Robustness of In Vitro Selection Assays of DNA-Encoded Peptidomimetic Ligands to CBX7 and CBX8

Challenges and Prospects of DNA-Encoded Library Data Interpretation

DNA-encoded library (DEL) technology is a powerful platform for the efficient identification of novel chemical matter in the early drug discovery process enabled by parallel screening of vast libraries of encoded small molecules through affinity selection and deep sequencing. While DEL selections provide rich data sets for computational drug discovery, the underlying technical factors influencing DEL data remain incompletely understood. This review systematically examines the key parameters affecting the chemical information in DEL data and their impact on hit triaging and machine learning integration. The need for rigorous data handling and interpretation is emphasized, with standardized methods being critical for the success of DEL-based approaches. Major challenges include the relationship between sequence counts and binding affinities, frequent hitters, and the influence of factors such as inhomogeneous library composition, DNA damage, and linkers on binding modes. Experimental artifacts, such as those caused by protein immobilization and screening matrix effects, further complicate data interpretation. Recent advancements in using machine learning to denoise DEL data and predict drug candidates are highlighted. This review offers practical guidance on adopting best practices for integrating robust methodologies, comprehensive data analysis, and computational tools to improve the accuracy and efficacy of DEL-driven hit discovery.

Discovery and Optimization of WDR5 Inhibitors via Cascade Deoxyribonucleic Acid-Encoded Library Selection Approach

The DNA-encoded library (DEL) is a powerful hit generation tool for chemical biology and drug discovery; however, the optimization of DEL hits remained a daunting challenge for the medicinal chemistry community. In this study, hit compounds targeting the WIN binding domain of WDR5 were discovered by the initial three-cycle linear DEL selection, and their potency was further enhanced by a cascade DEL selection from the focused DEL designed based on the original first run DEL hits. As expected, these new compounds from the second run of focused DEL were more potent WDR5 inhibitors in the protein binding assay confirmed by the off-DNA synthesis. Interestingly, selected inhibitors exhibited good antiproliferative activity in two human acute leukemia cell lines. Taken together, this new cascade DEL selection strategy may have tremendous potential for finding high-affinity leads against WDR5 and provide opportunities to explore and optimize inhibitors for other targets.

Small-molecule discovery through DNA-encoded libraries

The development of bioactive small molecules as probes or drug candidates requires discovery platforms that enable access to chemical diversity and can quickly reveal new ligands for a target of interest. Within the past 15 years, DNA-encoded library (DEL) technology has matured into a widely used platform for small-molecule discovery, yielding a wide variety of bioactive ligands for many therapeutically relevant targets. DELs offer many advantages compared with traditional screening methods, including efficiency of screening, easily multiplexed targets and library selections, minimized resources needed to evaluate an entire DEL and large library sizes. This Review provides accounts of recently described small molecules discovered from DELs, including their initial identification, optimization and validation of biological properties including suitability for clinical applications.

Machine-Learning-Based Data Analysis Method for Cell-Based Selection of DNA-Encoded Libraries

DNA-encoded library (DEL) is a powerful ligand discovery technology that has been widely adopted in the pharmaceutical industry. DEL selections are typically performed with a purified protein target immobilized on a matrix or in solution phase. Recently, DELs have also been used to interrogate the targets in the complex biological environment, such as membrane proteins on live cells. However, due to the complex landscape of the cell surface, the selection inevitably involves significant nonspecific interactions, and the selection data are much noisier than the ones with purified proteins, making reliable hit identification highly challenging. Researchers have developed several approaches to denoise DEL datasets, but it remains unclear whether they are suitable for cell-based DEL selections. Here, we report the proof-of-principle of a new machine-learning (ML)-based approach to process cell-based DEL selection datasets by using a Maximum A Posteriori (MAP) estimation loss function, a probabilistic framework that can account for and quantify uncertainties of noisy data. We applied the approach to a DEL selection dataset, where a library of 7,721,415 compounds was selected against a purified carbonic anhydrase 2 (CA-2) and a cell line expressing the membrane protein carbonic anhydrase 12 (CA-12). The extended-connectivity fingerprint (ECFP)-based regression model using the MAP loss function was able to identify true binders and also reliable structure-activity relationship (SAR) from the noisy cell-based selection datasets. In addition, the regularized enrichment metric (known as MAP enrichment) could also be calculated directly without involving the specific machine-learning model, effectively suppressing low-confidence outliers and enhancing the signal-to-noise ratio. Future applications of this method will focus on de novo ligand discovery from cell-based DEL selections.

