soils was investigated in a 1-year laboratory incubation at six different temperatures. SOM was separated into solvent extractable compounds, suberin- and cutin-derived compounds, and lignin-derived monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components have distinct chemical structures and stabilities and their decomposition patterns over the course of the experiment were fitted with a two-pool exponential decay model. The stability of SOM components was also assessed using geochemical parameters and kinetic parameters derived from model fitting. Compared with the solvent extractable compounds, a low percentage of lignin monomers partitioned into the labile SOM pool. Suberin- and cutin-derived compounds were poorly fitted by the decay model, and their recalcitrance was shown by the geochemical degradation parameter (ω - C16/∑C16), which was observed to stabilize during the incubation. The temperature sensitivity of decomposition, expressed as Q10, was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of lignin monomers exhibited higher Q10 values than the decomposition of solvent extractable compounds. Our study shows that Q10 values derived from soil respiration measurements may not be reliable indicators of temperature responses of individual SOM components.

Medicinal Plants from Mexico, Central America, and the Caribbean Used as Immunostimulants

PubMed Central

Juárez-Vázquez, María del Carmen; Campos-Xolalpa, Nimsi

2016-01-01

A literature review was undertaken by analyzing distinguished books, undergraduate and postgraduate theses, and peer-reviewed scientific articles and by consulting worldwide accepted scientific databases, such as SCOPUS, Web of Science, SCIELO, Medline, and Google Scholar. Medicinal plants used as immunostimulants were classified into two categories: (1) plants with pharmacological studies and (2) plants without pharmacological research. Medicinal plants with pharmacological studies of their immunostimulatory properties were subclassified into four groups as follows: (a) plant extracts evaluated for in vitro effects, (b) plant extracts with documented in vivo effects, (c) active compounds tested on in vitro studies, and (d) active compounds assayed in animal models. Pharmacological studies have been conducted on 29 of the plants, including extracts and compounds, whereas 75 plants lack pharmacological studies regarding their immunostimulatory activity. Medicinal plants were experimentally studied in vitro (19 plants) and in vivo (8 plants). A total of 12 compounds isolated from medicinal plants used as immunostimulants have been tested using in vitro (11 compounds) and in vivo (2 compounds) assays. This review clearly indicates the need to perform scientific studies with medicinal flora from Mexico, Central America, and the Caribbean, to obtain new immunostimulatory agents. PMID:27042188

Medicinal Plants from Mexico, Central America, and the Caribbean Used as Immunostimulants.

PubMed

Alonso-Castro, Angel Josabad; Juárez-Vázquez, María Del Carmen; Campos-Xolalpa, Nimsi

2016-01-01

A literature review was undertaken by analyzing distinguished books, undergraduate and postgraduate theses, and peer-reviewed scientific articles and by consulting worldwide accepted scientific databases, such as SCOPUS, Web of Science, SCIELO, Medline, and Google Scholar. Medicinal plants used as immunostimulants were classified into two categories: (1) plants with pharmacological studies and (2) plants without pharmacological research. Medicinal plants with pharmacological studies of their immunostimulatory properties were subclassified into four groups as follows: (a) plant extracts evaluated for in vitro effects, (b) plant extracts with documented in vivo effects, (c) active compounds tested on in vitro studies, and (d) active compounds assayed in animal models. Pharmacological studies have been conducted on 29 of the plants, including extracts and compounds, whereas 75 plants lack pharmacological studies regarding their immunostimulatory activity. Medicinal plants were experimentally studied in vitro (19 plants) and in vivo (8 plants). A total of 12 compounds isolated from medicinal plants used as immunostimulants have been tested using in vitro (11 compounds) and in vivo (2 compounds) assays. This review clearly indicates the need to perform scientific studies with medicinal flora from Mexico, Central America, and the Caribbean, to obtain new immunostimulatory agents.

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.

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

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.

Azomethines, isoxazole, N-substituted pyrazoles and pyrimidine containing curcumin derivatives: Urease inhibition and molecular modeling studies.

PubMed

Ahmed, Mahmood; Qadir, Muhammad Abdul; Hameed, Abdul; Arshad, Muhammad Nadeem; Asiri, Abdullah M; Muddassar, Muhammad

2017-08-19

Curcumin has shown large number of pharmacological properties against different phenotypes of various disease models. Different synthetic routes have been employed to develop its various derivatives for diverse biological functions. In this study, curcumin derived azomethine, isoxazole, pyrimidines and N-substituted pyrazoles were synthesized to investigate their urease enzyme inhibition. The structures of newly synthesized compounds were described by IR, MS, 1 H NMR and 13 C NMR spectral data. Urease enzyme inhibition was evaluated through in vitro assays in which compound 8b was found to be the most potent (IC 50  = 2.44 ± 0.07 μM) among the tested compounds. The compounds with diazine ring system except the 4d showed better urease inhibition (IC 50  = 11.43 ± 0.21-19.63 ± 0.28 μM) than the standard urease inhibitor thiourea (IC 50  = 22.61 ± 0.23 μM). Similarly enzyme kinetics data revealed that compounds 3c-3e and 8b were competitive inhibitors with Ki values of 20.0, 19.87, 20.23 and 19.11 μM respectively while the compounds 4b, 4c and 4e were mixed type of inhibitors with Ki values 6.72, 19.69 and 6.72 μM respectively. Molecular docking studies were also performed to identify the plausible binding modes of the most active compounds. Copyright © 2017 Elsevier Inc. All rights reserved.

NMR analysis and chemical shift calculations of poly(lactic acid) dimer model compounds with different tacticities

USDA-ARS?s Scientific Manuscript database

In this work, PLA dimer model compounds with different tacticities were synthesized and studied in detail by 1H and 13C NMR in three solvents, CDCl3/CCl4 (20/80 v/v), CDCl3 and DMSO-d6. All the peaks in the 1H and 13C NMR spectra were assigned with the help of two-dimensional NMR. Although the solve...

Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus ab Initio Methods.

PubMed

Legrain, Fleur; Carrete, Jesús; van Roekeghem, Ambroise; Madsen, Georg K H; Mingo, Natalio

2018-01-18

Machine learning (ML) is increasingly becoming a helpful tool in the search for novel functional compounds. Here we use classification via random forests to predict the stability of half-Heusler (HH) compounds, using only experimentally reported compounds as a training set. Cross-validation yields an excellent agreement between the fraction of compounds classified as stable and the actual fraction of truly stable compounds in the ICSD. The ML model is then employed to screen 71 178 different 1:1:1 compositions, yielding 481 likely stable candidates. The predicted stability of HH compounds from three previous high-throughput ab initio studies is critically analyzed from the perspective of the alternative ML approach. The incomplete consistency among the three separate ab initio studies and between them and the ML predictions suggests that additional factors beyond those considered by ab initio phase stability calculations might be determinant to the stability of the compounds. Such factors can include configurational entropies and quasiharmonic contributions.

Thermodynamic behavior of glassy state of structurally related compounds.

PubMed

Kaushal, Aditya Mohan; Bansal, Arvind Kumar

2008-08-01

Thermodynamic properties of amorphous pharmaceutical forms are responsible for enhanced solubility as well as poor physical stability. The present study was designed to investigate the differences in thermodynamic parameters arising out of disparate molecular structures and associations for four structurally related pharmaceutical compounds--celecoxib, valdecoxib, rofecoxib, and etoricoxib. Conventional and modulated temperature differential scanning calorimetry were employed to study glass forming ability and thermodynamic behavior of the glassy state of model compounds. Glass transition temperature of four glassy compounds was in a close range of 327.6-331.8 K, however, other thermodynamic parameters varied considerably. Kauzmann temperature, strength parameter and fragility parameter showed rofecoxib glass to be most fragile of the four compounds. Glass forming ability of the compounds fared similar in the critical cooling rate experiments, suggesting that different factors were determining the glass forming ability and subsequent behavior of the compounds in glassy state. A comprehensive understanding of such thermodynamic facets of amorphous form would help in rationalizing the approaches towards development of stable glassy pharmaceuticals.

Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model

PubMed Central

Coley, Rebecca Yates; Browna, Elizabeth R.

2016-01-01

Inconsistent results in recent HIV prevention trials of pre-exposure prophylactic interventions may be due to heterogeneity in risk among study participants. Intervention effectiveness is most commonly estimated with the Cox model, which compares event times between populations. When heterogeneity is present, this population-level measure underestimates intervention effectiveness for individuals who are at risk. We propose a likelihood-based Bayesian hierarchical model that estimates the individual-level effectiveness of candidate interventions by accounting for heterogeneity in risk with a compound Poisson-distributed frailty term. This model reflects the mechanisms of HIV risk and allows that some participants are not exposed to HIV and, therefore, have no risk of seroconversion during the study. We assess model performance via simulation and apply the model to data from an HIV prevention trial. PMID:26869051

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.

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.

The bleomycin animal model: a useful tool to investigate treatment options for idiopathic pulmonary fibrosis?

PubMed Central

Moeller, Antje; Ask, Kjetil; Warburton, David; Gauldie, Jack; Kolb, Martin

2008-01-01

Different animal models of pulmonary fibrosis have been developed to investigate potential therapies for idiopathic pulmonary fibrosis (IPF). The most common is the bleomycin model in rodents (mouse, rat and hamster). Over the years, numerous agents have been shown to inhibit fibrosis in this model. However, to date none of these compounds are used in the clinical management of IPF and none has shown a comparable antifibrotic effect in humans. We performed a systematic review of publications on drug efficacy studies in the bleomycin model to evaluate the value of this model regarding transferability to clinical use. Between 1980 and 2006 we identified 246 experimental studies describing beneficial antifibrotic compounds in the bleomycin model. In 221 of the studies we found enough details about the timing of drug application to allow inter-study comparison. 211 of those used a preventive regimen (drug given ≤ day 7 after last bleomycin application), only 10 were therapeutic trials (> 7 days after last bleomycin application). It is critical to distinguish between drugs interfering with the inflammatory and early fibrogenic response from those preventing progression of fibrosis, the latter likely much more meaningful for clinical application. All potential antifibrotic compounds should be evaluated in the phase of established fibrosis rather than in the early period of bleomycin-induced inflammation for assessment of its antifibrotic properties. Further care should be taken in extrapolation of drugs successfully tested in the bleomycin model due to partial reversibility of bleomycin induced fibrosis over time. The use of alternative and more robust animal models, which better reflect human IPF, is warranted. PMID:17936056

Screening plant derived dietary phenolic compounds for bioactivity related to cardiovascular disease.

PubMed

Croft, Kevin D; Yamashita, Yoko; O'Donoghue, Helen; Shirasaya, Daishi; Ward, Natalie C; Ashida, Hitoshi

2018-04-01

The potential health benefits of phenolic acids found in food and beverages has been suggested from a number of large population studies. However, the mechanism of how these compounds may exert biological effects is less well established. It is also now recognised that many complex polyphenols in the diet are metabolised to simple phenolic acids which can be taken up in the circulation. In this paper a number of selected phenolic compounds have been tested for their bioactivity in two cell culture models. The expression and activity of endothelial nitric oxide synthase (eNOS) in human aortic endothelial cells and the uptake of glucose in muscle cells. Our data indicate that while none of the compounds tested had a significant effect on eNOS expression or activation in endothelial cells, several of the compounds increased glucose uptake in muscle cells. These compounds also enhanced the translocation of the glucose transporter GLUT4 to the plasma membrane, which may explain the observed increase in cellular glucose uptake. These results indicate that simple cell culture models may be useful to help understand the bioactivity of phenolic compounds in relation to cardiovascular protection. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Key intermediates in nitrogen transformation during microwave pyrolysis of sewage sludge: a protein model compound study.

PubMed

Zhang, Jun; Tian, Yu; Cui, Yanni; Zuo, Wei; Tan, Tao

2013-03-01

The nitrogen transformations with attention to NH3 and HCN were investigated at temperatures of 300-800°C during microwave pyrolysis of a protein model compound. The evolution of nitrogenated compounds in the char, tar and gas products were conducted. The amine-N, heterocyclic-N and nitrile-N compounds were identified as three important intermediates during the pyrolysis. NH3 and HCN were formed with comparable activation energies competed to consume the same reactive substances at temperatures of 300-800°C. The deamination and dehydrogenation of amine-N compounds from protein cracking contributed to the formation of NH3 (about 8.9% of Soy-N) and HCN (6.6%) from 300 to 500°C. The cracking of nitrile-N and heterocyclic-N compounds from the dehydrogenation and polymerization of amine-N generated HCN (13.4%) and NH3 (31.3%) between 500 and 800°C. It might be able to reduce the HCN and NH3 emissions through controlling the intermediates production at temperatures of 500-800°C. Copyright © 2013 Elsevier Ltd. All rights reserved.

Discrete Fourier Transform-Based Multivariate Image Analysis: Application to Modeling of Aromatase Inhibitory Activity.

PubMed

Barigye, Stephen J; Freitas, Matheus P; Ausina, Priscila; Zancan, Patricia; Sola-Penna, Mauro; Castillo-Garit, Juan A

2018-02-12

We recently generalized the formerly alignment-dependent multivariate image analysis applied to quantitative structure-activity relationships (MIA-QSAR) method through the application of the discrete Fourier transform (DFT), allowing for its application to noncongruent and structurally diverse chemical compound data sets. Here we report the first practical application of this method in the screening of molecular entities of therapeutic interest, with human aromatase inhibitory activity as the case study. We developed an ensemble classification model based on the two-dimensional (2D) DFT MIA-QSAR descriptors, with which we screened the NCI Diversity Set V (1593 compounds) and obtained 34 chemical compounds with possible aromatase inhibitory activity. These compounds were docked into the aromatase active site, and the 10 most promising compounds were selected for in vitro experimental validation. Of these compounds, 7419 (nonsteroidal) and 89 201 (steroidal) demonstrated satisfactory antiproliferative and aromatase inhibitory activities. The obtained results suggest that the 2D-DFT MIA-QSAR method may be useful in ligand-based virtual screening of new molecular entities of therapeutic utility.

Benzofuran ketone dosage-dependent rayless goldenrod (Isocoma pluriflora) toxicosis in a caprine model

USDA-ARS?s Scientific Manuscript database

The objectives of this study were to determine the dosage of benzofuran ketone compounds (tremetone, 3-hydroxytremetone, dehydrotremetone, and 3-oxyangeloyltremetone) and the duration of exposure to these compounds required to produce clinical signs and the associated pathological changes of rayles ...

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

Interaction of Flavonoids from Woodwardia unigemmata with Bovine Serum Albumin (BSA): Application of Spectroscopic Techniques and Molecular Modeling Methods.

PubMed

Ma, Rui; Pan, Hong; Shen, Tao; Li, Peng; Chen, Yanan; Li, Zhenyu; Di, Xiaxia; Wang, Shuqi

2017-08-09

Phytochemical investigation on the methanol extract of Woodwardia unigemmata resulted in the isolation of seven flavonoids, including one new flavonol acylglycoside ( 1 ). The structures of these compounds were elucidated on the basis of extensive spectroscopic analysis and comparison of literature data. The multidrug resistance (MDR) reversing activity was evaluated for the isolated compounds using doxorubicin-resistant K562/A02 cells model. Compound 6 showed comparable MDR reversing effect to verapamil. Furthermore, the interaction between compounds and bovine serum albumin (BSA) was investigated by spectroscopic methods, including steady-state fluorescence, synchronous fluorescence, circular dichroism (CD) spectroscopies, and molecular docking approach. The experimental results indicated that the seven flavonoids bind to BSA by static quenching mechanisms. The negative ΔH and ΔS values indicated that van der Waals interactions and hydrogen bonds contributed in the binding of compounds 2 - 6 to BSA. In the case of compounds 1 and 7 systems, the hydrophobic interactions play a major role. The binding of compounds to BSA causes slight changes in the secondary structure of BSA. There are two binding sites of compound 6 on BSA and site I is the main site according to the molecular docking studies and the site marker competitive binding assay.

Prediction of mutagenic toxicity by combination of Recursive Partitioning and Support Vector Machines.

PubMed

Liao, Quan; Yao, Jianhua; Yuan, Shengang

2007-05-01

The study of prediction of toxicity is very important and necessary because measurement of toxicity is typically time-consuming and expensive. In this paper, Recursive Partitioning (RP) method was used to select descriptors. RP and Support Vector Machines (SVM) were used to construct structure-toxicity relationship models, RP model and SVM model, respectively. The performances of the two models are different. The prediction accuracies of the RP model are 80.2% for mutagenic compounds in MDL's toxicity database, 83.4% for compounds in CMC and 84.9% for agrochemicals in in-house database respectively. Those of SVM model are 81.4%, 87.0% and 87.3% respectively.

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

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.

Using Weighted Entropy to Rank Chemicals in Quantitative High Throughput Screening Experiments

PubMed Central

Shockley, Keith R.

2014-01-01

Quantitative high throughput screening (qHTS) experiments can simultaneously produce concentration-response profiles for thousands of chemicals. In a typical qHTS study, a large chemical library is subjected to a primary screen in order to identify candidate hits for secondary screening, validation studies or prediction modeling. Different algorithms, usually based on the Hill equation logistic model, have been used to classify compounds as active or inactive (or inconclusive). However, observed concentration-response activity relationships may not adequately fit a sigmoidal curve. Furthermore, it is unclear how to prioritize chemicals for follow-up studies given the large uncertainties that often accompany parameter estimates from nonlinear models. Weighted Shannon entropy can address these concerns by ranking compounds according to profile-specific statistics derived from estimates of the probability mass distribution of response at the tested concentration levels. This strategy can be used to rank all tested chemicals in the absence of a pre-specified model structure or the approach can complement existing activity call algorithms by ranking the returned candidate hits. The weighted entropy approach was evaluated here using data simulated from the Hill equation model. The procedure was then applied to a chemical genomics profiling data set interrogating compounds for androgen receptor agonist activity. PMID:24056003

Neurotoxicity in Preclinical Models of Occupational Exposure to Organophosphorus Compounds.

PubMed

Voorhees, Jaymie R; Rohlman, Diane S; Lein, Pamela J; Pieper, Andrew A

2016-01-01

Organophosphorus (OPs) compounds are widely used as insecticides, plasticizers, and fuel additives. These compounds potently inhibit acetylcholinesterase (AChE), the enzyme that inactivates acetylcholine at neuronal synapses, and acute exposure to high OP levels can cause cholinergic crisis in humans and animals. Evidence further suggests that repeated exposure to lower OP levels insufficient to cause cholinergic crisis, frequently encountered in the occupational setting, also pose serious risks to people. For example, multiple epidemiological studies have identified associations between occupational OP exposure and neurodegenerative disease, psychiatric illness, and sensorimotor deficits. Rigorous scientific investigation of the basic science mechanisms underlying these epidemiological findings requires valid preclinical models in which tightly-regulated exposure paradigms can be correlated with neurotoxicity. Here, we review the experimental models of occupational OP exposure currently used in the field. We found that animal studies simulating occupational OP exposures do indeed show evidence of neurotoxicity, and that utilization of these models is helping illuminate the mechanisms underlying OP-induced neurological sequelae. Still, further work is necessary to evaluate exposure levels, protection methods, and treatment strategies, which taken together could serve to modify guidelines for improving workplace conditions globally.

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.

Design, synthesis and screening studies of potent thiazol-2-amine derivatives as fibroblast growth factor receptor 1 inhibitors.

PubMed

Kumar, B V S Suneel; Lakshmi, Narasu; Kumar, M Ravi; Rambabu, Gundla; Manjashetty, Thimmappa H; Arunasree, Kalle M; Sriram, Dharmarajan; Ramkumar, Kavya; Neamati, Nouri; Dayam, Raveendra; Sarma, J A R P

2014-01-01

Fibroblast growth factor receptor 1 (FGFR1) a tyrosine kinase receptor, plays important roles in angiogenesis, embryonic development, cell proliferation, cell differentiation, and wound healing. The FGFR isoforms and their receptors (FGFRs) considered as a potential targets and under intense research to design potential anticancer agents. Fibroblast growth factors (FGF's) and its growth factor receptors (FGFR) plays vital role in one of the critical pathway in monitoring angiogenesis. In the current study, quantitative pharmacophore models were generated and validated using known FGFR1 inhibitors. The pharmacophore models were generated using a set of 28 compounds (training). The top pharmacophore model was selected and validated using a set of 126 compounds (test set) and also using external validation. The validated pharmacophore was considered as a virtual screening query to screen a database of 400,000 virtual molecules and pharmacophore model retrieved 2800 hits. The retrieved hits were subsequently filtered based on the fit value. The selected hits were subjected for docking studies to observe the binding modes of the retrieved hits and also to reduce the false positives. One of the potential hits (thiazole-2-amine derivative) was selected based the pharmacophore fit value, dock score, and synthetic feasibility. A few analogues of the thiazole-2-amine derivative were synthesized. These compounds were screened for FGFR1 activity and anti-proliferative studies. The top active compound showed 56.87% inhibition of FGFR1 activity at 50 µM and also showed good cellular activity. Further optimization of thiazole-2-amine derivatives is in progress.

Understanding Karma Police: The Perceived Plausibility of Noun Compounds as Predicted by Distributional Models of Semantic Representation

PubMed Central

Günther, Fritz; Marelli, Marco

2016-01-01

Noun compounds, consisting of two nouns (the head and the modifier) that are combined into a single concept, differ in terms of their plausibility: school bus is a more plausible compound than saddle olive. The present study investigates which factors influence the plausibility of attested and novel noun compounds. Distributional Semantic Models (DSMs) are used to obtain formal (vector) representations of word meanings, and compositional methods in DSMs are employed to obtain such representations for noun compounds. From these representations, different plausibility measures are computed. Three of those measures contribute in predicting the plausibility of noun compounds: The relatedness between the meaning of the head noun and the compound (Head Proximity), the relatedness between the meaning of modifier noun and the compound (Modifier Proximity), and the similarity between the head noun and the modifier noun (Constituent Similarity). We find non-linear interactions between Head Proximity and Modifier Proximity, as well as between Modifier Proximity and Constituent Similarity. Furthermore, Constituent Similarity interacts non-linearly with the familiarity with the compound. These results suggest that a compound is perceived as more plausible if it can be categorized as an instance of the category denoted by the head noun, if the contribution of the modifier to the compound meaning is clear but not redundant, and if the constituents are sufficiently similar in cases where this contribution is not clear. Furthermore, compounds are perceived to be more plausible if they are more familiar, but mostly for cases where the relation between the constituents is less clear. PMID:27732599

Lead Optimization of Anti-Malarial Propafenone Analogs

PubMed Central

Lowes, David; Pradhan, Anupam; Iyer, Lalitha V.; Parman, Toufan; Gow, Jason; Zhu, Fangyi; Furimsky, Anna; Lemoff, Andrew; Guiguemde, W. Armand; Sigal, Martina; Clark, Julie A.; Wilson, Emily; Tang, Liang; Connelly, Michele C.; DeRisi, Joseph L.; Kyle, Dennis E.; Mirsalis, Jon; Guy, R. Kiplin

2015-01-01

Previously reported studies identified analogs of propafenone that had potent antimalarial activity, reduced cardiac ion channel activity, and properties that suggested the potential for clinical development for malaria. Careful examination of the bioavailability, pharmacokinetics, toxicology, and efficacy of this series of compounds using rodent models revealed orally bioavailable compounds that are non-toxic and suppress parasitemia in vivo. Although these compounds possess potential for further preclinical development, they also carry some significant challenges. PMID:22708838

Design, synthesis and molecular modeling of new 4-phenylcoumarin derivatives as tubulin polymerization inhibitors targeting MCF-7 breast cancer cells.

PubMed

Batran, Rasha Z; Kassem, Asmaa F; Abbas, Eman M H; Elseginy, Samia A; Mounier, Marwa M

2018-07-23

A new set of 4-phenylcoumarin derivatives was designed and synthesized aiming to introduce new tubulin polymerization inhibitors as anti-breast cancer candidates. All the target compounds were evaluated for their cytotoxic effects against MCF-7 cell line, where compounds 2f, 3a, 3b, 3f, 7a and 7b, showed higher cytotoxic effect (IC 50  = 4.3-21.2 μg/mL) than the reference drug doxorubicin (IC 50  = 26.1 μg/mL), additionally, compounds 1 and 6b exhibited the same potency as doxorubicin (IC 50  = 25.2 and 28.0 μg/mL, respectively). The thiazolidinone derivatives 3a, 3b and 3f with potent and selective anticancer effects towards MCF-7 cells (IC 50  = 11.1, 16.7 and 21.2 μg/mL) were further assessed for tubulin polymerization inhibition effects which showed that the three compounds were potent tubulin polymerization suppressors with IC 50 values of 9.37, 2.89 and 6.13 μM, respectively, compared to the reference drug colchicine (IC 50  = 6.93 μM). The mechanistic effects on cell cycle progression and induction of apoptosis in MCF-7 cells were determined for compound 3a due to its potent and selective cytotoxic effects in addition to its promising tubulin polymerization inhibition potency. The results revealed that compound 3a induced cell cycle cessation at G2/M phase and accumulation of cells in pre-G1 phase and prevented its mitotic cycle, in addition to its activation of caspase-7 mediating apoptosis of MCF-7 cells. Molecular modeling studies for compounds 3a, 3b and 3f were carried out on tubulin crystallography, the results indicated that the compounds showed binding mode similar to the co-crystalized ligand; colchicine. Moreover, pharmacophore constructed models and docking studies revealed that thiazolidinone, acetamide and coumarin moieties are crucial for the activity. Molecular dynamics (MD) studies were carried out for the three compounds over 100 ps. MD results of compound 3a showed that it reached the stable state after 30 ps which was in agreement with the calculated potential and kinetic energy of compound 3a. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

2-(1H-pyrrolyl)carboxylic acids as pigment precursors in garlic greening.

PubMed

Wang, Dan; Nanding, Husile; Han, Na; Chen, Fang; Zhao, Guanghua

2008-02-27

Six model compounds having a 2-(1 H-pyrrolyl)carboxylic acid moiety and a hydrophobic R group were synthesized to study their effects on garlic greening, the structures of which are similar to that of 2-(3,4-dimethyl-1 H-pyrrolyl)-3-methylbutanoic acid (PP-Val) (a possible pigment precursor for garlic greening). The puree of freshly harvested garlic bulbs turned green after being soaked in solutions of all these compounds, and with both increasing concentrations and incubation time the green color of the puree became deeper. In contrast, neither pyrrole alone nor pyrrole combined with free amino acids had the ability to discolor the puree. The compounds exhibited a good relationship between structure and activity of garlic greening, namely, the smaller the size of the R group, the larger the contribution. Also, it was found that the unidentified yellow species can be produced by reacting the model compounds with pyruvic acid at room temperature (23-25 degrees C). Moreover, blue species were formed by incubation of the model compounds with di(2-propenyl) thiosulfinate at room temperature. On the basis of these observations, a pathway for garlic greening was proposed.

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.

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.

Evaluation of the intestinal permeability of rosemary (Rosmarinus officinalis L.) extract polyphenols and terpenoids in Caco-2 cell monolayers

PubMed Central

Arráez-Román, David; González-Álvarez, Isabel; Ibáñez, Elena; Segura-Carretero, Antonio; Bermejo, Marival; Micol, Vicente

2017-01-01

Rosemary (Rosmarinus officinalis) is grown throughout the world and is widely used as a medicinal herb and to season and preserve food. Rosemary polyphenols and terpenoids have attracted great interest due to their potential health benefits. However, complete information regarding their absorption and bioavailability in Caco-2 cell model is scarce. The permeation properties of the bioactive compounds (flavonoids, diterpenes, triterpenes and phenylpropanoids) of a rosemary extract (RE), obtained by supercritical fluid extraction, was studied in Caco-2 cell monolayer model, both in a free form or liposomed. Compounds were identified and quantitated by liquid chromatography coupled to quadrupole time-of-flight with electrospray ionization mass spectrometry analysis (HPLC-ESI-QTOF-MS), and the apparent permeability values (Papp) were determined, for the first time in the extract, for 24 compounds in both directions across cell monolayer. For some compounds, such as triterpenoids and some flavonoids, Papp values found were reported for the first time in Caco-2 cells.Our results indicate that most compounds are scarcely absorbed, and passive diffusion is suggested to be the primary mechanism of absorption. The use of liposomes to vehiculize the extract resulted in reduced permeability for most compounds. Finally, the biopharmaceutical classification (BCS) of all the compounds was achieved according to their permeability and solubility data for bioequivalence purposes. BCS study reveal that most of the RE compounds could be classified as classes III and IV (low permeability); therefore, RE itself should also be classified into this category. PMID:28234919

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.

Preparation, in vitro evaluation and molecular modelling of pyridinium-quinolinium/isoquinolinium non-symmetrical bisquaternary cholinesterase inhibitors.

