Automated affinity selection for rapid discovery of peptide binders

Area of Science:

• Biochemistry
• Chemical Biology
• Drug Discovery

Background:

• Affinity selection (AS) of synthetic peptide libraries identifies protein binders.
• Standard AS methods are often slow, low-throughput, and yield low-selectivity binders.
• Expanded chemical space offers opportunities for novel therapeutics.

Purpose of the Study:

• To develop an automated bio-layer interferometry (BLI)-assisted affinity selection platform.
• To enable rapid de novo discovery and affinity maturation of peptide binders.
• To enhance selectivity of identified peptide binders.

Main Methods:

• Utilized automated bio-layer interferometry (BLI) for affinity selection.
• Coupled BLI-assisted AS with tandem mass spectrometry (MS) for analysis.
• Implemented real-time monitoring of peptide binding during selection.

Main Results:

• Successfully identified novel nanomolar binders (KD < 50 nM) to the oncogenic protein menin.
• Demonstrated high selectivity of identified non-canonical binders.
• Achieved rapid de novo discovery and affinity maturation.

Conclusions:

• The BLI-assisted AS-MS platform enables rapid, selective discovery of peptide binders.
• This technology offers real-time binding monitoring, a novel feature for selection methods.
• The approach significantly accelerates the use of synthetic peptidomimetic libraries in drug discovery.