Infections caused by a range of bacteria represent a significant medical need that is not being sufficiently addressed by the pharmaceutical industry. M. tuberculosis, the ESKAPE bacteria, and Select Agent bacteria constitute three classes of microbes that are relevant to global health in large part because of their resistance to available therapeutics. Most new antibacterials are developed by classical discovery methodologies, such as randomly assaying small molecule collections for growth inhibition ofthe appropriate bacterium. We have chosen to look at antibacterial drug discovery differently and sought a novel strategy utilizing Bayesian models to discover and optimize small molecule antibacterials that is more efficient. For example, we viewed the M. tuberculosis data generated from these random """"""""screens"""""""" as a computational learning opportunity. We have used computational algorithms to analyze what attributes ofthe molecules tested are consistent with activity and inactivity. Significantly, this approach yielded validated models for M. tuberculosis that have predicted actives with comparatively high rates of success. Thus, we propose two important extensions of this technology: 1) the optimization ofthe three most promising antitubercular actives arising from our models and 2) the creation and validation of this Bayesian methodology to uncover novel actives against each ofthe ESKAPE and Select Agent bacteria, which will be subsequently optimized. These optimization processes will afford molecules with significant potential as novel therapeutics.

Public Health Relevance

The rise of infectious diseases such as those due to Mycobacterium tuberculosis, ESKAPE, and Select Agent bacteria necessitates novel drug treatments. We have developed and validated computational techniques that learn from activity and cytotoxicity data sets to significantly accelerate drug discovery. We seek to employ these techniques to the discovery and optimization of novel antibacterials.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Program--Cooperative Agreements (U19)
Project #
Application #
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Rutgers University
United States
Zip Code
Kumar, Pradeep; Capodagli, Glenn C; Awasthi, Divya et al. (2018) Synergistic Lethality of a Binary Inhibitor of Mycobacterium tuberculosis KasA. MBio 9:
Nukaga, Michiyoshi; Papp-Wallace, Krisztina M; Hoshino, Tyuji et al. (2018) Probing the Mechanism of Inactivation of the FOX-4 Cephamycinase by Avibactam. Antimicrob Agents Chemother 62:
Becka, Scott A; Zeiser, Elise T; Marshall, Steven H et al. (2018) Sequence heterogeneity of the PenA carbapenemase in clinical isolates of Burkholderia multivorans. Diagn Microbiol Infect Dis 92:253-258
Vila-Farres, Xavier; Chu, John; Ternei, Melinda A et al. (2018) An Optimized Synthetic-Bioinformatic Natural Product Antibiotic Sterilizes Multidrug-Resistant Acinetobacter baumannii-Infected Wounds. mSphere 3:
Papp-Wallace, Krisztina M; Barnes, Melissa D; Alsop, Jim et al. (2018) Relebactam Is a Potent Inhibitor of the KPC-2 ?-Lactamase and Restores Imipenem Susceptibility in KPC-Producing Enterobacteriaceae. Antimicrob Agents Chemother 62:
Lane, Thomas; Russo, Daniel P; Zorn, Kimberley M et al. (2018) Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery. Mol Pharm 15:4346-4360
Papp-Wallace, Krisztina M; Nguyen, Nhu Q; Jacobs, Michael R et al. (2018) Strategic Approaches to Overcome Resistance against Gram-Negative Pathogens Using ?-Lactamase Inhibitors and ?-Lactam Enhancers: Activity of Three Novel Diazabicyclooctanes WCK 5153, Zidebactam (WCK 5107), and WCK 4234. J Med Chem 61:4067-4086
Lin, Wei; Das, Kalyan; Degen, David et al. (2018) Structural Basis of Transcription Inhibition by Fidaxomicin (Lipiarmycin A3). Mol Cell 70:60-71.e15
Inoyama, Daigo; Paget, Steven D; Russo, Riccardo et al. (2018) Novel Pyrimidines as Antitubercular Agents. Antimicrob Agents Chemother 62:
Becka, Scott A; Zeiser, Elise T; Barnes, Melissa D et al. (2018) Characterization of the AmpC ?-Lactamase from Burkholderia multivorans. Antimicrob Agents Chemother 62:

Showing the most recent 10 out of 23 publications