Abstract
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.
