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Articles

Qualitative and quantitative structure–activity relationship modelling for predicting blood-brain barrier permeability of structurally diverse chemicals

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Pages 95-124 | Received 01 Sep 2014, Accepted 26 Nov 2014, Published online: 28 Jan 2015
 

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 (r2) 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 r2 > 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.

Acknowledgement

The authors thank the Director, CSIR-Indian Institute of Toxicology Research, Lucknow, India, for his keen interest in this work and for providing all necessary facilities.

Additional information

Funding

No funding for this work was received from any source, except Senior Research Fellowship provided by the Council of Scientific and Industrial Research (CSIR), New Delhi, India, to one of the authors (S.G.).

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