Affinity Selections of DNA-Encoded Chemical Libraries on Carbonic Anhydrase IX-Expressing Tumor Cells Reveal a Dependence on Ligand Valence

Discovering Cell-Targeting Ligands and Cell-Surface Receptors by Selection of DNA-Encoded Chemical Libraries against Cancer Cells without Predefined Targets

Small molecules that can bind to specific cells have broad application in cancer diagnosis and treatment. Screening large chemical libraries against live cells is an effective strategy for discovering cell-targeting ligands. The DNA-encoded chemical library (DEL or DECL) technology has emerged as a robust tool in drug discovery and has been successfully utilized in identifying ligands for biological targets. However, nearly all DEL selections have predefined targets, while target-agnostic DEL selections interrogating the entire cell surface remain underexplored. Herein, we systematically optimized a cell-based DEL selection method against cancer cells without predefined targets. A 104.96-million-member DEL was selected against MDA-MB-231 and MCF-7 breast cancer cells, representing high and low metastatic properties, respectively, which led to the identification of cell-specific small molecules. We further demonstrated cell-targeting applications of these ligands in cancer photodynamic therapy and targeted drug delivery. Finally, leveraging the DNA tag of DEL compounds, we identified α-enolase (ENO1) as the cell surface receptor of one of the ligands targeting the more aggressive MDA-MB-231 cells. Overall, this work offers an efficient approach for discovering cell-targeting small molecule ligands by using DELs and demonstrates that DELs can be a useful tool to identify specific surface receptors on cancer cells.

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.

Agonist Discovery for Membrane Proteins on Live Cells by Using DNA-encoded Libraries

Identifying biologically active ligands for membrane proteins is an important task in chemical biology. We report an approach to directly identify small molecule agonists against membrane proteins by selecting DNA-encoded libraries (DELs) on live cells. This method connects extracellular ligand binding with intracellular biochemical transformation, thereby biasing the selection toward agonist identification. We have demonstrated the methodology with three membrane proteins: epidermal growth factor receptor (EGFR), thrombopoietin receptor (TPOR), and insulin receptor (INSR). A ∼30 million and a 1.033 billion-compound DEL were selected against these targets, and novel agonists with subnanomolar affinity and low micromolar cellular activities have been discovered. The INSR agonists activated the receptor by possibly binding to an allosteric site, exhibited clear synergistic effects with insulin, and activated the downstream signaling pathways. Notably, the agonists did not activate the insulin-like growth factor 1 receptor (IGF-1R), a highly homologous receptor whose activation may lead to tumor progression. Collectively, this work has developed an approach toward "functional" DEL selections on the cell surface and may provide a widely applicable method for agonist discovery for membrane proteins.

Highly pure DNA-encoded chemical libraries by dual-linker solid-phase synthesis

The first drugs discovered using DNA-encoded chemical library (DEL) screens have entered late-stage clinical development. However, DEL technology as a whole still suffers from poor chemical purity resulting in suboptimal performance. In this work, we report a technique to overcome this issue through self-purifying release of the DEL after magnetic bead-based synthesis. Both the first and last building blocks of each assembled library member were linked to the beads by tethers that could be cleaved by mutually orthogonal chemistry. Sequential cleavage of the first and last tether, with washing in between, ensured that the final library comprises only the fully complete compounds. The outstanding purity attained by this approach enables a direct correlation of chemical display and encoding, allows for an increased chemical reaction scope, and facilitates the use of more diversity elements while achieving greatly improved signal-to-noise ratios in selections.

