Compound-Transporter Interaction Studies using Canonical Correlation Analysis

The efficient screening of lead compounds or drug candidates for efficacy and safety is critically important during the early stage of drug development. Compounds are usually screened from a diverse ‘chemical space’ based only on its pharmacological effects, but this screening is not enough to guarantee drug safety. To solve this problem, we devised a chemical space that takes into account interaction information with proteins such as drug transporters. We also created and evaluated a mathematical model for predicting compound-transporter interactions. This was achieved by first generating an interaction correlation matrix based on drug transporters and their corresponding inhibitor compounds. To implement a screening scheme that takes into account interaction with drug transporters, we created a model using Canonical Correlation Analysis (CCA) that makes use of the known information on interaction between drug transporters and their corresponding inhibitors. Cross-validation of the model gave satisfactory test results and a physiologically relevant chemical space was constructed based on the model.