THEORETICAL CALCULATION AND PREDICTION OF CACO-2 CELL-PERMEABILITY USING MOLSURF PARAMETRIZATION AND PLS STATISTICS

Purpose. To statistically model the permeability across Caco-2 cell mo nolayers using theoretically computed molecular descriptors and multiv ariate statistics. Methods. Seventeen structurally diverse compounds w ere investigated. The program MolSurf was used to compute theoretical molecular descriptors related to physico-chemical properties such as l ipophilicity, polarity, polarizability and hydrogen bonding. The multi variate Partial Least Squares Projections to Latent Structures (PLS) m ethod was used to delineate the relationship between the permeability across Caco-2 cell monolayers and the theoretically computed molecular descriptors. Results. Excellent statistical models were derived. Prop erties associated with hydrogen bonding had the largest impact on diff usion through the monolayers and should be kept at a minimum to promot e high permeability. High lipophilicity and the presence of surface el ectrons, i.e. valence electrons, which are not tightly bonded to the m olecule, were also found to have a favorable influence to achieve high permeability. Conclusions. The results indicate that theoretically co mputed molecular MolSurf descriptors in conjunction with multivariate statistics of PLS type can be used to successfully model permeability across Caco-2 cell monolayers and, thus, differentiate drugs with poor permeability from those with acceptable permeability at an early stag e of the preclinical drug discovery process.