Literature DB >> 33295769

Transplacental Transfer of Environmental Chemicals: Roles of Molecular Descriptors and Placental Transporters.

Jing Li1, Xiangfei Sun1, Jun Xu2, Hongli Tan1, Eddy Y Zeng1, Da Chen1.   

Abstract

Transplacental transfer of environmental chemicals results in direct risks to fetal development. Although numerous studies have investigated transplacental transfer efficiencies (TTEs) of environmental chemicals, the underlying mechanisms and influencing factors remain poorly understood. The present study aims to synthesize a current state of knowledge on the TTEs of major environmental chemicals and explore the roles of chemicals' molecular descriptors and placental transporters in the transplacental transfer. The results indicate great variations in TTEs (median: 0.29-2.86) across 51 chemicals. Chemical-dependent TTEs may partially be attributed to the influences of chemicals' molecular descriptors. Predictive models based on experimental TTEs and 1790 computed molecular descriptors indicate that a very limited number of molecular descriptors, such as the topological polar surface area, may substantially influence and efficiently predict chemicals' TTEs. In addition, molecular docking analyses were conducted to determine the binding affinities between 51 chemicals and six selected transporters, including BCRP, MDR1, hENT1, FRα, SERT, and MRP1. The results reveal transporter- and chemical-dependent binding affinities. Therefore, our study demonstrates that molecular descriptors and placental transporters, among a variety of other factors, can play important roles in the transplacental transfer of environmental chemicals. However, the underlying mechanisms and several important knowledge gaps identified herein require further investigations.

Entities:  

Year:  2020        PMID: 33295769     DOI: 10.1021/acs.est.0c06778

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  3 in total

1.  Modeling the transplacental transfer of small molecules using machine learning: a case study on per- and polyfluorinated substances (PFAS).

Authors:  Dimitri Abrahamsson; Adi Siddharth; Joshua F Robinson; Anatoly Soshilov; Sarah Elmore; Vincent Cogliano; Carla Ng; Elaine Khan; Randolph Ashton; Weihsueh A Chiu; Jennifer Fung; Lauren Zeise; Tracey J Woodruff
Journal:  J Expo Sci Environ Epidemiol       Date:  2022-10-07       Impact factor: 6.371

Review 2.  Drug Transporters in the Kidney: Perspectives on Species Differences, Disease Status, and Molecular Docking.

Authors:  Wei Zou; Birui Shi; Ting Zeng; Yan Zhang; Baolin Huang; Bo Ouyang; Zheng Cai; Menghua Liu
Journal:  Front Pharmacol       Date:  2021-11-29       Impact factor: 5.810

3.  A Comprehensive Non-targeted Analysis Study of the Prenatal Exposome.

Authors:  Dimitri Panagopoulos Abrahamsson; Aolin Wang; Ting Jiang; Miaomiao Wang; Adi Siddharth; Rachel Morello-Frosch; June-Soo Park; Marina Sirota; Tracey J Woodruff
Journal:  Environ Sci Technol       Date:  2021-07-14       Impact factor: 11.357

  3 in total

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