PubMed

Komloova, Marketa; Horova, Anna; Hrabinova, Martina; Jun, Daniel; Dolezal, Martin; Vinsova, Jarmila; Kuca, Kamil; Musilek, Kamil

2013-12-15

Two series of non-symmetrical bisquaternary pyridinium-quinolinium and pyridinium-isoquinolinium compounds were prepared as molecules potentially applicable in myasthenia gravis treatment. Their inhibitory ability towards human recombinant acetylcholinesterase and human plasmatic butyrylcholinesterase was determined and the results were compared to the known effective inhibitors such as ambenonium dichloride, edrophonium bromide and experimental compound BW284C51. Two compounds, 1-(10-(pyridinium-1-yl)decyl)quinolinium dibromide and 1-(12-(pyridinium-1-yl)dodecyl)quinolinium dibromide, showed very promising affinity for acetylcholinesterase with their IC50 values reaching nM inhibition of acetylcholinesterase. These most active compounds also showed satisfactory selectivity towards acetylcholinesterase and they seem to be very promising as leading structures for further modifications and optimization. Two of the most promising compounds were examined in the molecular modelling study in order to find the possible interactions between the ligand and tested enzyme. Copyright © 2013 Elsevier Ltd. All rights reserved.

Synthesis and evaluation of new 3-phenylcoumarin derivatives as potential antidepressant agents.

PubMed

Sashidhara, Koneni V; Rao, K Bhaskara; Singh, Seema; Modukuri, Ram K; Aruna Teja, G; Chandasana, Hardik; Shukla, Shubha; Bhatta, Rabi S

2014-10-15

A series of amine substituted 3-phenyl coumarin derivatives were designed and synthesized as potential antidepressant agents. In preliminary screening, all compounds were evaluated in forced swimming test (FST), a model to screen antidepressant activity in rodents. Among the series, compounds 5c and 6a potentially decreased the immobility time by 73.4% and 79.7% at a low dose of 0.5 mg/kg as compared to standard drug fluoxetine (FXT) which reduced the immobility time by 74% at a dose of 20 mg/kg, ip. Additionally, these active compounds also exhibited significant efficacy in tail suspension test (TST) (another model to screen antidepressant compounds). Interestingly, rotarod and locomotor activity tests confirmed that these two compounds do not have any motor impairment effect and neurotoxicity in mice. Our studies demonstrate that the new 3-phenylcoumarin derivatives may serve as a promising antidepressant lead and hence pave the way for further investigation around this chemical space. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spectroscopic, structural characterizations and antioxidant capacity of the chromium (III) niacinamide compound as a diabetes mellitus drug model

NASA Astrophysics Data System (ADS)

Refat, Moamen S.; El-Megharbel, Samy M.; Hussien, M. A.; Hamza, Reham Z.; Al-Omar, Mohamed A.; Naglah, Ahmed M.; Afifi, Walid M.; Kobeasy, Mohamed I.

2017-02-01

New binuclear chromium (III) niacinamide compound with chemical formula [Cr2(Nic)(Cl)6(H2O)4]·H2O was obtained upon the reaction of chromium (III) chloride with niacinamide (Nic) in methanol solvent at 60 °C. The proposed structure was discussed with the help of microanalytical analyses, conductivity, spectroscopic (FT-IR and UV-vis.), magnetic calculations, thermogravimetric analyses (TG/TGA), and morphological studies (X-ray of solid powder and scan electron microscopy. The infrared spectrum of free niacinamide in comparison with its chromium (III) compound indicated that the chelation mode occurs via both nitrogen atoms of pyridine ring and primary -NH2 group. The efficiency of chromium (III) niacinamide compound in decreasing of glucose level of blood and HbA1c in case of diabetic rats was checked. The ameliorating gluconeogenic enzymes, lipid profile and antioxidant defense capacities are considered as an indicator of the efficiency of new chromium (III) compound as antidiabetic drug model.

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

PubMed

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

2004-01-01

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

Mixture-amount design and response surface modeling to assess the effects of flavonoids and phenolic acids on developmental performance of Anastrepha ludens.

PubMed

Pascacio-Villafán, Carlos; Lapointe, Stephen; Williams, Trevor; Sivinski, John; Niedz, Randall; Aluja, Martín

2014-03-01

Host plant resistance to insect attack and expansion of insect pests to novel hosts may to be modulated by phenolic compounds in host plants. Many studies have evaluated the role of phenolics in host plant resistance and the effect of phenolics on herbivore performance, but few studies have tested the joint effect of several compounds. Here, we used mixture-amount experimental design and response surface modeling to study the effects of a variety of phenolic compounds on the development and survival of Mexican fruit fly (Anastrepha ludens [Loew]), a notorious polyphagous pest of fruit crops that is likely to expand its distribution range under climate change scenarios. (+)- Catechin, phloridzin, rutin, chlorogenic acid, and p-coumaric acid were added individually or in mixtures at different concentrations to a laboratory diet used to rear individuals of A. ludens. No effect was observed with any mixture or concentration on percent pupation, pupal weight, adult emergence, or survival from neonate larvae to adults. Larval weight, larval and pupal developmental time, and the prevalence of adult deformities were affected by particular mixtures and concentrations of the compounds tested. We suggest that some combinations/concentrations of phenolic compounds could contribute to the management of A. ludens. We also highlight the importance of testing mixtures of plant secondary compounds when exploring their effects upon insect herbivore performance, and we show that mixture-amount design is a useful tool for this type of experiments.

Probing Complex Free-Radical Reaction Pathways of Fuel Model Compounds

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

Buchanan III, A C; Kidder, Michelle; Beste, Ariana

2012-01-01

Fossil (e.g. coal) and renewable (e.g. woody biomass) organic energy resources have received considerable attention as possible sources of liquid transportation fuels and commodity chemicals. Knowledge of the reactivity of these complex materials has been advanced through fundamental studies of organic compounds that model constituent substructures. In particular, an improved understanding of thermochemical reaction pathways involving free-radical intermediates has arisen from detailed experimental kinetic studies and, more recently, advanced computational investigations. In this presentation, we will discuss our recent investigations of the fundamental pyrolysis pathways of model compounds that represent key substructures in the lignin component of woody biomass withmore » a focus on molecules representative of the dominant beta-O-4 aryl ether linkages. Additional mechanistic insights gleaned from DFT calculations on the kinetics of key elementary reaction steps will also be presented, as well as a few thoughts on the significant contributions of Jim Franz to this area of free radical chemistry.« less

Effective adsorption of phenolic compound from aqueous solutions on activated semi coke

NASA Astrophysics Data System (ADS)

Gao, Xiaoming; Dai, Yuan; Zhang, Yu; Fu, Feng

2017-03-01

Activated Semi coke was prepared by KOH activation and employed as adsorbent to study adsorption function of phenolic compound from aqueous solutions. The adsorption result showed that the adsorption capacity of the activated semi coke for phenolic compound increased with contact time and adsorbent dosage, and slightly affected by temperature. The surface structure property of the activated semi coke was characterized by N2 adsorption, indicating that the activated semi coke was essentially macroporous, and the BET surface area was 347.39 m2 g-1. Scanning electron microscopy indicated that the surface of the activated semi coke had a high developed pore. The adsorption kinetics were investigated according to pseudofirst order, pseudosecond order and intraparticle diffusion, and the kinetics data were fitted by pseudosecond order model, and intraparticle diffusion was not the only rate-controlling step. Adsorption isotherm was studied by Langmuir, Freundlich, Temkin, Redlich-Peterson, Sips and Toth models. The result indicated that adsorption isotherm data could fit well with Langmuir, Redlich-Peterson, Sips and Toth models.

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.

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.

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.

Respiratory carcinogenicity assessment of soluble nickel compounds.

PubMed Central

Oller, Adriana R

2002-01-01

The many chemical forms of nickel differ in physicochemical properties and biological effects. Health assessments for each main category of nickel species are needed. The carcinogenicity assessment of water-soluble nickel compounds has proven particularly difficult. Epidemiologic evidence indicates an association between inhalation exposures to nickel refinery dust containing soluble nickel compounds and increased risk of respiratory cancers. However, the nature of this association is unclear because of limitations of the exposure data, inconsistent results across cohorts, and the presence of mixed exposures to water-insoluble nickel compounds and other confounders that are known or suspected carcinogens. Moreover, well-conducted animal inhalation studies, where exposures were solely to soluble nickel, failed to demonstrate a carcinogenic potential. Similar negative results were seen in animal oral studies. A model exists that relates respiratory carcinogenic potential to the bioavailability of nickel ion at nuclear sites within respiratory target cells. This model helps reconcile human, animal, and mechanistic data for soluble nickel compounds. For inhalation exposures, the predicted lack of bioavailability of nickel ion at target sites suggests that water-soluble nickel compounds, by themselves, will not be complete human carcinogens. However, if inhaled at concentrations high enough to induce chronic lung inflammation, these compounds may enhance carcinogenic risks associated with inhalation exposure to other substances. Overall, the weight of evidence indicates that inhalation exposure to soluble nickel alone will not cause cancer; moreover, if exposures are kept below levels that cause chronic respiratory toxicity, any possible tumor-enhancing effects (particularly in smokers) would be avoided. PMID:12426143

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

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.

Chemical reaction networks as a model to describe UVC- and radiolytically-induced reactions of simple compounds.

PubMed

Dondi, Daniele; Merli, Daniele; Albini, Angelo; Zeffiro, Alberto; Serpone, Nick

2012-05-01

When a chemical system is submitted to high energy sources (UV, ionizing radiation, plasma sparks, etc.), as is expected to be the case of prebiotic chemistry studies, a plethora of reactive intermediates could form. If oxygen is present in excess, carbon dioxide and water are the major products. More interesting is the case of reducing conditions where synthetic pathways are also possible. This article examines the theoretical modeling of such systems with random-generated chemical networks. Four types of random-generated chemical networks were considered that originated from a combination of two connection topologies (viz., Poisson and scale-free) with reversible and irreversible chemical reactions. The results were analyzed taking into account the number of the most abundant products required for reaching 50% of the total number of moles of compounds at equilibrium, as this may be related to an actual problem of complex mixture analysis. The model accounts for multi-component reaction systems with no a priori knowledge of reacting species and the intermediates involved if system components are sufficiently interconnected. The approach taken is relevant to an earlier study on reactions that may have occurred in prebiotic systems where only a few compounds were detected. A validation of the model was attained on the basis of results of UVC and radiolytic reactions of prebiotic mixtures of low molecular weight compounds likely present on the primeval Earth.

Design, synthesis, biological evaluation, and molecular modeling studies of chalcone-rivastigmine hybrids as cholinesterase inhibitors.

PubMed

Wang, Ling; Wang, Yu; Tian, Yiguang; Shang, Jinling; Sun, Xiaoou; Chen, Hongzhuan; Wang, Hao; Tan, Wen

2017-01-01

A series of novel chalcone-rivastigmine hybrids were designed, synthesized, and tested in vitro for their ability to inhibit human acetylcholinesterase and butyrylcholinesterase. Most of the target compounds showed hBChE selective activity in the micro- and submicromolar ranges. The most potent compound 3 exhibited comparable IC 50 to the commercially available drug (rivastigmine). To better understand their structure activity relationships (SAR) and mechanisms of enzyme-inhibitor interactions, kinetic and molecular modeling studies including molecular docking and molecular dynamics (MD) simulations were carried out. Furthermore, compound 3 blocks the formation of reactive oxygen species (ROS) in SH-SY5Y cells and shows the required druggability and low cytotoxicity, suggesting this hybrid is a promising multifunctional drug candidate for Alzheimer's disease (AD) treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

D-Galacturonic acid as a highly reactive compound in nonenzymatic browning. 1. Formation of browning active degradation products.

PubMed

Bornik, Maria-Anna; Kroh, Lothar W

2013-04-10

Thermal treatment of an aqueous solution of D-galacturonic acid at pH 3, 5, and 8 led to rapid browning of the solution and to the formation of carbocyclic compounds such as reductic acid (2,3-dihydroxy-2-cyclopenten-1-one), DHCP (4,5-dihydroxy-2-cyclopenten-1-one), and furan-2-carbaldehyde, as degradation products in weak acidic solution. Studies on their formation revealed 2-ketoglutaraldehyde as their common key intermediate. Norfuraneol (4-hydroxy-5-methyl-3-(2H)-furanone) is a typical alkaline degradation product and formed after isomerization. Further model studies revealed reductic acid as an important and more browning active compound than furan-2-carbaldehyde, which led to a red color of the model solution. This red-brown color is also characteristic of thermally treated uronic acid solutions.

Formulation studies of InhA inhibitors and combination therapy to improve efficacy against Mycobacterium tuberculosis.

PubMed

Knudson, Susan E; Cummings, Jason E; Bommineni, Gopal R; Pan, Pan; Tonge, Peter J; Slayden, Richard A

2016-12-01

Previously, structure-based drug design was used to develop substituted diphenyl ethers with potency against the Mycobacterium tuberculosis (Mtb) enoyl-ACP reductase (InhA), however, the highly lipophilic centroid compound, SB-PT004, lacked sufficient efficacy in the acute murine Mtb infection model. A next generation series of compounds were designed with improved specificity, potency against InhA, and reduced cytotoxicity in vitro, but these compounds also had limited solubility. Accordingly, solubility and pharmacokinetics studies were performed to develop formulations for this class and other experimental drug candidates with high logP values often encountered in drug discovery. Lead diphenyl ethers were formulated in co-solvent and Self-Dispersing Lipid Formulations (SDLFs) and evaluated in a rapid murine Mtb infection model that assesses dissemination to and bacterial burden in the spleen. In vitro synergy studies were performed with the lead diphenyl ether compounds, SB-PT070 and SB-PT091, and rifampin (RIF), which demonstrated an additive effect, and that guided the in vivo studies. Combinatorial therapy in vivo studies with these compounds delivered in our Self-Micro Emulsifying Drug Delivery System (SMEDDS) resulted in an additional 1.4 log 10  CFU reduction in the spleen of animals co-treated with SB-PT091 and RIF and an additional 1.7 log 10 reduction in the spleen with animals treated with both SB-PT070 and RIF. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Geographical provenance of palm oil by fatty acid and volatile compound fingerprinting techniques.

PubMed

Tres, A; Ruiz-Samblas, C; van der Veer, G; van Ruth, S M

2013-04-15

Analytical methods are required in addition to administrative controls to verify the geographical origin of vegetable oils such as palm oil in an objective manner. In this study the application of fatty acid and volatile organic compound fingerprinting in combination with chemometrics have been applied to verify the geographical origin of crude palm oil (continental scale). For this purpose 94 crude palm oil samples were collected from South East Asia (55), South America (11) and Africa (28). Partial least squares discriminant analysis (PLS-DA) was used to develop a hierarchical classification model by combining two consecutive binary PLS-DA models. First, a PLS-DA model was built to distinguish South East Asian from non-South East Asian palm oil samples. Then a second model was developed, only for the non-Asian samples, to discriminate African from South American crude palm oil. Models were externally validated by using them to predict the identity of new authentic samples. The fatty acid fingerprinting model revealed three misclassified samples. The volatile compound fingerprinting models showed an 88%, 100% and 100% accuracy for the South East Asian, African and American class, respectively. The verification of the geographical origin of crude palm oil is feasible by fatty acid and volatile compound fingerprinting. Further research is required to further validate the approach and to increase its spatial specificity to country/province scale. Copyright © 2012 Elsevier Ltd. All rights reserved.

Perspectives from ab-initio and tight-binding: Applications to transition metal compounds and superlattices

NASA Astrophysics Data System (ADS)

Venkataraman, Vijay Shankar

The experimental and theoretical study of transition metal compounds have occupied condensed matter physicists for the best part of the last century. The rich variety of physical behaviour exhibited by these compounds owes its origin to the subtle balance of the energy scales at play for the d orbitals. In this thesis, we study three different systems comprised of transition metal atoms from the third, the fourth, and the fifth group of the periodic table using a combination of ab-initio density functional theory (DFT) computations and effective tight-binding models for the electronic properties. We first consider the electronic properties of artificially fabricated perovskite superlattices of the form [(SrIrO3)m / SrTiO3] with integer m denoting the number of layers of SrIrO3. After discussing the results of experiments undertaken by our collaborators, we present the results of our DFT calculations and build tight-binding models for the m = 1 and m = 2 superlattices. The active ingredient is found to be the 5d orbitals with significant spin-orbit coupling. We then study the energies of magnetic ground states within DFT and compare and contrast our results with those obtained for the bulk Ruddlesden-Popper iridates. Together with experimental measurements, our results suggest that these superlattices are an exciting venue to probe the magnetism and metal-insulator transitions that occur from the intricate balance of the spin-orbit coupling and electron interactions, as has been reported for their bulk counterparts. Next, we consider alpha-RuCl3, a honeycomb lattice compound. We first show using DFT calculations in conjunction with experiments performed by our collaborators, how spin-orbit coupling in the 4d orbitals of Ru is essential to understand the insulating state realized in this compound. Then, in the latter half of the chapter, we study the magnetic ground states of a two-dimensional analogue of alpha-RuCl3 in weak and strong-coupling regimes obtained from a tight-binding model for the 4d orbitals. We further compare these results with energies obtained from DFT calculations. We obtain a zig-zag magnetic ground state for this compound, in all the three approaches. Within DFT, we find that correlations enhance the spin-orbit coupling in this compound and that the anisotropic Kitaev interactions between the spins are dominant in a strong-coupling model. Then, we move on to study the electronic band structures of the higher manganese silicides, which are good thermoelectric materials. Using results from DFT calculations on Mn4Si7 and structural arguments, we construct an effective tight-binding model for the first three members of this series - Mn4Si7, Mn11Si19, and Mn15Si26.

Detection and classification of gaseous sulfur compounds by solid electrolyte cyclic voltammetry of cermet sensor array.

PubMed

Kramer, Kirsten E; Rose-Pehrsson, Susan L; Hammond, Mark H; Tillett, Duane; Streckert, Holger H

2007-02-12

Electrochemical sensors composed of a ceramic-metallic (cermet) solid electrolyte are used for the detection of gaseous sulfur compounds SO(2), H(2)S, and CS(2) in a study involving 11 toxic industrial chemical (TIC) compounds. The study examines a sensor array containing four cermet sensors varying in electrode-electrolyte composition, designed to offer selectivity for multiple compounds. The sensors are driven by cyclic voltammetry to produce a current-voltage profile for each analyte. Raw voltammograms are processed by background subtraction of clean air, and the four sensor signals are concatenated to form one vector of points. The high-resolution signal is compressed by wavelet transformation and a probabilistic neural network is used for classification. In this study, training data from one sensor array was used to formulate models which were validated with data from a second sensor array. Of the 11 gases studied, 3 that contained sulfur produced the strongest responses and were successfully analyzed when the remaining compounds were treated as interferents. Analytes were measured from 10 to 200% of their threshold-limited value (TLV) according to the 8-h time weighted average (TWA) exposure limits defined by the National Institute of Occupational Safety and Health (NIOSH). True positive classification rates of 93.3, 96.7, and 76.7% for SO(2), H(2)S, and CS(2), respectively, were achieved for prediction of one sensor unit when a second sensor was used for modeling. True positive rates of 83.3, 90.0, and 90.0% for SO(2), H(2)S, and CS(2), respectively, were achieved for the second sensor unit when the first sensor unit was used for modeling. Most of the misclassifications were for low concentration levels (such 10-25% TLV) in which case the compound was classified as clean air. Between the two sensors, the false positive rates were 2.2% or lower for the three sulfur compounds, 0.9% or lower for the interferents (eight remaining analytes), and 5.8% or lower for clean air. The cermet sensor arrays used in this analysis are rugged, low cost, reusable, and show promise for multiple compound detection at parts-per-million (ppm) levels.

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

PubMed

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

2013-11-25

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

Studies on the Low-Temp Oxidation of Coal Containing Organic Sulfur and the Corresponding Model Compounds.

PubMed

Zhang, Lanjun; Li, Zenghua; Li, Jinhu; Zhou, Yinbo; Yang, Yongliang; Tang, Yibo

2015-12-11

This paper selects two typical compounds containing organic sulfur as model compounds. Then, by analyzing the chromatograms of gaseous low-temp oxidation products and GC/MS of the extractable matter of the oxidation residue, we summarizing the mechanism of low-temp sulfur model compound oxidation. The results show that between 30°C to 80°C, the interaction between diphenyl sulfide and oxygen is mainly one of physical adsorption. After 80°C, chemical adsorption and chemical reactions begin. The main reaction mechanism in the low-temp oxidation of the model compound diphenyl sulfide is diphenyl sulfide generates diphenyl sulfoxide, and then this sulfoxide is further oxidized to diphenyl sulphone. A small amount of free radicals is generated in the process. The model compound cysteine behaves differently from diphenyl sulfide. The main reaction low-temp oxidation mechanism involves the thiol being oxidized into a disulphide and finally evolving to sulfonic acid, along with SO₂ being released at 130°C and also a small amount of free radicals. We also conducted an experiment on coal from Xingcheng using X-ray photoelectron spectroscopy (XPS). The results show that the major forms of organic sulfur in the original coal sample are thiophene and sulfone. Therefore, it can be inferred that there is none or little mercaptan and thiophenol in the original coal. After low-temp oxidation, the form of organic sulfur changes. The sulfide sulfur is oxidized to the sulfoxide, and then the sulfoxide is further oxidized to a sulfone, and these steps can be easily carried out under experimental conditions. What's more, the results illustrate that oxidation promotes sulfur element enrichment on the surface of coal.

Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates

NASA Astrophysics Data System (ADS)

Crivori, Patrizia; Zamora, Ismael; Speed, Bill; Orrenius, Christian; Poggesi, Italo

2004-03-01

A number of computational approaches are being proposed for an early optimization of ADME (absorption, distribution, metabolism and excretion) properties to increase the success rate in drug discovery. The present study describes the development of an in silico model able to estimate, from the three-dimensional structure of a molecule, the stability of a compound with respect to the human cytochrome P450 (CYP) 3A4 enzyme activity. Stability data were obtained by measuring the amount of unchanged compound remaining after a standardized incubation with human cDNA-expressed CYP3A4. The computational method transforms the three-dimensional molecular interaction fields (MIFs) generated from the molecular structure into descriptors (VolSurf and Almond procedures). The descriptors were correlated to the experimental metabolic stability classes by a partial least squares discriminant procedure. The model was trained using a set of 1800 compounds from the Pharmacia collection and was validated using two test sets: the first one including 825 compounds from the Pharmacia collection and the second one consisting of 20 known drugs. This model correctly predicted 75% of the first and 85% of the second test set and showed a precision above 86% to correctly select metabolically stable compounds. The model appears a valuable tool in the design of virtual libraries to bias the selection toward more stable compounds. Abbreviations: ADME - absorption, distribution, metabolism and excretion; CYP - cytochrome P450; MIFs - molecular interaction fields; HTS - high throughput screening; DDI - drug-drug interactions; 3D - three-dimensional; PCA - principal components analysis; CPCA - consensus principal components analysis; PLS - partial least squares; PLSD - partial least squares discriminant; GRIND - grid independent descriptors; GRID - software originally created and developed by Professor Peter Goodford.

[Identification of alkylbenzenes being formed in the model reaction of ribose with lysine].

PubMed

Biller, Elzbieta

2012-01-01

While studying volatile compounds in model experiments which simulated the broiling of meat (the reactions of ribose with lysine), there were alkylbenzenes identified. They belong to food contaminants and they could be originated from the detergents and petroleum as well as geochemical samples, but they were also obtained in Maillard reactions. The aim of the studies was the attempt of the alkylbenzenes identification being formed in the model reaction of ribose with lysine. Aqueous solutions of ribose and lysine (at concentration of 0.1 mol/dm3 each) were mixed in equal volumes 10 cm3 + 10 cm3. The pH of the mixtures were adjusted to 5.6 using citrate-phosphorous buffer. In that way conditions simulating pH of meat were obtained. The mixtures were heated inside the gastronomic roaster during 0, 5, 10, 15, 30, 45 and 60 minutes respectively, at the temperature 185 +/- 5 degrees C. After reactions, in the mixtures, the profiles of volatile compounds, including alkylbenzenes, were analyzed by GC-MS method. The compounds were being identified by: comparing each mass spectrum (MS) with spectra from the known libraries of MS; calculating the linear retention indexes (LRI); seeking similar LRI values of analogue compounds in literature. Amounts of volatiles were calculated in relation to amount of internal standard (IS) [-], dividing the area of the compound by area of IS. The kinds and amounts of alkylbenzenes depended on the duration of the reaction time. Maximally 16 various alkylbenzenes were developed. More of these compounds could be identified with the probability of 85-90%, using only MS, because of the lack information in literature. Moreover, the multi-dimensional GCxGC-MS or other chromatographic methods in order to make these compounds being better explored seems to be advisable. The identification of the compounds being formed during broiling of meat is very important, because of the fact that many of arising substances are considered to be unhealthy and undesirable food contaminants. Thus these compounds should be routinely investigated in food products.

Combinatorial QSAR Modeling of Rat Acute Toxicity by Oral Exposure

EPA Science Inventory

Quantitative Structure-Activity Relationship (QSAR) toxicity models have become popular tools for identifying potential toxic compounds and prioritizing candidates for animal toxicity tests. However, few QSAR studies have successfully modeled large, diverse mammalian toxicity end...

QSAR modelling using combined simple competitive learning networks and RBF neural networks.

PubMed

Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

2018-04-01

The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

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.

Compound prioritization methods increase rates of chemical probe discovery in model organisms

PubMed Central

Wallace, Iain M; Urbanus, Malene L; Luciani, Genna M; Burns, Andrew R; Han, Mitchell KL; Wang, Hao; Arora, Kriti; Heisler, Lawrence E; Proctor, Michael; St. Onge, Robert P; Roemer, Terry; Roy, Peter J; Cummins, Carolyn L; Bader, Gary D; Nislow, Corey; Giaever, Guri

2011-01-01

SUMMARY Pre-selection of compounds that are more likely to induce a phenotype can increase the efficiency and reduce the costs for model organism screening. To identify such molecules, we screened ~81,000 compounds in S. cerevisiae and identified ~7,500 that inhibit cell growth. Screening these growth-inhibitory molecules across a diverse panel of model organisms resulted in an increased phenotypic hit-rate. This data was used to build a model to predict compounds that inhibit yeast growth. Empirical and in silico application of the model enriched the discovery of bioactive compounds in diverse model organisms. To demonstrate the potential of these molecules as lead chemical probes we used chemogenomic profiling in yeast and identified specific inhibitors of lanosterol synthase and of stearoyl-CoA 9-desaturase. As community resources, the ~7,500 growth-inhibitory molecules has been made commercially available and the computational model and filter used are provided. PMID:22035796

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.

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

DOE PAGES

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

2014-10-04

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

Discovery and optimisation studies of antimalarial phenotypic hits

PubMed Central

Mital, Alka; Murugesan, Dinakaran; Kaiser, Marcel; Yeates, Clive; Gilbert, Ian H.

2015-01-01

There is an urgent need for the development of new antimalarial compounds. As a result of a phenotypic screen, several compounds with potent activity against the parasite Plasmodium falciparum were identified. Characterization of these compounds is discussed, along with approaches to optimise the physicochemical properties. The in vitro antimalarial activity of these compounds against P. falciparum K1 had EC50 values in the range of 0.09–29 μM, and generally good selectivity (typically >100-fold) compared to a mammalian cell line (L6). One example showed no significant activity against a rodent model of malaria, and more work is needed to optimise these compounds. PMID:26408453

Scientific Assessment of Stratospheric Ozone: 1989, volume 2. Appendix: AFEAS Report

NASA Technical Reports Server (NTRS)

1990-01-01

The results are presented of the Alternative Fluorocarbon Environmental Acceptability Study (AFEAS), which was organized to evaluate the potential effects on the environment of alternate compounds targeted to replace fully halogenated chlorofluorocarbons (CFCs). All relevant current scientific information to determine the environmental acceptability of the alternative fluorocarbons. Special emphasis was placed on: the potential of the compounds to affect stratospheric ozone; their potential to affect tropospheric ozone; their potential to contribute to model calculated global warming; the atmospheric degradation mechanisms of the compounds, in order to identify their products; and the potential environmental effects of the decomposition products. The alternative compounds to be studied were hydrofluorocarbons (HFCs) with one or two carbon atoms and one or more each of fluorine and hydrogen.

Development of a semi-quantitative risk assessment model for evaluating environmental threat posed by the three first EU watch-list pharmaceuticals to urban wastewater treatment plants: An Irish case study.

