PROJECT SUMMARY/ABSTRACT
This proposal presents a five-year research and career development plan focused on machine learning
(ML)-guided antibiotic development for multidrug-resistant Neisseria gonorrhoeae. The candidate, Melis
Anahtar, MD, PhD, has completed clinical pathology training at Massachusetts General Hospital (MGH) and is
now a postdoctoral researcher under the mentorship of Dr. James Collins at MIT and the Broad Institute. Dr.
Collins pioneered the field of ML-based antibiotic discovery and has trained over 70 independent research
investigators. The proposed project builds on Dr. Anahtar’s previous research experiences in the vaginal
microbiome and in genomic antimicrobial resistance (AMR) determinants. AMR poses an existential threat by
rendering existing antibiotics useless. This threat is exemplified by N. gonorrhoeae, a sexually transmitted
gram-negative bacterium that afflicts ~87 million people every year and has recently developed resistance to
ceftriaxone, the last remaining highly effective antibiotic treatment. Untreated gonorrhea causes infertility,
pregnancy complications, neonatal blindness, severe disseminated infection, and death, prompting the CDC
and WHO to recognize drug-resistant N. gonorrhoeae as one of the five most urgent AMR threats to human
health. Traditional drug discovery has failed to keep up with AMR and there is a critical need for innovative
approaches to fill the antibiotic development pipeline with promising candidates. To solve this problem, Dr.
Anahtar proposes using predictions from ML models to efficiently guide focused testing and development of
novel compounds for the treatment of drug-resistant N. gonorrhoeae. The central hypothesis is that ML models
such as graph neural networks can identify new antibiotic candidates for N. gonorrhoeae by predicting growth
inhibitory activity from chemical structures given high-quality training data. In preliminary work, Dr. Anahtar
phenotypically screened a foundational library of 38,000 chemically diverse compounds for N. gonorrhoeae
growth inhibition, used the results to train an ML model, and deployed the model to identify novel compounds
with activity against multidrug-resistant N. gonorrhoeae. To expand the pool of novel antibiotic candidates, Dr.
Anahtar will use this ML model to screen large (10^8) chemical libraries in silico and then validate the
predictions in vitro (Aim 1). The mechanism of action of the most potent and non-toxic compounds will then be
determined using microscopic, proteomic, and genomic approaches (Aim 2). Finally, their in vivo efficacy will
be tested in a preclinical animal model of N. gonorrhoeae infection (Aim 3). The long-term goal is to discover
new biological insights into the treatment of drug-resistant bacteria. This work will be performed at the Broad
Institute, MIT, and MGH, which provide an exceptional training environment and ample scientific resources.
The candidate is supported by an outstanding scientific advisory committee with decades of experience in N.
gonorrhoeae, AMR, medicinal chemistry, and mentoring physician-scientists. This career development award
will enable Dr. Anahtar’s transition to independence with a focus on understanding and combating AMR.