光毒性
数量结构-活动关系
工具箱
生物信息学
预测值
Nexus(标准)
生化工程
计算机科学
化学
计算生物学
机器学习
医学
生物
体外
生物化学
工程类
基因
程序设计语言
嵌入式系统
内科学
作者
Varun Ahuja,Gowrav Adiga Perdur,Zabiullah Aj,M Krishnappa,Helena Kanďárová
标识
DOI:10.1177/02611929241256040
摘要
Phototoxicity testing is crucial for evaluating the potential harmful effects of pharmaceuticals and chemicals on human skin when exposed to sunlight. Traditional in vivo models involving mice, rats, guinea pigs, as well as in vitro assays such as the 3T3 Neutral Red Uptake phototoxicity assay and methods based on the use of reconstructed human epidermis, have been established for phototoxicity testing. While these approaches are extremely valuable, they are costly in terms of both time and resources. Consequently, in silico approaches based on the use of predictive software tools can offer more rapid and cost-effective phototoxicity screening solutions. With this goal in mind, the current study evaluated two in silico tools — Derek Nexus 6.1.0/Derek Knowledge Base 2020 1.0 (Lhasa Limited, UK) and the QSAR Toolbox (v 4.5) developed by the Organisation for Economic Co-operation and Development (OECD) — for their capacity to predict the phototoxicity of several substances from diverse classes. Derek Nexus and the QSAR Toolbox were both found to be very useful for predicting the phototoxicity of drugs and other chemicals. Derek Nexus predicted phototoxicity of the compounds, with a sensitivity of 63%, specificity of 93%, Positive Predictive Values of 90% and Negative Predictive Value of 69%, overall accuracy of 77% and balanced accuracy of 78%. The QSAR Toolbox achieved sensitivity of 73%, specificity of 85%, Positive Predictive Value of 85% and Negative Predictive Value of 74%, overall accuracy of 79% and balanced accuracy of 79%. The results show that Derek Nexus and the QSAR Toolbox can be usefully incorporated in the workflow of phototoxicity testing for pharmaceuticals and chemicals.
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