title: TOPS-MODE approach for the prediction of blood-brain barrier permeation.
abstract: The blood-brain barrier permeation has been investigated by using a topological substructural molecular design approach (TOPS-MODE). A linear regression model was developed to predict the in vivo blood-brain partitioning coefficient on a data set of 119 compounds, treated as the logarithm of the blood-brain concentration ratio. The final model explained the 70% of the variance and it was validated through the use of an external validation set (33 compounds of the 119, MAE = 0.33), a leave-one-out crossvalidation (q(2) = 0.65, S(press) = 0.43), fivefold full crossvalidation (removing 28 compounds in each cycle, MAE = 33, RMSE = 0.43) and the prediction of +/- values for an external test set (85.7% of good prediction). This methodology evidenced that the hydrophobicity increase the blood-brain barrier permeation, while the polar surface and its interaction with the atomic mass of compounds decrease it; suggesting the capacity of the TOPS-MODE descriptors to estimate brain penetration potential of new drug candidates. Finally, by the present approach, positive and negative substructural contributions to the brain permeation were identified, and their possibilities in the lead generation and optimization processes were evaluated.
authors.affiliation: Drug Design Department, Centre of Chemical Bioactive, Central University of Las Villas, Santa Clara 54830, Villa Clara, Cuba. macabrera@cbq.uclv.edu.cu
authors.forename: Miguel Angel
authors.initials: MA
authors.lastname: Cabrera
authors.forename: Marival
authors.initials: M
authors.lastname: Bermejo
authors.forename: Maykel
authors.initials: M
authors.lastname: Pérez
authors.forename: Ronal
authors.initials: R
authors.lastname: Ramos
mesh_terms: D001812:Blood-Brain Barrier / Q000378:metabolism*; D002199:Capillary Permeability / Q000502:physiology; D003198:Computer Simulation; D016014:Linear Models; D008954:Models, Biological; D011237:Predictive Value of Tests