scholarly journals Assessment of the cytotoxic and mutagenic potential of dichlorvos (DDVP) using in silico classification model; a health hazard awareness in Nigeria

2020 ◽  
Vol 35 (3) ◽  
pp. e2020016
Author(s):  
Yahaya Abdulwahid Abaukaka ◽  
Salihu Sanusi ◽  
Kabir Abdullahi Ozigi ◽  
Fatima Umar Malo
Keyword(s):  
In Silico ◽  
Health Hazard ◽  
Classification Model ◽  
Mutagenic Potential ◽  
Hazard Awareness

scholarly journals Development of an in silico prediction system of human renal excretion and clearance from chemical structure information incorporating fraction unbound in plasma as a descriptor

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Reiko Watanabe ◽  
Rikiya Ohashi ◽  
Tsuyoshi Esaki ◽  
Hitoshi Kawashima ◽  
Yayoi Natsume-Kitatani ◽  
...  
Keyword(s):  
Renal Clearance ◽  
In Silico ◽  
Regression Models ◽  
Chemical Structure ◽  
Prediction Models ◽  
Renal Excretion ◽  
Early Stage ◽  
Classification Model ◽  
Prediction System ◽  
Structure Information

AbstractPrediction of pharmacokinetic profiles of new chemical entities is essential in drug development to minimize the risks of potential withdrawals. The excretion of unchanged compounds by the kidney constitutes a major route in drug elimination and plays an important role in pharmacokinetics. Herein, we created in silico prediction models of the fraction of drug excreted unchanged in the urine (fe) and renal clearance (CLr), with datasets of 411 and 401 compounds using freely available software; notably, all models require chemical structure information alone. The binary classification model for fe demonstrated a balanced accuracy of 0.74. The two-step prediction system for CLr was generated using a combination of the classification model to predict excretion-type compounds and regression models to predict the CLr value for each excretion type. The accuracies of the regression models increased upon adding a descriptor, which was the observed and predicted fraction unbound in plasma (fu,p); 78.6% of the samples in the higher range of renal clearance fell within 2-fold error with predicted fu,p value. Our prediction system for renal excretion is freely available to the public and can be used as a practical tool for prioritization and optimization of compound synthesis in the early stage of drug discovery.

scholarly journals Multiclass Classifier for P-Glycoprotein Substrates, Inhibitors, and Non-Active Compounds

Molecules ◽  
2019 ◽  
Vol 24 (10) ◽  
pp. 2006 ◽  
Author(s):  
Liadys Mora Lagares ◽  
Nikola Minovski ◽  
Marjana Novič
Keyword(s):  
In Silico ◽  
Transmembrane Protein ◽  
External Validation ◽  
Assessment Process ◽  
Classification Model ◽  
Training Set ◽  
Test Set ◽  
Active Compounds ◽  
P Glycoprotein ◽  
Validation Set

P-glycoprotein (P-gp) is a transmembrane protein that actively transports a wide variety of chemically diverse compounds out of the cell. It is highly associated with the ADMET (absorption, distribution, metabolism, excretion and toxicity) properties of drugs/drug candidates and contributes to decreasing toxicity by eliminating compounds from cells, thereby preventing intracellular accumulation. Therefore, in the drug discovery and toxicological assessment process it is advisable to pay attention to whether a compound under development could be transported by P-gp or not. In this study, an in silico multiclass classification model capable of predicting the probability of a compound to interact with P-gp was developed using a counter-propagation artificial neural network (CP ANN) based on a set of 2D molecular descriptors, as well as an extensive dataset of 2512 compounds (1178 P-gp inhibitors, 477 P-gp substrates and 857 P-gp non-active compounds). The model provided a good classification performance, producing non error rate (NER) values of 0.93 for the training set and 0.85 for the test set, while the average precision (AvPr) was 0.93 for the training set and 0.87 for the test set. An external validation set of 385 compounds was used to challenge the model’s performance. On the external validation set the NER and AvPr values were 0.70 for both indices. We believe that this in silico classifier could be effectively used as a reliable virtual screening tool for identifying potential P-gp ligands.

scholarly journals Development of Nitrocellulose-based Propellants With Natural Stabilizers

2020 ◽  
pp. 3-6 ◽  
Author(s):  
Rodrigo Leonard Barboza Rodrigues ◽  
Maurício Ferrapontoff Lemos ◽  
Tanos Celmar Costa França ◽  
Letivan Gonçalvez Mendonça Filho
Keyword(s):  
Heat Flux ◽  
Shelf Life ◽  
Chemical Stability ◽  
In Silico ◽  
In Silico Analysis ◽  
Toxicity Prediction ◽  
Mutagenic Potential ◽  
Natural Substances ◽  
Silico Analysis

Traditional stabilizers for nitrocellulose-based (NC-based) propellants are known to have carcinogenic, mutagenic and toxicity to reproduction potentials. Therefore, the replacement of these stabilizers in the propellants formulations is necessary, but with no losses regarding stabilization efficiency and shelf life of propellant. In this context, NC-based propellants were prepared using the natural substances curcumin and guaiacol as stabilizers. The chemical stability of the samples evaluated by a heat-flux microcalorimeter (HFC) suggests that the new propellants are more stable than the traditional ones. Also, a complementary in silico analysis was performed on toxicity prediction software (LAZAR, Toxtree, VEGA and TEST) based on the similarity with substances contained in their databases. The results concluded that curcumin stabilizer presents no toxicity, while guaiacol can have carcinogenic and mutagenic potential.