Chromobox proteins in cancer: Multifaceted functions and strategies for modulation (Review)

Chromobox (CBX) proteins are important epigenetic regulatory proteins and are widely involved in biological processes, such as embryonic development, the maintenance of stem cell characteristics and the regulation of cell proliferation and apoptosis. Disorder and dysfunction of CBXs in cancer usually lead to the blockade or ectoptic activation of developmental pathways, promoting the occurrence, development and progression of cancer. In the present review, the characteristics and functions of CBXs were first introduced. Subsequently, the expression of CBXs in cancers and the relationship between CBXs and clinical characteristics (mainly cancer grade, stage, metastasis and relapse) and prognosis were discussed. Finally, it was described how CBXs regulate cell proliferation and self‑renewal, apoptosis and the acquisition of malignant phenotypes, such as invasion, migration and chemoresistance, through mechanisms involving epigenetic modification, nuclear translocation, noncoding RNA interactions, transcriptional regulation, posttranslational modifications, protein‑protein interactions, signal transduction and metabolic reprogramming. The study also focused on cancer therapies targeting CBXs. The present review provides new insight and a comprehensive basis for follow‑up research on CBXs and cancer.

Machine Learning on DNA-Encoded Library Count Data Using an Uncertainty-Aware Probabilistic Loss Function

DNA-encoded library (DEL) screening and quantitative structure-activity relationship (QSAR) modeling are two techniques used in drug discovery to find novel small molecules that bind a protein target. Applying QSAR modeling to DEL selection data can facilitate the selection of compounds for off-DNA synthesis and evaluation. Such a combined approach has been done recently by training binary classifiers to learn DEL enrichments of aggregated "disynthons" in order to accommodate the sparse and noisy nature of DEL data. However, a binary classification model cannot distinguish between different levels of enrichment, and information is potentially lost during disynthon aggregation. Here, we demonstrate a regression approach to learning DEL enrichments of individual molecules, using a custom negative-log-likelihood loss function that effectively denoises DEL data and introduces opportunities for visualization of learned structure-activity relationships. Our approach explicitly models the Poisson statistics of the sequencing process used in the DEL experimental workflow under a frequentist view. We illustrate this approach on a DEL dataset of 108,528 compounds screened against carbonic anhydrase (CAIX), and a dataset of 5,655,000 compounds screened against soluble epoxide hydrolase (sEH) and SIRT2. Due to the treatment of uncertainty in the data through the negative-log-likelihood loss used during training, the models can ignore low-confidence outliers. While our approach does not demonstrate a benefit for extrapolation to novel structures, we expect our denoising and visualization pipeline to be useful in identifying structure-activity trends and highly enriched pharmacophores in DEL data. Further, this approach to uncertainty-aware regression modeling is applicable to other sparse or noisy datasets where the nature of stochasticity is known or can be modeled; in particular, the Poisson enrichment ratio metric we use can apply to other settings that compare sequencing count data between two experimental conditions.

Recent advances in DNA-encoded dynamic libraries

The DNA-encoded chemical library (DEL) has emerged as a powerful technology platform in drug discovery and is also gaining momentum in academic research. The rapid development of DNA-/DEL-compatible chemistries has greatly expanded the chemical space accessible to DELs. DEL technology has been widely adopted in the pharmaceutical industry and a number of clinical drug candidates have been identified from DEL selections. Recent innovations have combined DELs with other legacy and emerging techniques. Among them, the DNA-encoded dynamic library (DEDL) introduces DNA encoding into the classic dynamic combinatorial libraries (DCLs) and also integrates the principle of fragment-based drug discovery (FBDD), making DEDL a novel approach with distinct features from static DELs. In this Review, we provide a summary of the recently developed DEDL methods and their applications. Future developments in DEDLs are expected to extend the application scope of DELs to complex biological systems with unique ligand-discovery capabilities.

