Drug screening with Elastic-net multiple kernel learning

We apply Elastic-net Multiple Kernel Learning (MKL) to the MDL Drug Data Report (MDDR) database for the problem of drug screening. We show that combining a set of kernels constructed from fingerprint descriptors, can significantly improve the accuracy of prediction, against a Support Vector Machine trained on each kernel separately. To the best of our knowledge, this is the first application of MKL to the MDDR database for drug screening.