Development of Web and Mobile Applications for Chemical Toxicity Prediction

Alves, Vinícius M.; Braga, Rodolpho C.; Muratov, Eugene; Andrade, Carolina Horta

doi:10.21577/0103-5053.20180013

Cited by 11 publications

(9 citation statements)

References 48 publications

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“…These models are used in drug discovery and development and for assessment of the effects of xenobiotics on humans and environment. Computational tools that were developed for hazard assessment include (quantitative) structure-activity relationships [(Q)SARs], read-across methods, expert rule-based (structural alerts) methods, and molecular modeling techniques (Alves et al, 2018a; Myatt et al, 2018; Yang et al, 2018). The Organization of Economic and Co-operation Development (OECD) created QSAR guidelines already in 2004 and the principles for the construction of (Q)SAR models, computational methods, and model validation methods are described in detail since 2007 (Fjodorova et al, 2008; Lo Piparo and Worth, 2010).…”

Section: Introductionmentioning

confidence: 99%

Computational Assessment of the Pharmacological Profiles of Degradation Products of Chitosan

Roman

Som

et al. 2019

Front. Bioeng. Biotechnol.

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Chitosan is a natural polymer revealing an increased potential to be used in different biomedical applications, including drug delivery systems, and tissue engineering. It implies the evaluation of the organism response to the biomaterial implantation. Low-molecular degradation products, the chito-oligomers, are resulting mainly from the influence of enzymes, which are found in the organism fluids. Within this study, we have performed the computational assessment of pharmacological profiles and toxicological effects on human health of small chito-oligomers with distinct molecular weights, deacetylation degrees, and acetylation patterns. Our approach is based on the fact that regulatory agencies and researchers in the drug development field rely on the use of modeling to predict biological effects and to guide decision making. To be considered as valid for regulatory purposes, every model that is used for predictions should be associated with a defined toxicological endpoint and has appropriate robustness and predictivity. Within this context, we have used FAF-Drugs4, SwissADME, and PreADMET tools to predict the oral bioavailability of chito-oligomers and SwissADME, PreADMET, and admetSAR2.0 tools to predict their pharmacokinetic profiles. The organs and genomic toxicities have been assessed using admetSAR2.0 and PreADMET tools but specific computational facilities have been also used for predicting different toxicological endpoints: Pred-Skin for skin sensitization, CarcinoPred-EL for carcinogenicity, Pred-hERG for cardiotoxicity, ENDOCRINE DISRUPTOME for endocrine disruption potential and Toxtree for carcinogenicity and mutagenicity. Our computational assessment showed that investigated chito-oligomers reflect promising pharmacological profiles and limited toxicological effects on humans, regardless of molecular weight, deacetylation degree, and acetylation pattern. According to our results, there is a possible inhibition of the organic anion transporting peptides OATP1B1 and/or OATP1B3, a weak potential of cardiotoxicity, a minor probability of affecting the androgen receptor, and phospholipidosis. Consequently, these results may be used to guide or to complement the existing in vitro and in vivo toxicity tests, to optimize biomaterials properties and to contribute to the selection of prototypes for nanocarriers.

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Section: Introductionmentioning

confidence: 99%

Computational Assessment of the Pharmacological Profiles of Degradation Products of Chitosan

Roman

Som

et al. 2019

Front. Bioeng. Biotechnol.

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“…Calculation methods for predicting chemical toxicity are rapidly developed (Alves et al, 2018; Karim, Mishra, et al, 2019; Karim, Singh, et al, 2019; Yang et al, 2018). Toxicity modeling is one type of computer model that can predict the activities or properties of chemicals based on their physicochemical or structural parameters.…”

Section: Computer Simulation Modelsmentioning

confidence: 99%

Toxicity of transition metal nanoparticles: A review of different experimental models in the gastrointestinal tract

Wang

Gao

et al. 2022

J of Applied Toxicology

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The development of nanotechnology is becoming a major trend nowadays.Nanoparticles (NPs) have been widely used in fields including food, biomedicine, and cosmetics, endowing NPs more opportunities to enter the human body. It is wellknown that the gut microbiome plays a key role in human health, and the exposure of intestines to NPs is unavoidable. Accordingly, the toxicity of NPs has attracted more attention than before. This review mainly highlights recent advances in the evaluation of NPs' toxicity in the gastrointestinal system from the existing cell-based experimental models, such as the original mono-culture models, co-culture models, three-dimensional (3D) culture models, and the models established on microfluidic chips, to those in vivo experiments, such as mice models, Caenorhabditis elegans models, zebrafish models, human volunteers, as well as computer-simulated toxicity models. Owing to these models, especially those more biomimetic models, the outcome of the toxicity of NPs acting in the gastrointestinal tract can get results closer to what happened inside the real human microenvironment.

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“…Pred-hERG (Braga et al, 2015;Alves et al, 2018) is a web app that allows users to predict blockers and non-blockers of the hERG channels, and important drug anti-target associated with lethal cardiac arrhythmia (Mitcheson et al, 2000). The current version of the app (v. 4.2) was developed using ChEMBL (Willighagen et al, 2013) version 23, containing 8,134 compounds with hERG blockage data after curation, using robust and predictive machine learning models based on RF.…”

Section: Prediction Of Admet Properties Of New Compoundsmentioning

confidence: 99%