Integrating ¹⁹Focused Screening with Make-On-Demand Chemical Spaces for Enhanced Fragment Follow-Up.

Area of Science:

• Biochemistry
• Medicinal Chemistry
• Drug Discovery

Background:

• Fragment-based screening (FBS) is effective for identifying drug leads with good chemical properties.
• Ligand-observed 19F nuclear magnetic resonance (NMR) is a suitable biophysical technique for FBS.
• Challenges in hit follow-up due to limited chemistry resources can hinder FBS success.

Purpose of the Study:

• To integrate a 19F-focused screening platform with make-on-demand (MoD) spaces.
• To enhance fragment selection and streamline follow-up strategies for FBS hits.
• To demonstrate expandability of fragment hits using large, accessible chemical libraries.

Main Methods:

• Utilized a 19F-focused screening platform integrated with MoD spaces.
• Employed three distinct in silico approaches for fragment selection against the EED protein.
• Expanded hit chemotypes in the Enamine REAL Space using chemical space docking and free energy perturbation calculations.

Main Results:

• Successfully integrated FBS with MoD spaces for efficient fragment hit expansion.
• Identified and expanded two hit chemotypes against the EED protein.
• Demonstrated the utility of computational tools for selecting and ranking analogs from large chemical spaces.

Conclusions:

• The integration of FBS with MoD spaces effectively overcomes limitations in chemistry resources.
• This approach facilitates rapid analoging and hit expansion, accelerating the drug discovery pipeline.
• Computational methods play a crucial role in optimizing hit selection and follow-up strategies in fragment-based drug discovery.