Modeling skin sensitization potential of mechanistically hard-to-be-classified aniline and phenol compounds with quantum mechanistic properties

BMC Clinical Pharmacology

Xiang-Qun Xie³  Ying Mu¹  Lirong Wang⁴  Qin Ouyang² 

[1] Division of Biology, Office of Science and Engineering Laboratories, Center for Devices and Radiobiological Health, US Food and Drug Administration, Silver Spring, MD 20993, USA;College of Pharmacy, Third Military Medical University, Chongqing 400038, China;Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA;Department of Pharmaceutical Sciences, Computational Chemical Genomics Screening Center, School of Pharmacy, NIH National Center, of Excellence for Computational Drug Abuse Research, Drug Discovery Institute, Pittsburgh, PA 15261, USA

关键词: Quantum mechanism;    Phenols;    Anilines;    Skin sensitizer;    Structure-activity relationship;    Chemical mechanisms;   

Others  :  1088394
DOI  :  10.1186/2050-6511-15-76

 received in 2014-03-31, accepted in 2014-11-20,  发布年份 2014

【 摘 要 】

Background

Advanced structure-activity relationship (SAR) modeling can be used as an alternative tool for identification of skin sensitizers and in improvement of the medical diagnosis and more effective practical measures to reduce the causative chemical exposures. It can also circumvent ethical concern of using animals in toxicological tests, and reduce time and cost. Compounds with aniline or phenol moieties represent two large classes of frequently skin sensitizing chemicals but exhibiting very variable, and difficult to predict, potency. The mechanisms of action are not well-understood.

Methods

A group of mechanistically hard-to-be-classified aniline and phenol chemicals were collected. An in silico model was established by statistical analysis of quantum descriptors for the determination of the relationship between their chemical structures and skin sensitization potential. The sensitization mechanisms were investigated based on the features of the established model. Then the model was utilized to analyze a subset of FDA approved drugs containing aniline and/or phenol groups for prediction of their skin sensitization potential.

Results and discussion

A linear discriminant model using the energy of the highest occupied molecular orbital (ϵ_HOMO) as the descriptor yielded high prediction accuracy. The contribution of ϵ_HOMO as a major determinant may suggest that autoxidation or free radical binding could be involved. The model was further applied to predict allergic potential of a subset of FDA approved drugs containing aniline and/or phenol moiety. The predictions imply that similar mechanisms (autoxidation or free radical binding) may also play a role in the skin sensitization caused by these drugs.

Conclusions

An accurate and simple quantum mechanistic model has been developed to predict the skin sensitization potential of mechanistically hard-to-be-classified aniline and phenol chemicals. The model could be useful for the skin sensitization potential predictions of a subset of FDA approved drugs.

【 授权许可】

   
2014 Ouyang et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

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