PubMed

Tahar, Alexandre; Tiedeken, Erin Jo; Clifford, Eoghan; Cummins, Enda; Rowan, Neil

2017-12-15

Contamination of receiving waters with pharmaceutical compounds is of pressing concern. This constitutes the first study to report on the development of a semi-quantitative risk assessment (RA) model for evaluating the environmental threat posed by three EU watch list pharmaceutical compounds namely, diclofenac, 17-beta-estradiol and 17-alpha-ethinylestradiol, to aquatic ecosystems using Irish data as a case study. This RA model adopts the Irish Environmental Protection Agency Source-Pathway-Receptor concept to define relevant parameters for calculating low, medium or high risk score for each agglomeration of wastewater treatment plant (WWTP), which include catchment, treatments, operational and management factors. This RA model may potentially be used on a national scale to (i) identify WWTPs that pose a particular risk as regards releasing disproportionally high levels of these pharmaceutical compounds, and (ii) help identify priority locations for introducing or upgrading control measures (e.g. tertiary treatment, source reduction). To assess risks for these substances of emerging concern, the model was applied to 16 urban WWTPs located in different regions in Ireland that were scored for the three different compounds and ranked as low, medium or high risk. As a validation proxy, this case study used limited monitoring data recorded at some these plants receiving waters. It is envisaged that this semi-quantitative RA approach may aid other EU countries investigate and screen for potential risks where limited measured or predicted environmental pollutant concentrations and/or hydrological data are available. This model is semi-quantitative, as other factors such as influence of climate change and drug usage or prescription data will need to be considered in a future point for estimating and predicting risks. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Screening for Anti-Cancer Compounds in Marine Organisms in Oman

PubMed Central

Dobretsov, Sergey; Tamimi, Yahya; Al-Kindi, Mohamed A.; Burney, Ikram

2016-01-01

Objectives: Marine organisms are a rich source of bioactive molecules with potential applications in medicine, biotechnology and industry; however, few bioactive compounds have been isolated from organisms inhabiting the Arabian Gulf and the Gulf of Oman. This study aimed to isolate and screen the anti-cancer activity of compounds and extracts from 40 natural products of marine organisms collected from the Gulf of Oman. Methods: This study was carried out between January 2012 and December 2014 at the Sultan Qaboos University, Muscat, Oman. Fungi, bacteria, sponges, algae, soft corals, tunicates, bryozoans, mangrove tree samples and sea cucumbers were collected from seawater at Marina Bandar Al-Rowdha and Bandar Al-Khayran in Oman. Bacteria and fungi were isolated using a marine broth and organisms were extracted with methanol and ethyl acetate. Compounds were identified from spectroscopic data. The anti-cancer activity of the compounds and extracts was tested in a Michigan Cancer Foundation (MCF)-7 cell line breast adenocarcinoma model. Results: Eight pure compounds and 32 extracts were investigated. Of these, 22.5% showed strong or medium anti-cancer activity, with malformin A, kuanoniamine D, hymenialdisine and gallic acid showing the greatest activity, as well as the soft coral Sarcophyton sp. extract. Treatment of MCF-7 cells at different concentrations of Sarcophyton sp. extracts indicated the induction of concentration-dependent cell death. Ultrastructural analysis highlighted the presence of nuclear fragmentation, membrane protrusion, blebbing and chromatic segregation at the nuclear membrane, which are typical characteristics of cell death by apoptosis induction. Conclusion: Some Omani marine organisms showed high anti-cancer potential. The efficacy, specificity and molecular mechanisms of anti-cancer compounds from Omani marine organisms on various cancer models should be investigated in future in vitro and in vivo studies. PMID:27226907

Polyoxometalates as antitumor agents: Bioactivity of a new polyoxometalate with copper on a human osteosarcoma model.

PubMed

León, I E; Porro, V; Astrada, S; Egusquiza, M G; Cabello, C I; Bollati-Fogolin, M; Etcheverry, S B

2014-10-05

Polyoxometalates (POMs) are early transition metal oxygen anion clusters. They display interesting biological effects mainly related to their antiviral and antitumor properties. On the other hand, copper compounds also show different biological and pharmacological effects in cell culture and in animal models. We report herein for the first time, a detailed study of the mechanisms of action of a copper(II) compound of the group of HPOMs with the formula K7Na3[Cu4(H2O)2(PW9034)2]20H2O (PW9Cu), in a model of human osteosarcoma derived cell line, MG-63. The compound inhibited selectively the viability of the osteosarcoma cells in the range of 25-100μM (p<0.01). Besides, we have clearly shown a more deleterious action of PW9Cu on tumor osteoblasts than in normal cells. Cytotoxicity studies also showed deleterious effects for PW9Cu. The increment of reactive oxygen species (ROS) and the decrease of the GSH/GSSG ratio were involved in the antiproliferative effects of PW9Cu. Moreover, the compound caused cell cycle arrest in G2 phase, triggering apoptosis as determined by flow cytometry. As a whole, these results showed the main mechanisms of the deleterious effects of PW9Cu in the osteosarcoma cell line MG-63, demonstrating that this compound is a promissory agent for cancer treatments. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

DOE PAGES

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

2014-10-30

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

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.

A method to calculate fission-fragment yields Y(Z,N) versus proton and neutron number in the Brownian shape-motion model

DOE PAGES

Moller, Peter; Ichikawa, Takatoshi

2015-12-23

In this study, we propose a method to calculate the two-dimensional (2D) fission-fragment yield Y(Z,N) versus both proton and neutron number, with inclusion of odd-even staggering effects in both variables. The approach is to use the Brownian shape-motion on a macroscopic-microscopic potential-energy surface which, for a particular compound system is calculated versus four shape variables: elongation (quadrupole moment Q 2), neck d, left nascent fragment spheroidal deformation ϵ f1, right nascent fragment deformation ϵ f2 and two asymmetry variables, namely proton and neutron numbers in each of the two fragments. The extension of previous models 1) introduces a method tomore » calculate this generalized potential-energy function and 2) allows the correlated transfer of nucleon pairs in one step, in addition to sequential transfer. In the previous version the potential energy was calculated as a function of Z and N of the compound system and its shape, including the asymmetry of the shape. We outline here how to generalize the model from the “compound-system” model to a model where the emerging fragment proton and neutron numbers also enter, over and above the compound system composition.« less

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.

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...

COMDECOM: predicting the lifetime of screening compounds in DMSO solution.

PubMed

Zitha-Bovens, Emrin; Maas, Peter; Wife, Dick; Tijhuis, Johan; Hu, Qian-Nan; Kleinöder, Thomas; Gasteiger, Johann

2009-06-01

The technological evolution of the 1990s in both combinatorial chemistry and high-throughput screening created the demand for rapid access to the compound deck to support the screening process. The common strategy within the pharmaceutical industry is to store the screening library in DMSO solution. Several studies have shown that a percentage of these compounds decompose in solution, varying from a few percent of the total to a substantial part of the library. In the COMDECOM (COMpound DECOMposition) project, the compound stability of screening compounds in DMSO solution is monitored in an accelerated thermal, hydrolytic, and oxidative decomposition program. A large database with stability data is collected, and from this database, a predictive model is being developed. The aim of this program is to build an algorithm that can flag compounds that are likely to decompose-information that is considered to be of utmost importance (e.g., in the compound acquisition process and when evaluation screening results of library compounds, as well as in the determination of optimal storage conditions).

Computational Material Modeling of Hydrated Cement Paste Calcium Silicate Hydrate (C-S-H) Chemistry Structure - Influence of Magnesium Exchange on Mechanical Stiffness: C-S-H Jennite

DTIC Science & Technology

2015-04-27

MODELING OF C-S-H Material chemistry level modeling following the principles and techniques commonly grouped under Computational Material Science is...Henmi, C. and Kusachi, I. Monoclinic tobermorite from fuka, bitchu-cho, Okoyama Perfecture. Japan J. Min. Petr. Econ . Geol. (1989)84:374-379. [22...31] Liu, Y. et al. First principles study of the stability and mechanical properties of MC (M=Ti, V, Zr, Nb, Hf and Ta) compounds. Journal of Alloys and Compounds. (2014) 582:500-504. 10

Synthesis, cytotoxicity and molecular modelling studies of new phenylcinnamide derivatives as potent inhibitors of cholinesterases.

PubMed

Saeed, Aamer; Mahesar, Parvez Ali; Zaib, Sumera; Khan, Muhammad Siraj; Matin, Abdul; Shahid, Mohammad; Iqbal, Jamshed

2014-05-06

The present study reports the synthesis of cinnamide derivatives and their biological activity as inhibitors of both cholinesterases and anticancer agents. Controlled inhibition of brain acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) may slow neurodegeneration in Alzheimer's diseases (AD). The anticholinesterase activity of phenylcinnamide derivatives was determined against Electric Eel acetylcholinesterase (EeAChE) and horse serum butyrylcholinesterase (hBChE) and some of the compounds appeared as moderately potent inhibitors of EeAChE and hBChE. The compound 3-(2-(Benzyloxy)phenyl)-N-(3,4,5-trimethoxyphenyl)acrylamide (3i) showed maximum activity against EeAChE with an IC50 0.29 ± 0.21 μM whereas 3-(2-chloro-6-nitrophenyl)-N-(3,4,5-trimethoxyphenyl)acrylamide (3k) was proved to be the most potent inhibitor of hBChE having IC50 1.18 ± 1.31 μM. To better understand the enzyme-inhibitor interaction of the most active compounds toward cholinesterases, molecular modelling studies were carried out on high-resolution crystallographic structures. The anticancer effects of synthesized compounds were also evaluated against cancer cell line (lung carcinoma). The compounds may be useful leads for the design of a new class of anticancer drugs for the treatment of cancer and cholinesterase inhibitors for Alzheimer's disease (AD). Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Stability studies of endocrine disrupting tributyltin and triphenyltin compounds in an artificial sea water model.

PubMed

Novotny, Ladislav; Sharaf, Leyla; Abdel-Hamid, Mohammed E; Brtko, Julius

2018-01-01

Triorganotins belong to toxic components present predominantly in antifouling paints for marine vessels. Tributyltin/triphenyltin at pico- or nanomolar concentrations in sea water are known to induce an irreversible sexual abnormality in females of over 190 marine species, an "imposex" phenomenon - the superimposition of male genitalia on a female. Moreover, trialkyltins and triaryltins function as potent nuclear retinoid X receptors (RXR) agonists. In mammals, triorganotin compounds induce immunosuppressive, metabolic, reproductive or developmental effects. Toxic effects of triorganotins warrant the need for monitoring of their long-lasting presence in the environment. This study brings novel data on the stability of two triorganotin compounds in artificial sea water model obtained by applying ultra-pressure liquid chromatography (UPLC) and gas chromatography-mass spectrometry (GC-MS) methods. Stability of tributyltin and triphenyltin chlorides was studied for 180 days and the degradation kinetic parameters were obtained. Tributyltin chloride was the less stable with the degradation kinetic parameters Kdeg = 0.00014 day-1 and t1/2 = 4950 days (13.6 years). Kdeg of the more stable triphenyltin chloride was determined to be Kdeg = 0.00006 day-1 with t1/2 = 11550 days (31.6 years). Since similar stability data of triorganotin compounds were not published previously, we report high stability for both tested compounds, which indicates a significant environmental problem when these substances enter sea water and later coastal sediments.

Protein targets for anticancer gold compounds: mechanistic inferences.

PubMed

Gabbiani, Chiara; Messori, Luigi

2011-12-01

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

Predictive processing of novel compounds: evidence from Japanese.

PubMed

Hirose, Yuki; Mazuka, Reiko

2015-03-01

Our study argues that pre-head anticipatory processing operates at a level below the level of the sentence. A visual-world eye-tracking study demonstrated that, in processing of Japanese novel compounds, the compound structure can be constructed prior to the head if the prosodic information on the preceding modifier constituent signals that the Compound Accent Rule (CAR) is being applied. This prosodic cue rules out the single head analysis of the modifier noun, which would otherwise be a natural and economical choice. Once the structural representation for the head is computed in advance, the parser becomes faster in identifying the compound meaning. This poses a challenge to models maintaining that structural integration and word recognition are separate processes. At the same time, our results, together with previous findings, suggest the possibility that there is some degree of staging during the processing of different sources of information during the comprehension of compound nouns. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Morphological Awareness in Literacy Acquisition of Chinese Second Graders: A Path Analysis

ERIC Educational Resources Information Center

Zhang, Haomin

2016-01-01

The present study tested a path diagram regarding the contribution of morphological awareness (MA) to early literacy acquisition among Chinese-speaking second graders (N = 123). Three facets of MA were addressed, namely derivational awareness, compound awareness and compound structure awareness. The model aimed to test a theory of causal order…

Visualizing Compound Rotations with Virtual Reality

ERIC Educational Resources Information Center

Flanders, Megan; Kavanagh, Richard C.

2013-01-01

Mental rotations are among the most difficult of all spatial tasks to perform, and even those with high levels of spatial ability can struggle to visualize the result of compound rotations. This pilot study investigates the use of the virtual reality-based Rotation Tool, created using the Virtual Reality Modeling Language (VRML) together with…

Computational Chemistry Modeling of the Atmospheric Fate of Toxic Industrial Compounds (TICs)

DTIC Science & Technology

2007-06-01

1+G(3df,2p) number of atoms and number of basis functions) of the (LRG) compounds under study precludes the use of coupled 0 Zero Point Energy ( ZPE ...overlap (NDDO) The extrapolated energy = E(QCI) + E(LRG) - Hamiltonian that is reparameterized to accurately E(SML) + ZPE reproduce coupled cluster

USE OF GIS AND ANCILLARY VARIABLES TO PREDICT VOLATILE ORGANIC COMPOUND AND NITROGEN DIOXIDE LEVELS AT UNMONITORED LOCATIONS

EPA Science Inventory

This paper presents a GIS-based regression spatial method, known as land-use regression (LUR) modeling, to estimate ambient air pollution exposures used in the EPA El Paso Children's Health Study. Passive measurements of select volatile organic compounds (VOC) and nitrogen dioxi...

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking.

PubMed

Chen, H F; Dong, X C; Zen, B S; Gao, K; Yuan, S G; Panaye, A; Doucet, J P; Fan, B T

2003-08-01

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.

Influence of silicon defects on the adsorption of thiophene-like compounds on polycyclic aromatic hydrocarbons: a theoretical study using thiophene + coronene as the simplest model.

PubMed

Galano, Annia

2007-03-08

Physisorption and chemisorption processes of thiophene on coronene and 2Si-coronene have been studied using density functional theory and MP2 methods. These systems have been chosen as the simplest models to describe the adsorption of thiophene-like compounds on polycyclic aromatic hydrocarbons (PAHs). The calculated data suggest that the presence of silicon atoms in PAHs could favor their interaction with thiophene and similar compounds. Small stabilization energies have been found for several physisorbed complexes. The thiophene chemisorption on coronene seems very unlikely to occur, while that on 2Si-coronene leads to addition products which are very stable, with respect to the isolated reactants. These chemisorption processes were found to be exoergic (DeltaG < 0) in the gas phase and in the nonpolar liquid phase. The results reported in this work suggest that silicon defects on extended polycyclic aromatic hydrocarbons, such as graphite, soot, and large-diameter carbon nanotubes, could make them useful in the removal processes of aromatic sulfur compounds from oil hydrocarbons.

Adsorption isotherm studies of chromium (VI) from aqueous solutions using sol-gel hydrotalcite-like compounds.

PubMed

Ramos-Ramírez, Esthela; Ortega, Norma L Gutiérrez; Soto, Cesar A Contreras; Gutiérrez, Maria T Olguín

2009-12-30

In under-developed countries, industries such as paint and pigment manufacturing, leather tanning, chrome plating and textile processing, usually discharge effluents containing Cr(VI) and Cr(III) into municipal sanitary sewers. It has been reported that Cr(VI) acts as a powerful epithelial irritant and as a human carcinogen. In the present work, hydrotalcite-like compounds with a Mg/Al ratio=2 were synthesized by the sol-gel method. The hydrotalcite-like compounds and their corresponding thermally treated products were characterized by powder X-ray diffraction, infrared spectroscopy and N(2) adsorption. The hydrotalcite-like compounds and the heated solids were used as adsorbents for Cr(VI) in aqueous solutions. Adsorption isotherm studies of Cr(VI) from aqueous solution are described. The adsorbent capacity was determined using the Langmuir, Freundlich and Dubinin-Radushkevich adsorption isotherm models. The Cr(VI) adsorption isotherm data fit best to the Langmuir isotherm model. The maximum Cr(VI) uptake by hydrotalcite and the heated solids was determined using the Langmuir equation and was found to range between 26 and 29 mg Cr(VI)/g adsorbent.

Improved BM212 MmpL3 Inhibitor Analogue Shows Efficacy in Acute Murine Model of Tuberculosis Infection

PubMed Central

Alfonso, Salvatore; Cocozza, Martina; Porretta, Giulio Cesare; Ballell, Lluís; Rullas, Joaquin; Ortega, Fátima; De Logu, Alessandro; Agus, Emanuela; La Rosa, Valentina; Pasca, Maria Rosalia; De Rossi, Edda; Wae, Baojie; Franzblau, Scott G.; Manetti, Fabrizio; Botta, Maurizio; Biava, Mariangela

2013-01-01

1,5-Diphenyl pyrroles were previously identified as a class of compounds endowed with high in vitro efficacy against M. tuberculosis. To improve the physical chemical properties and drug-like parameters of this class of compounds, a medicinal chemistry effort was undertaken. By selecting the optimal substitution patterns for the phenyl rings at N1 and C5 and by replacing the thiomorpholine moiety with a morpholine one, a new series of compounds was produced. The replacement of the sulfur with oxygen gave compounds with lower lipophilicity and improved in vitro microsomal stability. Moreover, since the parent compound of this family has been shown to target MmpL3, mycobacterial mutants resistant to two compounds have been isolated and characterized by sequencing the mmpL3 gene; all the mutants showed point mutations in this gene. The best compound identified to date was progressed to dose-response studies in an acute murine TB infection model. The resulting ED99 of 49 mg/Kg is within the range of commonly employed tuberculosis drugs, demonstrating the potential of this chemical series. The in vitro and in vivo target validation evidence presented here adds further weight to MmpL3 as a druggable target of interest for anti-tubercular drug discovery. PMID:23437287

Benzofuran-pyran hybrids: A new class of potential bone anabolic agents.

PubMed

Gupta, Sampa; Adhikary, Sulekha; Modukuri, Ram K; Choudhary, Dharmendra; Trivedi, Ritu; Sashidhara, Koneni V

2018-06-01

Benzofuran moiety is an important pharmacophore showing positive effects on bone health. In the present study, sixteen benzofuran-pyran hybrids were synthesized and were evaluated for their osteogenic effects on primary osteoblast cells isolated from calvaria. Compounds 22 and 24 were found potent in stimulating osteoblast differentiation as assessed by the alkaline phosphatase activity. These compounds were also found to be nontoxic to osteoblast cells as compared to the control cells in MTT assay. Further, Alizarin Red-S staining for visualization of calcium nodules demonstrated compounds 22 and 34 as active in enhancing mineralization in osteoblast cells. Additionally, transcriptional analysis of these compounds on osteoblast cells revealed that compound 22 up-regulated the expression of osteogenic genes RUNX2, BMP-2, COL-1, thus substantiating that compound 22 having two geminal methyl groups in its R 3 position is a potent osteogenic agent. Additionally, compound 22 enhanced the ability of bone marrow stromal cells to differentiate towards osteoblast lineage and therefore can be further studied in vivo in bone loss model. Copyright © 2018 Elsevier Ltd. All rights reserved.

Design, synthesis and biological evaluation of multifunctional tacrine-curcumin hybrids as new cholinesterase inhibitors with metal ions-chelating and neuroprotective property.

PubMed

Liu, Zhikun; Fang, Lei; Zhang, Huan; Gou, Shaohua; Chen, Li

2017-04-15

Total sixteen tacrine-curcumin hybrid compounds were designed and synthesized for the purpose of searching for multifunctional anti-Alzheimer agents. In vitro studies showed that these hybrid compounds showed good cholinesterase inhibitory activity. Particularly, the potency of K 3-2 is even beyond tacrine. Some of the compounds exhibited different selectivity on acetylcholinesterase or butyrylcholinesterase due to the structural difference. Thus, the structure and activity relationship is summarized and further discussed based on molecular modeling studies. The ORAC and MTT assays indicated that the hybrid compounds possessed pronounced antioxidant activity and could effectively protect PC12 cells from the H 2 O 2 /Aβ42-induced toxicity. Moreover, the hybrid compounds also showed positive metal ions-chelating ability in vitro, suggesting a potential to halt ion-induced Aβ aggregation. All the obtained results demonstrated that the tacrine-curcumin hybrid compounds, in particular compound K 3-2 , can be considered as potential therapeutic agents for Alzheimer's disease. Copyright © 2017 Elsevier Ltd. All rights reserved.

Design and synthesis of some new 1-phenyl-3/4-[4-(aryl/heteroaryl/alkyl-piperazine1-yl)-phenyl-ureas as potent anticonvulsant and antidepressant agents.

PubMed

Mishra, Chandra Bhushan; Kumari, Shikha; Tiwari, Manisha

2016-05-01

A series of 1-phenyl-3/4-[4-(aryl/heteroaryl/alkyl-piperazine1-yl)-phenyl-urea derivatives (29-42) were designed, synthesized and evaluated for their anticonvulsant activity by using maximal electroshock (MES), subcutaneous pentylenetetrazole (scPTZ) seizure tests. The acute neurotoxicity was checked by rotarod assay. Most of the test compounds were found effective in both seizure tests. Compound 30 (1-{4-[4-(4-chloro-phenyl)-piperazin-1-yl]-phenyl}-3-phenyl-urea) exhibited marked anticonvulsant activity in MES as well as scPTZ tests. The phase II anticonvulsant quantification study of compound 30 indicates the ED50 value of 28.5 mg/kg against MES induced seizures. In addition, this compound also showed considerable protection against pilocarpine induced status epilepticus in rats. Seizures induced by 3-mercaptopropionic acid model and thiosemicarbazide were significantly attenuated by compound 30, which suggested its broad spectrum of anticonvulsant activity. Interestingly, compound 30 displayed better antidepressant activity than standard drug fluoxetine. Moreover, compound 30 appeared as a non-toxic chemical entity in sub-acute toxicity studies.

Novel Vitamin K analogs suppress seizures in zebrafish and mouse models of epilepsy.

PubMed

Rahn, J J; Bestman, J E; Josey, B J; Inks, E S; Stackley, K D; Rogers, C E; Chou, C J; Chan, S S L

2014-02-14

Epilepsy is a debilitating disease affecting 1-2% of the world's population. Despite this high prevalence, 30% of patients suffering from epilepsy are not successfully managed by current medication suggesting a critical need for new anti-epileptic drugs (AEDs). In an effort to discover new therapeutics for the management of epilepsy, we began our study by screening drugs that, like some currently used AEDs, inhibit histone deacetylases (HDACs) using a well-established larval zebrafish model. In this model, 7-day post fertilization (dpf) larvae are treated with the widely used seizure-inducing compound pentylenetetrazol (PTZ) which stimulates a rapid increase in swimming behavior previously determined to be a measurable manifestation of seizures. In our first screen, we tested a number of different HDAC inhibitors and found that one, 2-benzamido-1 4-naphthoquinone (NQN1), significantly decreased swim activity to levels equal to that of valproic acid, 2-n-propylpentanoic acid (VPA). We continued to screen structurally related compounds including Vitamin K3 (VK3) and a number of novel Vitamin K (VK) analogs. We found that VK3 was a robust inhibitor of the PTZ-induced swim activity, as were several of our novel compounds. Three of these compounds were subsequently tested on mouse seizure models at the National Institute of Neurological Disorders and Stroke (NINDS) Anticonvulsant Screening Program. Compound 2h reduced seizures particularly well in the minimal clonic seizure (6Hz) and corneal-kindled mouse models of epilepsy, with no observable toxicity. As VK3 affects mitochondrial function, we tested the effects of our compounds on mitochondrial respiration and ATP production in a mouse hippocampal cell line. We demonstrate that these compounds affect ATP metabolism and increase total cellular ATP. Our data indicate the potential utility of these and other VK analogs for the prevention of seizures and suggest the potential mechanism for this protection may lie in the ability of these compounds to affect energy production. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Pesticide nonextractable residue formation in soil: insights from inverse modeling of degradation time series.

PubMed

Loos, Martin; Krauss, Martin; Fenner, Kathrin

2012-09-18

Formation of soil nonextractable residues (NER) is central to the fate and persistence of pesticides. To investigate pools and extent of NER formation, an established inverse modeling approach for pesticide soil degradation time series was evaluated with a Monte Carlo Markov Chain (MCMC) sampling procedure. It was found that only half of 73 pesticide degradation time series from a homogeneous soil source allowed for well-behaved identification of kinetic parameters with a four-pool model containing a parent compound, a metabolite, a volatile, and a NER pool. A subsequent simulation indeed confirmed distinct parameter combinations of low identifiability. Taking the resulting uncertainties into account, several conclusions regarding NER formation and its impact on persistence assessment could nonetheless be drawn. First, rate constants for transformation of parent compounds to metabolites were correlated to those for transformation of parent compounds to NER, leading to degradation half-lives (DegT50) typically not being larger than disappearance half-lives (DT50) by more than a factor of 2. Second, estimated rate constants were used to evaluate NER formation over time. This showed that NER formation, particularly through the metabolite pool, may be grossly underestimated when using standard incubation periods. It further showed that amounts and uncertainties in (i) total NER, (ii) NER formed from the parent pool, and (iii) NER formed from the metabolite pool vary considerably among data sets at t→∞, with no clear dominance between (ii) and (iii). However, compounds containing aromatic amine moieties were found to form significantly more total NER when extrapolating to t→∞ than the other compounds studied. Overall, our study stresses the general need for assessing uncertainties, identifiability issues, and resulting biases when using inverse modeling of degradation time series for evaluating persistence and NER formation.

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity.

PubMed

Elferink, M G L; Olinga, P; Draaisma, A L; Merema, M T; Bauerschmidt, S; Polman, J; Schoonen, W G; Groothuis, G M M

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such as Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl(4), fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.

Three-dimensional quantitative structure-activity relationship studies on novel series of benzotriazine based compounds acting as Src inhibitors using CoMFA and CoMSIA.

PubMed

Gueto, Carlos; Ruiz, José L; Torres, Juan E; Méndez, Jefferson; Vivas-Reyes, Ricardo

2008-03-01

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of benzotriazine derivatives, as Src inhibitors. Ligand molecular superimposition on the template structure was performed by database alignment method. The statistically significant model was established of 72 molecules, which were validated by a test set of six compounds. The CoMFA model yielded a q(2)=0.526, non cross-validated R(2) of 0.781, F value of 88.132, bootstrapped R(2) of 0.831, standard error of prediction=0.587, and standard error of estimate=0.351 while the CoMSIA model yielded the best predictive model with a q(2)=0.647, non cross-validated R(2) of 0.895, F value of 115.906, bootstrapped R(2) of 0.953, standard error of prediction=0.519, and standard error of estimate=0.178. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that small steric volumes in the hydrophobic region, electron-withdrawing groups next to the aryl linker region, and atoms close to the solvent accessible region increase the Src inhibitory activity of the compounds. In fact, adding substituents at positions 5, 6, and 8 of the benzotriazine nucleus were generated new compounds having a higher predicted activity. The data generated from the present study will further help to design novel, potent, and selective Src inhibitors as anticancer therapeutic agents.

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity

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

Elferink, M.G.L.; Olinga, P.; Draaisma, A.L.

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such asmore » Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl{sub 4}, fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.« less

Agricultural Compounds in Water and Birth Defects.

PubMed

Brender, Jean D; Weyer, Peter J

2016-06-01

Agricultural compounds have been detected in drinking water, some of which are teratogens in animal models. The most commonly detected agricultural compounds in drinking water include nitrate, atrazine, and desethylatrazine. Arsenic can also be an agricultural contaminant, although arsenic often originates from geologic sources. Nitrate has been the most studied agricultural compound in relation to prenatal exposure and birth defects. In several case-control studies published since 2000, women giving birth to babies with neural tube defects, oral clefts, and limb deficiencies were more likely than control mothers to be exposed to higher concentrations of drinking water nitrate during pregnancy. Higher concentrations of atrazine in drinking water have been associated with abdominal defects, gastroschisis, and other defects. Elevated arsenic in drinking water has also been associated with birth defects. Since these compounds often occur as mixtures, it is suggested that future research focus on the impact of mixtures, such as nitrate and atrazine, on birth defects.

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

Neural activity in the hippocampus during conflict resolution.

PubMed

Sakimoto, Yuya; Okada, Kana; Hattori, Minoru; Takeda, Kozue; Sakata, Shogo

2013-01-15

This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. Copyright © 2012 Elsevier B.V. All rights reserved.

