Publications by authors named "Steve D Paget"

The triazine antitubercular JSF-2019 was of interest due to its in vitro efficacy and the nitro group shared with the clinically relevant delamanid and pretomanid. JSF-2019 undergoes activation requiring FH and one or more nitroreductases in addition to Ddn. An intrabacterial drug metabolism (IBDM) platform was leveraged to demonstrate the system kinetics, evidencing formation of NO and a des-nitro metabolite.

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Article Synopsis
  • Tuberculosis is a major global health issue, claiming 1.6 million lives each year and necessitating innovative drug discovery approaches.
  • A new computer-aided discovery method merges structure-based virtual screening with ligand-based machine learning using cell data, successfully identifying JSF-2164 as an effective inhibitor of InhA.
  • The study reveals that the drug's metabolism can mask its inhibitory effects, emphasizing the importance of understanding intrabacterial metabolism in drug development for tuberculosis treatment.
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Identification of unique leads represents a significant challenge in drug discovery. This hurdle is magnified in neglected diseases such as tuberculosis. We have leveraged public high-throughput screening (HTS) data to experimentally validate a virtual screening approach employing Bayesian models built with bioactivity information (single-event model) as well as bioactivity and cytotoxicity information (dual-event model).

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RWJ-416457, an investigational pyrrolopyrazolyl-substituted oxazolidinone, inhibited the growth of linezolid-susceptible staphylococci, enterococci, and streptococci at concentrations of < or =4 microg/ml, generally exhibiting two- to fourfold-greater potency than that of linezolid. Time-kill studies demonstrated bacteriostatic effects for both RWJ-416457 and linezolid.

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