insight

DNA encoded library (DEL) technology allows for rapid identification of novel small-molecule ligands and thus enables early-stage drug discovery. DEL technology is well-established, numerous cases of discovered hit molecules have been published, and the technology is widely employed throughout the pharmaceutical industry. Nonetheless, DEL selection results can be difficult to interpret, as library member enrichment may derive from not only desired products, but also DNA-conjugated byproducts and starting materials. Note that DELs are generally produced using split-and-pool combinatorial chemistry, and DNA-conjugated byproducts and starting materials cannot be removed from the library mixture. Herein, we describe a method for high-throughput parallel resynthesis of DNA-conjugated molecules such that byproducts, starting materials, and desired products are produced in a single pot, using the same chemical reactions and reagents as during library production. The low-complexity mixtures of DNA–conjugate are then assessed for protein binding by affinity selection mass spectrometry and the molecular weights of the binding ligands ascertained. This workflow is demonstrated to be a practical tool to triage and validate potential hits from DEL selection data.

Source: https://doi.org/10.1021/acs.bioconjchem.1c00170

DNA Encoded Libraries (DELs) use unique DNA sequences to tag each chemical warhead within a library mixture to enable deconvolution following affinity selection against a target protein. With next-generation sequencing, millions to billions of sequences can be read and counted to report binding events. This unprecedented capability has enabled researchers to synthesize and analyze numerically large chemical libraries. Despite the common perception that each library member undergoes a miniaturized affinity assay, selections with higher complexity libraries often produce results that are difficult to rank order. In this study, we aimed to understand the robustness of DEL selection by examining the sequencing readouts of warheads and chemotype families among a large number of experimentally repeated selections. The results revealed that (1) the output of DEL selection is intrinsically noisy but can be reliably modeled by the Poisson distribution, and (2) Poisson noise is the dominating noise at low copy counts and can be estimated even from a single experiment. We also discuss the shortcomings of data analyses based on directly using copy counts and their linear transformations, and propose a framework that incorporates proper normalization and confidence interval calculation to help researchers better understand DEL data.

Source: https://doi.org/10.1177/2472555218757718