Developing an Activity and Absorption-based Quality Control Platform for Chinese Traditional Medicine: Application to Zeng-Sheng-Ping

PubMed Central

Yin, Taijun; Yang, Guanyi; Ma, Yong; Xu, Beibei; Hu, Ming; You, Ming; Gao, Song

2015-01-01

Ethnopharmacological relevance Zeng-Sheng-Ping (ZSP) is a marketed Chinese traditional medicine used for cancer prevention. Aim of the study Currently, for the quality control of Chinese traditional medicines, marker compounds are not selected based on bioactivities and pharmaceutical behaviors in most of the cases. Therefore, even if the “quality” of the medicine is controlled, the pharmacological effect could still be inconsistent. The aim of this study is to establish an activity and absorption-based platform to select marker compound(s) for the quality control of Chinese traditional medicines. Materials and methods We used ZSP as a reference Chinese traditional medicine to establish the platform. Activity guided fractionation approach was used to purify the major components from ZSP. NMR and MS spectra were used to elucidate the structure of the isolated compounds. MTT assay against oral carcinoma cell line (SCC2095) was performed to evaluate the activities. UPLC-MS/MS was used to quantify the pure compounds in ZSP and the active fraction. The permeabilities of the identified compounds were evaluated in the Caco-2 cell culture model. The intracellular accumulation of the isolated compounds was evaluated in the SCC2095 cells. Results The major compounds were identified from ZSP. The contents, anti-proliferation activities, permeabilities, and intracellular accumulations of these compounds were also evaluated. The structure of these purified compounds were identified by comparing the NMR and MS data with those of references as rutaevine (1), limonin (2) , evodol (3), obacunone (4), fraxinellone (5), dictamnine (6), maackiain (7), trifolirhizin (8), and matrine (9). The IC50 of compounds 5, 6, and 7 against SCC2095 cells were significantly lower than that of ZSP. The uptake permeability of compounds 5, 6, and 7 were 2.58 ± 0. 3 × 10−5, 4.33 ± 0.5 × 10−5, and 4.27 ± 0.8 × 10−5 respectively in the Caco-2 cell culture model. The intracellular concentrations of these compounds showed that compounds 5, 6, and 7 were significantly accumulated inside the cells. Conclusion Based on the activity against oral carcinoma cell line as well as the absorption permeability, compound 5, 6, and 7 are selected as quality control markers for ZSP. A activity and absorption-based platform was established and successfully used for the quality control of ZSP. PMID:26099633

Molecular Docking, Synthesis And Biological Evaluation Of Sulphonylureas/Guanidine Derivatives As Promising Antidiabetics Agent.

PubMed

Panchal, Ishan; Sen, Dhrubo Jyoti; Patel, Ashish D; Shah, Umang; Patel, Mehul; Navle, Archana; Bhavsar, Vashisth

2017-10-02

A series of novel sulphonylureas/guanidine derivatives were designed, synthesized, and evaluated for the treatment of diabetes mellitus. In this study, the designed compounds were docked with AKR1C1 complexes by using glide docking program and docking calculations were performed to predict the binding affinity of the designed compounds with the binding pocket of protein 4YVP and QikProp program was used to predict the ADME/T properties of the analogues. All the targeted derivatives were synthesized and purified by recrystallization. Synthesize compounds were characterized by various physicochemical and various spectroscopic techniques like melting point, thin layer chromatography, infrared spectroscopy (KBr pellets), mass spectroscopy(m/z), 1H NMR (DMSO-d6), and 13C NMR. The synthesized compounds were further studied for biological evolution by alloxan (150 mg/dl, intraperitonial) induced diabetic rat model for in-vivo studies. Among all the synthesized derivatives, 5c and 5d were most potent as per binding energy. Compound 5i have shown a better plasma glucose reduction compared to glibenclamide. Hence, it will further use as a lead compound to develop a more such kind of agent. The docking study revealed that in all designed sulphonylureas/guanidine series of compounds 5c and 5d were found to be most potent compounds as per the binding energy compared to glibenclamide. With the help of details study of in vivo biological activity we observed that compound 5i gives better result compared to glibenclamide as standard. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Quantitative structural modeling on the wavelength interval (Δλ) in synchronous fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Samari, Fayezeh; Yousefinejad, Saeed

2017-11-01

Emission fluorescence spectroscopy has an extremely restricted scope of application to analyze of complex mixtures since its selectivity is reduced by the extensive spectral overlap. Synchronous fluorescence spectroscopy (SFS) is a technique enables us to analyze complex mixtures with overlapped emission and/or excitation spectra. The difference of excitation and emission wavelength of compounds (interval wavelength or Δλ) is an important characteristic in SFS. Thus a multi-parameter model was constructed to predict Δλ in 63 fluorescent compounds and the regression coefficient in training set, cross validation and test set were 0.88, 0.85 and 0.91 respectively. Furthermore, the applicability and validity of model were evaluated using different statistical methods such as y-scrambling and applicability domain. It was concluded that increasing average valence connectivity, number of Al2-NH functional group and Geary autocorrelation (lag 4) with electronegative weights can lead to increasing Δλ in the fluorescent compounds. The current study obtained an insight into the structural properties of compounds effective on their Δλ as an important parameter in SFS.

Effects of halogenated aromatics/aliphatics and nitrogen(N)-heterocyclic aromatics on estimating the persistence of future pharmaceutical compounds using a modified QSAR model.

PubMed

Lim, Seung Joo; Fox, Peter

2014-02-01

The effects of halogenated aromatics/aliphatics and nitrogen(N)-heterocyclic aromatics on estimating the persistence of future pharmaceutical compounds were investigated using a modified half life equation. The potential future pharmaceutical compounds investigated were approximately 2000 pharmaceutical drugs currently undergoing the United States Food and Drug Administration (US FDA) testing. EPI Suite (BIOWIN) model estimates the fates of compounds based on the biodegradability under aerobic conditions. While BIOWIN considered the biodegradability of a compound only, the half life equation used in this study was modified by biodegradability, sorption and cometabolic oxidation. It was possible that the potential future pharmaceutical compounds were more accurately estimated using the modified half life equation. The modified half life equation considered sorption and cometabolic oxidation of halogenated aromatic/aliphatics and nitrogen(N)-heterocyclic aromatics in the sub-surface, while EPI Suite (BIOWIN) did not. Halogenated aliphatics in chemicals were more persistent than halogenated aromatics in the sub-surface. In addition, in the sub-surface environment, the fates of organic chemicals were much more affected by halogenation in chemicals than by nitrogen(N)-heterocyclic aromatics. © 2013.

Electrophysiological evidence for the morpheme-based combinatoric processing of English compounds

PubMed Central

Fiorentino, Robert; Naito-Billen, Yuka; Bost, Jamie; Fund-Reznicek, Ella

2014-01-01

The extent to which the processing of compounds (e.g., “catfish”) makes recourse to morphological-level representations remains a matter of debate. Moreover, positing a morpheme-level route to complex word recognition entails not only access to morphological constituents, but also combinatoric processes operating on the constituent representations; however, the neurophysiological mechanisms subserving decomposition, and in particular morpheme combination, have yet to be fully elucidated. The current study presents electrophysiological evidence for the morpheme-based processing of both lexicalized (e.g., “teacup”) and novel (e.g., “tombnote”) visually-presented English compounds; these brain responses appear prior to and are dissociable from the eventual overt lexical decision response. The electrophysiological results reveal increased negativities for conditions with compound structure, including effects shared by lexicalized and novel compounds, as well as effects unique to each compound type, which may be related to aspects of morpheme combination. These findings support models positing across-the-board morphological decomposition, counter to models proposing that putatively complex words are primarily or solely processed as undecomposed representations, and motivate further electrophysiological research toward a more precise characterization of the nature and neurophysiological instantiation of complex word recognition. PMID:24279696

Effects of Vanadium-Containing Compounds on Membrane Lipids and on Microdomains Used in Receptor-Mediated Signaling

PubMed Central

Roess, Deborah A.; Smith, Steven M. L.; Winter, Peter; Zhou, Jun; Dou, Ping; Baruah, Bharat; Trujillo, Alejandro M.; Levinger, Nancy E.; Yang, Xioda; Barisas, B. George; Crans, Debbie C.

2011-01-01

There is increasing evidence for the involvement of plasma membrane microdomains in insulin receptor function. Moreover, disruption of these structures, which are typically enriched in sphingomyelin and cholesterol, results in insulin resistance. Treatment strategies for insulin resistance include the use of vanadium compounds which have been shown in animal models to enhance insulin responsiveness. One possible mechanism for insulin-enhancing effects might involve direct effects of vanadium compounds on membrane lipid organization. These changes in lipid organization promote the partitioning of insulin receptors and other receptors into membrane microdomains where receptors are optimally functional. To explore this possibility, we have used several strategies involving vanadium complexes such as [VO2dipic]− (pyridin-2,6-dicarboxylatodioxovanadium(V)), decavanadate (V10O286−, V10), BMOV (bis(maltolato)oxovanadium(IV)) and [VO(saltris)]2 (2-salicylideniminato-2-(hydroxymethyl)-1,3-dihydroxypropane-oxovanadium(V)). Our strategies include an evaluation of interactions between vanadium-containing compounds and model lipid systems, an evaluation of the effects of vanadium compounds on lipid fluidity in erythrocyte membranes, and studies of the effects of vanadium-containing compounds on signaling events initiated by receptors known to use membrane microdomains as signaling platforms. PMID:18729092

A ranking method for the concurrent learning of compounds with various activity profiles.

PubMed

Dörr, Alexander; Rosenbaum, Lars; Zell, Andreas

2015-01-01

In this study, we present a SVM-based ranking algorithm for the concurrent learning of compounds with different activity profiles and their varying prioritization. To this end, a specific labeling of each compound was elaborated in order to infer virtual screening models against multiple targets. We compared the method with several state-of-the-art SVM classification techniques that are capable of inferring multi-target screening models on three chemical data sets (cytochrome P450s, dehydrogenases, and a trypsin-like protease data set) containing three different biological targets each. The experiments show that ranking-based algorithms show an increased performance for single- and multi-target virtual screening. Moreover, compounds that do not completely fulfill the desired activity profile are still ranked higher than decoys or compounds with an entirely undesired profile, compared to other multi-target SVM methods. SVM-based ranking methods constitute a valuable approach for virtual screening in multi-target drug design. The utilization of such methods is most helpful when dealing with compounds with various activity profiles and the finding of many ligands with an already perfectly matching activity profile is not to be expected.

Ligand-based virtual screening and in silico design of new antimalarial compounds using nonstochastic and stochastic total and atom-type quadratic maps.

PubMed

Marrero-Ponce, Yovani; Iyarreta-Veitía, Maité; Montero-Torres, Alina; Romero-Zaldivar, Carlos; Brandt, Carlos A; Avila, Priscilla E; Kirchgatter, Karin; Machado, Yanetsy

2005-01-01

Malaria has been one of the most significant public health problems for centuries. It affects many tropical and subtropical regions of the world. The increasing resistance of Plasmodium spp. to existing therapies has heightened alarms about malaria in the international health community. Nowadays, there is a pressing need for identifying and developing new drug-based antimalarial therapies. In an effort to overcome this problem, the main purpose of this study is to develop simple linear discriminant-based quantitative structure-activity relationship (QSAR) models for the classification and prediction of antimalarial activity using some of the TOMOCOMD-CARDD (TOpological MOlecular COMputer Design-Computer Aided "Rational" Drug Design) fingerprints, so as to enable computational screening from virtual combinatorial datasets. In this sense, a database of 1562 organic chemicals having great structural variability, 597 of them antimalarial agents and 965 compounds having other clinical uses, was analyzed and presented as a helpful tool, not only for theoretical chemists but also for other researchers in this area. This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. Afterward, two linear classification functions were derived in order to discriminate between antimalarial and nonantimalarial compounds. The models (including nonstochastic and stochastic indices) correctly classify more than 93% of the compound set, in both training and external prediction datasets. They showed high Matthews' correlation coefficients, 0.889 and 0.866 for the training set and 0.855 and 0.857 for the test one. The models' predictivity was also assessed and validated by the random removal of 10% of the compounds to form a new test set, for which predictions were made using the models. The overall means of the correct classification for this process (leave group 10% full-out cross validation) using the equations with nonstochastic and stochastic atom-based quadratic fingerprints were 93.93% and 92.77%, respectively. The quadratic maps-based TOMOCOMD-CARDD approach implemented in this work was successfully compared with four of the most useful models for antimalarials selection reported to date. The developed models were then used in a simulation of a virtual search for Ras FTase (FTase = farnesyltransferase) inhibitors with antimalarial activity; 70% and 100% of the 10 inhibitors used in this virtual search were correctly classified, showing the ability of the models to identify new lead antimalarials. Finally, these two QSAR models were used in the identification of previously unknown antimalarials. In this sense, three synthetic intermediaries of quinolinic compounds were evaluated as active/inactive ones using the developed models. The synthesis and biological evaluation of these chemicals against two malaria strains, using chloroquine as a reference, was performed. An accuracy of 100% with the theoretical predictions was observed. Compound 3 showed antimalarial activity, being the first report of an arylaminomethylenemalonate having such behavior. This result opens a door to a virtual study considering a higher variability of the structural core already evaluated, as well as of other chemicals not included in this study. We conclude that the approach described here seems to be a promising QSAR tool for the molecular discovery of novel classes of antimalarial drugs, which may meet the dual challenges posed by drug-resistant parasites and the rapid progression of malaria illnesses.

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.

Synthesis, molecular modeling studies and biological evaluation of fluorine substituted analogs of GW 501516.

PubMed

Ciocoiu, Calin C; Ravna, Aina W; Sylte, Ingebrigt; Rustan, Arild C; Hansen, Trond Vidar

2011-12-01

(±)-2-Fluoro-2-(2-methyl-4-(((4-methyl-2-(4-(trifluoromethyl)phenyl)thiazol-5-yl)methyl)thio)phenoxy)acetic acid (2a) has been prepared and subjected to biological testing against all three subtypes of the PPARs. This compound exhibited agonist effects with EC(50) values of 560 and 55 nM against PPARα and PPARδ, respectively, in a luciferase assay. Moreover, compound (±)-2a also exhibited potent ability to induce oleic acid oxidation in a human myotube cell assay with EC(50)=3.7 nM. Compound (±)-2a can be classified as a dual PPARα/δ agonist with a 10-fold higher potency against the PPARδ receptor than against the PPARα receptor. Molecular modeling studies revealed that both enantiomers of 2a bind to the PPARδ receptor with similar binding energies. Copyright © 2011 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.

Effects of resveratrol, oxyresveratrol, and their acetylated derivatives on cellular melanogenesis.

PubMed

Park, Jiaa; Park, Joon Heum; Suh, Hwa-Jin; Lee, In Chul; Koh, Jaesook; Boo, Yong Chool

2014-07-01

Resveratrol and oxyresveratrol are naturally occurring phenolic compounds with various bioactivities, but their uses in cosmetics have been partly limited by their chemical instabilities. This study was performed to examine the anti-melanogenic effects of the acetylated derivatives from resveratrol and oxyresveratrol. Resveratrol and oxyresveratrol were chemically modified to triacetyl resveratrol and tetraacetyl oxyresveratrol, respectively. The acetylated compounds were less susceptible than the parent compounds to oxidative discoloration. The acetylated compounds inhibited the activities of tyrosinases less than parent compounds in vitro, but they were as effective at cellular melanogenesis inhibition, indicating bioconversion to parent compounds inside cells. Supporting this notion, the parent compounds were regenerated when the acetylated compounds were digested with cell lysates. Although resveratrol and triacetyl resveratrol inhibited tyrosinase activity less effectively than oxyresveratrol and tetraacetyl oxyresveratrol in vitro, they inhibited cellular melanogenesis more effectively. This discrepancy was explained by strong inhibition of tyrosinase expression by resveratrol and triacetyl resveratrol. Experiments using a reconstituted skin model indicated that resveratrol derivatives can affect melanin synthesis and cell viability to different extents. Collectively, this study suggests that acetylated derivatives of resveratrol have great potential as anti-melanogenic agents for cosmetic use in terms of efficacy, safety, and stability.

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.

Design, Synthesis, and Characterization of N-Oxide-Containing Heterocycles with in Vivo Sterilizing Antitubercular Activity

PubMed Central

2017-01-01

Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), is the infectious disease responsible for the highest number of deaths worldwide. Herein, 22 new N-oxide-containing compounds were synthesized followed by in vitro and in vivo evaluation of their antitubercular potential against Mtb. Compound 8 was found to be the most promising compound, with MIC90 values of 1.10 and 6.62 μM against active and nonreplicating Mtb, respectively. Additionally, we carried out in vivo experiments to confirm the safety and efficacy of compound 8; the compound was found to be orally bioavailable and highly effective, leading to a reduction of Mtb to undetectable levels in a mouse model of infection. Microarray-based initial studies on the mechanism of action suggest that compound 8 blocks translation. Altogether, these results indicate that benzofuroxan derivative 8 is a promising lead compound for the development of a novel chemical class of antitubercular drugs. PMID:28968083

Fumigant activity of the Psidium guajava var. pomifera (Myrtaceae) essential oil in Drosophila melanogaster by means of oxidative stress.

PubMed

Pinho, Antonio Ivanildo; Wallau, Gabriel Luz; Nunes, Mauro Eugenio Medina; Leite, Nadghia Figueiredo; Tintino, Saulo Relison; da Cruz, Litiele Cezar; da Cunha, Francisco Assis Bezerra; da Costa, José Galberto Martins; Douglas Melo Coutinho, Henrique; Posser, Thais; Franco, Jeferson Luis

2014-01-01

The guava fruit, Psidium guajava var. pomifera (Myrtaceae family), is a native plant from South America. Its leaves and fruits are widely used in popular medicine in tropical and subtropical countries. Drosophila melanogaster has been used as one of the main model organisms in genetic studies since the 1900s. The extensive knowledge about this species makes it one of the most suitable organisms to study many aspects of toxic compound effects. Due to the lack of studies on the effects of the bioactive compounds present in the P. guajava var. pomifera essential oil, we performed a phytochemical characterization by CG-MS and evaluated the toxicity induced by the essential oil in the D. melanogaster insect model. In order to understand the biochemical mechanisms of toxicity, changes on the Nrf2 signaling as well as hallmarks of oxidative stress response were followed in the exposed flies. Our results showed that exposure of insects to the P. guajava oil increased mortality and locomotor deficits in parallel with an oxidative stress response signaling. Therefore, it suggested a bioinsecticidal activity for P. guajava volatile compounds by means of oxidative stress. Further studies are ongoing to identify which oil compounds are responsible for such effect.

Fumigant Activity of the Psidium guajava Var. Pomifera (Myrtaceae) Essential Oil in Drosophila melanogaster by Means of Oxidative Stress

PubMed Central

Pinho, Antonio Ivanildo; Wallau, Gabriel Luz; Nunes, Mauro Eugenio Medina; Leite, Nadghia Figueiredo; Tintino, Saulo Relison; da Cruz, Litiele Cezar; da Cunha, Francisco Assis Bezerra; da Costa, José Galberto Martins; Douglas Melo Coutinho, Henrique; Posser, Thais

2014-01-01

The guava fruit, Psidium guajava var. pomifera (Myrtaceae family), is a native plant from South America. Its leaves and fruits are widely used in popular medicine in tropical and subtropical countries. Drosophila melanogaster has been used as one of the main model organisms in genetic studies since the 1900s. The extensive knowledge about this species makes it one of the most suitable organisms to study many aspects of toxic compound effects. Due to the lack of studies on the effects of the bioactive compounds present in the P. guajava var. pomifera essential oil, we performed a phytochemical characterization by CG-MS and evaluated the toxicity induced by the essential oil in the D. melanogaster insect model. In order to understand the biochemical mechanisms of toxicity, changes on the Nrf2 signaling as well as hallmarks of oxidative stress response were followed in the exposed flies. Our results showed that exposure of insects to the P. guajava oil increased mortality and locomotor deficits in parallel with an oxidative stress response signaling. Therefore, it suggested a bioinsecticidal activity for P. guajava volatile compounds by means of oxidative stress. Further studies are ongoing to identify which oil compounds are responsible for such effect. PMID:25478063

Assessment of the potential activity of major dietary compounds as selective estrogen receptor modulators in two distinct cell models for proliferation and differentiation

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

Lecomte, Sylvain; Lelong, Marie; Bourgine, Gaëlle

Estrogen receptors (ERs) α and β are distributed in most tissues of women and men. ERs are bound by estradiol (E2), a natural hormone, and mediate the pleiotropic and tissue-specific effects of E2, such as proliferation of breast epithelial cells or protection and differentiation of neuronal cells. Numerous environmental molecules, called endocrine disrupting compounds, also interact with ERs. Phytoestrogens belong to this large family and are considered potent therapeutic molecules that act through their selective estrogen receptor modulator (SERM) activity. Using breast cancer cell lines as a model of estrogen-dependent proliferation and a stably ER-expressing PC12 cell line as amore » model of neuronal differentiating cells, we studied the SERM activity of major dietary compounds, such as apigenin, liquiritigenin, daidzein, genistein, coumestrol, resveratrol and zearalenone. The ability of these compounds to induce ER-transactivation and breast cancer cell proliferation and enhance Nerve Growth Factor (NGF) -induced neuritogenesis was assessed. Surprisingly, although all compounds were able to activate the ER through an estrogen responsive element reporter gene, they showed differential activity toward proliferation or differentiation. Apigenin and resveratrol showed a partial or no proliferative effect on breast cancer cells but fully contributed to the neuritogenesis effect of NGF. However, daidzein and zearalenone showed full effects on cellular proliferation but did not induce cellular differentiation. In summary, our results suggest that the therapeutic potential of phytoestrogens can diverge depending on the molecule and the phenotype considered. Hence, apigenin and resveratrol might be used in the development of therapeutics for breast cancer and brain diseases. - Highlights: • SERM activity of dietary compounds on proliferation and differentiation is studied. • All the dietary compounds tested transactivate estrogen receptors. • Apigenin and resveratrol could be good candidates for future therapeutics. • Daidzein and zearalenone are to be avoided to maintain human health.« less

Evaluation of a Screening System for Obesogenic Compounds: Screening of Endocrine Disrupting Compounds and Evaluation of the PPAR Dependency of the Effect

PubMed Central

Pereira-Fernandes, Anna; Demaegdt, Heidi; Vandermeiren, Karine; Hectors, Tine L. M.; Jorens, Philippe G.; Blust, Ronny; Vanparys, Caroline

2013-01-01

Recently the environmental obesogen hypothesis has been formulated, proposing a role for endocrine disrupting compounds (EDCs) in the development of obesity. To evaluate this hypothesis, a screening system for obesogenic compounds is urgently needed. In this study, we suggest a standardised protocol for obesogen screening based on the 3T3-L1 cell line, a well-characterised adipogenesis model, and direct fluorescent measurement using Nile red lipid staining technique. In a first phase, we characterised the assay using the acknowledged obesogens rosiglitazone and tributyltin. Based on the obtained dose-response curves for these model compounds, a lipid accumulation threshold value was calculated to ensure the biological relevance and reliability of statistically significant effects. This threshold based method was combined with the well described strictly standardized mean difference (SSMD) method for classification of non-, weak- or strong obesogenic compounds. In the next step, a range of EDCs, used in personal and household care products (parabens, musks, phthalates and alkylphenol compounds), were tested to further evaluate the obesogenicity screening assay for its discriminative power and sensitivity. Additionally, the peroxisome proliferator activated receptor γ (PPARγ) dependency of the positive compounds was evaluated using PPARγ activation and antagonist experiments. Our results showed the adipogenic potential of all tested parabens, several musks and phthalate compounds and bisphenol A (BPA). PPARγ activation was associated with adipogenesis for parabens, phthalates and BPA, however not required for obesogenic effects induced by Tonalide, indicating the role of other obesogenic mechanisms for this compound. PMID:24155963

Unconventional superconductivity and surface pairing symmetry in half-Heusler compounds

NASA Astrophysics Data System (ADS)

Wang, Qing-Ze; Yu, Jiabin; Liu, Chao-Xing

2018-06-01

Signatures of nodal line/point superconductivity [Kim et al., Sci. Adv. 4, eaao4513 (2018), 10.1126/sciadv.aao4513; Brydon et al., Phys. Rev. Lett. 116, 177001 (2016), 10.1103/PhysRevLett.116.177001] have been observed in half-Heusler compounds, such as LnPtBi (Ln = Y, Lu). Topologically nontrivial band structures, as well as topological surface states, have also been confirmed by angular-resolved photoemission spectroscopy in these compounds [Liu et al., Nat. Commun. 7, 12924 (2016), 10.1038/ncomms12924]. In this paper, we present a systematical classification of possible gap functions of bulk states and surface states in half-Heusler compounds and the corresponding topological properties based on the representations of crystalline symmetry group. Different from all the previous studies based on the four band Luttinger model, our study starts with the six-band Kane model, which involves both four p-orbital type of Γ8 bands and two s-orbital type of Γ6 bands. Although the Γ6 bands are away from the Fermi energy, our results reveal the importance of topological surface states, which originate from the band inversion between Γ6 and Γ8 bands, in determining surface properties of these compounds in the superconducting regime by combining topological bulk state picture and nontrivial surface state picture.

Theoretical Modeling of (99)Tc NMR Chemical Shifts.

PubMed

Hall, Gabriel B; Andersen, Amity; Washton, Nancy M; Chatterjee, Sayandev; Levitskaia, Tatiana G

2016-09-06

Technetium-99 (Tc) displays a rich chemistry due to its wide range of accessible oxidation states (from -I to +VII) and ability to form coordination compounds. Determination of Tc speciation in complex mixtures is a major challenge, and (99)Tc nuclear magnetic resonance (NMR) spectroscopy is widely used to probe chemical environments of Tc in odd oxidation states. However, interpretation of (99)Tc NMR data is hindered by the lack of reference compounds. Density functional theory (DFT) calculations can help to fill this gap, but to date few computational studies have focused on (99)Tc NMR of compounds and complexes. This work evaluates the effectiveness of both pure generalized gradient approximation and their corresponding hybrid functionals, both with and without the inclusion of scalar relativistic effects, to model the (99)Tc NMR spectra of Tc(I) carbonyl compounds. With the exception of BLYP, which performed exceptionally well overall, hybrid functionals with inclusion of scalar relativistic effects are found to be necessary to accurately calculate (99)Tc NMR spectra. The computational method developed was used to tentatively assign an experimentally observed (99)Tc NMR peak at -1204 ppm to fac-Tc(CO)3(OH)3(2-). This study examines the effectiveness of DFT computations for interpretation of the (99)Tc NMR spectra of Tc(I) coordination compounds in high salt alkaline solutions.

Li intercalation in graphite: A van der Waals density-functional study

NASA Astrophysics Data System (ADS)

Hazrati, E.; de Wijs, G. A.; Brocks, G.

2014-10-01

Modeling layered intercalation compounds from first principles poses a problem, as many of their properties are determined by a subtle balance between van der Waals interactions and chemical or Madelung terms, and a good description of van der Waals interactions is often lacking. Using van der Waals density functionals we study the structures, phonons and energetics of the archetype layered intercalation compound Li-graphite. Intercalation of Li in graphite leads to stable systems with calculated intercalation energies of -0.2 to -0.3 eV/Li atom, (referred to bulk graphite and Li metal). The fully loaded stage 1 and stage 2 compounds LiC6 and Li1 /2C6 are stable, corresponding to two-dimensional √{3 }×√{3 } lattices of Li atoms intercalated between two graphene planes. Stage N >2 structures are unstable compared to dilute stage 2 compounds with the same concentration. At elevated temperatures dilute stage 2 compounds easily become disordered, but the structure of Li3 /16C6 is relatively stable, corresponding to a √{7 }×√{7 } in-plane packing of Li atoms. First-principles calculations, along with a Bethe-Peierls model of finite temperature effects, allow for a microscopic description of the observed voltage profiles.

[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.

Prediction of biodegradability of aromatics in water using QSAR modeling.

PubMed

Cvetnic, Matija; Juretic Perisic, Daria; Kovacic, Marin; Kusic, Hrvoje; Dermadi, Jasna; Horvat, Sanja; Bolanca, Tomislav; Marin, Vedrana; Karamanis, Panaghiotis; Loncaric Bozic, Ana

2017-05-01

The study was aimed at developing models for predicting the biodegradability of aromatic water pollutants. For that purpose, 36 single-benzene ring compounds, with different type, number and position of substituents, were used. The biodegradability was estimated according to the ratio of the biochemical (BOD 5 ) and chemical (COD) oxygen demand values determined for parent compounds ((BOD 5 /COD) 0 ), as well as for their reaction mixtures in half-life achieved by UV-C/H 2 O 2 process ((BOD 5 /COD) t1/2 ). The models correlating biodegradability and molecular structure characteristics of studied pollutants were derived using quantitative structure-activity relationship (QSAR) principles and tools. Upon derivation of the models and calibration on the training and subsequent testing on the test set, 3- and 5-variable models were selected as the most predictive for (BOD 5 /COD) 0 and (BOD 5 /COD) t1/2 , respectively, according to the values of statistical parameters R 2 and Q 2 . Hence, 3-variable model predicting (BOD 5 /COD) 0 possessed R 2 =0.863 and Q 2 =0.799 for training set, and R 2 =0.710 for test set, while 5-variable model predicting (BOD 5 /COD) 1/2 possessed R 2 =0.886 and Q 2 =0.788 for training set, and R 2 =0.564 for test set. The selected models are interpretable and transparent, reflecting key structural features that influence targeted biodegradability and can be correlated with the degradation mechanisms of studied compounds by UV-C/H 2 O 2 . Copyright © 2017 Elsevier Inc. All rights reserved.

