Small molecule therapeutics have an extensive, and only partially known, multi-target pharmacology that defines both their beneficial and adverse effects. We have characterized these network for all cancer drugs. Furthermore, a team of researchers at Molsoft and UCSD developed a set of thousands models in which 3D models are combined with machine-learning layer to predict activity of any chemical against protein targets included in this panel. The models can be used to discover targets of any known drug or drug candidate, search for compounds with specific multi-target profile, repurpose drugs for a new indication or disease, or identify potential liabilities. Applications of multi-profile approach are presented.