Control of the antitumour activity and specificity of CAR T cells via organic adapters covalently tethering the CAR to tumour cells

On-target off-tumour toxicity limits the anticancer applicability of chimaeric antigen receptor (CAR) T cells. Here we show that the tumour-targeting specificity and activity of T cells with a CAR consisting of an antibody with a lysine residue that catalytically forms a reversible covalent bond with a 1,3-diketone hapten can be regulated by the concentration of a small-molecule adapter. This adapter selectively binds to the hapten and to a chosen tumour antigen via a small-molecule binder identified via a DNA-encoded library. The adapter therefore controls the formation of a covalent bond between the catalytic antibody and the hapten, as well as the tethering of the CAR T cells to the tumour cells, and hence the cytotoxicity and specificity of the cytotoxic T cells, as we show in vitro and in mice with prostate cancer xenografts. Such small-molecule switches of T-cell cytotoxicity and specificity via an antigen-independent 'universal' CAR may enhance the control and safety profile of CAR-based cellular immunotherapies.

Advancing small-molecule drug discovery by encoded dual-display technologies

DNA-encoded chemical library technology (DECL or DEL) has become an important pillar for small-molecule drug discovery. The technology rapidly identifies small-molecule hits for relevant target proteins at low cost and with a high success rate, including ligands for targeted protein degradation (TPD). More recently, the setup of DNA- or peptide nucleic acid (PNA)-encoded chemical libraries based on the simultaneous display of ligand pairs, termed dual-display, allows for more sophisticated applications which will be reviewed herein. Both stable and dynamic dual-display DEL technologies enable innovative affinity-based selection modalities, even on and in cells. Novel methods for a seamless conversion between single- and double-stranded library formats allow for even more versatility. We present the first candidates emerging from dual-display technologies and discuss the future potential of dual-display for drug discovery.

Recording Binding Information Directly into DNA-Encoded Libraries Using Terminal Deoxynucleotidyl Transferase

Terminal deoxynucleotidyl transferase (TdT) is an unusual DNA polymerase that adds untemplated dNTPs to 3'-ends of DNA. If a target protein is expressed as a TdT fusion and incubated with a DNA-encoded library (DEL) in the presence of dATP, the binders of the target induce proximity between TdT and the DNA, promoting the synthesis of a poly-adenine (polyA) tail. The polyA tail length is proportional to the binding affinity, effectively serving as a stable molecular record of binding events. The polyA tail is also a convenient handle to enrich binders with magnetic poly(dT)25 beads before sequencing. In a benchmarking system, we show that ligands spanning nanomolar to double-digit micromolar binding can be cleanly identified by TdT extension, whereas only the tightest binding ligands are identified by classical affinity selection. The method is simple to implement and can function on any DEL that bears a free 3'-end.

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.

Direct Selection of DNA-Encoded Libraries for Biased Agonists of GPCRs on Live Cells

G protein-coupled receptors (GPCRs) are the largest superfamily of human membrane target proteins for approved drugs. GPCR ligands can have a complex array of pharmacological activities. Among these activities, biased agonists have potential to serve as both chemical probes to understand specific aspects of receptor signaling and therapeutic leads with more specific, desired activity. Challenges exist, however, in the development of new biased activators due, in part, to the low throughput of traditional screening approaches. DNA-encoded chemical libraries (DELs) dramatically improve the throughput of drug discovery by allowing a collective selection, rather than discrete screening, of large compound libraries. The use of DELs has been largely limited to affinity-based selections against purified protein targets, which identify binders only. Herein, we report a split protein complementation approach that allows direct identification of DNA-linked molecules that induce the dimerization of two proteins. We used this selection with a DEL against opioid receptor GPCRs on living cells for the identification of small molecules that possess the specific function of activation of either β-arrestin or G protein signaling pathways. This approach was applied to δ-, μ-, and κ-opioid receptors and enabled the discovery of compound [66,66], a selective, G-protein-biased agonist of the κ-opioid receptor (EC₅₀ = 100 nM, E _max = 82%, G_i bias factor = 6.6). This approach should be generally applicable for the direct selection of chemical inducers of dimerization from DELs and expand the utility of DELs to enrich molecules with a specific and desired biochemical function.

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.

