STopTox: An
            <i>in Silico</i>
            Alternative to Animal Testing for Acute Systemic and Topical Toxicity

Borba, Joyce Villa Verde Bastos; Alves, Vinícius M.; Braga, Rodolpho C.; Korn, Daniel; Overdahl, Kirsten E.; Silva, Arthur C.; Hall, Steven U S; Overdahl, Erik; Kleinstreuer, Nicole; Strickland, Judy; Allen, David; Andrade, Carolina Horta; Muratov, Eugene; Tropsha, Alexander

doi:10.1289/ehp9341

Cited by 42 publications

(29 citation statements)

References 55 publications

(58 reference statements)

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“…In this study, we developed a novel prediction model for the early assessment of chemically induced reproductive toxicity potential in humans (males and females) by using a two-tier approach combined with multiple QSARs based on molecular, cellular, and animal data. QSARs always perform well in predicting in vitro endpoints with relatively simple molecular mechanisms but present poor performance on in vivo toxicities because of the complex biological context. , The implementation of the AOP framework in this study avoided this shortcoming. ,− Data imbalance and small in vivo data sets were the most important issues that hindered the predictive performance of QSARs . In this study, a weight correction method for the minor class improved the predictive performance of QSAR models, but still had limitations.…”

Section: Resultsmentioning

confidence: 89%

“…61,91−96 Data imbalance and small in vivo data sets were the most important issues that hindered the predictive performance of QSARs. 97 In this study, a weight correction method for the minor class improved the predictive performance of QSAR models, but still had limitations. In the future, more data balancing techniques and in vivo datasets should be used to improve predictive performance.…”

Section: Curation Of Heterogeneous In Vitro and In Vivo Datamentioning

confidence: 90%

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Development, Validation, and Application of a Human Reproductive Toxicity Prediction Model Based on Adverse Outcome Pathway

Tan

Zhang

et al. 2022

Environ. Sci. Technol.

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A growing number of environmental contaminants have been proved to have reproductive toxicity to males and females. However, the unclear toxicological mechanism of reproductive toxicants limits the development of virtual screening methods. By consolidating androgen (AR)-/estrogen receptors (ERs)-mediated adverse outcome pathways (AOPs) with more than 8000 chemical substances, we uncovered relationships between chemical features, a series of pathway-related effects, and reproductive apical outcomeschanges in sex organ weights. An AOP-based computational model named RepTox was developed and evaluated to predict and characterize chemicals’ reproductive toxicity for males and females. Results showed that RepTox has three outstanding advantages. (I) Compared with the traditional models (37 and 81% accuracy, respectively), AOP significantly improved the predictive robustness of RepTox (96.3% accuracy). (II) Compared with the application domain (AD) of models based on small in vivo datasets, AOP expanded the ADs of RepTox by 1.65-fold for male and 3.77-fold for female, respectively. (III) RepTox implied that hydrophobicity, cyclopentanol substructure, and several topological indices (e.g., hydrogen-bond acceptors) were important, unbiased features associated with reproductive toxicants. Finally, RepTox was applied to the inventory of existing chemical substances of China and identified 2100 and 7281 potential toxicants to the male and female reproductive systems, respectively.

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Section: Resultsmentioning

confidence: 89%

Section: Curation Of Heterogeneous In Vitro and In Vivo Datamentioning

confidence: 90%

Development, Validation, and Application of a Human Reproductive Toxicity Prediction Model Based on Adverse Outcome Pathway

Tan

Zhang

et al. 2022

Environ. Sci. Technol.

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“…The STopTox online acute toxicity prediction tool predicts the commonly known “6-pack” assays ( Table 5 and Figures S11–S13 ) that are required by various drug regulatory agencies to evaluate multiple aspects of acute toxicities in humans, using machine learning (ML) models [ 51 ]. The “6-pack” assay for acute toxicity includes acute oral, dermal and inhalation toxicity, skin and eye irritation and corrosion as well as skin sensitization.…”

Section: Resultsmentioning

confidence: 99%

“…The STopTox online toxicity prediction tool was employed to predict acute toxicities of the compounds in humans. The acute toxicity prediction assessments included acute oral, dermal and inhalation toxicity, as well as skin and eye irritation and corrosion, and skin sensitization ( , accessed on 15 January 2022) [ 51 ]. The AdmetSAR online ADMET tool was employed to further predict the ADMET properties of the compounds ( , accessed on 18 December 2021) [ 80 , 81 ].…”

