A Novel Method for Normalizing Data from DNA-Encoded Library Selections

Abstract

DNA-encoded library screening represents a significant advancement in the field of drug discovery. Its ability to rapidly and cost-effectively identify potential drug candidates from large compound libraries has the potential to revolutionize the way new medicines are discovered and developed. While the strategies for DEL screening and data analysis have improved over the years, data normalization remains an open challenge. Existing normalization methods can yield poor correlation for compounds with high read count, and they do not account for inherent sources of noise. To overcome these drawbacks, we have developed a robust normalization technique using an antibody fragment and a DNA-conjugated peptide as an internal control. This innovative approach allows for normalization between samples of different conditions and accounts for technical challenges that occur during screening. Table of Contents Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/700605v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1b04b91org.highwire.dtl.DTLVardef@1312295org.highwire.dtl.DTLVardef@d59713org.highwire.dtl.DTLVardef@b1786a_HPS_FORMAT_FIGEXP M_FIG C_FIG SynopsisNormalization of DNA-encoded library selection data reduces bias and noise, enabling accurate identification of true binders and reliable enrichment analysis.