A series of quinazolin-4-one based hydroxamic acids was rationally designed and synthesized as novel dual PI3K/HDAC inhibitors by incorporating an HDAC pharmacophore into a PI3K inhibitor (Idelalisib) via an optimized linker. Several of these dual inhibitors were highly potent (IC 50 < 10 nM) and selective against PI3Kγ, δ and HDAC6 enzymes and exhibited good antiproliferative activity against multiple cancer cell lines. The lead compound 48c, induced necrosis in several mutant and FLT3-resistant AML cell lines and primary blasts from AML patients, while showing no cytotoxicity against normal PBMCs, NIH3T3, and HEK293 cells. Target engagement of PI3Kδ and HDAC6 by 48c was demonstrated in MV411 cells using the cellular thermal shift assay (CETSA). Compound 48c showed good pharmacokinetics properties in mice via intraperitoneal (ip) administration and provides a means to examine the biological effects of inhibiting these two important enzymes with a single molecule, either in vitro or in vivo.

Lactate dehydrogenase (LDH) catalyzes the conversion of pyruvate to lactate, with concomitant oxidation of reduced nicotinamide adenine dinucleotide as the final step in the glycolytic pathway. Glycolysis plays an important role in the metabolic plasticity of cancer cells and has long been recognized as a potential therapeutic target. Thus, potent, selective inhibitors of LDH represent an attractive therapeutic approach. However, to date, pharmacological agents have failed to achieve significant target engagement in vivo, possibly because the protein is present in cells at very high concentrations. We report herein a lead optimization campaign focused on a pyrazole-based series of compounds, using structure-based design concepts, coupled with optimization of cellular potency, in vitro drug−target residence times, and in vivo PK properties, to identify first-in-class inhibitors that demonstrate LDH inhibition in vivo. The lead compounds, named NCATS-SM1440 (43) and NCATS-SM1441 (52), possess desirable attributes for further studying the effect of in vivo LDH inhibition.

Hepatic metabolic stability is a key pharmacokinetic parameter in drug discovery. Metabolic stability is usually assessed in microsomal fractions and only the best compounds progress in the drug discovery process. A high-throughput single time point substrate depletion assay in rat liver microsomes (RLM) is employed at the National Center for Advancing Translational Sciences. Between 2012 and 2020, RLM stability data was generated for ~ 24,000 compounds from more than 250 projects that cover a wide range of pharmacological targets and cellular pathways. Although a crucial endpoint, little or no data exists in the public domain. In this study, computational models were developed for predicting RLM stability using different machine learning methods. In addition, a retrospective time-split validation was performed, and local models were built for projects that performed poorly with global models. Further analysis revealed inherent medicinal chemistry knowledge potentially useful to chemists in the pursuit of synthesizing metabolically stable compounds. In addition, we deposited experimental data for ~ 2500 compounds in the PubChem bioassay database (AID: 1508591). The global prediction models are made publicly accessible (https://opendata.ncats.nih.gov/adme). This is to the best of our knowledge, the first publicly available RLM prediction model built using high-quality data generated at a single laboratory.