The ESKAPE Model is a machine learning-based online resource to facilitate discovery of novel antibiotics against the ESKAPE pathogens, a group of multidrug-resistant bacteria that are responsible for the majority of hospital-acquired infections. These pathogens have been identified by the World Health Organization as priority pathogens for the research and development of new treatments.

The ESKAPE Model predicts the antibacterial activity of inputted molecules against each of the following ESKAPE pathogens:

• EF - Enterococcus faecium
• SA - Staphylococcus aureus
• KP - Klebsiella pneumoniae
• AB - Acinetobacter baumannii
• PA - Pseudomonas aeruginosa
• BW - Escherichia coli (wildtype)
• DKO - Escherichia coli (hyperpermeable and efflux deficient)

Models were trained on in-house growth inhibition screening datasets against common laboratory strains of each pathogen. A total of 21 models were trained - three model architectures for each pathogen:

• Random forest using Morgan fingerprints
• Chemprop graph neural network
• Chemprop with RDKit features