A Screening Pattern Recognition Method Finds New and Divergent Targets for Drugs and Natural Products

Computational target prediction methods using chemical descriptors have been applied exhaustively in drug discovery to elucidate the mechanisms-of-action (MOAs) of small molecules. To predict truly novel and unexpected small molecule–target interactions, compounds must be compared by means other than their chemical structure alone. Here we investigated predictions made by a method, HTS fingerprints (HTSFPs), that matches patterns of activities in experimental screens. Over 1,400 drugs and 1,300 natural products (NPs) were screened in more than 200 diverse assays, creating encodable activity patterns. The comparison of these activity patterns to an MOA-annotated reference panel led to the prediction of 5,281 and 2,798 previously unknown targets for the NP and drug sets, respectively. Intriguingly, there was limited overlap among the targets predicted; the drugs were more biased toward membrane receptors and the NPs toward soluble enzymes, consistent with the idea that they represent unexplored pharmacologies. Importantly, HTSFPs inferred targets that were beyond the prediction capabilities of standard chemical descriptors, especially for NPs but also for the more explored drug set. Of 65 drug–target predictions that we tested <i>in vitro</i>, 48 (73.8%) were confirmed with AC₅₀ values ranging from 38 nM to 29 μM. Among these interactions was the inhibition of cyclooxygenases 1 and 2 by the HIV protease inhibitor Tipranavir. These newly discovered targets that are phylogenetically and phylochemically distant to the primary target provide an explanation for spontaneous bleeding events observed for patients treated with this drug, a physiological effect that was previously difficult to reconcile with the drug’s known MOA

Discovery of Novel Dot1L Inhibitors through a Structure-Based Fragmentation Approach

Oncogenic MLL fusion proteins aberrantly recruit Dot1L, a histone methyltransferase, to ectopic loci, leading to local hypermethylation of H3K79 and misexpression of HoxA genes driving MLL-rearranged leukemias. Inhibition of the methyltransferase activity of Dot1L in this setting is predicted to reverse aberrant H3K79 methylation, leading to repression of leukemogenic genes and tumor growth inhibition. In the context of our Dot1L drug discovery program, high-throughput screening led to the identification of <b>2</b>, a weak Dot1L inhibitor with an unprecedented, induced pocket binding mode. A medicinal chemistry campaign, strongly guided by structure-based consideration and ligand-based morphing, enabled the discovery of <b>12</b> and <b>13</b>, potent, selective, and structurally completely novel Dot1L inhibitors