Most recently, a deep-learning guided study predicted a novel antibiotic against Acinetobacter baumannii, which was named abaucin . Chemically synthesized abaucin and derivatives inhibited in vitro A.baumannii growth at the low micromolar range (~ 5 µM) and suppressed A.baumannii in a wound-infected mice model. Furthermore, abaucin displayed a desirable narrow bacterial spectrum which would favor host microbiota preservation during treatment, in contrast to many other antibiotics. In particular, abaucin was discovered by training a deep-learning model with a chemical library of 7500 molecules obtained from patented and synthetic origins. Briefly, 6.2 % inhibited A.baumannii in vitro growth at < 50 µM (active molecules). A training-set containing active and inactive virtual molecules computationally trained a deeplearning model. Finally, screening of the Drug Repurposing Hub library 2 with the deep-learning model, predicted high affinity compounds and discovered the abaucin lead . Additional molecular mechanistic studies found out that abaucin perturbs lipoprotein trafficking in A. baumannii by interacting with the lipoprotein outer membrane localization (Lol) protein complex.