A method for estimating binding affinity from primary DEL selection data.

Area of Science:

• Biochemistry
• Chemical Biology
• Drug Discovery

Background:

• DNA-encoded library (DEL) selections are binding assays used to identify ligands with high affinity for a screening target.
• These assays typically rely on DNA sequence counts to quantify target binding, but a clear correlation between signal and affinity is often lacking.
• This disconnect may stem from incomplete library synthesis reactions and repetitive binding/elution steps in standard DEL selection protocols.

Purpose of the Study:

• To develop a novel strategy for DEL selections that accurately calculates ligand binding affinity from primary selection data.
• To address and overcome the limitations of current DEL selection methods, specifically issues related to library chemistry fidelity and selection round repetitions.
• To enable prediction of reaction yields for selected compounds during DEL library synthesis.

Main Methods:

• A new strategy was developed to analyze primary data from DEL selection experiments.
• The method accounts for potential biases introduced by library synthesis reaction yields and multiple binding/elution cycles.
• This approach allows for the direct calculation of ligand affinity.

Main Results:

• The described strategy provides a means to accurately calculate ligand affinity from DEL selection primary data.
• The method successfully addresses the disconnect between DNA sequence counts (assay signal) and actual binding affinity.
• The approach also enables the prediction of reaction yields for synthesized compounds within the DEL library.

Conclusions:

• This work presents a significant advancement in DEL selection methodology, enabling precise affinity determination.
• The developed strategy enhances the reliability and interpretability of DEL selection data.
• This method offers a valuable tool for optimizing ligand discovery and predicting synthesis outcomes in drug discovery programs.