The antibiotic sorangicin A inhibits promoter DNA unwinding in a Mycobacterium tuberculosis rifampicin-resistant RNA polymerase.
Mirjana LilicJames ChenHande BoyaciNathaniel R BraffmanElizabeth A HubinJennifer HerrmannDaniel KrugRachel MooneyRobert LandickSeth A DarstElizabeth A CampbellPublished in: Proceedings of the National Academy of Sciences of the United States of America (2020)
Rifampicin (Rif) is a first-line therapeutic used to treat the infectious disease tuberculosis (TB), which is caused by the pathogen Mycobacterium tuberculosis (Mtb). The emergence of Rif-resistant (RifR) Mtb presents a need for new antibiotics. Rif targets the enzyme RNA polymerase (RNAP). Sorangicin A (Sor) is an unrelated inhibitor that binds in the Rif-binding pocket of RNAP. Sor inhibits a subset of RifR RNAPs, including the most prevalent clinical RifR RNAP substitution found in Mtb infected patients (S456>L of the β subunit). Here, we present structural and biochemical data demonstrating that Sor inhibits the wild-type Mtb RNAP by a similar mechanism as Rif: by preventing the translocation of very short RNAs. By contrast, Sor inhibits the RifR S456L enzyme at an earlier step, preventing the transition of a partially unwound promoter DNA intermediate to the fully opened DNA and blocking the template-strand DNA from reaching the active site in the RNAP catalytic center. By defining template-strand blocking as a mechanism for inhibition, we provide a mechanistic drug target in RNAP. Our finding that Sor inhibits the wild-type and mutant RNAPs through different mechanisms prompts future considerations for designing antibiotics against resistant targets. Also, we show that Sor has a better pharmacokinetic profile than Rif, making it a suitable starting molecule to design drugs to be used for the treatment of TB patients with comorbidities who require multiple medications.
Keyphrases
- pulmonary tuberculosis
- mycobacterium tuberculosis
- wild type
- circulating tumor
- single molecule
- cell free
- dna methylation
- gene expression
- magnetic resonance
- infectious diseases
- transcription factor
- nucleic acid
- electronic health record
- machine learning
- candida albicans
- computed tomography
- mass spectrometry
- deep learning
- contrast enhanced
- drug induced
- artificial intelligence
- current status