Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractA rapid and green GC-MS method for the sampling of volatile organic compounds in spices and flowers by concurrent headspace single-drop microextraction and solid-phase microextraction    Next AbstractThe Scent of Life: Phoretic Nematodes Use Wasp Volatiles and Carbon Dioxide to Choose Functional Vehicles for Dispersal »

SAR QSAR Environ Res


Title:Qualitative and quantitative structure-activity relationship modelling for predicting blood-brain barrier permeability of structurally diverse chemicals
Author(s):Gupta S; Basant N; Singh KP;
Address:"a Academy of Scientific and Innovative Research , Anusandhan Bhawan, New Delhi , India"
Journal Title:SAR QSAR Environ Res
Year:2015
Volume:20150128
Issue:2
Page Number:95 - 124
DOI: 10.1080/1062936X.2014.994562
ISSN/ISBN:1029-046X (Electronic) 1026-776X (Linking)
Abstract:"In this study, structure-activity relationship (SAR) models have been established for qualitative and quantitative prediction of the blood-brain barrier (BBB) permeability of chemicals. The structural diversity of the chemicals and nonlinear structure in the data were tested. The predictive and generalization ability of the developed SAR models were tested through internal and external validation procedures. In complete data, the QSAR models rendered ternary classification accuracy of >98.15%, while the quantitative SAR models yielded correlation (r(2)) of >0.926 between the measured and the predicted BBB permeability values with the mean squared error (MSE) <0.045. The proposed models were also applied to an external new in vitro data and yielded classification accuracy of >82.7% and r(2) > 0.905 (MSE < 0.019). The sensitivity analysis revealed that topological polar surface area (TPSA) has the highest effect in qualitative and quantitative models for predicting the BBB permeability of chemicals. Moreover, these models showed predictive performance superior to those reported earlier in the literature. This demonstrates the appropriateness of the developed SAR models to reliably predict the BBB permeability of new chemicals, which can be used for initial screening of the molecules in the drug development process"
Keywords:"Animals Artificial Intelligence Blood-Brain Barrier/*metabolism Databases, Chemical Humans Models, Statistical Permeability *Quantitative Structure-Activity Relationship Volatile Organic Compounds/chemistry/pharmacokinetics BBB permeability molecular desc;"
Notes:"MedlineGupta, S Basant, N Singh, K P eng England 2015/01/30 SAR QSAR Environ Res. 2015; 26(2):95-124. doi: 10.1080/1062936X.2014.994562. Epub 2015 Jan 28"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 06-07-2024