MISTRA mechanism development: A new mechanism focused on marine environments

NASA Astrophysics Data System (ADS)

Bräuer, Peter; Sommariva, Roberto; von Glasow, Roland

2015-04-01

The tropospheric multiphase chemistry of halogen compounds plays a key role in marine environments. Moreover, halogen compounds have an impact on the tropospheric oxidation capacity and climate. With more than two thirds of the Earth's surface covered with oceans, effects are of global importance. Various conditions are found in marine environments ranging from pristine regions to polluted regimes in the continental outflow. Furthermore, there are important sources for halogen compounds over land, such as volcanoes, salt lakes, or emissions from industrial processes. To assess the impact of halogen chemistry with numerical models under these distinct conditions, a multiphase mechanism has been developed in the last decades and applied successfully in numerous box and 1D model studies. Contributions from these model studies helped to identify important chemical cycles affecting the composition and chemistry of the troposphere. However, several discrepancies between model results and field measurements remain. Therefore, a major revision of the chemical mechanism has been performed including an update of the kinetic data and the addition of new reaction cycles. The extended mechansims have been evaluated in several model studies with the 1D model MISTRA. Current work focuses at the identification of the most important reaction cycles, which led to significant changes in the concentration-time profiles of several halogen species. Subsequently, the mechanism will be reduced to the most imporatant reactions, which are currently investigated. As regional and global model studies become more important to identify the importance of tropospheric halogen multiphase chemistry, the goal is to derive parameterisations for the most important halogen chemistry cycles, which can than be implemented in regional and global 3D models. In the reduction process, the extented MISTRA version will serve as a benchmark to assess the quality and accuracy of the reduced mechansim versions.

The impact of model peptides on structural and dynamic properties of egg yolk lecithin liposomes - experimental and DFT studies.

PubMed

Wałęsa, Roksana; Man, Dariusz; Engel, Grzegorz; Siodłak, Dawid; Kupka, Teobald; Ptak, Tomasz; Broda, Małgorzata A

2015-07-01

Electron spin resonance (ESR), (1) H-NMR, voltage and resistance experiments were performed to explore structural and dynamic changes of Egg Yolk Lecithin (EYL) bilayer upon addition of model peptides. Two of them are phenylalanine (Phe) derivatives, Ac-Phe-NHMe (1) and Ac-Phe-NMe2 (2), and the third one, Ac-(Z)-ΔPhe-NMe2 (3), is a derivative of (Z)-α,β-dehydrophenylalanine. The ESR results revealed that all compounds reduced the fluidity of liposome's membrane, and the highest activity was observed for compound 2 with N-methylated C-terminal amide bond (Ac-Phe-NMe2 ). This compound, being the most hydrophobic, penetrates easily through biological membranes. This was also observed in voltage and resistance studies. (1) H-NMR studies provided a sound evidence on H-bond interactions between the studied diamides and lecithin polar head. The most significant changes in H-atom chemical shifts and spin-lattice relaxation times T1 were observed for compound 1. Our experimental studies were supported by theoretical calculations. Complexes EYLAc-Phe-NMe2 and EYLAc-(Z)-ΔPhe-NMe2 , stabilized by NH⋅⋅⋅O or/and CH⋅⋅⋅O H-bonds were created and optimized at M06-2X/6-31G(d) level of theory in vacuo and in H2 O environment. According to our molecular-modeling studies, the most probable lecithin site of H-bond interaction with studied diamides is the negatively charged O-atom in phosphate group which acts as H-atom acceptor. Moreover, the highest binding energy to hydrocarbon chains were observed in the case of Ac-Phe-NMe2 (2). Copyright © 2015 Verlag Helvetica Chimica Acta AG, Zürich.

Students' Understanding of the Descriptive and Predictive Nature of Teaching Models in Organic Chemistry

ERIC Educational Resources Information Center

Treagust, David F.; Chittleborough, Gail D.; Mamiala, Thapelo L.

2004-01-01

The purpose of the study was to investigate secondary students' understanding of the descriptive and predictive nature of teaching models used in representing compounds in introductory organic chemistry. Of interest were the relationships between teaching models, scientific models, and students' mental models and expressed models. The results from…

Chromatographic behaviour predicts the ability of potential nootropics to permeate the blood-brain barrier.

PubMed

Farsa, Oldřich

2013-01-01

The log BB parameter is the logarithm of the ratio of a compound's equilibrium concentrations in the brain tissue versus the blood plasma. This parameter is a useful descriptor in assessing the ability of a compound to permeate the blood-brain barrier. The aim of this study was to develop a Hansch-type linear regression QSAR model that correlates the parameter log BB and the retention time of drugs and other organic compounds on a reversed-phase HPLC containing an embedded amide moiety. The retention time was expressed by the capacity factor log k'. The second aim was to estimate the brain's absorption of 2-(azacycloalkyl)acetamidophenoxyacetic acids, which are analogues of piracetam, nefiracetam, and meclofenoxate. Notably, these acids may be novel nootropics. Two simple regression models that relate log BB and log k' were developed from an assay performed using a reversed-phase HPLC that contained an embedded amide moiety. Both the quadratic and linear models yielded statistical parameters comparable to previously published models of log BB dependence on various structural characteristics. The models predict that four members of the substituted phenoxyacetic acid series have a strong chance of permeating the barrier and being absorbed in the brain. The results of this study show that a reversed-phase HPLC system containing an embedded amide moiety is a functional in vitro surrogate of the blood-brain barrier. These results suggest that racetam-type nootropic drugs containing a carboxylic moiety could be more poorly absorbed than analogues devoid of the carboxyl group, especially if the compounds penetrate the barrier by a simple diffusion mechanism.

Atmospheric Composition Change: Climate-Chemistry Interactions

NASA Technical Reports Server (NTRS)

Isaksen, I.S.A.; Granier, C.; Myhre, G.; Bernsten, T. K.; Dalsoren, S. B.; Gauss, S.; Klimont, Z.; Benestad, R.; Bousquet, P.; Collins, W.;

2-Benzylpiperazine: A new scaffold for potent human carbonic anhydrase inhibitors. Synthesis, enzyme inhibition, enantioselectivity, computational and crystallographic studies and in vivo activity for a new class of intraocular pressure lowering agents.

PubMed

Chiaramonte, Niccolò; Bua, Silvia; Ferraroni, Marta; Nocentini, Alessio; Bonardi, Alessandro; Bartolucci, Gianluca; Durante, Mariaconcetta; Lucarini, Laura; Chiapponi, Donata; Dei, Silvia; Manetti, Dina; Teodori, Elisabetta; Gratteri, Paola; Masini, Emanuela; Supuran, Claudiu T; Romanelli, Maria Novella

2018-05-10

Two series of 2-benzylpiperazines have been prepared and tested for the inhibition of physiologically relevant isoforms of human carbonic anhydrases (hCA, EC 4.2.1.1). The new compounds carry on one nitrogen atom of the piperazine ring a sulfamoylbenzamide group as zinc-binding moiety, and different alkyl/acyl/sulfonyl groups on the other nitrogen. Regio- and stero-isomers are described. The majority of these compounds showed Ki values in the low-medium nanomolar range against hCA I, II and IV, but not IX. In many instances interaction with the enzyme was enantioselective. The binding mode has been studied by means of X-ray crystallography and molecular modelling. Two compounds, evaluated in rabbit models of glaucoma, were able to significantly reduce intraocular pressure, making them interesting candidates for further studies. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Facile synthesis, biological evaluation and molecular docking studies of novel substituted azole derivatives

NASA Astrophysics Data System (ADS)

Rafiq, Muhammad; Saleem, Muhammad; Jabeen, Farukh; Hanif, Muhammad; Seo, Sung-Yum; Kang, Sung Kwon; Lee, Ki Hwan

2017-06-01

In this study, we synthesized the series of novel azole derivatives and evaluated for enzyme inhibition assays, corresponding kinetic analysis and molecular modeling. Among the investigated bioassays, the oxadiazole derivatives 4a-k were found potent α-glucosidase inhibitors while the Schiff base derivatives 7a-k exhibited considerable potential toward urease inhibition. The inhibition kinetics for the most active compounds were analyzed by the Lineweaver-Burk plots to investigate the possible binding modes of the synthesized compounds toward the tested proteins. Moreover, the detailed docking studies were performed on the synthesized library of 4a-k and 7a-k to study the molecular interaction and binding mode in the active site of the modeled yeast α-glucosidase and Jack Bean Urease, respectively. It could be inferred from docking results that theoretical studies are in close agreement to that of the experimental results. The structure of one of the compound 7k was characterized by the single crystal X-ray diffraction analysis in order to find out the predominant conformation of the molecules.

Synthesis, and anticonvulsant activity of new amides derived from 3-methyl- or 3-ethyl-3-methyl-2,5-dioxo-pyrrolidin-1-yl-acetic acids.

PubMed

Obniska, Jolanta; Rapacz, Anna; Rybka, Sabina; Góra, Małgorzata; Kamiński, Krzysztof; Sałat, Kinga; Żmudzki, Paweł

2016-04-15

This paper describes the synthesis of the library of 22 new 3-methyl- and 3-ethyl-3-methyl-2,5-dioxo-pyrrolidin-1-yl-acetamides as potential anticonvulsant agents. The maximal electroshock (MES) and the subcutaneous pentylenetetrazole (scPTZ) seizure models were used for screening all the compounds. The 6 Hz model of pharmacoresistant limbic seizures was applied for studying selected derivatives. Six amides were chosen for pharmacological characterization of their antinociceptive activity in the formalin model of tonic pain as well as local anesthetic activity was assessed in mice. The pharmacological data indicate on the broad spectra of activity across the preclinical seizure models. Compounds 10 (ED50=32.08 mg/kg, MES test) and 9 (ED50=40.34 mg/kg, scPTZ test) demonstrated the highest potency. These compounds displayed considerably better safety profiles than clinically relevant antiepileptic drugs phenytoin, ethosuximide, or valproic acid. Several molecules showed antinociceptive and local anesthetic properties. The in vitro radioligand binding studies demonstrated that the influence on the sodium and calcium channels may be one of the essential mechanisms of action. Copyright © 2016. Published by Elsevier Ltd.

Neurotoxicity in Preclinical Models of Occupational Exposure to Organophosphorus Compounds

PubMed Central

Voorhees, Jaymie R.; Rohlman, Diane S.; Lein, Pamela J.; Pieper, Andrew A.

2017-01-01

Organophosphorus (OPs) compounds are widely used as insecticides, plasticizers, and fuel additives. These compounds potently inhibit acetylcholinesterase (AChE), the enzyme that inactivates acetylcholine at neuronal synapses, and acute exposure to high OP levels can cause cholinergic crisis in humans and animals. Evidence further suggests that repeated exposure to lower OP levels insufficient to cause cholinergic crisis, frequently encountered in the occupational setting, also pose serious risks to people. For example, multiple epidemiological studies have identified associations between occupational OP exposure and neurodegenerative disease, psychiatric illness, and sensorimotor deficits. Rigorous scientific investigation of the basic science mechanisms underlying these epidemiological findings requires valid preclinical models in which tightly-regulated exposure paradigms can be correlated with neurotoxicity. Here, we review the experimental models of occupational OP exposure currently used in the field. We found that animal studies simulating occupational OP exposures do indeed show evidence of neurotoxicity, and that utilization of these models is helping illuminate the mechanisms underlying OP-induced neurological sequelae. Still, further work is necessary to evaluate exposure levels, protection methods, and treatment strategies, which taken together could serve to modify guidelines for improving workplace conditions globally. PMID:28149268

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

Neuroprotective Effect of the Marine-Derived Compound 11-Dehydrosinulariolide through DJ-1-Related Pathway in In Vitro and In Vivo Models of Parkinson’s Disease

PubMed Central

Feng, Chien-Wei; Hung, Han-Chun; Huang, Shi-Ying; Chen, Chun-Hong; Chen, Yun-Ru; Chen, Chun-Yu; Yang, San-Nan; Wang, Hui-Min David; Sung, Ping-Jyun; Sheu, Jyh-Horng; Tsui, Kuan-Hao; Chen, Wu-Fu; Wen, Zhi-Hong

2016-01-01

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by tremor, rigidity, bradykinesia, and gait impairment. In a previous study, we found that the marine-derived compound 11-dehydrosinulariolide (11-de) upregulates the Akt/PI3K pathway to protect cells against 6-hydroxydopamine (6-OHDA)-mediated damage. In the present study, SH-SY5Y, zebrafish and rats were used to examine the therapeutic effect of 11-de. The results revealed the mechanism by which 11-de exerts its therapeutic effect: the compound increases cytosolic or mitochondrial DJ-1 expression, and then activates the downstream Akt/PI3K, p-CREB, and Nrf2/HO-1 pathways. Additionally, we found that 11-de could reverse the 6-OHDA-induced downregulation of total swimming distance in a zebrafish model of PD. Using a rat model of PD, we showed that a 6-OHDA-induced increase in the number of turns, and increased time spent by rats on the beam, could be reversed by 11-de treatment. Lastly, we showed that 6-OHDA-induced attenuation in tyrosine hydroxylase (TH), a dopaminergic neuronal marker, in zebrafish and rat models of PD could also be reversed by treatment with 11-de. Moreover, the patterns of DJ-1 expression observed in this study in the zebrafish and rat models of PD corroborated the trend noted in previous in vitro studies. PMID:27763504

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

PubMed

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

2013-02-14

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

Combination of partial least squares regression and design of experiments to model the retention of pharmaceutical compounds in supercritical fluid chromatography.

PubMed

Andri, Bertyl; Dispas, Amandine; Marini, Roland Djang'Eing'a; Hubert, Philippe; Sassiat, Patrick; Al Bakain, Ramia; Thiébaut, Didier; Vial, Jérôme

2017-03-31

This work presents a first attempt to establish a model of the retention behaviour for pharmaceutical compounds in gradient mode SFC. For this purpose, multivariate statistics were applied on the basis of data gathered with the Design of Experiment (DoE) methodology. It permitted to build optimally the experiments needed, and served as a basis for providing relevant physicochemical interpretation of the effects observed. Data gathered over a broad experimental domain enabled the establishment of well-fit linear models of the retention of the individual compounds in presence of methanol as co-solvent. These models also allowed the appreciation of the impact of each experimental parameter and their factorial combinations. This approach was carried out with two organic modifiers (i.e. methanol and ethanol) and provided comparable results. Therefore, it demonstrates the feasibility to model retention in gradient mode SFC for individual compounds as a function of the experimental conditions. This approach also permitted to highlight the predominant effect of some parameters (e.g. gradient slope and pressure) on the retention of compounds. Because building of individual models of retention was possible, the next step considered the establishment of a global model of the retention to predict the behaviour of given compounds on the basis of, on the one side, the physicochemical descriptors of the compounds (e.g. Linear Solvation Energy Relationship (LSER) descriptors) and, on the other side, of the experimental conditions. This global model was established by means of partial least squares regression for the selected compounds, in an experimental domain defined by the Design of Experiment (DoE) methodology. Assessment of the model's predictive capabilities revealed satisfactory agreement between predicted and actual retention (i.e. R 2 =0.942, slope=1.004) of the assessed compounds, which is unprecedented in the field. Copyright © 2017 Elsevier B.V. All rights reserved.

Formation process and mechanism of iron-nitride compounds on Si(1 1 1)-7 × 7-CH3OH surface

NASA Astrophysics Data System (ADS)

Li, Wenxin; Ding, Wanyu; Ju, Dongying; Tanaka, Ken-ichi; Komori, Fumio

2018-07-01

Fe atoms were deposited on Si(1 1 1)-7 × 7 restructured surface, which had been covered by CH3OH molecules. A newly formed surface is stabilized by a quasi-potential made by breaking, and adsorbed atoms or molecules can be stabilized by forming "quasi-compounds". Then, aim to greatly enhance the magnetic properties of the memory units, nitriding experiments were implemented on the existing Fe compounds. With the in-situ observation of STM, a series of Fe3N structures make up the newly emerged iron-nitride compounds, showing good linear characteristics. By adjusting the concentration, this study further explored its formation process and compounds models.

Translational diffusion coefficients of volatile compounds in various aqueous solutions at low and subzero temperatures.

PubMed

Covarrubias-Cervantes, Marco; Champion, Dominique; Debeaufort, Frédéric; Voilley, Andrée

2005-08-24

Translational diffusion coefficients (D(12)) of volatile compounds were measured in model media with the profile concentration method. The influence of sample temperature (from 25 to -10 degrees C) was studied on translational diffusion in sucrose or maltodextrin solutions at various concentrations. Results show that diffusivity of volatile compounds in sucrose solutions is controlled by temperature, molecule size, and the viscosity of the liquid phase as expected with the Stokes-Einstein equation; moreover, physicochemical interactions between volatile compounds and the medium are determinant for diffusion estimation. At negative temperature, the winding path induced by an ice crystal content of >70% lowered volatile compound diffusion. On the contrary, no influence on translational diffusion coefficients was observed for lower ice content.

Novel tetracyclic benzo[b]carbazolones as highly potent and orally bioavailable ALK inhibitors: design, synthesis, and structure-activity relationship study.

PubMed

Jiang, Xiaolong; Zhou, Ji; Ai, Jing; Song, Zilan; Peng, Xia; Xing, Li; Xi, Yong; Guo, Junfeng; Yao, Qizheng; Ding, Jian; Geng, Meiyu; Zhang, Ao

2015-11-13

Four series of tetracyclic benzo[b]carbazolone compounds possessing more rotatable bonds and higher molecular flexibility were designed by either inserting a linker within the C8-side chain or by opening the middle ketone ring on the basis of compound 5 (Alectinib, CH5424802). Compound 15b was identified showing nearly identical high potency against both wild-type and the gatekeeper mutant ALK kinase (3.4 vs 3.9 nM). This compound has favorable PK profile with an oral bioavailability of 67.1% in rats. Moreover, compound 15b showed significant growth inhibition against ALK driven cancer cells and KARPAS-299 xenograft model. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

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

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.

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.

Therapeutic effect of the natural compounds baicalein and baicalin on autoimmune diseases.

PubMed

Xu, Jian; Liu, Jinlong; Yue, Guolin; Sun, Mingqiang; Li, Jinliang; Xiu, Xia; Gao, Zhenzhong

2018-05-23

A series of natural compounds have been implicated to be useful in regulating the pathogenesis of various autoimmune diseases. The present study demonstrated that the Scutellariae radix compounds baicalein and baicalin may serve as drugs for the treatment of autoimmune diseases, including rheumatoid arthritis and inflammatory bowel disease. Following the administration of baicalein and baicalin in vivo, T cell‑mediated autoimmune diseases in the mouse model were profoundly ameliorated: In the collagen‑induced arthritis model (CIA), the severity of the disease was reduced by baicalein and, consistently, baicalein was demonstrated to suppress T cell proliferation in CIA mice. In the dextran sodium sulfate (DSS)‑induced colitis model, the disease was attenuated by baicalin, and baicalin promoted colon epithelial cell (CEC) proliferation in vitro. The present study further revealed that the mRNA expression of signal transducer and activator of transcription (STAT)3 and STAT4 in the tyrosine‑protein kinase JAK‑STAT signaling pathway in T cells was downregulated by baicalein, contributing to its regulation of T cell proliferation. However, in the DSS model, the STAT4 transcription in CECs, which are the target cells of activated T cells in the gut, was downregulated by baicalin, suggesting that baicalein and baicalin mediated similar STAT expression in different cell types in autoimmune diseases. In conclusion, the similarly structured compounds baicalein and baicalin selectively exhibited therapeutic effects on autoimmune diseases by regulating cell proliferation and STAT gene expression, albeit in different cell types.

Predicting targets of compounds against neurological diseases using cheminformatic methodology

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Novel Locally Active Estrogens Accelerate Cutaneous Wound Healing-Part 2.

PubMed

Brufani, Mario; Rizzi, Nicoletta; Meda, Clara; Filocamo, Luigi; Ceccacci, Francesca; D'Aiuto, Virginia; Bartoli, Gabriele; Bella, Angela La; Migneco, Luisa M; Bettolo, Rinaldo Marini; Leonelli, Francesca; Ciana, Paolo; Maggi, Adriana

2017-05-31

Estrogen deprivation is associated with delayed healing, while estrogen replacement therapy (ERT) accelerates acute wound healing and protects against development of chronic wounds. However, current estrogenic molecules have undesired systemic effects, thus the aim of our studies is to generate new molecules for topic administration that are devoid of systemic effects. Following a preliminary study, the new 17β-estradiol derivatives 1 were synthesized. The estrogenic activity of these novel compounds was evaluated in vitro using the cell line ERE-Luc B17 stably transfected with an ERE-Luc reporter. Among the 17β-estradiol derivatives synthesized, compounds 1e and 1f showed the highest transactivation potency and were therefore selected for the study of their systemic estrogenic activity. The study of these compounds in the ERE-Luc mouse model demonstrated that both compounds lack systemic effects when administered in the wound area. Furthermore, wound-healing experiments showed that 1e displays a significant regenerative and anti-inflammatory activity. It is therefore confirmed that this class of compounds are suitable for topical administration and have a clear beneficial effect on wound healing.

Interest of new alkylsulfonylhydrazide-type compound in the treatment of alcohol use disorders.

PubMed

Jeanblanc, Jérôme; Bourguet, Erika; Sketriené, Diana; Gonzalez, Céline; Moroy, Gautier; Legastelois, Rémi; Létévé, Mathieu; Trussardi-Régnier, Aurélie; Naassila, Mickaël

2018-06-01

Recent preclinical research suggested that histone deacetylase inhibitors (HDACIs) and specifically class I HDAC selective inhibitors might be useful to treat alcohol use disorders (AUDs). The objective of this study was to find a new inhibitor of the HDAC-1 isoenzyme and to test its efficacy in an animal model of AUDs. In the present study, we prepared new derivatives bearing sulfonylhydrazide-type zinc-binding group (ZBG) and evaluated these compounds in vitro on HDAC-1 isoenzyme. The most promising compound was tested on ethanol operant self-administration and relapse in rats. We showed that the alkylsulfonylhydrazide-type compound (ASH) reduced by more than 55% the total amount of ethanol consumed after one intracerebroventricular microinjection, while no effect was observed on motivation of the animals to consume ethanol. In addition, one ASH injection in the central amygdala reduced relapse. Our study demonstrated that a new compound designed to target HDAC-1 is effective in reducing ethanol intake and relapse in rats and further confirm the interest of pursuing research to study the exact mechanism by which such inhibitor may be useful to treat AUDs.

Receptor model comparisons and wind direction analyses of volatile organic compounds and submicrometer particles in an arid, binational, urban air shed.

PubMed

Mukerjee, Shaibal; Norris, Gary A; Smith, Luther A; Noble, Christopher A; Neas, Lucas M; Ozkaynak, A Halûk; Gonzales, Melissa

2004-04-15

The relationship between continuous measurements of volatile organic compounds sources and particle number was evaluated at a Photochemical Assessment Monitoring Station Network (PAMS) site located near the U.S.-Mexico Border in central El Paso, TX. Sources of volatile organic compounds (VOCs) were investigated using the multivariate receptor model UNMIX and the effective variance least squares receptor model known as Chemical Mass Balance (CMB, Version 8.0). As expected from PAMS measurements, overall findings from data screening as well as both receptor models confirmed that mobile sources were the major source of VOCs. Comparison of hourly source contribution estimates (SCEs) from the two receptor models revealed significant differences in motor vehicle exhaust and evaporative gasoline contributions. However, the motor vehicle exhaust contributions were highly correlated with each other. Motor vehicle exhaust was also correlated with the ultrafine and accumulation mode particle count, which suggests that motor vehicle exhaust is a source of these particles at the measurement site. Wind sector analyses were performed using the SCE and pollutant data to assess source location of VOCs, particle count, and criteria pollutants. Results from this study have application to source apportionment studies and mobile source emission control strategies that are ongoing in this air shed.

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

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

Teng, S.; Tebby, C.

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-timemore » cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.« less

Catalytic cracking of model compounds of bio-oil over HZSM-5 and the catalyst deactivation.

PubMed

Chen, Guanyi; Zhang, Ruixue; Ma, Wenchao; Liu, Bin; Li, Xiangping; Yan, Beibei; Cheng, Zhanjun; Wang, Tiejun

2018-08-01

The catalytic cracking upgrading reactions over HZSM-5 of different model compounds of bio-oil have been studied with a self-designed fluid catalytic cracking (FCC) equipment. Typical bio-oil model compounds, such as acetic acid, guaiacol, n-heptane, acetol and ethyl acetate, were chosen to study the products distribution, reaction pathway and deactivation of catalysts. The results showed: C 6 -C 8 aromatic hydrocarbons, C 2 -C 4 olefins, C 1 -C 5 alkanes, CO and CO 2 were the main products, and the selectivity of olefins was: ethylene>propylene>butylene. Catalyst characterization methods, such as FI-IR, TG-TPO and Raman, were used to study the deactivation mechanism of catalysts. According to the catalyst characterization results, a catalyst deactivation mechanism was proposed as follows: Firstly, the precursor which consisted of a large number of long chain saturated aliphatic hydrocarbons and a small amount CC of aromatics formed on the catalyst surface. Then the active sites of catalysts had been covered, the coke type changed from thermal coke to catalytic coke and gradually blocked the channels of the molecular sieve, which accelerated the deactivation of catalyst. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification of compounds protective against G93A-SOD1 toxicity for the treatment of amyotrophic lateral sclerosis.

PubMed

Benmohamed, Radhia; Arvanites, Anthony C; Kim, Jinho; Ferrante, Robert J; Silverman, Richard B; Morimoto, Richard I; Kirsch, Donald R

2011-03-01

The underlying cause of amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disorder, remains unknown. However, there is strong evidence that one pathophysiological mechanism, toxic protein misfolding and/or aggregation, may trigger motor neuron dysfunction and loss. Since the clinical and pathological features of sporadic and familial ALS are indistinguishable, all forms of the disease may be better understood and ultimately treated by studying pathogenesis and therapy in models expressing mutant forms of SOD1. We developed a cellular model in which cell death depended on the expression of G93A-SOD1, a mutant form of superoxide dismutase found in familial ALS patients that produces toxic protein aggregates. This cellular model was optimized for high throughput screening to identify protective compounds from a >50,000 member chemical library. Three novel chemical scaffolds were selected for further study following screen implementation, counter-screening and secondary testing, including studies with purchased analogs. All three scaffolds blocked SOD1 aggregation in high content screening assays and data on the optimization and further characterization of these compounds will be reported separately. These data suggest that optimization of these chemicals scaffolds may produce therapeutic candidates for ALS patients.

Superacid Catalyzed Coal Conversion Chemistry. 1st and 2nd Quarterly Technical Progress Reports, September 1, 1983-March 30, 1984.

DOE R&D Accomplishments Database

Olah, G. A.

1984-01-01

In our laboratories we have previously developed a mild coal conversion process. This involves the use of a superacid system consisting of HF and BF{sub 3} in presence of hydrogen and/or a hydrogen donor solvent. In order to understand the chemistry involved in the process of depolymerization of coal by the HF:BF{sub 3}:H{sub 2} system we are carrying out a systematic study of a number of coal model compounds. The model compounds selected for present study have two benzene rings connected with various bridging units such as alkylidene, ether, sulfide etc. From studies so far carried out it appears that high pyridine extractibilities achieved by treating coal at temperature below 100 degrees C results from the cleavage of bridges such as present in bibenzyl, diphenyl methane, dibenzyl ether, dibenzyl sulfide etc. On the other hand the increased cyclohexane extractibility and distillability observed at relatively higher temperatures and hydrogen pressures reflects the hydrogenation and cleavage of the aromatic backbone in coal structure similar to what is seen in the conversion of model compounds such as biphenyl, diphenyl ether, diphenyl sulfide, anthracene, etc.

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.

Numerical Modeling of High-Temperature Corrosion Processes

NASA Technical Reports Server (NTRS)

Nesbitt, James A.

1995-01-01

Numerical modeling of the diffusional transport associated with high-temperature corrosion processes is reviewed. These corrosion processes include external scale formation and internal subscale formation during oxidation, coating degradation by oxidation and substrate interdiffusion, carburization, sulfidation and nitridation. The studies that are reviewed cover such complexities as concentration-dependent diffusivities, cross-term effects in ternary alloys, and internal precipitation where several compounds of the same element form (e.g., carbides of Cr) or several compounds exist simultaneously (e.g., carbides containing varying amounts of Ni, Cr, Fe or Mo). In addition, the studies involve a variety of boundary conditions that vary with time and temperature. Finite-difference (F-D) techniques have been applied almost exclusively to model either the solute or corrodant transport in each of these studies. Hence, the paper first reviews the use of F-D techniques to develop solutions to the diffusion equations with various boundary conditions appropriate to high-temperature corrosion processes. The bulk of the paper then reviews various F-D modeling studies of diffusional transport associated with high-temperature corrosion.

