Artikel,

Targeting in silico GPCR conformations with ultra-large library screening for hit discovery

, , , , und .
Trends Pharmacol. Sci., 44 (3): 150--161 (März 2023)

Zusammenfassung

The use of deep machine learning (ML) in protein structure prediction has made it possible to easily access a large number of annotated conformations that can potentially compensate for missing experimental structures in structure-based drug discovery (SBDD). However, it is still unclear whether the accuracy of these predicted conformations is sufficient for screening chemical compounds that will effectively interact with a protein target for pharmacological purposes. In this opinion article, we examine the potential benefits and limitations of using state-annotated conformations for ultra-large library screening (ULLS) in light of the growing size of ultra-large libraries (ULLs). We believe that targeting different conformational states of common drug targets like G-protein-coupled receptors (GPCRs), which can regulate human physiology by switching between different conformations, can offer multiple advantages.

Tags

Nutzer

  • @scadsfct

Kommentare und Rezensionen