A machine learning model trained on a high-throughput antibacterial screen increases the hit rate of drug discovery
Fig 5
Synergy maps of STL558147 and rifampicin combined with other antibiotics against B. cenocepacia K56-2.
Synergy plots of STL558147 (A) and rifampicin (B) with ceftazidime, colistin, and polymyxin B. The synergy scores were calculated based on the widely used Bliss independence [52] and Loewe additivity [53] models. The most synergistic area in each combination is highlighted with a rectangular box inside the plot. Green (negative δ-scores) indicate antagonistic interactions, and red (positive δ-scores) indicate synergistic interactions. Synergy scores >15, between -5 to 15, and < -15 were considered synergistic, additive and antagonistic, respectively. Results are average of at least three independent biological replicates. Synergy scores are shown as mean ± SEM. Synergy scores were calculated using SynergyFinder 2.0 [31].