A platform for target prediction of phenotypic screening hit molecules

Nadine Homeyer, Ruud van Deursen, Bernardo Ochoa-Montaño, Kathrin Heikamp, Peter Ray, Fabio Zuccotto, Tom L. Blundell, Ian H. Gilbert (Lead / Corresponding author)

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Abstract

Many drug discovery programmes, particularly for infectious diseases, are conducted phenotypically. Identifying the targets of phenotypic screening hits experimentally can be complex, time-consuming, and expensive. However, it would be valuable to know what the molecular target(s) is, as knowledge of the binding pose of the hit molecule in the binding site can facilitate the compound optimisation. Furthermore, knowing the target would allow de-prioritisation of less attractive chemical series or molecular targets. To generate target-hypotheses for phenotypic active compounds, an in silico platform was developed that utilises both ligand and protein-structure information to generate a ranked set of predicted molecular targets. As a result of the web-based workflow the user obtains a set of 3D structures of the predicted targets with the active molecule bound. The platform was exemplified using Mycobacterium tuberculosis, the causative organism of tuberculosis. In a test that we performed, the platform was able to predict the targets of 60% of compounds investigated, where there was some similarity to a ligand in the protein database.

Original languageEnglish
Article number107485
Pages (from-to)1-9
Number of pages9
JournalJournal of Molecular Graphics & Modelling
Volume95
Early online date24 Oct 2019
DOIs
Publication statusPublished - Mar 2020

Keywords

  • Fragment-based target prediction
  • Ligand similarity
  • Scaffold hopping
  • Cavity comparison
  • Hit docking with constraints

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