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Prioritization of Molecular Targets for Antimalarial Drug Discovery.

Barbara ForteSabine OttilieAndrew PlaterBrice CampoKoen J DecheringFrancisco Javier GamoDaniel E GoldbergEva S IstvanMarcus LeeAmanda K LukensCase W MacNamaraJacquin C NilesJohn OkomboCharisse Flerida A PasajeMiles G SiegelDyann WirthSusan WyllieDavid A FidockBeatriz BaragañaElizabeth A WinzelerIan H Gilbert
Published in: ACS infectious diseases (2021)
There is a shift in antimalarial drug discovery from phenotypic screening toward target-based approaches, as more potential drug targets are being validated in Plasmodium species. Given the high attrition rate and high cost of drug discovery, it is important to select the targets most likely to deliver progressible drug candidates. In this paper, we describe the criteria that we consider important for selecting targets for antimalarial drug discovery. We describe the analysis of a number of drug targets in the Malaria Drug Accelerator (MalDA) pipeline, which has allowed us to prioritize targets that are ready to enter the drug discovery process. This selection process has also highlighted where additional data are required to inform target progression or deprioritization of other targets. Finally, we comment on how additional drug targets may be identified.
Keyphrases
  • drug discovery
  • plasmodium falciparum
  • machine learning
  • risk assessment
  • climate change
  • big data
  • deep learning
  • single molecule
  • artificial intelligence