| Literature DB >> 30376998 |
Jephthe Jean1, Supratik Kar2, Jerzy Leszczynski3.
Abstract
Physiologically-based toxicokinetic (PBTK) model has immense role to play in the risk assessment process due to specified mathematical representation of the absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) of chemicals in diverse environmental compartment. Determination of adipose/blood partition coefficient [logP(adipose/blood)] is regarded as one of the crucial constraints of PBTK models. In respect to the challenge for identifying the chemical-definite parameters for these models, especially within short time frame and with limited resources, quantitative structure-activity relationship (QSAR) models are beneficial for providing the chemical-specific parameters of PBTK models. In the present study, we have developed robust, statistically highly significant (R2 = 0.92, QLOO2 = 0.90, RPred2 = 0.92) and mechanistically interpretable three descriptors QSAR models for 67 environmental chemicals [Alcohols, polybrominated diphenyl ethers (PBDEs), polychlorinated dibenzodioxins (PCDDs), polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs)] employing the experimental values of adipose/blood partition coefficient for human. The partitioning of chemicals into adipose tissue and blood offers information related to distribution and toxicological effects of these molecules in to the mammal system. The developed models are helpful to understand the mechanistic basis of toxicokinetic processes into the mammal system followed by risk assessment and risk management process. The applicability domain (AD) of the developed model was checked and followed by its employment to predict adipose/blood partition coefficient of 513 environmental contaminants consist of PCBs, PBDEs, PCDDs and PAHs from USA Environmental protection agency (US EPA) site.Entities:
Keywords: Adipose/blood partition coefficient; MLR; PBTK; QSAR
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Year: 2018 PMID: 30376998 DOI: 10.1016/j.envint.2018.10.037
Source DB: PubMed Journal: Environ Int ISSN: 0160-4120 Impact factor: 9.621