In silico prediction of blood-brain barrier permeation using the calculated molecular cross-sectional area as main parameter.

The cross-sectional area, AD, of a compound oriented in an amphiphilic gradient such as the air-water or lipid-water interface has previously been shown to be crucial for membrane partitioning and permeation, respectively. Here, we developed an algorithm that determines the molecular axis of amphiphilicity and the cross-sectional area, ADcalc, perpendicular to this axis. Starting from the conformational ensemble of each molecule, the three-dimensional conformation selected as the membrane-binding conformation was the one with the smallest cross-sectional area, ADcalcM, and the strongest amphiphilicity. The calculated, ADcalcM, and the measured, AD, cross-sectional areas correlated linearly (n=55, slope, m=1.04, determination coefficient, r2=0.95). The calculated cross-sectional areas, ADcalcM, were then used together with the calculated octanol-water distribution coefficients, log D7.4, of the 55 compounds (with a known ability to permeate the blood-brain barrier) to establish a calibration diagram for the prediction of blood-brain barrier permeation. It yielded a limiting cross-sectional area (ADcalcM=70 A2) and an optimal range of octanol-water distribution coefficients (-1.4<or=log D7.4<7.0). The calibration diagram was validated with an independent set of 43 compounds with the known ability to permeate the blood-brain barrier, yielding a prediction accuracy of 86%. The incorrectly predicted compounds exhibited log D7.4 values comprised between -0.6 and -1.4, suggesting that the limitation for log D7.4 is less rigorous than the limitation for AD. An accuracy of 83% has been obtained for a second validation set of 42 compounds which were previously shown to be difficult to predict. The calculated parameters, ADcalcM and log D7.4, thus allow for a fast and accurate prediction of blood-brain barrier permeation. Analogous calibration diagrams can be established for other membrane barriers.