Journal
MOLECULAR DIVERSITY
Volume 21, Issue 2, Pages 355-365Publisher
SPRINGER
DOI: 10.1007/s11030-016-9715-6
Keywords
Support vector machine (SVM); Artificial neural network (ANN); Blood-brain barrier (BBB); Multidrug resistance protein (MRP-1); Homology model; CNS
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Funding
- Department of Electronics and Information Technology, GOI, New Delhi, India [DIT/R&D/Bio/15(3)/ 2011]
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Drugs acting on central nervous system (CNS) may take longer duration to reach the market as these compounds have a higher attrition rate in clinical trials due to the complexity of the brain, side effects, and poor blood-brain barrier (BBB) permeability compared to non-CNS-acting compounds. The roles of active efflux transporters with BBB are still unclear. The aim of the present work was to develop a predictive model for BBB permeability that includes the MRP-1 transporter, which is considered as an active efflux transporter. A support vector machine model was developed for the classification of MRP-1 substrates and non-substrates, which was validated with an external data set and Y-randomization method. An artificial neural network model has been developed to evaluate the role of MRP-1 on BBB permeation. A total of nine descriptors were selected, which included molecular weight, topological polar surface area, ClogP, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds, P-gp, BCRP, and MRP-1 substrate probabilities for model development. We identified 5 molecules that fulfilled all criteria required for passive permeation of BBB, but they all have a low logBB value, which suggested that the molecules were effluxed by the MRP-1 transporter.
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