Automated screening for small organic ligands using DNA-encoded chemical libraries

Copper-Mediated Three-Component Reaction for the Synthesis of N-Sulfonylamidine on DNA

DNA-encoded library (DEL) technology is a transformative tool for identifying bioactive compounds in pharmaceutical research. This study presents an optimized copper-mediated reaction to synthesize N-sulfonylamidine derivatives from DNA-conjugated alkynes and sulfonyl azides under mild conditions. Amines serve as nucleophiles, enabling selective functionalization under mild conditions while preserving DNA integrity. Through systematic refinement of reaction conditions and substrate evaluation, the approach demonstrated a high tolerance to diverse functional groups, significantly expanding DEL-accessible chemical space. The developed DNA-compatible method underscores the role of DELs in enhancing drug discovery by facilitating the introduction of novel pharmacophores into compound libraries.

Encoded Display of Chemical Libraries on Nanoparticles as a Versatile Selection Tool To Discover Protein Ligands

DNA-encoded library (DEL) technology is a powerful tool for discovering potent ligands for biological targets but constrained by limitations, including the insolubility of DNA in organic solvents and its instability under various reaction conditions, which restrict the reactivity scope and structural diversity achievable in library synthesis. Here, we present a new strategy called nanoDEL, where library molecules and DNA tags are displayed on the surface of nanoparticles. Since nanoparticles disperse well in both organic solvents and aqueous solutions, DEL synthesis can be accomplished using well-established organic solvent-based conditions, eliminating the need for aqueous conditions. Moreover, nanoDEL enables air-sensitive reactions that are inaccessible with conventional DEL methods relying on aqueous conditions. Notably, in nanoDEL, multiple copies of a DNA tag are attached to an individual nanoparticle to encode a single compound, significantly enhancing tolerance to DNA-damaging conditions. Even when most DNA tags are damaged, sequence analysis remains feasible via amplification of intact tags. Consequently, nanoDEL facilitates the convenient use of existing organic reactions without the necessity to develop DNA-compatible reactions. The potential of nanoDEL was validated by affinity selection against streptavidin as a model system and successfully applied to the discovery of potent small-molecule inhibitors for a kinase and stapled peptide inhibitors targeting a protein-protein interaction, exhibiting dissociation constants in the nanomolar range. Furthermore, we demonstrated that a large combinatorial library can be efficiently synthesized on nanoparticles using a synthetic scheme including moisture-sensitive reaction steps, which are not feasible with conventional DELs.

Flexibility-tuning of dual-display DNA-encoded chemical libraries facilitates cyclic peptide ligand discovery

Cyclic peptides constitute an important drug modality since they offer significant advantages over small molecules and macromolecules. However, access to diverse chemical sets of cyclic peptides is difficult on a large library scale. DNA-encoded Chemical Libraries (DELs) provide a suitable tool to obtain large chemical diversity, but cyclic DELs made by standard DEL implementation cannot efficiently explore their conformational diversity. On the other hand, dual-display Encoded Self-Assembling Chemical (ESAC) Libraries can be used for modulating macrocycle flexibility since the two displayed peptides can be connected in an incremental fashion. In this work, we construct a 56 million dual-display ESAC library using a two-step cyclization strategy. We show that varying the level of conformational restraint is essential for the discovery of specific ligands for the three protein targets thrombin, human alkaline phosphatase and streptavidin.

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.

Exploring Chemical Spaces in the Billion Range: Is Docking a Computational Alternative to DNA-Encoded Libraries?

The concept of DNA-encoded libraries (DELs) enables the experimental screening of billions of compounds simultaneously, offering an unprecedented boost in the coverage of chemical space. In parallel, however, dramatically increased access to supercomputers and a number of ultrahigh throughput virtual screening (uHTVS) tools have made screening of billion-membered virtual libraries available. Here, we investigate whether current, brute-force, or AI-enabled uHTVS approaches might constitute a computational alternative to DEL screening. While it is tempting to look at uHTVS as a computational analogue of DEL screening, we found specific advantages and limitations of both methodologies that suggest them being complementary rather than competitive.

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.