Strategies for developing DNA-encoded libraries beyond binding assays

DNA-encoded chemical libraries (DELs) have emerged as a powerful technology in drug discovery. The wide adoption of DELs in the pharmaceutical industry and the rapid advancements of DEL-compatible chemistry have further fuelled its development and applications. In general, a DEL has been considered as a massive binding assay to identify physical binders for individual protein targets. However, recent innovations demonstrate the capability of DELs to operate in the complex milieu of biological systems. In this Perspective, we discuss the recent progress in using DNA-encoded chemical libraries to interrogate complex biological targets and their potential to identify structures that elicit function or possess other useful properties. Future breakthroughs in these aspects are expected to catapult DEL to become a momentous technology platform not only for drug discovery but also to explore fundamental biology.

Discovery of Potent Peptidomimetic Antagonists for Heterochromatin Protein 1 Family Proteins

The heterochromatin protein 1 (HP1) sub-family of CBX chromodomains are responsible for the recognition of histone H3 lysine 9 tri-methyl (H3K9me3)-marked nucleosomal substrates through binding of the N-terminal chromodomain. These HP1 proteins, namely, CBX1 (HP1β), CBX3 (HP1γ), and CBX5 (HP1α), are commonly associated with regions of pericentric heterochromatin, but recent literature studies suggest that regulation by these proteins is likely more dynamic and includes other loci. Importantly, there are no chemical tools toward HP1 chromodomains to spatiotemporally explore the effects of HP1-mediated processes, underscoring the need for novel HP1 chemical probes. Here, we report the discovery of HP1 targeting peptidomimetic compounds, UNC7047 and UNC7560, and a biotinylated derivative tool compound, UNC7565. These compounds represent an important milestone, as they possess nanomolar affinity for the CBX5 chromodomain by isothermal titration calorimetry (ITC) and bind HP1-containing complexes in cell lysates. These chemical tools provide a starting point for further optimization and the study of CBX5-mediated processes.

Polycomb group proteins in cancer: multifaceted functions and strategies for modulation

Polycomb repressive complexes (PRCs) are a heterogenous collection of dozens, if not hundreds, of protein complexes composed of various combinations of subunits. PRCs are transcriptional repressors important for cell-type specificity during development, and as such, are commonly mis-regulated in cancer. PRCs are broadly characterized as PRC1 with histone ubiquitin ligase activity, or PRC2 with histone methyltransferase activity; however, the mechanism by which individual PRCs, particularly the highly diverse set of PRC1s, alter gene expression has not always been clear. Here we review the current understanding of how PRCs act, both individually and together, to establish and maintain gene repression, the biochemical contribution of individual PRC subunits, the mis-regulation of PRC function in different cancers, and the current strategies for modulating PRC activity. Increased mechanistic understanding of PRC function, as well as cancer-specific roles for individual PRC subunits, will uncover better targets and strategies for cancer therapies.

Polycomb Paralog Chromodomain Inhibitors Active against Both CBX6 and CBX8*

Methyllysine reader proteins bind to methylated lysine residues and alter gene transcription by changing either the compaction state of chromatin or by the recruitment of other multiprotein complexes. The polycomb paralog family of methyllysine readers bind to trimethylated lysine on the tail of histone 3 (H3) via a highly conserved aromatic cage located in their chromodomains. Each of the polycomb paralogs are implicated in several disease states. CBX6 and CBX8 are members of the polycomb paralog family with two structurally similar chromodomains. By exploring the structure-activity relationships of a previously reported CBX6 inhibitor we have discovered more potent and cell permeable analogs. Our current report includes potent, dual-selective inhibitors of CBX6 and CBX8. We have shown that the -2 position in our scaffold is an important residue for selectivity amongst the polycomb paralogs. Preliminary cell-based studies show that the new inhibitors impact cell proliferation in a rhabdoid tumor cell line.

