Cheminformatics-driven discovery of hit compounds against Paracoccidioides spp

Future Med Chem. 2023 Sep;15(17):1553-1567. doi: 10.4155/fmc-2022-0288. Epub 2023 Sep 20.

Abstract

Aims: The development of safe and effective therapies for treating paracoccidioidomycosis using computational strategies were employed to discover anti-Paracoccidioides compounds. Materials & methods: We 1) collected, curated and integrated the largest library of compounds tested against Paracoccidioides spp.; 2) employed a similarity search to virtually screen the ChemBridge database and select nine compounds for experimental evaluation; 3) performed an experimental evaluation to determine the minimum inhibitory concentration and minimum fungicidal concentration as well as cytotoxicity; and 4) employed computational tools to identify potential targets for the most active compounds. Seven compounds presented activity against Paracoccidioides spp. Conclusion: These compounds are new hits with a predicted mechanisms of action, making them potentially attractive to develop new compounds.

Keywords: antifungal; drug discovery; in silico; paracoccidioidomycosis; targets.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antifungal Agents / pharmacology
  • Antifungal Agents / therapeutic use
  • Cheminformatics
  • Microbial Sensitivity Tests
  • Paracoccidioides*
  • Paracoccidioidomycosis* / drug therapy

Substances

  • Antifungal Agents