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AntiBac-Pred: A Web Application for Predicting Antibacterial Activity of Chemical Compounds.

Pavel V PogodinAlexey A LaguninAnastassia V RudikDmitry S DruzhilovskiyDmitry A FilimonovVladimir V Poroikov
Published in: Journal of chemical information and modeling (2019)
Discovery of new antibacterial agents is a never-ending task of medicinal chemistry. Every new drug brings significant improvement to patients with bacterial infections, but prolonged usage of antibacterials leads to the emergence of resistant strains. Therefore, novel active structures with new modes of action are required. We describe a web application called AntiBac-Pred aimed to help users in the rational selection of the chemical compounds for experimental studies of antibacterial activity. This application is developed using antibacterial activity data available in ChEMBL and PASS software. It allows users to classify chemical structures of interest into growth inhibitors or noninhibitors of 353 different bacteria strains, including both resistant and nonresistant ones.
Keyphrases
  • silver nanoparticles
  • escherichia coli
  • high resolution
  • small molecule
  • emergency department
  • data analysis
  • machine learning
  • drug discovery