From biomass to advanced bio-fuel by catalytic pyrolysis/hydro-processing: hydrodeoxygenation of bio-oil derived from biomass catalytic pyrolysis.

PubMed

Wang, Yuxin; He, Tao; Liu, Kaituo; Wu, Jinhu; Fang, Yunming

2012-03-01

Compared hydrodeoxygenation experimental studies of both model compounds and real bio-oil derived from biomass fast pyrolysis and catalytic pyrolysis was carried out over two different supported Pt catalysts. For the model compounds, the deoxygenation degree of dibenzofuran was higher than that of cresol and guaiacol over both Pt/Al(2)O(3) and the newly developed Pt supported on mesoporous zeolite (Pt/MZ-5) catalyst, and the deoxygenation degree of cresol over Pt/MZ-5 was higher than that over Pt/Al(2)O(3). The results indicated that hydrodeoxygenation become much easier upon oxygen reduction. Similar to model compounds study, the hydrodeoxygenation of the real bio-oil derived from catalytic pyrolysis was much easier than that from fast pyrolysis over both Pt catalysts, and the Pt/MZ-5 again shows much higher deoxygenation ability than Pt/Al(2)O(3). Clearly synergy between catalytic pyrolysis and bio-oil hydro-processing was found in this paper and this finding will lead an advanced biofuel production pathway in the future. Copyright © 2012 Elsevier Ltd. All rights reserved.

Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening

NASA Astrophysics Data System (ADS)

Halim, Sobia A.; Khan, Shanza; Khan, Ajmal; Wadood, Abdul; Mabood, Fazal; Hussain, Javid; Al-Harrasi, Ahmed

2017-10-01

Dengue fever is an emerging public health concern, with several million viral infections occur annually, for which no effective therapy currently exist. Non-structural protein 3 (NS-3) Helicase encoded by the dengue virus (DENV) is considered as a potential drug target to design new and effective drugs against dengue. Helicase is involved in unwinding of dengue RNA. This study was conducted to design new NS-3 Helicase inhibitor by in silico ligand- and structure based approaches. Initially ligand-based pharmacophore model was generated that was used to screen a set of 1201474 compounds collected from ZINC Database. The compounds matched with the pharmacophore model were docked into the active site of NS-3 helicase. Based on docking scores and binding interactions, twenty five compounds are suggested to be potential inhibitors of NS3 Helicase. The pharmacokinetic properties of these hits were predicted. The selected hits revealed acceptable ADMET properties. This study identified potential inhibitors of NS-3 Helicase in silico, and can be helpful in the treatment of Dengue.

Study of Synthesis of N-Nitroborazine Compounds. I. Nitryl Chloride as Nitrating Agent.

DTIC Science & Technology

dinitrogen tetroxide (N2O4) as the solid complexes of boron trifluoride (BF3). Nearly water-white nitryl chloride was obtained in this manner. A tinge of...yellow was attributed to the presence of chlorine . The reaction of nitryl chloride with a model compound, lithium dimethylamide, was found to yield

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...

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

A comprehensive study of the optoelectronic properties of donor-acceptor based derivatives of 1,3,4-oxadiazole

NASA Astrophysics Data System (ADS)

Joshi, Ankita; Ramachandran, C. N.

2017-07-01

A variety of 1,3,4-oxadiazole derivatives based on electron- donor pyrrole and -acceptor nitro groups are modelled. Various isomers of pyrole-oxadiazole-nitro unit and its dimer linked to substituted and unsubstituted phenyl group are studied using the dispersion corrected density functional theoretical method. The electron density distribution in frontier orbitals of the phenyl-spacer compounds bearing amino and phenylamino groups indicates the possibility of intramolecular charge transfer. The isomers of phenyl-spacer compounds absorb in visible region of electromagnetic spectrum. The compounds show high values of light harvesting efficiency, despite the weak anchoring nature of nitro groups.

In silico strain optimization by adding reactions to metabolic models.

PubMed

Correia, Sara; Rocha, Miguel

2012-07-24

Nowadays, the concerns about the environment and the needs to increase the productivity at low costs, demand for the search of new ways to produce compounds with industrial interest. Based on the increasing knowledge of biological processes, through genome sequencing projects, and high-throughput experimental techniques as well as the available computational tools, the use of microorganisms has been considered as an approach to produce desirable compounds. However, this usually requires to manipulate these organisms by genetic engineering and/ or changing the enviromental conditions to make the production of these compounds possible. In many cases, it is necessary to enrich the genetic material of those microbes with hereologous pathways from other species and consequently adding the potential to produce novel compounds. This paper introduces a new plug-in for the OptFlux Metabolic Engineering platform, aimed at finding suitable sets of reactions to add to the genomes of selected microbes (wild type strain), as well as finding complementary sets of deletions, so that the mutant becomes able to overproduce compounds with industrial interest, while preserving their viability. The necessity of adding reactions to the metabolic model arises from existing gaps in the original model or motivated by the productions of new compounds by the organism. The optimization methods used are metaheuristics such as Evolutionary Algorithms and Simulated Annealing. The usefulness of this plug-in is demonstrated by a case study, regarding the production of vanillin by the bacterium E. coli.

In silico strain optimization by adding reactions to metabolic models.

PubMed

Correia, Sara; Rocha, Miguel

2012-12-01

Nowadays, the concerns about the environment and the needs to increase the productivity at low costs, demand for the search of new ways to produce compounds with industrial interest. Based on the increasing knowledge of biological processes, through genome sequencing projects, and high-throughput experimental techniques as well as the available computational tools, the use of microorganisms has been considered as an approach to produce desirable compounds. However, this usually requires to manipulate these organisms by genetic engineering and/ or changing the enviromental conditions to make the production of these compounds possible. In many cases, it is necessary to enrich the genetic material of those microbes with hereologous pathways from other species and consequently adding the potential to produce novel compounds. This paper introduces a new plug-in for the OptFlux Metabolic Engineering platform, aimed at finding suitable sets of reactions to add to the genomes of selected microbes (wild type strain), as well as finding complementary sets of deletions, so that the mutant becomes able to overproduce compounds with industrial interest, while preserving their viability. The necessity of adding reactions to the metabolic model arises from existing gaps in the original model or motivated by the productions of new compounds by the organism. The optimization methods used are metaheuristics such as Evolutionary Algorithms and Simulated Annealing. The usefulness of this plug-in is demonstrated by a case study, regarding the production of vanillin by the bacterium E. coli.

Application of computer assisted combinatorial chemistry in antivirial, antimalarial and anticancer agents design

NASA Astrophysics Data System (ADS)

Burello, E.; Bologa, C.; Frecer, V.; Miertus, S.

Combinatorial chemistry and technologies have been developed to a stage where synthetic schemes are available for generation of a large variety of organic molecules. The innovative concept of combinatorial design assumes that screening of a large and diverse library of compounds will increase the probability of finding an active analogue among the compounds tested. Since the rate at which libraries are screened for activity currently constitutes a limitation to the use of combinatorial technologies, it is important to be selective about the number of compounds to be synthesized. Early experience with combinatorial chemistry indicated that chemical diversity alone did not result in a significant increase in the number of generated lead compounds. Emphasis has therefore been increasingly put on the use of computer assisted combinatorial chemical techniques. Computational methods are valuable in the design of virtual libraries of molecular models. Selection strategies based on computed physicochemical properties of the models or of a target compound are introduced to reduce the time and costs of library synthesis and screening. In addition, computational structure-based library focusing methods can be used to perform in silico screening of the activity of compounds against a target receptor by docking the ligands into the receptor model. Three case studies are discussed dealing with the design of targeted combinatorial libraries of inhibitors of HIV-1 protease, P. falciparum plasmepsin and human urokinase as potential antivirial, antimalarial and anticancer drugs. These illustrate library focusing strategies.

Synthesis, anti-inflammatory evaluation in vivo and docking studies of some new 5-(benzo[b]furan-2-ylmethyl)-6-methyl-pyridazin-3(2H)-one derivatives

NASA Astrophysics Data System (ADS)

Boukharsa, Youness; Lakhlili, Wiame; El harti, Jaouad; Meddah, Bouchra; Tiendrebeogo, Ramata Yvette; Taoufik, Jamal; El Abbes Faouzi, My; Ibrahimi, Azeddine; Ansar, M'hammed

2018-02-01

Seven novel 5-(benzo[b]furan-2-ylmethyl)-6-methyl-pyridazin-3(2H)-one derivatives (6a to 6g) have been synthesized by the condensation of appropriate 3-(benzofuran-2-ylmethylene)-4-oxopentanoic acid and hydrazine hydrate in ethanol. Structures of all compounds were elucidated by elemental analysis, IR, 1H NMR and 13C NMR. These compounds were tested for their anti-inflammatory activity in carrageenan-induced rat paw edema model. In silico molecular docking study has been executed to study the binding interactions of the synthesized compounds with COX-2 protein. Compounds 6a, 6b, 6e and 6g showed a good anti-inflammatory activity at 50 mg/kg compared with the indometacin at 10 mg/kg and the aspirin at 150 mg/kg and good binding affinity with COX-2.

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.

Stereoisomeric effects on dynamic viscosity versus pressure and temperature for the system cis- + trans-decalin

NASA Astrophysics Data System (ADS)

Miyake, Yasufumi; Boned, Christian; Baylaucq, Antoine; Bessières, David; Zéberg-Mikkelsen, Claus K.; Galliéro, Guillaume; Ushiki, Hideharu

2007-07-01

In order to study the influence of stereoisomeric effects on the dynamic viscosity, an extensive experimental study of the viscosity of the binary system composed of the two stereoisomeric molecular forms of decalin - cis and trans - has been carried out for five different mixtures at three temperatures (303.15, 323.15 and 343.15) K and six isobars up to 100 MPa with a falling-body viscometer (a total of 90 points). The experimental relative uncertainty is estimated to be 2%. The variations of dynamic viscosity versus composition are discussed with respect to their behavior due to stereoisomerism. Four different models with a physical and theoretical background are studied in order to investigate how they take the stereoisomeric effect into account through their required model parameters. The evaluated models are based on the hard-sphere scheme, the concepts of the free-volume and the friction theory, and a model derived from molecular dynamics. Overall, a satisfactory representation of the viscosity of this binary system is found for the different models within the considered ( T, p) range taken into account their simplicity. All the models are able to distinguish between the two stereoisomeric decalin compounds. Further, based on the analysis of the model parameters performed on the pure compounds, it has been found that the use of simple mixing rules without introducing any binary interaction parameters are sufficient in order to predict the viscosity of cis + trans-decalin mixtures with the same accuracy in comparison with the experimental values as obtained for the pure compounds. In addition to these models, a semi-empirical self-referencing model and the simple mixing laws of Grunberg-Nissan and Katti-Chaudhri are also applied in the representation of the viscosity behavior of these systems.

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.

Preclinical characterization of three transient receptor potential vanilloid receptor 1 antagonists for early use in human intradermal microdose analgesic studies.

PubMed

Sjögren, E; Halldin, M M; Stålberg, O; Sundgren-Andersson, A K

2018-05-01

The transient receptor potential vanilloid receptor 1 (TRPV1) is a nonselective cation channel involved in the mediation of peripheral pain to the central nervous system. As such, the TRPV1 is an accessible molecular target that lends itself well to the understanding of nociceptive signalling. This study encompasses preclinical investigations of three molecules with the prospect to establish them as suitable analgesic model compounds in human intradermal pain relief studies. The inhibitory effectiveness was evaluated by means of in vitro assays, TRPV1 expressing Chinese hamster ovary cells (CHO-K1) and rat dorsal root ganglion cultures in fluorescent imaging plate reader and whole cell patch clamp systems, as well as in vivo by capsaicin-evoked pain-related behavioural response studies in rat. Secondary pharmacology, pharmacokinetics and preclinical safety were also assessed. In vitro, all three compounds were effective at inhibiting capsaicin-activated TRPV1. The concentration producing 50% inhibition (IC 50 ) determined was in the range of 3-32 nmol/L and 10-501 nmol/L using CHO-K1 and dorsal root ganglion cultures, respectively. In vivo, all compounds showed dose-dependent reduction in capsaicin-evoked pain-related behavioural responses in rat. None of the three compounds displayed any significant activity on any of the secondary targets tested. The compounds were also shown to be safe from a toxicological, drug metabolism and pharmacokinetic perspective, for usage in microgram doses in the human skin. The investigated model compounds displayed ideal compound characteristics as pharmacological and translational tools to address efficacy on the human native TRPV1 target in human skin in situ. This work details the pharmaceutical work-up of three TRPV1-active investigational compounds, to obtain regulatory approval, for subsequent use in humans. This fast and cost-effective preclinical development path may impact research beyond the pain management area, as it allows human target engagement information gathering early in drug development. © 2018 European Pain Federation - EFIC®.

Translational neuropharmacology and the appropriate and effective use of animal models.

PubMed

Green, A R; Gabrielsson, J; Fone, K C F

2011-10-01

This issue of the British Journal of Pharmacology is dedicated to reviews of the major animal models used in neuropharmacology to examine drugs for both neurological and psychiatric conditions. Almost all major conditions are reviewed. In general, regulatory authorities require evidence for the efficacy of novel compounds in appropriate animal models. However, the failure of many compounds in clinical trials following clear demonstration of efficacy in animal models has called into question both the value of the models and the discovery process in general. These matters are expertly reviewed in this issue and proposals for better models outlined. In this editorial, we further suggest that more attention be made to incorporate pharmacokinetic knowledge into the studies (quantitative pharmacology). We also suggest that more attention be made to ensure that full methodological details are published and recommend that journals should be more amenable to publishing negative data. Finally, we propose that new approaches must be used in drug discovery so that preclinical studies become more reflective of the clinical situation, and studies using animal models mimic the anticipated design of studies to be performed in humans, as closely as possible. © 2011 The Authors. British Journal of Pharmacology © 2011 The British Pharmacological Society.

Different Therapeutic Outcomes of Benznidazole and VNI Treatments in Different Genders in Mouse Experimental Models of Trypanosoma cruzi Infection

PubMed Central

Guedes-da-Silva, F. H.; Batista, D. G. J.; da Silva, C. F.; Meuser, M. B.; Simões-Silva, M. R.; de Araújo, J. S.; Ferreira, C. G.; Moreira, O. C.; Britto, C.; Lepesheva, G. I.

2015-01-01

The lack of translation between preclinical assays and clinical trials for novel therapies for Chagas disease (CD) indicates a need for more feasible and standardized protocols and experimental models. Here, we investigated the effects of treatment with benznidazole (Bz) and with the potent experimental T. cruzi CYP51 inhibitor VNI in mouse models of Chagas disease by using different animal genders and parasite strains and employing distinct types of therapeutic schemes. Our findings confirm that female mice are less vulnerable to the infection than males, show that male models are less susceptible to treatment with both Bz and VNI, and thus suggest that male models are much more suitable for selection of the most promising antichagasic agents. Additionally, we have found that preventive protocols (compound given at 1 dpi) result in higher treatment success rates, which also should be avoided during advanced steps of in vivo trials of novel anti-T. cruzi drug candidates. Another consideration is the relevance of immunosuppression methods in order to verify the therapeutic profile of novel compounds, besides the usefulness of molecular diagnostic tools (quantitative PCR) to ascertain compound efficacy in experimental animals. Our study aims to contribute to the development of more reliable methods and decision gates for in vivo assays of novel antiparasitic compounds in order to move them from preclinical to clinical trials for CD. PMID:26416857

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

Model for High-Throughput Screening of Multitarget Drugs in Chemical Neurosciences: Synthesis, Assay, and Theoretic Study of Rasagiline Carbamates

PubMed Central

2013-01-01

The disappointing results obtained in recent clinical trials renew the interest in experimental/computational techniques for the discovery of neuroprotective drugs. In this context, multitarget or multiplexing QSAR models (mt-QSAR/mx-QSAR) may help to predict neurotoxicity/neuroprotective effects of drugs in multiple assays, on drug targets, and in model organisms. In this work, we study a data set downloaded from CHEMBL; each data point (>8000) contains the values of one out of 37 possible measures of activity, 493 assays, 169 molecular or cellular targets, and 11 different organisms (including human) for a given compound. In this work, we introduce the first mx-QSAR model for neurotoxicity/neuroprotective effects of drugs based on the MARCH-INSIDE (MI) method. First, we used MI to calculate the stochastic spectral moments (structural descriptors) of all compounds. Next, we found a model that classified correctly 2955 out of 3548 total cases in the training and validation series with Accuracy, Sensitivity, and Specificity values > 80%. The model also showed excellent results in Computational-Chemistry simulations of High-Throughput Screening (CCHTS) experiments, with accuracy = 90.6% for 4671 positive cases. Next, we reported the synthesis, characterization, and experimental assays of new rasagiline derivatives. We carried out three different experimental tests: assay (1) in the absence of neurotoxic agents, assay (2) in the presence of glutamate, and assay (3) in the presence of H2O2. Compounds 11 with 27.4%, 8 with 11.6%, and 9 with 15.4% showed the highest neuroprotective effects in assays (1), (2), and (3), respectively. After that, we used the mx-QSAR model to carry out a CCHTS of the new compounds in >400 unique pharmacological tests not carried out experimentally. Consequently, this model may become a promising auxiliary tool for the discovery of new drugs for the treatment of neurodegenerative diseases. PMID:23855599

Synthesis, biological evaluation and structure-activity correlation study of a series of imidazol-based compounds as Candida albicans inhibitors.

PubMed

Moraca, Francesca; De Vita, Daniela; Pandolfi, Fabiana; Di Santo, Roberto; Costi, Roberta; Cirilli, Roberto; D'Auria, Felicia Diodata; Panella, Simona; Palamara, Anna Teresa; Simonetti, Giovanna; Botta, Maurizio; Scipione, Luigi

2014-08-18

A new series of 2-(1H-imidazol-1-yl)-1-phenylethanol derivatives was synthesized. The antifungal activity was evaluated in vitro against different fungal species. The biological results show that the most active compounds possess an antifungal activity comparable or higher than Fluconazole against Candida albicans, non-albicans Candida species, Cryptococcus neoformans and dermathophytes. Because of their racemic nature, the most active compounds 5f and 6c were tested as pure enantiomers. For 6c the (R)-enantiomer resulted more active than the (S)-one, otherwise for 5f the (S)-enantiomer resulted the most active. To rationalize the experimental data, a ligand-based computational study was carried out; the results of the modelling study show that (S)-5f and (R)-6c perfectly align to the ligand-based model, showing the same relative configuration. Preliminary studies on the human lung adenocarcinoma epithelial cells (A549) have shown that 6c, 5e and 5f possess a low cytotoxicity. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

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

PubMed

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

2014-07-23

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

Structure Based Virtual Screening Studies to Identify Novel Potential Compounds for GPR142 and Their Relative Dynamic Analysis for Study of Type 2 Diabetes

NASA Astrophysics Data System (ADS)

Kaushik, Aman C.; Kumar, Sanjay; Wei, Dong Q.; Sahi, Shakti

2018-02-01

GPR142 (G protein receptor 142) is a novel orphan GPCR (G protein coupled receptor) belonging to ‘Class A’ of GPCR family and expressed in beta cells of pancreas. In this study, we reported the structure based virtual screening to identify the hit compounds which can be developed as leads for potential agonists. The results were validated through induced fit docking, pharmacophore modeling and system biology approaches. Since, there is no solved crystal structure of GPR142, we attempted to predict the 3D structure followed by validation and then identification of active site using threading and ab initio methods. Also, structure based virtual screening was performed against a total of 1171519 compounds from different libraries and only top 20 best hit compounds were screened and analyzed. Moreover, the biochemical pathway of GPR142 complex with screened compound2 was also designed and compared with experimental data. Interestingly, compound2 showed an increase in insulin production via Gq mediated signaling pathway suggesting the possible role of novel GPR142 agonists in therapy against type 2 diabetes.

Bioconcentration model for non-ionic, polar, and ionizable organic compounds in amphipod.

PubMed

Chen, Ciara Chun; Kuo, Dave Ta Fu

2018-05-01

The present study presents a bioconcentration model for non-ionic, polar, and ionizable organic compounds in amphipod based on first-order kinetics. Uptake rate constant k 1 is modeled as logk1=10.81logKOW + 0.15 (root mean square error [RMSE] = 0.52). Biotransformation rate constant k M is estimated using an existing polyparameter linear free energy relationship model. Respiratory elimination k 2 is calculated as modeled k 1 over theoretical biota-water partition coefficient K biow considering the contributions of lipid, protein, carbohydrate, and water. With negligible contributions of growth and egestion over a typical amphipod bioconcentration experiment, the bioconcentration factor (BCF) is modeled as k 1 /(k M  + k 2 ) (RMSE = 0.68). The proposed model performs well for non-ionic organic compounds (log K OW range = 3.3-7.62) within 1 log-unit error margin. Approximately 12% of the BCFs are underpredicted for polar and ionizable compounds. However, >50% of the estimated k 2 values are found to exceed the total depuration rate constants. Analyses suggest that these excessive k 2 values and underpredicted BCFs reflect underestimation in K biow , which may be improved by incorporating exoskeleton as a relevant partitioning component and refining the membrane-water partitioning model. The immediate needs to build up high-quality experimental k M values, explore the sorptive role of exoskeleton, and investigate the prevalence of k 2 overestimation in other bioconcentration models are also identified. The resulting BCF model can support, within its limitations, the ecotoxicological and risk assessment of emerging polar and ionizable organic contaminants in aquatic environments and advance the science of invertebrate bioaccumulation. Environ Toxicol Chem 2018;37:1378-1386. © 2018 SETAC. © 2018 SETAC.

Polycyclic aromatic hydrocarbons - fate and long-range atmospheric transport studied using a global model, EMAC-SVOC

NASA Astrophysics Data System (ADS)

Octaviani, Mega; Tost, Holger; Lammel, Gerhard

2017-04-01

Polycyclic aromatic hydrocarbons (PAHs) are emitted by incomplete combustion from fossil fuel, vehicles, and biomass burning. They may persist in environmental compartments, pose a health hazard and may bio accumulate along food chains. The ECHAM/MESSy Atmospheric Chemistry (EMAC) model had been used to simulate global tropospheric, stratospheric chemistry and climate. In this study, we improve the model to include simulations of the transport and fate of semi-volatile organic compounds (SVOC). The EMAC-SVOC model takes into account essential environmental processes including gas-particle partitioning, dry and wet deposition, chemical and bio-degradation, and volatilization from sea surface, soils, vegetation, and snow. The model was evaluated against observational data in the Arctic, mid-latitudes, and tropics, and further applied to study total environmental lifetime and long-range transport potential (LRTP) of PAHs. We selected four compounds for study, spanning a wide range of volatility, i.e., phenanthrene, fluoranthene, pyrene, and benzo[a]pyrene. Several LRTP indicators were investigated, including the Arctic contamination potential, meridional spreading, and zonal and meridional fluxes to remote regions.

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

Pressure induced phase transition and elastic properties of cerium mono-nitride (CeN)

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

Yaduvanshi, Namrata, E-mail: namrata-yaduvanshi@yahoo.com; Singh, Sadhna

2016-05-23

In the present paper, we have investigated the high-pressure structural phase transition and elastic properties of cerium mono-nitride. We studied theoretically the structural properties of this compound (CeN) by using the improved interaction potential model (IIPM) approach. This compound exhibits first order crystallographic phase transition from NaCl (B{sub 1}) to tetragonal (BCT) phase at 37 GPa. The phase transition pressures and associated volume collapse obtained from present potential model (IIPM) show a good agreement with available theoretical data.

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.

Evaluating novel synthetic compounds active against Bacillus subtilis and Bacillus cereus spores using Live imaging with SporeTrackerX.

PubMed

Omardien, Soraya; Ter Beek, Alexander; Vischer, Norbert; Montijn, Roy; Schuren, Frank; Brul, Stanley

2018-06-14

An empirical approach was taken to screen a novel synthetic compound library designed to be active against Gram-positive bacteria. We obtained five compounds that were active against spores from the model organism Bacillus subtilis and the food-borne pathogen Bacillus cereus during our population based experiments. Using single cell live imaging we were able to observe effects of the compounds on spore germination and outgrowth. Difference in sensitivity to the compounds could be observed between B. subtilis and B. cereus using live imaging, with minor difference in the minimal inhibitory and bactericidal concentrations of the compounds against the spores. The compounds all delayed the bursting time of germinated spores and affected the generation time of vegetative cells at sub-inhibitory concentrations. At inhibitory concentrations spore outgrowth was prevented. One compound showed an unexpected potential for preventing spore germination at inhibitory concentrations, which merits further investigation. Our study shows the valuable role single cell live imaging can play in the final selection process of antimicrobial compounds.

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.

Recent trends in the development of nanophytobioactive compounds and delivery systems for their possible role in reducing oxidative stress in Parkinson's disease models.

PubMed

Ganesan, Palanivel; Ko, Hyun-Myung; Kim, In-Su; Choi, Dong-Kug

2015-01-01

Oxidative stress plays a very critical role in neurodegenerative diseases, such as Parkinson's disease (PD), which is the second most common neurodegenerative disease among elderly people worldwide. Increasing evidence has suggested that phytobioactive compounds show enhanced benefits in cell and animal models of PD. Curcumin, resveratrol, ginsenosides, quercetin, and catechin are phyto-derived bioactive compounds with important roles in the prevention and treatment of PD. However, in vivo studies suggest that their concentrations are very low to cross blood-brain barrier thereby it limits bioavailability, stability, and dissolution at target sites in the brain. To overcome these problems, nanophytomedicine with the controlled size of 1-100 nm is used to maximize efficiency in the treatment of PD. Nanosizing of phytobioactive compounds enhances the permeability into the brain with maximized efficiency and stability. Several nanodelivery techniques, including solid lipid nanoparticles, nanostructured lipid carriers, nanoliposomes, and nanoniosomes can be used for controlled delivery of nanobioactive compounds to brain. Nanocompounds, such as ginsenosides (19.9 nm) synthesized using a nanoemulsion technique, showed enhanced bioavailability in the rat brain. Here, we discuss the most recent trends and applications in PD, including 1) the role of phytobioactive compounds in reducing oxidative stress and their bioavailability; 2) the role of nanotechnology in reducing oxidative stress during PD; 3) nanodelivery systems; and 4) various nanophytobioactive compounds and their role in PD.

Evaluation of Empirical Data and Modeling Studies to Support Soil Vapor Intrusion Screening Criteria for Petroleum Hydrocarbon Compounds

EPA Science Inventory

This study is an evaluation of empirical data and select modeling studies of the behavior of petroleum hydrocarbon (PHC) vapors in subsurface soils and how they can affect subsurface-to-indoor air vapor intrusion (VI), henceforth referred to as petroleum vapor intrusion or “PVI” ...

EFFECTS OF CHRONIC STRESS ON WILDLIFE POPULATIONS: A POPULATION MODELING APPROACH AND CASE STUDY

EPA Science Inventory

This chapter describes a matrix modeling approach to characterize and project risks to wildlife populations subject to chronic stress. Population matrix modeling was used to estimate effects of one class of environmental contaminants, dioxin-like compounds (DLCs), to populations ...

Roles of molecular hydrogen and a hydrogen donor solvent in the cracking of moal model compounds with dispersed catalysts

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

Suzuki, Toshimitsu; Ikenaga, Na-oki; Sakota, Takahiro

1994-12-31

It is of great importance to evaluate quantitative hydrogen transfer process by using coal model compounds with a hydrogen-donor solvent. Cronauer el al. showed that in the cracking of benzyl phenyl ether the hydrogen required to stabilize free radicals comes from a donor solvent or intramolecular rearrangement and not from gaseous hydrogen in the absence of a catalyst. Korobkov et al. and Schlosberg et al. showed that the thermolysis of benzyl phenyl ether and dibenzyl ether were accomplished by intramolecular rearrangements. Yokokawa et al. reported that tetralin retarded the catalyzed hydrocracking of coal model compounds containing C-C and C-O bonds.more » However, few studies dealt with quantitative discussion in the hydrogen transfer process from a hydrogen-donor solvent or molecular hydrogen to free radicals derived from a model compound except a series of studies by Nicole and co-workers. On the other hand, it is well known that the amount of naphthalene produced from tetralin decreases after the liquefaction of coal in tetralin with catalyst as compared to the liquefaction in the absence of catalysts. To account for this, two mechanisms are proposed. One is that the catalyst hydrogenates naphthalene produced from tetralin, and the other is that the catalyst promotes the direct hydrogen transfer from molecular hydrogen to free radicals. The purpose of this work is to elucidate the role of catalyst and tetralin by means of the quantitative treatment of the hydrogen transfer reaction stabilizing thermally decomposed free radicals. Cracking of benzyl phenyl ether (BPE), dibenzyl ether (DBE), 1,2-diphenylethane, and 1,3-diphenylpropane was studied in tetralin in the presence of highly disposed catalyst.« less

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.