Optimizing the affinity selection mass spectrometry workflow for efficient identification and ranking of potent USP1 inhibitors

An optimized Affinity Selection-Mass Spectrometry (AS-MS) workflow has been developed for the efficient identification of potent USP1 inhibitors. USP1 was immobilized on agarose beads, ensuring low small molecule retention, efficient protein capture, and protein stability. The binding affinity of 49 compounds to USP1 was evaluated using the optimized AS-MS method, calculating binding index (BI) values for each compound. Biochemical inhibition assays validated the AS-MS results, revealing a potential correlation between higher BI values and lower IC50 values. This optimized workflow enables rapid identification of high-quality USP1 inhibitor hits, facilitating structure-activity relationship studies and accelerating the discovery of potential cancer therapeutics.

Permutational Encoding Strategy Accelerates HIT Validation from Single-Stranded DNA-Encoded Libraries

DNA-Encoded Libraries (DELs) allow the parallel screening of millions of compounds for various applications, including de novo discovery or affinity maturation campaigns. However, library construction and HIT resynthesis can be cumbersome, especially when library members present an unknown stereochemistry. We introduce a permutational encoding strategy suitable for the construction of highly pure single-stranded single-pharmacophore DELs, designed to distinguish isomers at the sequencing level (e.g., stereoisomers, regio-isomers, and peptide sequences). This approach was validated by synthesizing a mock 921,600-member 4-amino-proline single-stranded DEL ("DEL1"). While screening DEL1 against different targets, high-throughput sequencing results showed selective enrichment of the most potent stereoisomers, with enrichment factors that outperform conventional encoding strategies. The versatility of our methodology was additionally validated by encoding 24 scaffolds derived from different permutations of the amino acid sequence of a previously described cyclic peptide targeting Fibroblast Activation Protein (FAP-2286). The resulting library ("DEL2") was interrogated against human FAP, showing selective enrichment of five cyclic peptides. We observed a direct correlation between enrichment factors and on-DNA binding affinities. The presented encoding methodology accelerates drug discovery by facilitating library synthesis and streamlining HIT resynthesis while enhancing enrichment factors at the DEL sequencing level. This facilitates the identification of HIT candidates prior to medicinal chemistry and affinity maturation campaigns.

In silico fragment-based discovery of CIB1-directed anti-tumor agents by FRASE-bot

Chemical probes are an indispensable tool for translating biological discoveries into new therapies, though are increasingly difficult to identify since novel therapeutic targets are often hard-to-drug proteins. We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets. FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE). The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments. A neural network model is used to retain fragments with the highest likelihood of being native binders. The seeded fragments then inform ultra-large-scale virtual screening of commercially available compounds. We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1), a promising drug target implicated in triple negative breast cancer. FRASE-based virtual screening identifies a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay) showing specific cell-killing activity in CIB1-dependent cancer cells, but not in CIB1-depletion-insensitive cells.

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.

DNA-encoded chemical libraries enable the discovery of potent PSMA-ligands with substantially reduced affinity towards the GCPIII anti-target

Prostate-specific membrane antigen (PSMA) is a tumor-associated protein that has been successfully targeted with small organic ligands and monoclonal antibodies. Pluvicto™ is a PSMA-targeted radioligand therapeutic (RLT) recently approved by the FDA for the treatment of metastatic castration-resistant prostate cancer (2022 FDA marketing authorization). Although a large Phase III clinical trial (VISION trial) demonstrated clinical benefits in patients treated with Pluvicto™, the therapeutic window of the drug is narrowed by its undesired accumulation in healthy organs. Glutamate carboxypeptidase III (GCPIII), an enzyme sharing 70% identity with PSMA, may be responsible for the off-target accumulation of PSMA-RLTs in salivary glands and kidneys. In this work, we designed and synthesized affinity and selectivity maturation DNA-encoded chemical libraries (ASM-DELs) comprising 18'284'658 compounds that were screened in parallel against PSMA and GCPIII with the aim to identify potent and selective PSMA ligands for tumor-targeting applications. Compound A70-B104 was isolated as the most potent and selective ligand (KD of 900 pM for PSMA, KD of 40 nM for GCPIII). 177Lu-A70-B104-DOTA, a radiolabeled derivative of compound A70-B104, presented selective accumulation in PSMA-positive cancer lesions (i.e., 7.4% ID g-1, 2 hour time point) after systemic administration in tumor-bearing mice. The results of autoradiography experiments showed that 177Lu-A70-B104-DOTA selectively binds to PSMA-positive cancer tissues, while negligible binding on human salivary glands was observed.