Converting Double-Stranded DNA-Encoded Libraries (DELs) to Single-Stranded Libraries for More Versatile Selections

DNA-encoded library (DEL) is an efficient high-throughput screening technology platform in drug discovery and is also gaining momentum in academic research. Today, the majority of DELs are assembled and encoded with double-stranded DNA tags (dsDELs) and has been selected against numerous biological targets; however, dsDELs are not amendable to some of the recently developed selection methods, such as the cross-linking-based selection against immobilized targets and live-cell-based selections, which require DELs encoded with single-stranded DNAs (ssDELs). Herein, we present a simple method to convert dsDELs to ssDELs using exonuclease digestion without library redesign and resynthesis. We show that dsDELs could be efficiently converted to ssDELs and used for affinity-based selections either with purified proteins or on live cells.

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.

Target Protein Design and Preselection Analysis

DNA-encoded library (DEL) technology utilizes affinity-based selection methods to screen chemical libraries. DEL technology possesses some unique features compared to other small molecule screening technologies, such as the use of DNA identification tags and use of target protein immobilization in the standard library screening process. Therefore, it is of great importance to ensure the target protein is properly designed for DEL selections, that the protein is of high quality, and that ligand binding sites are accessible under DEL selection conditions. Here we describe general considerations for target protein design and expression and experiments that are conducted before initiating selections to assess protein quality and validate methods that will be used for the DEL selection.

OUP accepted manuscript

DNA-encoded library (DEL) technology is a powerful tool for small molecule identification in drug discovery, yet the reported DEL selection strategies were applied primarily on protein targets in either purified form or in cellular context. To expand the application of this technology, we employed DEL selection on an RNA target HIV-1 TAR (trans-acting responsive region), but found that the majority of signals were resulted from false positive DNA–RNA binding. We thus developed an optimized selection strategy utilizing RNA patches and competitive elution to minimize unwanted DNA binding, followed by k-mer analysis and motif search to differentiate false positive signal. This optimized strategy resulted in a very clean background in a DEL selection against Escherichia coli FMN Riboswitch, and the enriched compounds were determined with double digit nanomolar binding affinity, as well as similar potency in functional FMN competition assay. These results demonstrated the feasibility of small molecule identification against RNA targets using DEL selection. The developed experimental and computational strategy provided a promising opportunity for RNA ligand screening and expanded the application of DEL selection to a much wider context in drug discovery.

Carbonic anhydrase inhibitors: an update on experimental agents for the treatment and imaging of hypoxic tumors

INTRODUCTION

Hypoxic tumors, unlike normal tissues, overexpress proteins involved in oxygen sensing, metabolism, pH regulation, angiogenesis, immunological response, and other survival mechanisms, which are under investigation as antitumor drug targets.

AREAS COVERED

Carbonic anhydrase (CA) isoforms CA IX and XII are among these validated antitumor/antimetastatic drug targets, with several of their inhibitors undergoing preclinical or clinical-stage investigations. Alone or in combination with other chemotherapeutic agents or radiotherapy, CA IX/XII inhibitors, such as SLC-0111, SLC-149, S4, 6A10, etc., were shown to inhibit the growth of the primary tumor, metastases, and invasiveness of many tumor types, being also amenable for the development of imaging agents.

EXPERT OPINION

SLC-0111 is the most investigated agent, being in Phase Ib/II clinical trials. In addition to its interference with extracellular acidifications, it has been shown to promote ferroptosis in cancer cells, another antitumor mechanism of this compound and the entire class. A large number sulfonamide and non-sulfonamide inhibitors have been developed using SLC-0111 as lead in the last three years, together with hybrid agents incorporating CA inhibitors and other anticancer chemotypes, including cytotoxins, telomerase, thioredoxin or P-glycoprotein inhibitors, adenosine A₂A receptor antagonists, pyrophosphatase/phosphodiesterase-3 inhibitors or antimetabolites. All of them showed significant antitumor activity.