Small constrained SP1-7 analogs bind to a unique site and promote anti-allodynic effects following systemic injection in mice.

PubMed

Jonsson, A; Fransson, R; Haramaki, Y; Skogh, A; Brolin, E; Watanabe, H; Nordvall, G; Hallberg, M; Sandström, A; Nyberg, F

2015-07-09

Previous results have shown that the substance P (SP) N-terminal fragment SP1-7 may attenuate hyperalgesia and produce anti-allodynia in animals using various experimental models for neuropathic pain. The heptapeptide was found to induce its effects through binding to and activating specific sites apart from any known neurokinin or opioid receptor. Furthermore, we have applied a medicinal chemistry program to develop lead compounds mimicking the effect of SP1-7. The present study was designed to evaluate the pharmacological effect of these compounds using the mouse spared nerve injury (SNI) model of chronic neuropathic pain. Also, as no comprehensive screen with the aim to identify the SP1-7 target has yet been performed we screened our lead compound H-Phe-Phe-NH2 toward a panel of drug targets. The extensive target screen, including 111 targets, did not reveal any hit for the binding site among a number of known receptors or enzymes involved in pain modulation. Our animal studies confirmed that SP1-7, but also synthetic analogs thereof, possesses anti-allodynic effects in the mouse SNI model of neuropathic pain. One of the lead compounds, a constrained H-Phe-Phe-NH2 analog, was shown to exhibit a significant anti-allodynic effect. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

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.

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

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.

The Mast Cell Degranulator Compound 48/80 Directly Activates Neurons

PubMed Central

Schemann, Michael; Kugler, Eva Maria; Buhner, Sabine; Eastwood, Christopher; Donovan, Jemma; Jiang, Wen; Grundy, David

2012-01-01

Background Compound 48/80 is widely used in animal and tissue models as a “selective” mast cell activator. With this study we demonstrate that compound 48/80 also directly activates enteric neurons and visceral afferents. Methodology/Principal Findings We used in vivo recordings from extrinsic intestinal afferents together with Ca++ imaging from primary cultures of DRG and nodose neurons. Enteric neuronal activation was examined by Ca++ and voltage sensitive dye imaging in isolated gut preparations and primary cultures of enteric neurons. Intraluminal application of compound 48/80 evoked marked afferent firing which desensitized on subsequent administration. In egg albumen-sensitized animals, intraluminal antigen evoked a similar pattern of afferent activation which also desensitized on subsequent exposure to antigen. In cross-desensitization experiments prior administration of compound 48/80 failed to influence the mast cell mediated response. Application of 1 and 10 µg/ml compound 48/80 evoked spike discharge and Ca++ transients in enteric neurons. The same nerve activating effect was observed in primary cultures of DRG and nodose ganglion cells. Enteric neuron cultures were devoid of mast cells confirmed by negative staining for c-kit or toluidine blue. In addition, in cultured enteric neurons the excitatory action of compound 48/80 was preserved in the presence of histamine H1 and H2 antagonists. The mast cell stabilizer cromolyn attenuated compound 48/80 and nicotine evoked Ca++ transients in mast cell-free enteric neuron cultures. Conclusions/Significance The results showed direct excitatory action of compound 48/80 on enteric neurons and visceral afferents. Therefore, functional changes measured in tissue or animal models may involve a mast cell independent effect of compound 48/80 and cromolyn. PMID:23272218

Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening

NASA Astrophysics Data System (ADS)

Hsieh, Jui-Hua; Wang, Xiang S.; Teotico, Denise; Golbraikh, Alexander; Tropsha, Alexander

2008-09-01

The use of inaccurate scoring functions in docking algorithms may result in the selection of compounds with high predicted binding affinity that nevertheless are known experimentally not to bind to the target receptor. Such falsely predicted binders have been termed `binding decoys'. We posed a question as to whether true binders and decoys could be distinguished based only on their structural chemical descriptors using approaches commonly used in ligand based drug design. We have applied the k-Nearest Neighbor ( kNN) classification QSAR approach to a dataset of compounds characterized as binders or binding decoys of AmpC beta-lactamase. Models were subjected to rigorous internal and external validation as part of our standard workflow and a special QSAR modeling scheme was employed that took into account the imbalanced ratio of inhibitors to non-binders (1:4) in this dataset. 342 predictive models were obtained with correct classification rate (CCR) for both training and test sets as high as 0.90 or higher. The prediction accuracy was as high as 100% (CCR = 1.00) for the external validation set composed of 10 compounds (5 true binders and 5 decoys) selected randomly from the original dataset. For an additional external set of 50 known non-binders, we have achieved the CCR of 0.87 using very conservative model applicability domain threshold. The validated binary kNN QSAR models were further employed for mining the NCGC AmpC screening dataset (69653 compounds). The consensus prediction of 64 compounds identified as screening hits in the AmpC PubChem assay disagreed with their annotation in PubChem but was in agreement with the results of secondary assays. At the same time, 15 compounds were identified as potential binders contrary to their annotation in PubChem. Five of them were tested experimentally and showed inhibitory activities in millimolar range with the highest binding constant Ki of 135 μM. Our studies suggest that validated QSAR models could complement structure based docking and scoring approaches in identifying promising hits by virtual screening of molecular libraries.

Arylthioindole inhibitors of tubulin polymerization. 3. Biological evaluation, structure-activity relationships and molecular modeling studies.

PubMed

La Regina, Giuseppe; Edler, Michael C; Brancale, Andrea; Kandil, Sahar; Coluccia, Antonio; Piscitelli, Francesco; Hamel, Ernest; De Martino, Gabriella; Matesanz, Ruth; Díaz, José Fernando; Scovassi, Anna Ivana; Prosperi, Ennio; Lavecchia, Antonio; Novellino, Ettore; Artico, Marino; Silvestri, Romano

2007-06-14

The new arylthioindole (ATI) derivatives 10, 14-18, and 21-24, which bear a halogen atom or a small size ether group at position 5 of the indole moiety, were compared with the reference compounds colchicine and combretastatin A-4 for biological activity. Derivatives 10, 11, 16, and 21-24 inhibited MCF-7 cell growth with IC50 values <50 nM. A halogen atom (14-17) at position 5 caused a significant reduction in the free energy of binding of compound to tubulin, with a concomitant reduction in cytotoxicity. In contrast, methyl (21) and methoxy (22) substituents at position 5 caused an increase in cytotoxicity. Compound 16, the most potent antitubulin agent, led to a large increase (56%) in HeLa cells in the G2/M phase at 24 h, and at 48 h, 26% of the cells were hyperploid. Molecular modeling studies showed that, despite the absence of the ester moiety present in the previously examined analogues, most of the compounds bind in the colchicine site in the same orientation as the previously studied ATIs. Binding to beta-tubulin involved formation of a hydrogen bond between the indole and Thr179 and positioning of the trimethoxy phenyl group in a hydrophobic pocket near Cys241.

A review of QSAR studies to discover new drug-like compounds actives against leishmaniasis and trypanosomiasis.

PubMed

Castillo-Garit, Juan Alberto; Abad, Concepción; Rodríguez-Borges, J Enrique; Marrero-Ponce, Yovani; Torrens, Francisco

2012-01-01

The neglected tropical diseases (NTDs) affect more than one billion people (one-sixth of the world's population) and occur primarily in undeveloped countries in sub-Saharan Africa, Asia, and Latin America. Available drugs for these diseases are decades old and present an important number of limitations, especially high toxicity and, more recently, the emergence of drug resistance. In the last decade several Quantitative Structure-Activity Relationship (QSAR) studies have been developed in order to identify new organic compounds with activity against the parasites responsible for these diseases, which are reviewed in this paper. The topics summarized in this work are: 1) QSAR studies to identify new organic compounds actives against Chaga's disease; 2) Development of QSAR studies to discover new antileishmanial drusg; 3) Computational studies to identify new drug-like compounds against human African trypanosomiasis. Each topic include the general characteristics, epidemiology and chemotherapy of the disease as well as the main QSAR approaches to discovery/identification of new actives compounds for the corresponding neglected disease. The last section is devoted to a new approach know as multi-target QSAR models developed for antiparasitic drugs specifically those actives against trypanosomatid parasites. At present, as a result of these QSAR studies several promising compounds, active against these parasites, are been indentify. However, more efforts will be required in the future to develop more selective (specific) useful drugs.

Effects of Gas-Wall Partitioning in Teflon Tubing, Instrumentation and Other Materials on Time-Resolved Measurements of Gas-Phase Organic Compounds

NASA Astrophysics Data System (ADS)

Pagonis, D.; Deming, B.; Krechmer, J. E.; De Gouw, J. A.; Jimenez, J. L.; Ziemann, P. J.

2017-12-01

Recently it has been shown that gas-phase organic compounds partition to and from the walls of Teflon environmental chambers. This process is fast, reversible, and can be modeled as absorptive partitioning. Here these studies were extended to investigate gas-wall partitioning inside Teflon tubing by introducing step function changes in the concentration of compounds being sampled and measuring the delay in the response of a proton transfer reaction-mass spectrometer (PTR-MS). We find that these delays are significant for compounds with a saturation vapor concentration (c*) below 106 μg m-3, and that the Teflon tubing and the PTR-MS both contribute to the delays. Tubing delays range from minutes to hours under common sampling conditions and can be accurately predicted by a simple chromatography model across a range of tubing lengths and diameters, flow rates, compound functional groups, and c*. This method also allows one to determine the volatility-dependent response function of an instrument, which can be convolved with the output of the tubing model to correct for delays in instrument response time for these "sticky" compounds. This correction is expected to be of particular interest to researchers utilizing and developing chemical ionization mass spectrometry (CIMS) techniques, since many of the multifunctional organic compounds detected by CIMS show significant tubing and instrument delays. These results also enable better design of sampling systems, in particular when fast instrument response is needed, such as for rapid transients, aircraft, or eddy covariance measurements. Additional results presented here extend this method to quantify the relative sorptive capacities for other commonly used tubing materials, including PFA, FEP, PTFE, PEEK, glass, copper, stainless steel, and passivated steel.

The preclinical testing strategy for the development of novel chemical entities for the treatment of asthma.

PubMed

Hahn, Christian; Erb, Klaus Joseph

2008-06-01

Identifying and developing novel chemical entities (NCE) for the treatment of asthma is a time-consuming process and liabilities that endanger the successful progression of a compound from research into the patient are found throughout all phases of drug discovery. In particular the failure of advanced compounds in clinical studies due to lack of efficacy and/or safety concerns is tremendously costly. Therefore, in order to try and reduce the failure rate in clinical trials various in vitro and in vivo tests are performed during preclinical development, to rapidly identify liabilities, eliminate high risk compounds and promote promising potential drug candidates. To achieve this objective, numerous prerequisites have to be met regarding the physico-chemical properties of the compound, and bioactivity or model systems are needed to rate the therapeutic potential of new compounds. Drug liabilities such as target and species specificity, formulation issues, pharmacokinetics as well as pharmacodynamics and the toxic potential of the compound have to be analyzed in great detail before a compound can enter a clinical trial. A particularly challenging aspect of developing novel NCEs for the treatment of asthma is choosing and setting up in vivo models believed to be predictive for human disease. Numerous companies have in the past and are currently developing NCEs targeting many different pathways and cells with the aim to treat asthma. However, currently the only NCE having a significant market share are long-acting beta-agonists (LABA), inhaled and orally active steroids and leukotriene receptor antagonists. In the past many novel NCE for the treatment of asthma were effective in animal models but failed in the clinic. In this review we outline the prerequisites of novel NCE needed for clinical development.

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.

Biorelevant Dissolution Models for a Weak Base To Facilitate Formulation Development and Overcome Reduced Bioavailability Caused by Hypochlordyria or Achlorhydria.

PubMed

Kou, Dawen; Dwaraknath, Sudharsan; Fischer, Yannick; Nguyen, Daniel; Kim, Myeonghui; Yiu, Hiuwing; Patel, Preeti; Ng, Tania; Mao, Chen; Durk, Matthew; Chinn, Leslie; Winter, Helen; Wigman, Larry; Yehl, Peter

2017-10-02

In this study, two dissolution models were developed to achieve in vitro-in vivo relationship for immediate release formulations of Compound-A, a poorly soluble weak base with pH-dependent solubility and low bioavailability in hypochlorhydric and achlorhydric patients. The dissolution models were designed to approximate the hypo-/achlorhydric and normal fasted stomach conditions after a glass of water was ingested with the drug. The dissolution data from the two models were predictive of the relative in vivo bioavailability of various formulations under the same gastric condition, hypo-/achlorhydric or normal. Furthermore, the dissolution data were able to estimate the relative performance under hypo-/achlorhydric and normal fasted conditions for the same formulation. Together, these biorelevant dissolution models facilitated formulation development for Compound-A by identifying the right type and amount of key excipient to enhance bioavailability and mitigate the negative effect of hypo-/achlorhydria due to drug-drug interaction with acid-reducing agents. The dissolution models use readily available USP apparatus 2, and their broader utility can be evaluated on other BCS 2B compounds with reduced bioavailability caused by hypo-/achlorhydria.

Statistical molecular design of balanced compound libraries for QSAR modeling.

PubMed

Linusson, A; Elofsson, M; Andersson, I E; Dahlgren, M K

2010-01-01

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.

New insights into highly potent tyrosinase inhibitors based on 3-heteroarylcoumarins: Anti-melanogenesis and antioxidant activities, and computational molecular modeling studies.

PubMed

Pintus, Francesca; Matos, Maria J; Vilar, Santiago; Hripcsak, George; Varela, Carla; Uriarte, Eugenio; Santana, Lourdes; Borges, Fernanda; Medda, Rosaria; Di Petrillo, Amalia; Era, Benedetta; Fais, Antonella

2017-03-01

Melanogenesis is a physiological pathway for the formation of melanin. Tyrosinase catalyzes the first step of this process and down-regulation of its activity is responsible for the inhibition of melanogenesis. The search for molecules capable of controlling hyperpigmentation is a trend topic in health and cosmetics. A series of heteroarylcoumarins have been synthesized and evaluated. Compounds 4 and 8 exhibited higher tyrosinase inhibitory activities (IC 50 =0.15 and 0.38μM, respectively), than the reference compound, kojic acid (IC 50 =17.9μM). Compound 4 acts as competitive, while compound 8 as uncompetitive inhibitor of mushroom tyrosinase. Furthermore, compounds 2 and 8 inhibited tyrosinase activity and melanin production in B16F10 cells. In addition, compounds 2-4 and 8 proved to have an interesting antioxidant profile in both ABTS and DPPH radicals scavenging assays. Docking experiments were carried out in order to study the interactions between these heteroarylcoumarins and mushroom tyrosinase. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computer predictions on Rh-based double perovskites with unusual electronic and magnetic properties

NASA Astrophysics Data System (ADS)

Halder, Anita; Nafday, Dhani; Sanyal, Prabuddha; Saha-Dasgupta, Tanusri

2018-03-01

In search for new magnetic materials, we make computer prediction of structural, electronic and magnetic properties of yet-to-be synthesized Rh-based double perovskite compounds, Sr(Ca)2BRhO6 (B=Cr, Mn, Fe). We use combination of evolutionary algorithm, density functional theory, and statistical-mechanical tool for this purpose. We find that the unusual valence of Rh5+ may be stabilized in these compounds through formation of oxygen ligand hole. Interestingly, while the Cr-Rh and Mn-Rh compounds are predicted to be ferromagnetic half-metals, the Fe-Rh compounds are found to be rare examples of antiferromagnetic and metallic transition-metal oxide with three-dimensional electronic structure. The computed magnetic transition temperatures of the predicted compounds, obtained from finite temperature Monte Carlo study of the first principles-derived model Hamiltonian, are found to be reasonably high. The prediction of favorable growth condition of the compounds, reported in our study, obtained through extensive thermodynamic analysis should be useful for future synthesize of this interesting class of materials with intriguing properties.

Proposed structural basis of interaction of piperine and related compounds with monoamine oxidases.

PubMed

Rahman, Taufiq; Rahmatullah, Mohammed

2010-01-15

Several studies have revealed piperine and a few related compounds as potent inhibitors of monoamine oxidases without delineating the underlying mechanism. Using in silico modelling, we propose a structural basis of such activity by showing that these compounds can successfully dock into the inhibitor binding pockets of human monoamine oxidase isoforms with predicted affinities comparable to some known inhibitors. The results therefore suggest that piperine can be a promising lead for developing novel monoamine oxidase inhibitors. Copyright 2009 Elsevier Ltd. All rights reserved.

Involvement of CYP4F2 in the Metabolism of a Novel Monophosphate Ester Prodrug of Gemcitabine and Its Interaction Potential In Vitro.

PubMed

Wang, Yedong; Li, Yuan; Lu, Jia; Qi, Huixin; Cheng, Isabel; Zhang, Hongjian

2018-05-16

Compound- 3 is an oral monophosphate prodrug of gemcitabine. Previous data showed that Compound- 3 was more potent than gemcitabine and it was orally active in a tumor xenograft model. In the present study, the metabolism of Compound- 3 was investigated in several well-known in vitro matrices. While relatively stable in human and rat plasma, Compound- 3 demonstrated noticeable metabolism in liver and intestinal microsomes in the presence of NADPH and human hepatocytes. Compound- 3 could also be hydrolyzed by alkaline phosphatase, leading to gemcitabine formation. Metabolite identification using accurate mass- and information-based scan techniques revealed that Compound- 3 was subjected to sequential metabolism, forming alcohol, aldehyde and carboxylic acid metabolites, respectively. Results from reaction phenotyping studies indicated that cytochrome P450 4F2 (CYP4F2) was a key CYP isozyme involved in Compound- 3 metabolism. Interaction assays suggested that CYP4F2 activity could be inhibited by Compound- 3 or an antiparasitic prodrug pafuramidine. Because CYP4F2 is a key CYP isozyme involved in the metabolism of eicosanoids and therapeutic drugs, clinical relevance of drug-drug interactions mediated via CYP4F2 inhibition warrants further investigation.

In silico validation and structure activity relationship study of a series of pyridine-3-carbohydrazide derivatives as potential anticonvulsants in generalized and partial seizures.

PubMed

Sinha, Reema; Sara, Udai Vir Singh; Khosa, Ratan Lal; Stables, James; Jain, Jainendra

2013-06-01

A series of twelve compounds (Compounds RNH1-RNH12) of acid hydrazones of pyridine-3-carbohydrazide or nicotinic acid hydrazide was synthesized and evaluated for anticonvulsant activity by MES, scPTZ, minimal clonic seizure and corneal kindling seizure test. Neurotoxicity was also determined for these compounds by rotarod test. Results showed that halogen substitution at meta and para position of phenyl ring exhibited better protection than ortho substitution. Compounds RNH4 and RNH12, were found to be the active analogs displaying 6Hz ED50 of 75.4 and 14.77 mg/kg while the corresponding MES ED50 values were 113.4 and 29.3 mg/kg respectively. In addition, compound RNH12 also showed scPTZ ED50 of 54.2 mg/kg. In the series, compound RNH12 with trifluoromethoxy substituted phenyl ring was the most potent analog exhibiting protection in all four animal models of epilepsy. Molecular docking study has also shown significant binding interactions of these two compounds with 1OHV, 2A1H and 1PBQ receptors. Thus, N-[(meta or para halogen substituted) benzylidene] pyridine-3-carbohydrazides could be used as lead compounds in anticonvulsant drug design and discovery.

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.

Design, synthesis, and evaluation of inhibitors of trypanosomal and leishmanial dihydrofolate reductase.

PubMed

Chowdhury, S F; Villamor, V B; Guerrero, R H; Leal, I; Brun, R; Croft, S L; Goodman, J M; Maes, L; Ruiz-Perez, L M; Pacanowska, D G; Gilbert, I H

1999-10-21

This paper concerns the design, synthesis, and evaluation of inhibitors of leishmanial and trypanosomal dihydrofolate reductase. Initially study was made of the structures of the leishmanial and human enzyme active sites to see if there were significant differences which could be exploited for selective drug design. Then a series of compounds were synthesized based on 5-benzyl-2, 4-diaminopyrimidines. These compounds were assayed against the protozoan and human enzymes and showed selectivity for the protozoan enzymes. The structural data was then used to rationalize the enzyme assay data. Compounds were also tested against the clinically relevant forms of the intact parasite. Activity was seen against the trypanosomes for a number of compounds. The compounds were in general less active against Leishmania. This latter result may be due to uptake problems. Two of the compounds also showed some in vivo activity in a model of African trypanosomiasis.

BK/TD models for analyzing in vitro impedance data on cytotoxicity.

PubMed

Teng, S; Barcellini-Couget, S; Beaudouin, R; Brochot, C; Desousa, G; Rahmani, R; Pery, A R R

2015-06-01

The ban of animal testing has enhanced the development of new in vitro technologies for cosmetics safety assessment. Impedance metrics is one such technology which enables monitoring of cell viability in real time. However, analyzing real time data requires moving from static to dynamic toxicity assessment. In the present study, we built mechanistic biokinetic/toxicodynamic (BK/TD) models to analyze the time course of cell viability in cytotoxicity assay using impedance. These models account for the fate of the tested compounds during the assay. BK/TD models were applied to analyze HepaRG cell viability, after single (48 h) and repeated (4 weeks) exposures to three hepatotoxic compounds (coumarin, isoeugenol and benzophenone-2). The BK/TD models properly fit the data used for their calibration that was obtained for single or repeated exposure. Only for one out of the three compounds, the models calibrated with a single exposure were able to predict repeated exposure data. We therefore recommend the use of long-term exposure in vitro data in order to adequately account for chronic hepatotoxic effects. The models we propose here are capable of being coupled with human biokinetic models in order to relate dose exposure and human hepatotoxicity. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2017-01-01

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

Novel CYP17 inhibitors: synthesis, biological evaluation, structure-activity relationships and modelling of methoxy- and hydroxy-substituted methyleneimidazolyl biphenyls.

PubMed

Hille, Ulrike E; Hu, Qingzhong; Vock, Carsten; Negri, Matthias; Bartels, Marc; Müller-Vieira, Ursula; Lauterbach, Thomas; Hartmann, Rolf W

2009-07-01

Recently, the steroidal CYP17 inhibitor Abiraterone entered phase II clinical trial for the treatment of androgen-dependent prostate cancer. As 17alpha-hydroxylase-17,20-lyase (CYP17) catalyzes the last step in androgen biosynthesis, inhibition of this target should affect not only testicular but also adrenal androgen formation. Therefore CYP17 inhibitors should be advantageous over existing therapies, for example with GnRH analogues. However, steroidal drugs are known for side effects which are due to affinities for steroid receptors. Therefore we decided to synthesize non-steroidal compounds mimicking the natural CYP17 substrates pregnenolone and progesterone. The synthesis and biological evaluation of a series of 15 novel and highly active non-steroidal CYP17 inhibitors are reported. The compounds were prepared via Suzuki-cross-coupling, Grignard reaction and CDI-assisted S(N)t-reaction with imidazole and their inhibitory activity was examined with recombinant human CYP17 expressed in Escherichia coli. Promising compounds were further tested for their selectivity against the hepatic enzyme CYP3A4 and the glucocorticoid-forming enzyme CYP11B1. All compounds turned out to be potent CYP17 inhibitors. The most active compounds 7 and 8 were much more active than Ketoconazole showing activity comparable to Abiraterone (IC(50) values of 90 and 52nM vs. 72nM). Most compounds also showed higher selectivities than Ketoconazole, but turned out to be less selective than Abiraterone. Docking studies using our CYP17 protein model were performed with selected compounds to study the interactions between the inhibitors and the amino acid residues of the active site.

Production of a compound against methicillin resistant Staphylococcus aureus (MRSA) from Streptomyces rubrolavendulae ICN3 & its evaluation in zebrafish embryos

PubMed Central

Kannan, Rajaretinam Rajesh; Iniyan, Appadurai Muthamil; Vincent, Samuel Gnana Prakash

2014-01-01

Background & objectives: Antibiotic resistance in pathogens has become a serious problem worldwide. Therefore, the search for new antibiotics for drug resistanct pathogens is an important endeavor. The present study deals with the production of anti-methicillin resistant Staphylococcus aureus (MRSA) potential of Streptomyces rubrolavendulae ICN3 and evaluation of anti-MRSA compound in zebrafish embryos. Methods: The antibiotic production from S. rubrolavendulae ICN3 was optimized in solid state fermentation and extracted. The antagonistic activity was confirmed against MRSA and purified in silica gel column and reverse phase - HPLC with an absorption maximum at 215 nm. Minimal inhibitory concentration of the compound was determined by broth microdilution method. Zebrafish embryos were used to evaluate the extract/compound for its minimal inhibition studies, influences on heart beat rates, haematopoietic blood cell count and lethal dose values. Results: Streptomyces rubrolavendulae ICN3 showed potent antagonistic activity against MRSA with a zone of 42 mm. The minimum inhibitory concentration was calculated as 500 μg/ml of the crude extract and the purified C23 exhibited 2.5 μg/ml in in vitro assay. The LC50 value of the anti MRSA compound C23 was calculated as 60.49 μg/ml and the MRSA treated embryos survived in the presence of purified compound C23 at a dose of 10 μg/ml. Interpretation & conclusions: Our results suggested that the compound was potent with less toxic effects in zebrafish embryonic model system for MRSA infection. Further structural evaluation and analysis in higher mammalian model system may lead to a novel drug candidate for drug resistant Staphylococcus aureus. PMID:25109726

Synthesis, biological evaluation and molecular modelling of diversely functionalized heterocyclic derivatives as inhibitors of acetylcholinesterase/butyrylcholinesterase and modulators of Ca2+ channels and nicotinic receptors.

PubMed

Marco, José L; de los Ríos, Cristóbal; García, Antonio G; Villarroya, Mercedes; Carreiras, M Carmo; Martins, Carla; Eleutério, Ana; Morreale, Antonio; Orozco, M; Luque, F Javier

2004-05-01

The synthesis and the biological activity of compounds 5-40 as inhibitors of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE), as well as modulators of voltage-dependent Ca(2+) channels and nicotinic receptors, are described. These molecules are tacrine analogues, which have been prepared from polyfunctionalized 6-amino-5-cyano-4H-pyrans, 6-amino-5-cyano-pyridines and 5-amino-2-aryl-3-cyano-1,3-oxazoles via Friedländer reaction with selected cycloalkanones. These compounds are moderate acetylcholinesterase and butyrylcholinesterase inhibitors, the BuChE/AChE selectivity of the most active molecules ranges from 10.0 (compound 29) to 76.9 (compound 16). Interestingly, the 'oxazolo-tacrine' derivatives are devoid of any activity. All compounds showed an important inhibitory effect on the nicotinic acetylcholine receptor. Most of them also blocked L-type Ca(2+) channels, and three of them, 64, 19 and 67, the non-L type of Ca(2+) channels. Molecular modelling studies suggest that these compounds might bind at the peripheral binding site of AChE, which opens the possibility to design inhibitors able to bind at both, the catalytic and peripheral binding sites of the enzyme.

Measuring and statistically testing the size of the effect of a chemical compound on a continuous in-vitro pharmacological response through a new statistical model of response detection limit

PubMed Central

Diaz, Francisco J.; McDonald, Peter R.; Pinter, Abraham; Chaguturu, Rathnam

2018-01-01

Biomolecular screening research frequently searches for the chemical compounds that are most likely to make a biochemical or cell-based assay system produce a strong continuous response. Several doses are tested with each compound and it is assumed that, if there is a dose-response relationship, the relationship follows a monotonic curve, usually a version of the median-effect equation. However, the null hypothesis of no relationship cannot be statistically tested using this equation. We used a linearized version of this equation to define a measure of pharmacological effect size, and use this measure to rank the investigated compounds in order of their overall capability to produce strong responses. The null hypothesis that none of the examined doses of a particular compound produced a strong response can be tested with this approach. The proposed approach is based on a new statistical model of the important concept of response detection limit, a concept that is usually neglected in the analysis of dose-response data with continuous responses. The methodology is illustrated with data from a study searching for compounds that neutralize the infection by a human immunodeficiency virus of brain glioblastoma cells. PMID:24905187

Design, synthesis and biological evaluation of tetrahydronaphthyridine derivatives as bioavailable CDK4/6 inhibitors for cancer therapy.

PubMed

Zha, Chuantao; Deng, Wenjia; Fu, Yan; Tang, Shuai; Lan, Xiaojing; Ye, Yan; Su, Yi; Jiang, Lei; Chen, Yi; Huang, Ying; Ding, Jian; Geng, Meiyu; Huang, Min; Wan, Huixin

2018-03-25

CDK4/6 pathway is an attractive chemotherapeutic target for antitumor drug discovery and development. Herein, we reported the structure-based design and synthesis of a series of novel tetrahydronaphthyridine analogues as selective CDK4/6 inhibitors. Compound 5 was identified as a hit and then systematically structure optimization study was conducted. These efforts led to compound 28, which exhibited excellent in vitro potencies against CDK4/6 enzymatic activity with high selectivity over CDK1, and against Colo-205 cell growth. The compound demonstrated favorable in vitro metabolic and robust mice pharmacokinetic properties. In Colo-205 xenograft models, compound 28 showed potent tumor growth inhibition with acceptable toxic effects, which could serve as a novel anticancer agent for further preclinical study. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Design and Synthesis of Novel Phenylpiperazine Derivatives as Potential Anticonvulsant Agents.