High-Throughput DNA-Encoded Libraries Affinity Selection Platform for Binder Identification with Solid Support Protein Immobilization

DNA-encoded libraries (DELs) have demonstrated to be one of the most powerful technologies within the ligand identification toolbox, widely used either in academia or biotech and pharma companies. DEL methodology utilizes affinity selection (AS) as the approach to interrogate the protein of interest for the identification of binders. Here we present a high-throughput, fully automated AS platform developed to fulfill industrial standards and compatible with different assay formats to improve the reproducibility of the AS process for DEL binders identification. This platform is flexible enough to virtually set aside all kinds of DELs and AS methods and conditions using immobilized proteins. It bears the two main immobilization methods to support of the proteins of interest: magnetic beads or resin tip columns. A combination of a broad variety of protocol options with a wide range of different experimental conditions can be set up with a throughput of 96 samples at the same time. In addition, small modifications of the protocols provide the platform with the versatility to run not only the routine DEL screens, but also test covalent libraries, the successful immobilization of the proteins of interest, and many other experiments that may be required. This versatile AS platform for DEL can be a powerful instrument for direct application of the technology in academic and industry settings.

Asymmetry of Dual-Display DNA-Encoded Chemical Libraries

While dual-display DNA-encoded chemical libraries (DELs) are increasingly employed for ligand discovery, some of their fundamental properties have not yet been studied in-depth. Aided with fluorescence polarization experiments, we demonstrate that dual-display DELs are intrinsically asymmetrical entities, and we deduce practical guidelines to perform better-informed on-DNA hit validation from these libraries.

Evolution of chemistry and selection technology for DNA-encoded library

DNA-encoded chemical library (DEL) links the power of amplifiable genetics and the non-self-replicating chemical phenotypes, generating a diverse chemical world. In analogy with the biological world, the DEL world can evolve by using a chemical central dogma, wherein DNA replicates using the PCR reactions to amplify the genetic codes, DNA sequencing transcripts the genetic information, and DNA-compatible synthesis translates into chemical phenotypes. Importantly, DNA-compatible synthesis is the key to expanding the DEL chemical space. Besides, the evolution-driven selection system pushes the chemicals to evolve under the selective pressure, i.e., desired selection strategies. In this perspective, we summarized recent advances in expanding DEL synthetic toolbox and panning strategies, which will shed light on the drug discovery harnessing in vitro evolution of chemicals via DEL.

Impact of library input on the hit discovery rate in DNA-encoded chemical library selections

DNA-encoded chemical libraries (DELs) are powerful drug discovery tools, enabling the parallel screening of millions of DNA-barcoded compounds. We investigated how the DEL input affects the hit discovery rate in DEL screenings. Evaluation of selection fingerprints revealed that the use of approximately 105 copies of each library member is required for the confident identification of nanomolar hits, using generally applicable methodologies.

Covalent Capture and Selection of DNA-Encoded Chemical Libraries via Photo-Activated Lysine-Selective Crosslinkers

Covalent crosslinking probes have arisen as efficient toolkits to capture and elucidate biomolecular interaction networks. Exploiting the potential of crosslinking in DNA-encoded chemical library (DEL) selection methods significantly boosted bioactive ligand discovery in complex physiological contexts. Herein, we incorporated o-nitrobenzyl alcohol (o-NBA) as a photo-activated lysine-selective crosslinker into divergent DEL formats and achieved covalent capture of ligand-target interactions featuring improved crosslinking efficiency and site-specificity. In addition, covalent DEL selection was realized with the modularly designed o-NBA-functionalized mock libraries.

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.

