Quantitative Comparison of Enrichment from DNA-Encoded Chemical Library Selections

Area of Science:

• Medicinal Chemistry
• Biotechnology
• Computational Biology

Background:

• DNA-encoded chemical libraries (DELs) enable high-throughput screening of vast molecular libraries for drug discovery.
• Accurate measurement of compound enrichment is crucial for identifying potent binders in DEL selections.
• Current methods for analyzing DEL selection data lack a standardized and robust enrichment metric.

Purpose of the Study:

• To propose and validate a novel, normalized z-score enrichment metric for DNA-encoded chemical library selections.
• To address the lack of consensus on how to measure and report enrichment in DEL experiments.
• To enable quantitative comparisons and robust analysis of DEL selection data.

Main Methods:

• Development of a normalized z-score enrichment metric based on a binomial distribution model.
• Application of the metric to analyze DNA-encoded chemical library selection data.
• Evaluation of the metric's robustness concerning library diversity and sampling.

Main Results:

• The proposed z-score metric provides a quantitative and comparable measure of enrichment for DEL selections.
• The metric is robust against variations in library diversity and sampling.
• It facilitates comparative analysis of n-synthons across parallel DEL selections.

Conclusions:

• The normalized z-score enrichment metric offers a reliable approach for analyzing DEL selection data.
• This method improves the identification of hit compounds in early-stage drug discovery.
• Standardization of enrichment measurement in DELs is essential for reproducible and informative results.