Molecular structural characteristics that influence partitioning of xenobiotics into human breast milk Jain Laviha, Dhar Aashir, Bhardwaj Nikunaj* Department of Biotechnology, Noida International University, Greater Noida (UP), India *E-mail: nikunj.bhardwaj@niu.edu.in
Online published on 18 July, 2018. Abstract As we aware that breast milk is the most complete infant nutrition, which is why breastfeeding is recommended as the optimal feeding choice for most infants. Environment pollutant is constantly harming us and we are being exposed drastically. The antagonistic effects on our body can't be ignored. As milk is the only nutrient source for the infanthence new born is easily exposed to all the xenobiotics present in the milk. The factors that affect M/P (milk-to-plasma) ratio of several compounds were assessed in vitro using samples collected from a healthy lactating women. The M/P ratio is a key parameter used to estimate an infant's exposure to different xenobiotic and the ratio of drugs is used to estimate the amount of drug offered to the suckling infant. 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 the 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 empricial values 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 char-acteristics 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. Top Keywords Milk-To-Plasma concentration ratio, Insilico methods(QSAR), Molecular descriptors, xenoboitics, computational and empirical value. Top |