A DNA-encoded chemical library based on chiral 4-amino-proline enables stereospecific isozyme-selective protein recognition

DNA-encoded chemical libraries (DELs) consist of large chemical compound collections individually linked to DNA barcodes, facilitating pooled construction and screening. However, screening campaigns often fail if the molecular arrangement of the building blocks is not conducive to an efficient interaction with a protein target. Here we postulated that the use of rigid, compact and stereo-defined central scaffolds for DEL synthesis may facilitate the discovery of very specific ligands capable of discriminating between closely related protein targets. We synthesized a DEL comprising 3,735,936 members, featuring the four stereoisomers of 4-aminopyrrolidine-2-carboxylic acid as central scaffolds. The library was screened in comparative selections against pharmaceutically relevant targets and their closely related protein isoforms. Hit validation results revealed a strong impact of stereochemistry, with large affinity differences between stereoisomers. We identified potent isozyme-selective ligands against multiple protein targets. Some of these hits, specific to tumour-associated antigens, demonstrated tumour-selective targeting in vitro and in vivo. Collectively, constructing DELs with stereo-defined elements contributed to high library productivity and ligand selectivity.

Machine Learning-driven Fragment-based Discovery of CIB1-directed Anti-Tumor Agents by FRASE-bot

Chemical probes are an indispensable tool for translating biological discoveries into new therapies, though are increasingly difficult to identify. Novel therapeutic targets are often hard-to-drug proteins, such as messengers or transcription factors. Computational strategies arise as a promising solution to expedite drug discovery for unconventional therapeutic targets. FRASE-bot exploits big data and machine learning (ML) to distill 3D information relevant to the target protein from thousands of protein-ligand complexes to seed it with ligand fragments. The seeded fragments can then inform either (i) de novo design of 3D ligand structures or (ii) ultra-large-scale virtual screening of commercially available compounds. Here, FRASE-bot was applied to identify ligands for Calcium and Integrin Binding protein 1 (CIB1), a promising but ligand-orphan drug target implicated in triple negative breast cancer. The signaling function of CIB1 relies on protein-protein interactions and its structure does not feature any natural ligand-binding pocket. FRASE-based virtual screening identified the first small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay) showing specific cell-killing activity in CIB1-dependent cancer cells, but not in CIB1-depleted cells.

Evaluation of the Topology Space of DNA-Encoded Libraries

DNA-encoded libraries (DELs) are widely used in the discovery of drug candidates, and understanding their design principles is critical for accessing better libraries. Most DELs are combinatorial in nature and are synthesized by assembling sets of building blocks in specific topologies. In this study, different aspects of library topology were explored and their effect on DEL properties and chemical diversity was analyzed. We introduce a descriptor for DEL topological assignment (DELTA) and use it to examine the landscape of possible DEL topologies and their coverage in the literature. A generative topographic mapping analysis revealed that the impact of library topology on chemical space coverage is secondary to building block selection. Furthermore, it became apparent that the descriptor used to analyze chemical space dictates how structures cluster, with the effects of topology being apparent when using three-dimensional descriptors but not with common two-dimensional descriptors. This outcome points to potential challenges of attempts to predict DEL productivity based on chemical space analyses alone. While topology is rather inconsequential for defining the chemical space of encoded compounds, it greatly affects possible interactions with target proteins as illustrated in docking studies using NAD/NADP binding proteins as model receptors.

Deep Learning Approach for the Discovery of Tumor-Targeting Small Organic Ligands from DNA-Encoded Chemical Libraries

DNA-Encoded Chemical Libraries (DELs) have emerged as efficient and cost-effective ligand discovery tools, which enable the generation of protein-ligand interaction data of unprecedented size. In this article, we present an approach that combines DEL screening and instance-level deep learning modeling to identify tumor-targeting ligands against carbonic anhydrase IX (CAIX), a clinically validated marker of hypoxia and clear cell renal cell carcinoma. We present a new ligand identification and hit-to-lead strategy driven by machine learning models trained on DELs, which expand the scope of DEL-derived chemical motifs. CAIX-screening datasets obtained from three different DELs were used to train machine learning models for generating novel hits, dissimilar to elements present in the original DELs. Out of the 152 novel potential hits that were identified with our approach and screened in an in vitro enzymatic inhibition assay, 70% displayed submicromolar activities (IC₅₀ < 1 μM). To generate lead compounds that are functionalized with anticancer payloads, analogues of top hits were prioritized for synthesis based on the predicted CAIX affinity and synthetic feasibility. Three lead candidates showed accumulation on the surface of CAIX-expressing tumor cells in cellular binding assays. The best compound displayed an in vitro K_D of 5.7 nM and selectively targeted tumors in mice bearing human renal cell carcinoma lesions. Our results demonstrate the synergy between DEL and machine learning for the identification of novel hits and for the successful translation of lead candidates for in vivo targeting 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.

