New techniques for systematic profiling of small-molecule effects can enhance traditional growth inhibition screens for antibiotic discovery and change how we search for new antibacterial agents. Computational models that integrate physicochemical compound properties with their phenotypic and molecular downstream effects can not only predict efficacy of molecules yet to be tested, but also reveal unprecedented insights on compound modes of action (MoAs). The unbiased characterization of compounds that themselves are not growth inhibitory but exhibit diverse MoAs, can expand antibacterial strategies beyond direct inhibition of core essential functions. Early and systematic functional annotation of compound libraries thus paves the way to new models in the selection of lead antimicrobial compounds. In this Review, we discuss how multidimensional small-molecule profiling and the ever-increasing computing power are accelerating the discovery of unconventional antibacterials capable of bypassing resistance and exploiting synergies with established antibacterial treatments and with protective host mechanisms.
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We thank N. de Souza, J. Sollier and M. Berney for helpful feedbacks and discussions. This work was supported by the National Center of Competence in Research AntiResist funded by the Swiss National Science Foundation (grant no. 180541) to M.Z., SNF Sinergia grant no. CRSII5_189952 to M.Z and the Swiss Cancer League (KLS 4124-02-2017) to M.Z. and K.O.
The authors declare no competing interests.
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Ortmayr, K., de la Cruz Moreno, R. & Zampieri, M. Expanding the search for small-molecule antibacterials by multidimensional profiling. Nat Chem Biol 18, 584–595 (2022). https://doi.org/10.1038/s41589-022-01040-4