Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk

Breast milk is the most complete infant nutrition, which is why breastfeeding is recommended as the optimal feeding choice for most infants. However, humans are also constantly exposed to environmental pollutants, often with potentially synergistic effects and at levels that can cause side effects....

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Published in:Computational Methods for Reproductive and Developmental Toxicology
Main Author: Agatonovic-Kustrin S.; Morton D.W.
Format: Book chapter
Language:English
Published: CRC Press 2015
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053978098&doi=10.1201%2fb19189&partnerID=40&md5=6733d06b25cefc07ebb05817d2b3beff
id 2-s2.0-85053978098
spelling 2-s2.0-85053978098
Agatonovic-Kustrin S.; Morton D.W.
Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk
2015
Computational Methods for Reproductive and Developmental Toxicology


10.1201/b19189
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053978098&doi=10.1201%2fb19189&partnerID=40&md5=6733d06b25cefc07ebb05817d2b3beff
Breast milk is the most complete infant nutrition, which is why breastfeeding is recommended as the optimal feeding choice for most infants. However, humans are also constantly exposed to environmental pollutants, often with potentially synergistic effects and at levels that can cause side effects. Because milk is the only nutrient source for the infant, a newborn will be exposed to all the xenobiotics present in the milk. The milk-to-plasma-concentration ratio is a key parameter used to estimate an infant’s exposure to different xenobiotics. Due to the countless number of chemicals released into environment, computational in silico methods and quantitative structure-activity relationships (QSARs) are gaining more and more attention in assessing this risk. The ability to predict the approximate amount of a chemical that might be present in milk from its structure can be very useful in the clinical setting. Molecular descriptors are numerical values that characterize properties of molecules, i.e., experimentally measured physicochemical properties (empirical) or calculated values from algorithms, such as two-dimensional fingerprints or three-dimensional structure. In silico QSAR models enable us to identify the essential structural characteristics that are responsible for secretion of a xenobiotic into milk. These models can be used to screen the milk/plasma partitioning potential for a huge number of compounds using data in existing xenobiotics/drugs databases. © 2016 by Taylor & Francis Group, LLC.
CRC Press

English
Book chapter

author Agatonovic-Kustrin S.; Morton D.W.
spellingShingle Agatonovic-Kustrin S.; Morton D.W.
Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk
author_facet Agatonovic-Kustrin S.; Morton D.W.
author_sort Agatonovic-Kustrin S.; Morton D.W.
title Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk
title_short Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk
title_full Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk
title_fullStr Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk
title_full_unstemmed Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk
title_sort Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk
publishDate 2015
container_title Computational Methods for Reproductive and Developmental Toxicology
container_volume
container_issue
doi_str_mv 10.1201/b19189
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053978098&doi=10.1201%2fb19189&partnerID=40&md5=6733d06b25cefc07ebb05817d2b3beff
description Breast milk is the most complete infant nutrition, which is why breastfeeding is recommended as the optimal feeding choice for most infants. However, humans are also constantly exposed to environmental pollutants, often with potentially synergistic effects and at levels that can cause side effects. Because milk is the only nutrient source for the infant, a newborn will be exposed to all the xenobiotics present in the milk. The milk-to-plasma-concentration ratio is a key parameter used to estimate an infant’s exposure to different xenobiotics. Due to the countless number of chemicals released into environment, computational in silico methods and quantitative structure-activity relationships (QSARs) are gaining more and more attention in assessing this risk. The ability to predict the approximate amount of a chemical that might be present in milk from its structure can be very useful in the clinical setting. Molecular descriptors are numerical values that characterize properties of molecules, i.e., experimentally measured physicochemical properties (empirical) or calculated values from algorithms, such as two-dimensional fingerprints or three-dimensional structure. In silico QSAR models enable us to identify the essential structural characteristics that are responsible for secretion of a xenobiotic into milk. These models can be used to screen the milk/plasma partitioning potential for a huge number of compounds using data in existing xenobiotics/drugs databases. © 2016 by Taylor & Francis Group, LLC.
publisher CRC Press
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