PubMed

Habib, Monica M W; Abdelfattah, Mohamed A O; Abadi, Ashraf H

2015-12-01

Eighteen new 5-benzylidene-3-(4-arylpiperazin-1-ylmethyl)-2-thioxo-imidazolidin-4-ones were designed as hybrid structures from previously reported anticonvulsant compounds, synthesized and tested for anticonvulsant activity. Initial anticonvulsant screening was performed using the strychnine (2 mg/kg IP) potent generalized-induced seizure and pentylenetetrazole (PTZ) (60 mg/kg IP) acute clonic-induced convulsion screens in mice. All the molecules were found to be effective in at least one seizure model, compounds 10, 13, 15, 17, and 18 were active against both types of seizures induced. Compound 13 turned out to be the most active candidate within the strychnine model, having an average survival time of 6 min close to that of the positive control phenytoin, while compound 8 showed 100% protection from the induced PTZ seizures, resembling the protection of the positive control phenobarbital. Initial SAR studies for anticonvulsant activity are discussed. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Activation energies of diffusion of organic migrants in cyclo olefin polymer.

PubMed

Welle, Frank

2014-10-01

Cyclo olefin polymer (COP) is an amorphous polymer with good optical transparency and barrier properties, which is increasingly used for pharmaceutical packaging applications like pre-filled syringes, plastic vials, nutrition bags and blisters as well as for micro-well plates. For regulatory purposes, it is important to know the amount and quantity of compounds which migrate from the polymer into the pharmaceutical product. Within the study, diffusion coefficients of organic (model) compounds in COP at various temperatures were determined and the activation energies of diffusion were calculated according to the Arrhenius approach. Correlations were established between the molecular volume V of the migrating compound and the activation energy of diffusion EA as well as between the pre-exponential factor in the Arrhenius equation D0 and EA. From these correlations a prediction model was established for the migration of organic compounds in COP. This might be a useful tool supporting the evaluation process of COP packed pharmaceutical products. Copyright © 2014 Elsevier B.V. All rights reserved.

Synthesis of novel 1-[5-(4-methoxy-phenyl)-[1,3,4]oxadiazol-2-yl]-piperazine derivatives and evaluation of their in vivo anticonvulsant activity.

PubMed

Harish, Kikkeri P; Mohana, Kikkeri N; Mallesha, Lingappa; Prasanna Kumar, Basavapatna N

2013-07-01

A series of novel 1-[5-(4-methoxy-phenyl)-[1,3,4]oxadiazol-2-yl]-piperazine derivatives 8(a-o) were synthesized and characterized by elemental analyses, (1)H NMR, (13)C NMR and mass spectral studies. The newly synthesized compounds were screened for their anticonvulsant activity against maximal electroshock seizure (MES) model in male wistar rats and compared with the standard drug phenytoin. The neurotoxic effects were determined by rotorod test by using mice. Compounds 8d, 8e, 8f and 8h were found to be most potent of this series. The same compounds showed no neurotoxicity at the maximum dose administered (100 mg/kg). The efforts were also made to establish the structure activity relationships among synthesized compounds. The pharmacophore model was used to validate the anticonvulsant activity of the synthesized molecules. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Non-invasive method for quantitative evaluation of exogenous compound deposition on skin.

PubMed

Stamatas, Georgios N; Wu, Jeff; Kollias, Nikiforos

2002-02-01

Topical application of active compounds on skin is common to both pharmaceutical and cosmetic industries. Quantification of the concentration of a compound deposited on the skin is important in determining the optimum formulation to deliver the pharmaceutical or cosmetic benefit. The most commonly used techniques to date are either invasive or not easily reproducible. In this study, we have developed a noninvasive alternative to these techniques based on spectrofluorimetry. A mathematical model based on diffusion approximation theory is utilized to correct fluorescence measurements for the attenuation caused by endogenous skin chromophore absorption. The limitation is that the compound of interest has to be either fluorescent itself or fluorescently labeled. We used the method to detect topically applied salicylic acid. Based on the mathematical model a calibration curve was constructed that is independent of endogenous chromophore concentration. We utilized the method to localize salicylic acid in epidermis and to follow its dynamics over a period of 3 d.

Predicting mixture toxicity of seven phenolic compounds with similar and dissimilar action mechanisms to Vibrio qinghaiensis sp.nov.Q67.

PubMed

Huang, Wei Ying; Liu, Fei; Liu, Shu Shen; Ge, Hui Lin; Chen, Hong Han

2011-09-01

The predictions of mixture toxicity for chemicals are commonly based on two models: concentration addition (CA) and independent action (IA). Whether the CA and IA can predict mixture toxicity of phenolic compounds with similar and dissimilar action mechanisms was studied. The mixture toxicity was predicted on the basis of the concentration-response data of individual compounds. Test mixtures at different concentration ratios and concentration levels were designed using two methods. The results showed that the Weibull function fit well with the concentration-response data of all the components and their mixtures, with all relative coefficients (Rs) greater than 0.99 and root mean squared errors (RMSEs) less than 0.04. The predicted values from CA and IA models conformed to observed values of the mixtures. Therefore, it can be concluded that both CA and IA can predict reliable results for the mixture toxicity of the phenolic compounds with similar and dissimilar action mechanisms. Copyright © 2011 Elsevier Inc. 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.

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.

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

PubMed

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

2009-09-01

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

Design, synthesis, α-glucosidase inhibitory activity, molecular docking and QSAR studies of benzimidazole derivatives

NASA Astrophysics Data System (ADS)

Dinparast, Leila; Valizadeh, Hassan; Bahadori, Mir Babak; Soltani, Somaieh; Asghari, Behvar; Rashidi, Mohammad-Reza

2016-06-01

In this study the green, one-pot, solvent-free and selective synthesis of benzimidazole derivatives is reported. The reactions were catalyzed by ZnO/MgO containing ZnO nanoparticles as a highly effective, non-toxic and environmentally friendly catalyst. The structure of synthesized benzimidazoles was characterized using spectroscopic technics (FT-IR, 1HNMR, 13CNMR). Synthesized compounds were evaluated for their α-glucosidase inhibitory potential. Compounds 3c, 3e, 3l and 4n were potent inhibitors with IC50 values ranging from 60.7 to 168.4 μM. In silico studies were performed to explore the binding modes and interactions between enzyme and synthesized benzimidazoles. Developed linear QSAR model based on density and molecular weight could predict bioactivity of newly synthesized compounds well. Molecular docking studies revealed the availability of some hydrophobic interactions. In addition, the bioactivity of most potent compounds had good correlation with estimated free energy of binding (ΔGbinding) which was calculated according to docked best conformations.

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

Evaluation of land use regression models (LURs) for nitrogen dioxide and benzene in four U.S. Cities.

EPA Science Inventory

Spatial analysis studies have included application of land use regression models (LURs) for health and air quality assessments. Recent LUR studies have collected nitrogen dioxide (NO2) and volatile organic compounds (VOCs) using passive samplers at urban air monitoring networks ...

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 %.

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.

Interpreting linear support vector machine models with heat map molecule coloring

PubMed Central

2011-01-01

Background Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity. Results We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support vector machine model. The coloring of ligands in the binding pocket of several crystal structures of a maximum unbiased validation data set target indicates that our approach assists to determine the correct ligand orientation in the binding pocket. Additionally, the heat map coloring enables the identification of substructures important for the binding of an inhibitor. Conclusions In combination with heat map coloring, linear support vector machine models can help to guide the modification of a compound in later stages of drug discovery. Particularly substructures identified as important by our method might be a starting point for optimization of a lead compound. The heat map coloring should be considered as complementary to structure based modeling approaches. As such, it helps to get a better understanding of the binding mode of an inhibitor. PMID:21439031

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

Mobilization of PCBs and lindane from soil during in vitro digestion and their distribution among bile salt micelles and proteins of human digestive fluid and the soil

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

Oomen, A.G.; Sips, A.J.A.M.; Groten, J.P.

2000-01-15

Children can take up contaminated soil via hand-to-mouth behavior. The contaminants can be mobilized from the soil by digestive juices and thus become available for intestinal absorption. In the present study components of an in vitro digestion model were varied to study their effect on the mobilization of several PCBs and lindane from surrogate soil (OECD-medium). Approximately 35% of the PCBs and 57% of lindane were bioaccessible after a default digestion. Since the mobilization was independent of the spiking level, a partitioning-based model could describe the distribution of the test compounds. Fitting the data to the model yielded a ratiomore » of partitioning coefficients that indicated that approximately 60% of the PCBs were sorbed to the OECD-medium, 25% to bile salt micelles, and 15% to proteins. The respective values for lindane were 40%, 23%, and 32%. The relatively large fraction of the mobilized compounds that was sorbed to bile salt micelles indicates that micelles play a central role in making hydrophobic compounds bioaccessible. The distribution model is suitable for explaining the results reported in several literature studies and can be used to extrapolate the physiological parameters for the worst case situation and trends in the bioaccessible fraction.« less

Semi-volatile organic compounds at the leaf/atmosphere interface: numerical simulation of dispersal and foliar uptake.

PubMed

Riederer, Markus; Daiss, Andreas; Gilbert, Norbert; Köhle, Harald

2002-08-01

The behaviour of (semi-)volatile organic compounds at the interface between the leaf surface and the atmosphere was investigated by finite-element numerical simulation. Three model systems with increasing complexity and closeness to the real situation were studied. The three-dimensional model systems were translated into appropriate grid structures and diffusive and convective transport in the leaf/atmosphere interface was simulated. Fenpropimorph (cis-4-[3-(4-tert-butylphenyl)-2-methylpropyl]-2,6-dimethylmorpholine) and Kresoxim-methyl ((E)-methyl-2-methoxyimino-2-[2-(o-tolyloxy-methyl)phenyl] acetate) were used as model compounds. The simulation showed that under still and convective conditions the vapours emitted by a point source rapidly form stationary envelopes around the leaves. Vapour concentrations within these unstirred layers depend on the vapour pressure of the compound in question and on its affinity to the lipoid surface layers of the leaf (cuticular waxes, cutin). The rules deduced from the numerical simulation of organic vapour behaviour in the leaf/atmosphere interface are expected to help in assessing how (semi-)volatile plant products (e.g. hormones, pheromones, secondary metabolites) and xenobiotics (e.g. pesticides, pollutants) perform on plant surfaces.

Modeling nasopharyngeal carcinoma in three dimensions

PubMed Central

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

2017-01-01

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

Developmental neurotoxicity of pyrethroid insecticides in zebrafish embryos.

PubMed

DeMicco, Amy; Cooper, Keith R; Richardson, Jason R; White, Lori A

2010-01-01

Pyrethroid insecticides are one of the most commonly used residential and agricultural insecticides. Based on the increased use of pyrethroids and recent studies showing that pregnant women and children are exposed to pyrethroids, there are concerns over the potential for developmental neurotoxicity. However, there have been relatively few studies on the developmental neurotoxicity of pyrethroids. In this study, we sought to investigate the developmental toxicity of six common pyrethroids, three type I compounds (permethrin, resmethrin, and bifenthrin) and three type II compounds (deltamethrin, cypermethrin, and lambda-cyhalothrin), and to determine whether zebrafish embryos may be an appropriate model for studying the developmental neurotoxicity of pyrethroids. Exposure of zebrafish embryos to pyrethroids caused a dose-dependent increase in mortality and pericardial edema, with type II compounds being the most potent. At doses approaching the LC(50), permethrin and deltamethrin caused craniofacial abnormalities. These findings are consistent with mammalian studies demonstrating that pyrethroids are mildly teratogenic at very high doses. However, at lower doses, body axis curvature and spasms were observed, which were reminiscent of the classic syndromes observed with pyrethroid toxicity. Treatment with diazepam ameliorated the spasms, while treatment with the sodium channel antagonist MS-222 ameliorated both spasms and body curvature, suggesting that pyrethroid-induced neurotoxicity is similar in zebrafish and mammals. Taken in concert, these data suggest that zebrafish may be an appropriate alternative model to study the mechanism(s) responsible for the developmental neurotoxicity of pyrethroid insecticides and aid in identification of compounds that should be further tested in mammalian systems.

Developmental Neurotoxicity of Pyrethroid Insecticides in Zebrafish Embryos

PubMed Central

DeMicco, Amy; Cooper, Keith R.; Richardson, Jason R.; White, Lori A.

2010-01-01

Pyrethroid insecticides are one of the most commonly used residential and agricultural insecticides. Based on the increased use of pyrethroids and recent studies showing that pregnant women and children are exposed to pyrethroids, there are concerns over the potential for developmental neurotoxicity. However, there have been relatively few studies on the developmental neurotoxicity of pyrethroids. In this study, we sought to investigate the developmental toxicity of six common pyrethroids, three type I compounds (permethrin, resmethrin, and bifenthrin) and three type II compounds (deltamethrin, cypermethrin, and λ-cyhalothrin), and to determine whether zebrafish embryos may be an appropriate model for studying the developmental neurotoxicity of pyrethroids. Exposure of zebrafish embryos to pyrethroids caused a dose-dependent increase in mortality and pericardial edema, with type II compounds being the most potent. At doses approaching the LC50, permethrin and deltamethrin caused craniofacial abnormalities. These findings are consistent with mammalian studies demonstrating that pyrethroids are mildly teratogenic at very high doses. However, at lower doses, body axis curvature and spasms were observed, which were reminiscent of the classic syndromes observed with pyrethroid toxicity. Treatment with diazepam ameliorated the spasms, while treatment with the sodium channel antagonist MS-222 ameliorated both spasms and body curvature, suggesting that pyrethroid-induced neurotoxicity is similar in zebrafish and mammals. Taken in concert, these data suggest that zebrafish may be an appropriate alternative model to study the mechanism(s) responsible for the developmental neurotoxicity of pyrethroid insecticides and aid in identification of compounds that should be further tested in mammalian systems. PMID:19861644

QSAR study of anthranilic acid sulfonamides as inhibitors of methionine aminopeptidase-2 using LS-SVM and GRNN based on principal components.

PubMed

Shahlaei, Mohsen; Sabet, Razieh; Ziari, Maryam Bahman; Moeinifard, Behzad; Fassihi, Afshin; Karbakhsh, Reza

2010-10-01

Quantitative relationships between molecular structure and methionine aminopeptidase-2 inhibitory activity of a series of cytotoxic anthranilic acid sulfonamide derivatives were discovered. We have demonstrated the detailed application of two efficient nonlinear methods for evaluation of quantitative structure-activity relationships of the studied compounds. Components produced by principal component analysis as input of developed nonlinear models were used. The performance of the developed models namely PC-GRNN and PC-LS-SVM were tested by several validation methods. The resulted PC-LS-SVM model had a high statistical quality (R(2)=0.91 and R(CV)(2)=0.81) for predicting the cytotoxic activity of the compounds. Comparison between predictability of PC-GRNN and PC-LS-SVM indicates that later method has higher ability to predict the activity of the studied molecules. Copyright (c) 2010 Elsevier Masson SAS. All rights reserved.

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.

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

PubMed

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

2000-05-04

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

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

PubMed

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

2018-04-16

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

Biocides in hydraulic fracturing: A comparison to agricultural and assessment of hazard and vulnerability with respect to groundwater pollution

NASA Astrophysics Data System (ADS)

Worrall, Fred; Wilson, Miles; Davies, Richard

2017-04-01

Biocides are one possible chemical additive to frack fluids and their role is to control bacterial growth. Since biocides are designed to be toxic to particular organisms, their accidental or deliberate release into the environment has become a growing topic of concern, especially with regards to fracking. The objective of this study was to consider whether biocides proposed for use in fracking, could be a threat to English groundwater based on past groundwater monitoring data. The study considered all groundwater samples analysed for biocides in English groundwater between 2005 and 2014. The monitoring records were compared to: records of application (both amount and area); and chemical and molecular data for the biocides. The study did not use traditional adsorption and degradation data as these parameters are prone to variability and are not pure molecular parameters. The study showed that of the 110 biocides tested for in English groundwaters in the decade 2005 - 2014. The total number of detections was 2234 out of 1475000 observations of 95 compounds, and 38 were compounds that were not applied during the period of record. The detection of these 38 compounds did not decline over the 10 year period implying very long residence times and that once compounds do pollute an aquifer, then they will be a persistent problem. The study was able to develop binomial regression models of the probability of detecting pesticide in groundwater based upon molecular and application variables; and solely upon molecular properties. The solubility of the range of biocides used in frack fluids would imply a potentially higher hazard than for most agricultural biocides, but molecular modelling implied that one compound could be safer than others.

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

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

Lead Optimization Studies of Cinnamic Amide EP2 Antagonists

PubMed Central

2015-01-01

Prostanoid receptor EP2 can play a proinflammatory role, exacerbating disease pathology in a variety of central nervous system and peripheral diseases. A highly selective EP2 antagonist could be useful as a drug to mitigate the inflammatory consequences of EP2 activation. We recently identified a cinnamic amide class of EP2 antagonists. The lead compound in this class (5d) displays anti-inflammatory and neuroprotective actions. However, this compound exhibited moderate selectivity to EP2 over the DP1 prostanoid receptor (∼10-fold) and low aqueous solubility. We now report compounds that display up to 180-fold selectivity against DP1 and up to 9-fold higher aqueous solubility than our previous lead. The newly developed compounds also display higher selectivity against EP4 and IP receptors and a comparable plasma pharmacokinetics. Thus, these compounds are useful for proof of concept studies in a variety of models where EP2 activation is playing a deleterious role. PMID:24773616

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Flavonoids and biphenylneolignans with anti-inflammatory activity from the stems of Millettia griffithii.

PubMed

Tang, Huan; Pei, He-Ying; Wang, Tai-Jin; Chen, Kai; Wu, Bo; Yang, Qiu-Nan; Zhang, Qiang; Yang, Jian-Hong; Wang, Xiao-Yan; Tang, Ming-Hai; Peng, Ai-Hua; Ye, Hao-Yu; Chen, Li-Juan

2016-09-15

Five new flavonoids, griffinones A-E (1-5), a new biphenylneolignan, griffilignan A (6) and ten known compounds were isolated from the n-hexane and EtOAc extracts of Millettia griffithii. The structures of the new compounds were determined by 1D and 2D NMR, and by HRMS. The anti-inflammatory activity of the isolated compounds was evaluated on lipopolysaccharide (LPS)-induced nitric oxide (NO) production in RAW 264.7 cells. Among the isolated compounds, compounds 1, 2 and 14 showed significant anti-inflammatory activity with IC50 values of 20.4, 2.1 and 35.7μM, respectively and no obvious toxicities were observed at 100μM. Western blot and PCR assay further showed that inhibition of nitric oxide production by compound 2 was associated with suppression of iNOS expression. Modeling studies suggested that the amino group, phenyl ring as well as the isopentenyl tails of compound 2 could help bind to iNOs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization.

PubMed

Turk, Samo; Merget, Benjamin; Rippmann, Friedrich; Fulle, Simone

2017-12-26

Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with machine learning (ML) approaches to extrapolate to novel compounds. The here introduced MMP/ML method combines a fragment-based MMP implementation with different machine learning methods to obtain automated SAR decomposition and prediction. To test the prediction capabilities and model transferability, two different compound optimization scenarios were designed: (1) "new fragments" which occurs when exploring new fragments for a defined compound series and (2) "new static core and transformations" which resembles for instance the identification of a new compound series. Very good results were achieved by all employed machine learning methods especially for the new fragments case, but overall deep neural network models performed best, allowing reliable predictions also for the new static core and transformations scenario, where comprehensive SAR knowledge of the compound series is missing. Furthermore, we show that models trained on all available data have a higher generalizability compared to models trained on focused series and can extend beyond chemical space covered in the training data. Thus, coupling MMP with deep neural networks provides a promising approach to make high quality predictions on various data sets and in different compound optimization scenarios.

Antinociceptive activity of novel amide derivatives of imidazolidine-2,4-dione in a mouse model of acute pain.

PubMed

Czopek, Anna; Sałat, Kinga; Byrtus, Hanna; Rychtyk, Joanna; Pawłowski, Maciej; Siwek, Agata; Soluch, Joanna; Mureddu, Valentina; Filipek, Barbara

2016-06-01

Antiepileptic drugs are commonly used in non-epileptic disorders. For example, phenytoin and levetiracetam demonstrate analgesic properties in rodent models of pain. In order to enhance their antinociceptive activity, structural features of phenytoin and levetiracetam, such as imidazolidine-2,4-dione and amide bond in alkyl chain, were combined in one molecule. Furthermore, in preliminary studies, methoxyphenylpiperazinpropyl derivatives of imidazolidine-2,4-dione acted as antinociceptive agents in several rodent models of acute pain. The final compounds and the reference drugs - levetiracetam and phenytoin were evaluated in the hot plate test to assess their antinociceptive activity in this acute pain model. Furthermore, for the analgesic active compounds the impact on animals' locomotor activity and motor performance were estimated and the affinity to serotonergic (5-HT1A, 5-HT7) and adrenergic (α1) receptors was determined. Three of the tested compounds: 7, 15 and 18 showed statistically significant antinociceptive properties at the dose of 30mg/kg. Among them, compound 18, 1-methyl-3-[1-(morpholin-4-yl)-1-oxobutan-2-yl]imidazolidine-2,4-dione, exhibited the most significant and long-lasting antinociceptive activity. Noteworthy, this activity was not associated with a negative effect on animals' motor functions. Serotonergic or adrenergic neurotransmission is not involved in this antinociceptive effect. Some amide derivatives of imidazolidine-2,4-diones possess antinociceptive properties in mice but further studies are needed to explain their mechanism of action and assess their toxicity. Copyright © 2016 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Hit identification of novel heparanase inhibitors by structure- and ligand-based approaches.

PubMed

Gozalbes, Rafael; Mosulén, Silvia; Ortí, Leticia; Rodríguez-Díaz, Jesús; Carbajo, Rodrigo J; Melnyk, Patricia; Pineda-Lucena, Antonio

2013-04-01

Heparanase is a key enzyme involved in the dissemination of metastatic cancer cells. In this study a combination of in silico techniques and experimental methods was used to identify new potential inhibitors against this target. A 3D model of heparanase was built from sequence homology and applied to the virtual screening of a library composed of 27 known heparanase inhibitors and a commercial collection of drugs and drug-like compounds. The docking results from this campaign were combined with those obtained from a pharmacophore model recently published based in the same set of chemicals. Compounds were then ranked according to their theoretical binding affinity, and the top-rated commercial drugs were selected for further experimental evaluation. Biophysical methods (NMR and SPR) were applied to assess experimentally the interaction of the selected compounds with heparanase. The binding site was evaluated via competition experiments, using a known inhibitor of heparanase. Three of the selected drugs were found to bind to the active site of the protein and their KD values were determined. Among them, the antimalarial drug amodiaquine presented affinity towards the protein in the low-micromolar range, and was singled out for a SAR study based on its chemical scaffold. A subset of fourteen 4-arylaminoquinolines from a global set of 249 analogues of amodiaquine was selected based on the application of in silico models, a QSAR solubility prediction model and a chemical diversity analysis. Some of these compounds displayed binding affinities in the micromolar range. Copyright © 2013 Elsevier Ltd. All rights reserved.

Interaction between municipal solid waste leachate and Bauru aquifer system: a study case in Brazil.

PubMed

de Faria, Gabriel Messias Moura; Mondelli, Giulliana

2017-12-01

Leachate contamination is a chronic and urgent problem present in municipal solid waste (MSW) landfill. Geochemical mathematical models in this work was suitable to study the dynamics of the leachate from an MSW landfill located in the Midwest of Sao Paulo, Brazil, a region with high precipitation and temperature and rich in chalcophile compounds and lithophile compounds, despite contamination with nitrogenous compounds. After 13 years of local aquifer monitoring, some groundwater samplings in Feb. 2004, Aug. 2007, Nov. 2009, and Feb. 2014 were chosen to be simulated. The hydrolysis is the main process at the landfill, together with absorption, adsorption, complexation, dilution, cation exchange, and oxidation, besides nitrification, reoxidation, and reduction.

Pharmacological and structure-activity relationship evaluation of 4-aryl-1-diphenylacetyl(thio)semicarbazides.

PubMed

Wujec, Monika; Kędzierska, Ewa; Kuśmierz, Edyta; Plech, Tomasz; Wróbel, Andrzej; Paneth, Agata; Orzelska, Jolanta; Fidecka, Sylwia; Paneth, Piotr

2014-04-16

This article describes the synthesis of six 4-aryl-(thio)semicarbazides (series a and b) linked with diphenylacetyl moiety along with their pharmacological evaluation on the central nervous system in mice and computational studies, including conformational analysis and electrostatic properties. All thiosemicarbazides (series b) were found to exhibit strong antinociceptive activity in the behavioural model. Among them, compound 1-diphenylacetyl-4-(4-methylphenyl)thiosemicarbazide 1b was found to be the most potent analgesic agent, whose activity is connected with the opioid system. For compounds from series a significant anti-serotonergic effect, especially for compound 1-diphenylacetyl-4-(4-methoxyphenyl)semicarbazide 2b was observed. The computational studies strongly support the obtained results.

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.

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.

ESTIMATING TRANSPORT AND DEPOSITION OF A SEMI-VOLATILE COMPOUND WITH A REGIONAL PHOTOCHEMICAL MODEL

EPA Science Inventory

To simulate the fate of compounds that are considered semi-volatile and toxic, we have modified a model for regional particulate matter. Our changes introduce a semi-volatile compound into the atmosphere as gaseous emissions from an area source. Once emitted, the gas can transf...

Design, synthesis, and biological evaluation of 6-methoxy-2-arylquinolines as potential P-glycoprotein inhibitors.

PubMed

Aboutorabzadeh, Sayyed Mohammad; Mosaffa, Fatemeh; Hadizadeh, Farzin; Ghodsi, Razieh

2018-01-01

In the present study, a new series of 6-methoxy-2-arylquinoline analogues was designed and synthesized as P-glycoprotein (P-gp) inhibitors using quinine and flavones as the lead compounds. The cytotoxic activity of the synthesized compounds was evaluated against two human cancer cell lines including EPG85-257RDB, multidrug-resistant gastric carcinoma cells (P-gp-positive gastric carcinoma cell line), and EPG85-257P, drug-sensitive gastric carcinoma cells. Compounds showing low to moderate toxicity in the MTT test were selected to investigate their P-gp inhibition activity. Moreover, trying to explain the results of biological experiments, docking studies of the selected compounds into the homology-modeled human P-gp, were carried out. The physicochemical and ADME properties of the compounds as drug candidate were also predicted. Most of our compounds exhibited negligible or much lower cytotoxic effect in both cancer cells. Among the series, 5a and 5b, alcoholic quinoline derivatives were found to inhibit the efflux of rhodamine 123 at the concentration of 10 μM significantly. Among the tested quinolines, 5a and 5b showed the most potent P-gp inhibitory activity in the series and were 1.3-fold and 2.1-fold stronger than verapamil, respectively. SAR data revealed that hydroxyl methyl in position 4 of quinolines has a key role in P-gp efflux inhibition of our compounds. ADME studies suggested that all of the compounds included in this study may have a good human intestinal absorption.

Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 1. Boiling point and melting point.

PubMed

Admire, Brittany; Lian, Bo; Yalkowsky, Samuel H

2015-01-01

The UPPER (Unified Physicochemical Property Estimation Relationships) model uses enthalpic and entropic parameters to estimate 20 biologically relevant properties of organic compounds. The model has been validated by Lian and Yalkowsky on a data set of 700 hydrocarbons. The aim of this work is to expand the UPPER model to estimate the boiling and melting points of polyhalogenated compounds. In this work, 19 new group descriptors are defined and used to predict the transition temperatures of an additional 1288 compounds. The boiling points of 808 and the melting points of 742 polyhalogenated compounds are predicted with average absolute errors of 13.56 K and 25.85 K, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Chemistry Experiments

NASA Technical Reports Server (NTRS)

Brasseur, Guy; Remsberg, Ellis; Purcell, Patrick; Bhatt, Praful; Sage, Karen H.; Brown, Donald E.; Scott, Courtney J.; Ko, Malcolm K. W.; Tie, Xue-Xi; Huang, Theresa

1999-01-01

The purpose of the chemistry component of the model comparison is to assess to what extent differences in the formulation of chemical processes explain the variance between model results. Observed concentrations of chemical compounds are used to estimate to what degree the various models represent realistic situations. For readability, the materials for the chemistry experiment are reported in three separate sections. This section discussed the data used to evaluate the models in their simulation of the source gases and the Nitrogen compounds (NO(y)) and Chlorine compounds (Cl(y)) species.

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.