High-power screening (HPS) empowered by DNA-encoded libraries

The world is totally dependent on medications. As science progresses, new, better, and cheaper drugs are needed more than ever. The pharmaceutical industry has been predominantly dependent on high-throughput screening (HTS) for the past three decades. Considering that the discovery rate has been relatively constant, can one hope for a much-needed sudden trend uptick? DNA-encoded libraries (DELs) and similar technologies, that have several orders of magnitude more screening power than HTS, and that we propose to group together under the umbrella term of high-power screening (HPS), are very well positioned to do exactly that. HPS also offers novel screening options such as parallel screening, ex vivo and in vivo screening, as well as a new path to druggable alternatives such as proteolysis targeting chimeras (PROTACs). Altogether, HPS unlocks novel powerful drug discovery avenues.

Evolution of the Selection Methods of DNA-Encoded Chemical Libraries

In the past two decades, a DNA-encoded chemical library (DEL or DECL) has emerged and has become a major technology platform for ligand discovery in drug discovery as well as in chemical biology research. Although based on a simple concept, i.e., encoding each compound with a unique DNA tag in a combinatorial chemical library, DEL has been proven to be a powerful tool for interrogating biological targets by accessing vast chemical space at a fraction of the cost of traditional high-throughput screening (HTS). Moreover, the recent technological advances and rapid developments of DEL-compatible reactions have greatly enhanced the chemical diversity of DELs. Today, DELs have been adopted by nearly all major pharmaceutical companies and are also gaining momentum in academia. However, this field is heavily biased toward library encoding and synthesis, and an underexplored aspect of DEL research is the selection methods. Generally, DEL selection is considered to be a massive binding assay conducted over an immobilized protein to identify the physical binders using the typical bind-wash-elute procedure. In recent years, we and other research groups have developed new approaches that can perform DEL selections in the solution phase, which has enabled the selection against complex biological targets beyond purified proteins. On the one hand, these methods have significantly widened the target scope of DELs; on the other hand, they have enabled the functional and potentially phenotypic assays of DELs beyond simple binding. An overview of these methods is provided in this Account.Our laboratory has been using DNA-programmed affinity labeling (DPAL) as the main strategy to develop new DEL selection methods. DPAL is based on DNA-templated synthesis; by using a known ligand to guide the target binding, DPAL is able to specifically establish a stable linkage between the target protein and the ligand. The DNA tag of the target-ligand conjugates serves as a programmable handle for protein characterization or hit compound decoding in the case of DEL selections. DPAL also takes advantage of the fast reaction kinetics of photo-cross-linking to achieve high labeling specificity and fidelity, especially in the selection of DNA-encoded dynamic libraries (DEDLs). DPAL has enabled DEL selections not only in buffer and cell lysates but also with complex biological systems, such as large protein complexes and live cells. Moreover, this strategy has also been employed in other biological applications, such as site-specific protein labeling, protein detection, protein profiling, and target identification. In the Account, we describe these methods, highlight their underlying principles, and conclude with perspectives of the development of the DEL technology.

Identification of isoform/domain-selective fragments from the selection of DNA-encoded dynamic library

DNA-encoded chemical library (DEL) has emerged to be a powerful ligand screening technology in drug discovery. Recently, we reported a DNA-encoded dynamic library (DEDL) approach that combines the principle of traditional dynamic combinatorial library (DCL) with DEL. DEDL has shown excellent potential in fragment-based ligand discovery with a variety of protein targets. Here, we further tested the utility of DEDL in identifying low molecular weight fragments that are selective for different isoforms or domains of the same protein family. A 10,000-member DEDL was selected against sirtuin-1, 2, and 5 (SIRT1, 2, 5) and the BD1 and BD2 domains of bromodomain 4 (BRD4), respectively. Albeit with modest potency, a series of isoform/domain-selective fragments were identified and the corresponding inhibitors were derived by fragment linking.