Literature DB >> 32166484

Modeling and insights into molecular basis of low molecular weight respiratory sensitizers.

Xueyan Cui1, Rui Yang1, Siwen Li1, Juan Liu1, Qiuyun Wu1, Xiao Li2,3.   

Abstract

Respiratory sensitization has been considered an important toxicological endpoint, because of the severe risk to human health. A great part of sensitization events were caused by low molecular weight (< 1000) respiratory sensitizers in the past decades. However, there is currently no widely accepted test method that can identify prospective low molecular weight respiratory sensitisers. Herein, we performed the study of modeling and insights into molecular basis of low molecular weight respiratory sensitizers with a high-quality data set containing 136 respiratory sensitizers and 518 nonsensitizers. We built a number of classification models by using OCHEM tools, and a consensus model was developed based on the ten best individual models. The consensus model showed good predictive ability with a balanced accuracy of 0.78 and 0.85 on fivefold cross-validation and external validation, respectively. The readers can predict the respiratory sensitization of organic compounds via https://ochem.eu/article/114857 . The effect of several molecular properties on respiratory sensitization was also evaluated. The results indicated that these properties differ significantly between respiratory sensitizers and nonsensitizers. Furthermore, 14 privileged substructures responsible for respiratory sensitization were identified. We hope the models and the findings could provide useful help for environmental risk assessment.

Entities:  

Keywords:  Consensus model; Machine learning; Molecular property; Respiratory sensitizer; Structural alert

Year:  2020        PMID: 32166484     DOI: 10.1007/s11030-020-10069-3

Source DB:  PubMed          Journal:  Mol Divers        ISSN: 1381-1991            Impact factor:   2.943


  33 in total

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Authors:  Sander Dik; Jeroen L A Pennings; Henk van Loveren; Janine Ezendam
Journal:  Toxicol In Vitro       Date:  2015-10-28       Impact factor: 3.500

2.  Development of mechanism-based structural alerts for respiratory sensitization hazard identification.

Authors:  S J Enoch; M J Seed; D W Roberts; M T D Cronin; S J Stocks; R M Agius
Journal:  Chem Res Toxicol       Date:  2012-10-19       Impact factor: 3.739

Review 3.  Occupational asthma.

Authors:  Susan M Tarlo; Catherine Lemiere
Journal:  N Engl J Med       Date:  2014-02-13       Impact factor: 91.245

4.  Evaluation of in silico models for the identification of respiratory sensitizers.

Authors:  Sander Dik; Janine Ezendam; Albert R Cunningham; Carl Alex Carrasquer; Henk van Loveren; Emiel Rorije
Journal:  Toxicol Sci       Date:  2014-09-19       Impact factor: 4.849

5.  Exploring QSAR modeling of toxicity of chemicals on earthworm.

Authors:  Sulekha Ghosh; Probir Kumar Ojha; Edoardo Carnesecchi; Anna Lombardo; Kunal Roy; Emilio Benfenati
Journal:  Ecotoxicol Environ Saf       Date:  2019-12-17       Impact factor: 6.291

6.  Development of an information-intensive structure-activity relationship model and its application to human respiratory chemical sensitizers.

Authors:  A R Cunningham; S L Cunningham; D M Consoer; S T Moss; M H Karol
Journal:  SAR QSAR Environ Res       Date:  2005-06       Impact factor: 3.000

7.  The direct peptide reactivity assay: selectivity of chemical respiratory allergens.

Authors:  Jon F Lalko; Ian Kimber; G Frank Gerberick; Leslie M Foertsch; Anne Marie Api; Rebecca J Dearman
Journal:  Toxicol Sci       Date:  2012-06-19       Impact factor: 4.849

Review 8.  Animal models to test respiratory allergy of low molecular weight chemicals: a guidance.

Authors:  Josje H E Arts; C Frieke Kuper
Journal:  Methods       Date:  2007-01       Impact factor: 3.608

Review 9.  Respiratory sensitization and allergy: current research approaches and needs.

Authors:  Darrell R Boverhof; Richard Billington; B Bhaskar Gollapudi; John A Hotchkiss; Shannon M Krieger; Alan Poole; Connie M Wiescinski; Michael R Woolhiser
Journal:  Toxicol Appl Pharmacol       Date:  2007-10-22       Impact factor: 4.219

10.  ProTox-II: a webserver for the prediction of toxicity of chemicals.

Authors:  Priyanka Banerjee; Andreas O Eckert; Anna K Schrey; Robert Preissner
Journal:  Nucleic Acids Res       Date:  2018-07-02       Impact factor: 16.971

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  2 in total

1.  In Silico Prediction and Insights Into the Structural Basis of Drug Induced Nephrotoxicity.

Authors:  Yinping Shi; Yuqing Hua; Baobao Wang; Ruiqiu Zhang; Xiao Li
Journal:  Front Pharmacol       Date:  2022-01-05       Impact factor: 5.810

2.  SApredictor: An Expert System for Screening Chemicals Against Structural Alerts.

Authors:  Yuqing Hua; Xueyan Cui; Bo Liu; Yinping Shi; Huizhu Guo; Ruiqiu Zhang; Xiao Li
Journal:  Front Chem       Date:  2022-07-13       Impact factor: 5.545

  2 in total

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