A Potent, Selective CBX2 Chromodomain Ligand and Its Cellular Activity During Prostate Cancer Neuroendocrine Differentiation

Polycomb group (PcG) proteins are epigenetic regulators that facilitate both embryonic development and cancer progression. PcG proteins form Polycomb repressive complexes 1 and 2 (PRC1 and PRC2). PRC2 trimethylates histone H3 lysine 27 (H3K27me3), a histone mark recognized by the N-terminal chromodomain (ChD) of the CBX subunit of canonical PRC1. There are five PcG CBX paralogs in humans. CBX2 in particular is upregulated in a variety of cancers, particularly in advanced prostate cancers. Using CBX2 inhibitors to understand and target CBX2 in prostate cancer is highly desirable; however, high structural similarity among the CBX ChDs has been challenging for developing selective CBX ChD inhibitors. Here, we utilize selections of focused DNA encoded libraries (DELs) for the discovery of a selective CBX2 chromodomain probe, SW2_152F. SW2_152F binds to CBX2 ChD with a Kd of 80 nM and displays 24-1000-fold selectivity for CBX2 ChD over other CBX paralogs in vitro. SW2_152F is cell permeable, selectively inhibits CBX2 chromatin binding in cells, and blocks neuroendocrine differentiation of prostate cancer cell lines in response to androgen deprivation.

Scanning Protein Surfaces with DNA-Encoded Libraries

Understanding the ligandability of a target protein, defined as the capability of a protein to bind drug-like compounds on any site, can give important stimuli to drug-development projects. For instance, inhibition of protein-protein interactions usually depends on the identification of protein surface binders. DNA-encoded chemical libraries (DELs) allow scanning of protein surfaces with large chemical space. Encoded library selection screens uncovered several protein-protein interaction inhibitors and compounds binding to the surface of G protein-coupled receptors (GPCRs) and kinases. The protein surface-binding chemotypes from DELs are predominantly chemically modified and cyclized peptides, and functional small-molecule peptidomimetics. Peptoid libraries and structural peptidomimetics have been less studied in the DEL field, hinting at hitherto less populated chemical space and suggesting alternative library designs. Roughly a third of bioactive molecules evolved from smaller, target-focused libraries. They showcase the potential of encoded libraries to identify more potent molecules from weak, for example, fragment-like, starting points.

Peptides and pseudopeptide ligands: a powerful toolbox for the affinity purification of current and next-generation biotherapeutics

Following the consolidation of therapeutic proteins in the fight against cancer, autoimmune, and neurodegenerative diseases, recent advancements in biochemistry and biotechnology have introduced a host of next-generation biotherapeutics, such as CRISPR-Cas nucleases, stem and car-T cells, and viral vectors for gene therapy. With these drugs entering the clinical pipeline, a new challenge lies ahead: how to manufacture large quantities of high-purity biotherapeutics that meet the growing demand by clinics and biotech companies worldwide. The protein ligands employed by the industry are inadequate to confront this challenge: while featuring high binding affinity and selectivity, these ligands require laborious engineering and expensive manufacturing, are prone to biochemical degradation, and pose safety concerns related to their bacterial origin. Peptides and pseudopeptides make excellent candidates to form a new cohort of ligands for the purification of next-generation biotherapeutics. Peptide-based ligands feature excellent target biorecognition, low or no toxicity and immunogenicity, and can be manufactured affordably at large scale. This work presents a comprehensive and systematic review of the literature on peptide-based ligands and their use in the affinity purification of established and upcoming biological drugs. A comparative analysis is first presented on peptide engineering principles, the development of ligands targeting different biomolecular targets, and the promises and challenges connected to the industrial implementation of peptide ligands. The reviewed literature is organized in (i) conventional (α-)peptides targeting antibodies and other therapeutic proteins, gene therapy products, and therapeutic cells; (ii) cyclic peptides and pseudo-peptides for protein purification and capture of viral and bacterial pathogens; and (iii) the forefront of peptide mimetics, such as β-/γ-peptides, peptoids, foldamers, and stimuli-responsive peptides for advanced processing of biologics.

