Optimization of Benzoxazinorifamycins to Improve Mycobacterium tuberculosis RNA Polymerase Inhibition and Treatment of Tuberculosis

Optimization of Benzoxazinorifamycins to Minimize hPXR Activation for the Treatment of Tuberculosis and HIV Coinfection

Tuberculosis (TB) is one of the most significant world health problems, responsible for 1.5 M deaths in 2020, and yet, current treatments rely largely on 40 year old paradigms. Although the rifamycins (RIFs), best exemplified by the drug rifampin (RMP), represent a well-studied and therapeutically effective chemotype that targets the bacterial RNA polymerase (RNAP), these agents still suffer from serious drawbacks including the following: 3-9 month treatment times; cytochrome P450 (Cyp450) induction [particularly problematic for human immunodeficiency virus-Mycobacterium tuberculosis (MTB) co-infection]; and the existence of RIF-resistant (RIF^R) MTB strains. We have utilized a structure-based drug design approach to synthesize and test 15 benzoxazinorifamycins (bxRIFs), congeners of the clinical candidate rifalazil, to minimize human pregnane X receptor (hPXR) activation while improving potency against MTB. We have determined the compounds' activation of the hPXR [responsible for inducing Cyp450 3A4 (CYP3A4)]. Compound IC₅₀s have been determined against the wild-type and the most prevalent RIF^R (β-S450L) mutant MTB RNAPs. We have also determined their bactericidal activity against "normal" replicating MTB and a model for non-replicating, persister MTB. We have identified a minimal substitution and have probed larger substitutions that exhibit negligible hPXR activation (1.2-fold over the dimethyl sulfoxide control), many of which are 5- to 10-fold more potent against RNAPs and MTB than RMP. Importantly, we have analogues that are essentially equipotent against replicating MTB and non-replicating persister MTB, a property that is correlated with faster kill rates and may lead to shorter treatment durations. This work provides a proof of principle that the ansamycin core remains an attractive and effective scaffold for novel and dramatically improved RIFs.