Dearomative intermolecular [2 + 2] photocycloaddition for construction of C(sp3)-rich heterospirocycles on-DNA

DNA-encoded library (DEL) screens have significantly impacted new lead compound identification efforts within drug discovery. An advantage of DELs compared to traditional screening methods is that an exponentially broader chemical space can be effectively screened using only nmol quantities of billions of DNA-tagged, drug-like molecules. The synthesis of DELs containing diverse, sp³-rich spirocycles, an important class of molecules in drug discovery, has not been previously reported. Herein, we demonstrate the synthesis of complex and novel spirocyclic cores via an on-DNA, visible light-mediated intermolecular [2 + 2] cycloaddition of olefins with heterocycles, including indoles, azaindoles, benzofurans, and coumarins. The DNA-tagged exo-methylenecyclobutane substrates were prepared from easily accessible alkyl iodides and styrene derivatives. Broad reactivity with many other DNA-conjugated alkene substrates was observed, including unactivated and activated alkenes, and the process is tolerant of various heterocycles. The cycloaddition was successfully scaled from 10 to 100 nmol without diminished yield, indicative of this reaction's suitability for DNA-encoded library production. Evaluation of DNA compatibility with the developed reaction in a mock-library format showed that the DNA barcode was maintained with high fidelity, with <1% mutated sequences and >99% amplifiable DNA from quantitative polymerase chain reaction (PCR) and next generation sequencing (NGS).

Discovery of RNA-targeted small molecules through the merging of experimental and computational technologies

INTRODUCTION

The field of RNA-targeted small molecules is rapidly evolving, owing to the advances in experimental and computational technologies. With the identification of several bioactive small molecules that target RNA, including the FDA-approved risdiplam, the biopharmaceutical industry is gaining confidence in the field. This review, based on the literature obtained from PubMed, aims to disseminate information about the various technologies developed for targeting RNA with small molecules and propose areas for improvement to develop drugs more efficiently, particularly those linked to diseases with unmet medical needs.

AREAS COVERED

The technologies for the identification of RNA targets, screening of chemical libraries against RNA, assessing the bioactivity and target engagement of the hit compounds, structure determination, and hit-to-lead optimization are reviewed. Along with the description of the technologies, their strengths, limitations, and examples of how they can impact drug discovery are provided.

EXPERT OPINION

Many existing technologies employed for protein targets have been repurposed for use in the discovery of RNA-targeted small molecules. In addition, technologies tailored for RNA targets have been developed. Nevertheless, more improvements are necessary, such as artificial intelligence to dissect important RNA structures and RNA-small-molecule interactions and more powerful chemical probing and structure prediction techniques.

Combining pharmacophore models derived from DNA-encoded chemical libraries with structure-based exploration to predict Tankyrase 1 inhibitors

DNA-encoded chemical libraries (DECLs) interrogate the interactions of a target of interest with vast numbers of molecules. DECLs hence provide abundant information about the chemical ligand space for therapeutic targets, and there is considerable interest in methods for exploiting DECL screening data to predict novel ligands. Here we introduce one such approach and demonstrate its feasibility using the cancer-related poly-(ADP-ribose)transferase tankyrase 1 (TNKS1) as a model target. First, DECL affinity selections resulted in structurally diverse TNKS1 inhibitors with high potency including compound 2 with an IC50 value of 0.8 nM. Additionally, TNKS1 hits from four DECLs were translated into pharmacophore models, which were exploited in combination with docking-based screening to identify TNKS1 ligand candidates in databases of commercially available compounds. This computational strategy afforded TNKS1 inhibitors that are outside the chemical space covered by the DECLs and yielded the drug-like lead compound 12 with an IC50 value of 22 nM. The study further provided insights in the reliability of screening data and the effect of library design on hit compounds. In particular, the study revealed that while in general DECL screening data are in good agreement with off-DNA ligand binding, unpredictable interactions of the DNA-attachment linker with the target protein contribute to the noise in the affinity selection data.