Peptide Folding and Binding Probed by Systematic Non-canonical Mutagenesis

Many proteins and peptides fold upon binding another protein. Mutagenesis has proved an essential tool in the study of these multi-step molecular recognition processes. By comparing the biophysical behavior of carefully selected mutants, the concert of interactions and conformational changes that occur during folding and binding can be separated and assessed. Recently, this mutagenesis approach has been radically expanded by deep mutational scanning methods, which allow for many thousands of mutations to be examined in parallel. Furthermore, these high-throughput mutagenesis methods have been expanded to include mutations to non-canonical amino acids, returning peptide structure-activity relationships with unprecedented depth and detail. These developments are timely, as the insights they provide can guide the optimization of de novo cyclic peptides, a promising new modality for chemical probes and therapeutic agents.

An overview of DNA-encoded libraries: A versatile tool for drug discovery

DNA-encoded libraries (DELs) are collections of small molecules covalently attached to amplifiable DNA tags carrying unique information about the structure of each library member. A combinatorial approach is used to construct the libraries with iterative DNA encoding steps, facilitating tracking of the synthetic history of the attached compounds by DNA sequencing. Various screening protocols have been developed which allow protein target binders to be selected out of pools containing up to billions of different small molecules. The versatile methodology has allowed identification of numerous biologically active compounds and is now increasingly being adopted as a tool for lead discovery campaigns and identification of chemical probes. A great focus in recent years has been on developing DNA compatible chemistries that expand the structural diversity of the small molecule library members in DELs. This chapter provides an overview of the challenges and accomplishments in DEL technology, reviewing the technological aspects of producing and screening DELs with a perspective on opportunities, limitations, and future directions.

The Impact of Variable Selection Coverage on Detection of Ligands from a DNA-Encoded Library Screen

DNA-encoded library (DEL) technology has become a prominent screening platform in drug discovery owing to the capacity to screen billions or trillions of compounds in a single experiment. Although numerous successes with DEL technology have been reported, we are unaware of a rigorous examination of the many different variables that can influence a screen’s success. Herein, we explore the impact of variable sample sequencing depth on the detection of tool compounds with known affinities toward a given target while simultaneously probing the effect of initial compound input. Our sequencing data confirm reports that high-affinity compounds can be discovered directly from a DEL screen, but we demonstrate that a mismatch between selection output and sequencing quantity can obscure useful ligands. Our results highlight the importance of selection coverage in grasping the entire picture of a DEL screen where the signal of a weak or underrepresented ligand may be suppressed by the inherent noise of a selection. These potential missed ligands may be critical to the success or failure of a drug discovery program.

Design and Construction of a Focused DNA-Encoded Library for Multivalent Chromatin Reader Proteins

Chromatin structure and function, and consequently cellular phenotype, is regulated in part by a network of chromatin-modifying enzymes that place post-translational modifications (PTMs) on histone tails. These marks serve as recruitment sites for other chromatin regulatory complexes that ‘read’ these PTMs. High-quality chemical probes that can block reader functions of proteins involved in chromatin regulation are important tools to improve our understanding of pathways involved in chromatin dynamics. Insight into the intricate system of chromatin PTMs and their context within the epigenome is also therapeutically important as misregulation of this complex system is implicated in numerous human diseases. Using computational methods, along with structure-based knowledge, we have designed and constructed a focused DNA-Encoded Library (DEL) containing approximately 60,000 compounds targeting bi-valent methyl-lysine (Kme) reader domains. Additionally, we have constructed DNA-barcoded control compounds to allow optimization of selection conditions using a model Kme reader domain. We anticipate that this target-class focused approach will serve as a new method for rapid discovery of inhibitors for multivalent chromatin reader domains.

