Drugging the undruggable: From TranscriptOMICS to drug-targets to modulating signaling pathways
Many high-value pharmaceutical targets are very difficult to drug using traditional approaches, with flexibility or outright intrinsic disorder being the main obstacle. I will describe the origin of disorder in protein interactions and biophysical and omics "out-of-the-box" approaches to drug this new class of targets. Specifically, using gene expression profiles, we validated a machine learning/structural methods approach that reveals important, human-interpretable insights into perturbation-response properties of cellular networks. This methodology allows us to prospectively identified modulators to challenging targets, providing a unique view on the translational potential of gene expression data to various realms of biology and medicine.