Section: Methodsmentioning

confidence: 99%

Weak Noncovalent Interactions in Three Closely Related Adamantane-Linked 1,2,4-Triazole N-Mannich Bases: Insights from Energy Frameworks, Hirshfeld Surface Analysis, In Silico 11β-HSD1 Molecular Docking and ADMET Prediction

et al. 2022

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Structural analysis and docking studies of three adamantane-linked 1,2,4-triazole N-Mannich bases (1–3) are presented. Compounds 1, 2 and 3 crystallized in the monoclinic P21/c, P21 and P21/n space groups, respectively. Crystal packing of 1 was stabilized by intermolecular C‒H···O interactions, whereas compounds 2 and 3 were stabilized through intermolecular C‒H···N, C‒H···S and C‒H···π interactions. The energy frameworks for crystal structures of 1–3 were described. The substituent effect on the intermolecular interactions and their contributions were described on the basis of Hirshfeld surface analyses. The 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) inhibition potential, pharmacokinetic and toxicity profiles of compounds 1–3 were determined using in silico techniques. Molecular docking of the compounds into the 11β-HSD1 active site showed comparable binding affinity scores (−7.50 to −8.92 kcal/mol) to the 11β-HSD1 co-crystallized ligand 4YQ (−8.48 kcal/mol, 11β-HSD1 IC50 = 9.9 nM). The compounds interacted with key active site residues, namely Ser170 and Tyr183, via strong hydrogen bond interactions. The predicted pharmacokinetic and toxicity profiles of the compounds were assessed, and were found to exhibit excellent ADMET potential.

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“…The toxicity properties of compounds were evaluated using two software products, STopTox 29 , 30 and ProTox-II. 31 In this step, 892 molecules with a toxicity class-4/5 with a predicted LD50 (mg/kg) ranged from 2,000 to 5,000 for Class V and more than 5,000 for class VI by ProTox-II and noncardiotox by STopTox were kept.…”

Section: Methodsmentioning

confidence: 99%

Facing Antitubercular Resistance: Identification of Potential Direct Inhibitors Targeting InhA Enzyme and Generation of 3D-pharmacophore Model by in silico Approach

Haddoumi¹,

Mansouri²,

Bendani³

et al. 2023

AABC

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Purpose The enoyl-acyl carrier protein reductase (InhA) is one of the important key enzymes employed in mycolic acids biosynthesis pathway and an important component of mycobacterial cell walls. This enzyme has also been identified as major target of isoniazid drug, except that isoniazid needs to be activated first by the catalase peroxidase (KatG) protein to form the isonicotinoyl-NAD (INH-NAD) adduct that inhibits the action of InhA enzyme. However, this activation becomes more difficult and unreachable with the problem of mutation-related resistance caused mainly by acquired mutations in KatG and InhA protein. Our main interest in this study is to identify direct InhA inhibitors using computer-aided drug design. Methods Computer-aided drug design was used to solve this problem by applying three different approaches including mutation impact modelling, virtual screening and 3D-pharmacophore search. Results A total of 15 mutations were collected from the literature, then a 3D model was generated for each of them and their impact was predicted. Of the 15 mutations, 10 were found to be deleterious and have a direct effect on flexibility, stability and SASA of the protein. In virtual screening, from 1,000 similar INH-NAD analogues obtained by the similarity search method, 823 compounds passed toxicity filter and drug likeness rules, which were then docked to the wild-type of InhA protein. Subsequently, 34 compounds with binding energy score better than that of INH-NAD were selected and docked against the 10 generated mutated models of InhA. Only three leads showed a lower binding affinity better than the reference. The 3D-pharmacophore model approach was used to identify the common features between those three compounds by generating a pharmacophoric map. Conclusion The result of this study may pave the way to develop more potent mutant-specific inhibitors to overcome this resistance.

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STopTox: An in Silico Alternative to Animal Testing for Acute Systemic and Topical Toxicity

Cited by 42 publications

References 55 publications

Development, Validation, and Application of a Human Reproductive Toxicity Prediction Model Based on Adverse Outcome Pathway

Development, Validation, and Application of a Human Reproductive Toxicity Prediction Model Based on Adverse Outcome Pathway

Weak Noncovalent Interactions in Three Closely Related Adamantane-Linked 1,2,4-Triazole N-Mannich Bases: Insights from Energy Frameworks, Hirshfeld Surface Analysis, In Silico 11β-HSD1 Molecular Docking and ADMET Prediction

Facing Antitubercular Resistance: Identification of Potential Direct Inhibitors Targeting InhA Enzyme and Generation of 3D-pharmacophore Model by in silico Approach

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