Optimization of Ligands Using Focused DNA-Encoded Libraries To Develop a Selective, Cell-Permeable CBX8 Chromodomain Inhibitor

Polycomb repressive complex 1 (PRC1) is critical for mediating gene expression during development. Five chromobox (CBX) homolog proteins, CBX2, CBX4, CBX6, CBX7, and CBX8, are incorporated into PRC1 complexes, where they mediate targeting to trimethylated lysine 27 of histone H3 (H3K27me3) via the N-terminal chromodomain (ChD). Individual CBX paralogs have been implicated as drug targets in cancer; however, high similarities in sequence and structure among the CBX ChDs provide a major obstacle in developing selective CBX ChD inhibitors. Here we report the selection of small, focused, DNA-encoded libraries (DELs) against multiple homologous ChDs to identify modifications to a parental ligand that confer both selectivity and potency for the ChD of CBX8. This on-DNA, medicinal chemistry approach enabled the development of SW2_110A, a selective, cell-permeable inhibitor of the CBX8 ChD. SW2_110A binds CBX8 ChD with a K_d of 800 nM, with minimal 5-fold selectivity for CBX8 ChD over all other CBX paralogs in vitro. SW2_110A specifically inhibits the association of CBX8 with chromatin in cells and inhibits the proliferation of THP1 leukemia cells driven by the MLL-AF9 translocation. In THP1 cells, SW2_110A treatment results in a significant decrease in the expression of MLL-AF9 target genes, including HOXA9, validating the previously established role for CBX8 in MLL-AF9 transcriptional activation, and defining the ChD as necessary for this function. The success of SW2_110A provides great promise for the development of highly selective and cell-permeable probes for the full CBX family. In addition, the approach taken provides a proof-of-principle demonstration of how DELs can be used iteratively for optimization of both ligand potency and selectivity.

Beyond protein binding: recent advances in screening DNA-encoded libraries

DNA-encoded library (DEL) screening has emerged as an important method for early stage drug and probe molecule discovery. The vast majority of screens using DELs have been relatively simple binding assays. The library is incubated with a target molecule, which is almost always a protein, and the DNAs that remain associated with the target after thorough washing are amplified and deep sequenced to reveal the chemical structures of the ligands they encode. Recently however, a number of different screening formats have been introduced that demand more than simple binding. These include a format that demands hits exhibit high selectivity for target vs. off-targets, a protocol to screen for enzyme inhibitors and another to identify organocatalysts in a DEL. These and other novel assay formats are reviewed in this article. We also consider some of the most significant remaining challenges in DEL assay development.

Selection of DNA-Encoded Libraries to Protein Targets within and on Living Cells

We report the selection of DNA-encoded small molecule libraries against protein targets within the cytosol and on the surface of live cells. The approach relies on generation of a covalent linkage of the DNA to protein targets by affinity labeling. This cross-linking event enables subsequent copurification by a tag on the recombinant protein. To access targets within cells, a cyclic cell-penetrating peptide is appended to DNA-encoded libraries for delivery across the cell membrane. As this approach assesses binding of DELs to targets in live cells, it provides a strategy for selection of DELs against challenging targets that cannot be expressed and purified as active.

Engagement of DNA and H3K27me3 by the CBX8 chromodomain drives chromatin association

Polycomb repressive complex 1 (PRC1) is critical for mediating gene repression during development and adult stem cell maintenance. Five CBX proteins, CBX2,4,6,7,8, form mutually exclusive PRC1 complexes and are thought to play a role in the association of PRC1 with chromatin. Specifically, the N-terminal chromodomain (CD) in the CBX proteins is thought to mediate specific targeting to methylated histones. For CBX8, however, the chromodomain has demonstrated weak affinity and specificity for methylated histones in vitro, leaving doubt as to its role in CBX8 chromatin association. Here, we investigate the function of the CBX8 CD in vitro and in vivo. We find that the CD is in fact a major driver of CBX8 chromatin association and determine that this is driven by both histone and previously unrecognized DNA binding activity. We characterize the structural basis of histone and DNA binding and determine how they integrate on multiple levels. Notably, we find that the chromatin environment is critical in determining the ultimate function of the CD in CBX8 association.

