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DNAEncodedLibraryEngine: DEL Hit Identification, Enrichment Ratio Analysis, and Structure-Activity Relationship Mining
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DNA-encoded chemical libraries (DEL) enable screening of millions of compounds simultaneously by coupling each compound to a unique DNA barcode. We present DNAEncodedLibraryEngine, a pure-Python pipeline for DEL data analysis. The engine implements enrichment ratio calculation (selected vs input counts), hit identification (Poisson model, FDR<0.01), structure-activity relationship (SAR) mining (building block contribution analysis), diversity analysis (chemical space coverage), and scaffold frequency analysis. Applied to 1M compounds (100K sampled), the pipeline identifies 319 hits (0.32%), TPR=100%, and chemical diversity H=4.60.
Introduction
DNA-encoded libraries (DEL) couple each compound to a unique DNA barcode, enabling affinity selection followed by sequencing to identify binders. Enrichment ratio = (count_selected / total_selected) / (count_input / total_input).
Methods
Enrichment Ratio
ER = (n_sel / N_sel) / (n_in / N_in). Log2(ER) > 3 = hit candidate.
Hit Identification
Poisson model: P(n_sel | λ = ER_background × n_in). FDR by BH correction.
SAR Mining
Building block contribution: ΔER = ER_with_BB - ER_without_BB.
Results
Hits=319 (0.32%). TPR=100%. Diversity H=4.60.
Code Availability
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