Structural Alerts for Genotoxicity and Carcinogenicity

2014 ◽  
pp. 65-92
Author(s):  
Heewon Lee
Keyword(s):  
Structural Alerts

Inhalation threshold of toxicological concern (TTC) — Structural alerts discriminate high from low repeated-dose inhalation toxicity

2016 ◽  
Vol 88 ◽  
pp. 123-132 ◽  
Author(s):  
Gerrit Schüürmann ◽  
Ralf-Uwe Ebert ◽  
Inga Tluczkiewicz ◽  
Sylvia E. Escher ◽  
Ralph Kühne
Keyword(s):  
Repeated Dose ◽  
Inhalation Toxicity ◽  
Structural Alerts ◽  
Threshold Of Toxicological Concern ◽  
Dose Inhalation

scholarly journals Machine Learning for Predicting Risk of Drug-Induced Autoimmune Diseases by Structural Alerts and Daily Dose

2021 ◽  
Vol 18 (13) ◽  
pp. 7139
Author(s):  
Yue Wu ◽  
Jieqiang Zhu ◽  
Peter Fu ◽  
Weida Tong ◽  
Huixiao Hong ◽  
...  
Keyword(s):  
Machine Learning ◽  
Autoimmune Diseases ◽  
Odds Ratio ◽  
Area Under Curve ◽  
Predictive Performance ◽  
Drug Induced ◽  
Drug Candidates ◽  
Daily Dose ◽  
Structural Alerts ◽  
Underlying Mechanisms

An effective approach for assessing a drug’s potential to induce autoimmune diseases (ADs) is needed in drug development. Here, we aim to develop a workflow to examine the association between structural alerts and drugs-induced ADs to improve toxicological prescreening tools. Considering reactive metabolite (RM) formation as a well-documented mechanism for drug-induced ADs, we investigated whether the presence of certain RM-related structural alerts was predictive for the risk of drug-induced AD. We constructed a database containing 171 RM-related structural alerts, generated a dataset of 407 AD- and non-AD-associated drugs, and performed statistical analysis. The nitrogen-containing benzene substituent alerts were found to be significantly associated with the risk of drug-induced ADs (odds ratio = 2.95, p = 0.0036). Furthermore, we developed a machine-learning-based predictive model by using daily dose and nitrogen-containing benzene substituent alerts as the top inputs and achieved the predictive performance of area under curve (AUC) of 70%. Additionally, we confirmed the reactivity of the nitrogen-containing benzene substituent aniline and related metabolites using quantum chemistry analysis and explored the underlying mechanisms. These identified structural alerts could be helpful in identifying drug candidates that carry a potential risk of drug-induced ADs to improve their safety profiles.

scholarly journals Evaluation of Different Methods for Identification of Structural Alerts Using Chemical Ames Mutagenicity Data Set as a Benchmark

2017 ◽  
Vol 30 (6) ◽  
pp. 1355-1364 ◽  
Author(s):  
Hongbin Yang ◽  
Jie Li ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
...  
Keyword(s):  
Data Set ◽  
Structural Alerts

Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds

2007 ◽  
Vol 221 (2) ◽  
pp. 189-202 ◽  
Author(s):  
Aliuska Morales Helguera ◽  
Maykel Pérez González ◽  
Maria Natália D. S. Cordeiro ◽  
Miguel Ángel Cabrera Pérez
Keyword(s):  
Nitroso Compounds ◽  
Quantitative Structure ◽  
Structural Alerts

Identification of concealed structural alerts using QSTR modeling for Pseudokirchneriella subcapitata

2021 ◽  
Vol 239 ◽  
pp. 105962
Author(s):  
Vijay H. Masand ◽  
Magdi E.A. Zaki ◽  
Sami A. Al-Hussain ◽  
Anis Ben Ghorbal ◽  
Siddhartha Akasapu ◽  
...  
Keyword(s):  
Pseudokirchneriella Subcapitata ◽  
Structural Alerts

scholarly journals Computational Approach to Structural Alerts: Furans, Phenols, Nitroaromatics, and Thiophenes

2017 ◽  
Vol 30 (4) ◽  
pp. 1046-1059 ◽  
Author(s):  
Na Le Dang ◽  
Tyler B. Hughes ◽  
Grover P. Miller ◽  
S. Joshua Swamidass
Keyword(s):  
Computational Approach ◽  
Structural Alerts

Large-Scale Predictive Drug Safety: From Structural Alerts to Biological Mechanisms

2015 ◽  
Vol 28 (10) ◽  
pp. 1875-1887 ◽  
Author(s):  
Ricard Garcia-Serna ◽  
David Vidal ◽  
Nikita Remez ◽  
Jordi Mestres
Keyword(s):  
Drug Safety ◽  
Large Scale ◽  
Biological Mechanisms ◽  
Structural Alerts
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