Application of a Substrate-Mediated Selection with c-Src Tyrosine Kinase to a DNA-Encoded Chemical Library

As aberrant activity of protein kinases is observed in many disease states, these enzymes are common targets for therapeutics and detection of activity levels. The development of non-natural protein kinase substrates offers an approach to protein substrate competitive inhibitors, a class of kinase inhibitors with promise for improved specificity. Also, kinase activity detection approaches would benefit from substrates with improved activity and specificity. Here, we apply a substrate-mediated selection to a peptidomimetic DNA-encoded chemical library for enrichment of molecules that can be phosphorylated by the protein tyrosine kinase, c-Src. Several substrates were identified and characterized for activity. A lead compound (SrcDEL10) showed both the ability to serve as a substrate and to promote ATP hydrolysis by the kinase. In inhibition assays, compounds displayed IC_50's ranging from of 8-100 µM. NMR analysis of SrcDEL10 bound to the c-Src:ATP complex was conducted to characterize the binding mode. An ester derivative of the lead compound demonstrated cellular activity with inhibition of Src-dependent signaling in cell culture. Together, the results show the potential for substrate-mediated selections of DNA-encoded libraries to discover molecules with functions other than simple protein binding and offer a new discovery method for development of synthetic tyrosine kinase substrates.

Encoded Library Technologies as Integrated Lead Finding Platforms for Drug Discovery

The scope of targets investigated in pharmaceutical research is continuously moving into uncharted territory. Consequently, finding suitable chemical matter with current compound collections is proving increasingly difficult. Encoded library technologies enable the rapid exploration of large chemical space for the identification of ligands for such targets. These binders facilitate drug discovery projects both as tools for target validation, structural elucidation and assay development as well as starting points for medicinal chemistry. Novartis internalized two complementing encoded library platforms to accelerate the initiation of its drug discovery programs. For the identification of low-molecular weight ligands, we apply DNA-encoded libraries. In addition, encoded peptide libraries are employed to identify cyclic peptides. This review discusses how we apply these two platforms in our research and why we consider it beneficial to run both pipelines in-house.

Open-Air Alkylation Reactions in Photoredox-Catalyzed DNA-Encoded Library Synthesis

DNA-encoded library (DEL) technology is a powerful tool commonly used by the pharmaceutical industry for the identification of compounds with affinity to biomolecular targets. Success in this endeavor lies in sampling diverse chemical libraries. However, current DELs tend to be deficient in C(sp³) carbon counts. We report unique solutions to the challenge of increasing both the chemical diversity of these libraries and their C(sp³) carbon counts by merging Ni/photoredox dual catalytic C(sp²)-C(sp³) cross-coupling as well as photoredox-catalyzed radical/polar crossover alkylation protocols with DELs. The successful integration of multiple classes of radical sources enables the rapid incorporation of a diverse set of alkyl fragments.

DNA-encoded chemical libraries - achievements and remaining challenges

DNA-encoded chemical libraries (DECLs) are collections of compounds, individually coupled to DNA tags serving as amplifiable identification barcodes. Since individual compounds can be identified by the associated DNA tag, they can be stored as a mixture, allowing the synthesis and screening of combinatorial libraries of unprecedented size, facilitated by the implementation of split-and-pool synthetic procedures or other experimental methodologies. In this review, we briefly present relevant concepts and technologies, which are required for the implementation and interpretation of screening procedures with DNA-encoded chemical libraries. Moreover, we illustrate some success stories, detailing how novel ligands were discovered from encoded libraries. Finally, we critically review what can realistically be achieved with the technology at the present time, highlighting challenges and opportunities for the future.