Investigative analysis of blood-brain barrier penetrating potential of electronic nicotine delivery systems (e-cigarettes) chemicals using predictive computational models.

Kimberly Stratford, Jueichuan Connie Kang, Sheila M Healy, Zheng Tu, Luis G Valerio
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Abstract

Introduction: Seizures are known potential side effects of nicotine toxicity and have been reported in electronic nicotine delivery systems (ENDS, e-cigarettes) users, with the majority involving youth or young adults.

Areas covered: Using chemoinformatic computational models, chemicals (including flavors) documented to be present in ENDS were compared to known neuroactive compounds to predict the blood-brain barrier (BBB) penetration potential, central nervous system (CNS) activity, and their structural similarities. The literature search used PubMed/Google Scholar, through September 2023, to identify individual chemicals in ENDS and neuroactive compounds.The results show that ENDS chemicals in this study contain >60% structural similarity to neuroactive compounds based on chemical fingerprint similarity analyses. The majority of ENDS chemicals we studied were predicted to cross the BBB, with approximately 60% confidence, and were also predicted to have CNS activity; those not predicted to passively diffuse through the BBB may be actively transported through the BBB to elicit CNS impacts, although it is currently unknown.

Expert opinion: In lieu of in vitro and in vivo testing, this study screens ENDS chemicals for potential CNS activity and predicts BBB penetration potential using computer-based models, allowing for prioritization for further study and potential early identification of CNS toxicity.

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利用预测性计算模型对电子尼古丁给药系统(电子烟)化学品的血脑屏障穿透潜力进行调查分析。
简介:众所周知,癫痫发作是尼古丁毒性的潜在副作用,在电子尼古丁输送系统(ENDS,电子烟)使用者中也有癫痫发作的报道,其中大多数是青少年或年轻成年人:利用化学信息计算模型,将ENDS中记录的化学物质(包括香料)与已知的神经活性化合物进行比较,以预测血脑屏障(BBB)渗透潜力、中枢神经系统(CNS)活性及其结构相似性。结果显示,根据化学指纹相似性分析,本研究中的ENDS化学物质与神经活性化合物的结构相似性大于60%。我们研究的大多数ENDS化学物质都被预测可穿过BBB,可信度约为60%,而且还被预测具有中枢神经系统活性;那些未被预测可被动扩散穿过BBB的化学物质可能会被主动转运穿过BBB以引起中枢神经系统影响,但目前尚不清楚:这项研究利用基于计算机的模型筛选ENDS化学品的潜在中枢神经系统活性并预测其通过生物BB的可能性,从而确定进一步研究的优先次序,并及早发现潜在的中枢神经系统毒性。
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