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

2018 ◽  
Vol 18 (3) ◽  
pp. 2329-2340
Author(s):  
Stefano Decesari ◽  
Simona Kovarich ◽  
Manuela Pavan ◽  
Arianna Bassan ◽  
Andrea Ciacci ◽  
...  
Keyword(s):  
In Silico ◽  
Airborne Particulate Matter ◽  
Coupling Model ◽  
Toxicological Screening ◽  
Multivariate Statistical ◽  
Mutagenic Potential ◽  
Multifunctional Compounds ◽  
Physico Chemical ◽  
Concept Evaluation ◽  
Policy Objectives

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

Mutagenic Potential of Chemicals Associated with Tenebrionid Flour Beetle Secretions as Determined by the Ames Assay

1982 ◽  
Vol 45 (12) ◽  
pp. 1129-1130
Author(s):  
LEONARD J. SAUERS ◽  
JOHN T. FRUIN ◽  
LINDA S. GUTHERTZ
Keyword(s):  
Screening Test ◽  
Health Hazard ◽  
Stored Products ◽  
Mutagenic Potential ◽  
Ames Assay ◽  
The Public ◽  
Flour Beetle ◽  
Flour Beetles ◽  
Mutagenicity Assay

Infestation of flour and other stored products by the tenebrionid (flour beetles) has been proven a health hazard to the public. Secretions from these insects have been found to be harmful toxicologically. These secretions also possess characteristics typical of mutagens. Therefore the mutagenic potential of 2-methyl-1, 4-benzoquinone (MBQ), 2-ethyl-1, 4 benzoquinone (EBQ) and 1-pentadecene (P-dec) was assessed by using the Ames Salmonella/Mammalian Microsome Mutagenicity Assay, a screening test for detection of mutagens. Tester strains TA 98, TA 100, TA 1535, TA 1537, and TA 1538 were exposed to doses of 10−1 mg/plate to 3.2 × 10−5 mg of MBQ/plate, 10−2 mg/plate to 3.2 × 10−6 mg of EBQ/plate and 1 mg/plate to 3.2 × 10−4 mg of P-dec/plate. No evidence of mutagenic potential was observed at the levels tested.

scholarly journals An In Silico Classification Model for Putative ABCC2 Substrates

2012 ◽  
Vol 31 (8) ◽  
pp. 547-553 ◽  
Author(s):  
Marta Pinto ◽  
Michael Trauner ◽  
Gerhard F. Ecker
Keyword(s):  
In Silico ◽  
Classification Model

scholarly journals Pharmacokinetic and Toxicological Evaluation of a Zinc Gluconate-Based Chemical Sterilant Using In Vitro and In Silico Approaches

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Carlos F. Araujo-Lima ◽  
Rafael J. M. Nunes ◽  
Raphael M. Carpes ◽  
Claudia A. F. Aiub ◽  
Israel Felzenszwalb
Keyword(s):  
In Silico ◽  
Animal Health ◽  
Optimal Dose ◽  
Dependent Manner ◽  
Toxicological Evaluation ◽  
Mutagenic Potential ◽  
Zinc Gluconate ◽  
Sclerosing Agents ◽  
Toxicological Activity

Sclerosing agents as zinc gluconate-based chemical sterilants (Infertile®) are used for chemical castration. This solution is injected into the animal testis, but there are not enough evidences of its safety profiles for the receivers. The present work aimed to establish the pharmacokinetics and toxicological activity of Infertile, using in vitro and in silico approaches. The evaluation at the endpoint showed effects in a dose-dependent manner. Since necrosis is potentially carcinogenic, the possible cell death mechanism could be apoptosis. Our data suggested that Infertile at 60 mM presented risk for animal health. Even though Infertile is a licensed product by the Brazilian Ministry of Agriculture, Livestock and Supply, it presented a high mutagenic potential. We suggest that the optimal dose must be less than 6 mM, once, at this concentration, no mutagenicity or genotoxicity was observed.

Trainer Evaluation of a Union-based Ten-hour Safety and Health Hazard-awareness Program for U.S. Construction Workers

2007 ◽  
Vol 13 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Rosemary K. Sokas ◽  
Leslie Nickels ◽  
Kristin Rankin ◽  
Janie L. Gittleman ◽  
Christina Trahan
Keyword(s):  
Health Hazard ◽  
Construction Workers ◽  
Awareness Program ◽  
Safety And Health ◽  
Hazard Awareness

In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: An industry survey

2012 ◽  
Vol 62 (3) ◽  
pp. 449-455 ◽  
Author(s):  
Krista L. Dobo ◽  
Nigel Greene ◽  
Charlotta Fred ◽  
Susanne Glowienke ◽  
James S. Harvey ◽  
...  
Keyword(s):  
In Silico ◽  
Expert Knowledge ◽  
Mutagenic Potential ◽  
Industry Survey ◽  
Knowledge Rule ◽  
Pharmaceutical Impurities ◽  
In Silico Methods ◽  
Rule Out
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