Nonlinear manipulation and analysis of large DNA datasets

Information processing functions are essential for organisms to perceive and react to their complex environment, and for humans to analyze and rationalize them. While our brain is extraordinary at processing complex information, winner-take-all, as a type of biased competition is one of the simplest models of lateral inhibition and competition among biological neurons. It has been implemented as DNA-based neural networks, for example, to mimic pattern recognition. However, the utility of DNA-based computation in information processing for real biotechnological applications remains to be demonstrated. In this paper, a biased competition method for nonlinear manipulation and analysis of mixtures of DNA sequences was developed. Unlike conventional biological experiments, selected species were not directly subjected to analysis. Instead, parallel computation among a myriad of different DNA sequences was carried out to reduce the information entropy. The method could be used for various oligonucleotide-encoded libraries, as we have demonstrated its application in decoding and data analysis for selection experiments with DNA-encoded chemical libraries against protein targets.

Isolation of a Natural Killer Group 2D Small-Molecule Ligand from DNA-Encoded Chemical Libraries

Natural Killer Group 2D (NKG2D) is a homo-dimeric transmembrane protein which is typically expressed on the surface of natural killer (NK) cells, natural killer T (NKT) cells, gamma delta T (γδT) cells, activated CD8 positive T-cells and activated macrophages. Bispecific molecules, capable of bridging NKG2D with a target protein expressed on the surface of tumor cells, may be used to redirect the cytotoxic activity of NK-cells towards antigen-positive malignanT-cells. In this work, we report the discovery of a novel NKG2D small molecule binder [K D = (410±60) nM], isolated from a DNA-Encoded Chemical Library (DEL). The discovery of small organic NKG2D ligands may facilitate the generation of fully synthetic bispecific adaptors, which may serve as an alternative to bispecific antibody products and which may benefit from better tumor targeting properties.

Discovery of TIGIT inhibitors based on DEL and machine learning

Drug discovery has entered a new period of vigorous development with advanced technologies such as DNA-encoded library (DEL) and artificial intelligence (AI). The previous DEL-AI combination has been successfully applied in the drug discovery of classical kinase and receptor targets mainly based on the known scaffold. So far, there is no report of the DEL-AI combination on inhibitors targeting protein-protein interaction, including those undruggable targets with few or unknown active scaffolds. Here, we applied DEL technology on the T cell immunoglobulin and ITIM domain (TIGIT) target, resulting in the unique hit compound 1 (IC50 = 20.7 μM). Based on the screening data from DEL and hit derivatives a1-a34, a machine learning (ML) modeling process was established to address the challenge of poor sample distribution uniformity, which is also frequently encountered in DEL screening on new targets. In the end, the established ML model achieved a satisfactory hit rate of about 75% for derivatives in a high-scored area.

Maximizing the integration of virtual and experimental screening in hit discovery

INTRODUCTION

Experimental and virtual screening contributes to the discovery of more than 50% of clinical candidates. Considering the similar concept and goals, early-phase drug discovery would benefit from the effective integration of these approaches.

AREAS COVERED

After reviewing the recent trends in both experimental and virtual screening, the authors discuss different integration strategies from parallel, focused, sequential, and iterative screening. Strategic considerations are demonstrated in a number of real-life case studies.

EXPERT OPINION

Experimental and virtual screening are complementary approaches that should be integrated in lead discovery settings. Virtual screening can access extremely large synthetically feasible chemical space that can be effectively searched on GPU clusters or cloud architectures. Experimental screening provides reliable datasets by quantitative HTS applications, and DNA-encoded libraries (DEL) have enlarged the chemical space covered by these technologies. These developments, together with the use of artificial intelligence methods, represent new options for their efficient integration. The case studies discussed here demonstrate the benefits of complementary strategies, such as focused and iterative screening.

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.

In-solution direct oxidative coupling for the integration of sulfur/selenium into DNA-encoded chemical libraries

Sulfur/selenium-containing electron-rich arenes (ERAs) exist in a wide range of both approved and investigational drugs with diverse pharmacological activities. These unique chemical structures and bioactive properties, if combined with the emerging DNA-encoded chemical library (DEL) technique, would facilitate drug and chemical probe discovery. However, it remains challenging, as there is no general DNA-compatible synthetic methodology available for the formation of C-S and C-Se bonds in aqueous solution. Herein, an in-solution direct oxidative coupling procedure that could efficiently integrate sulfur/selenium into the ERA under mild conditions is presented. This method features simple DNA-conjugated electron-rich arenes with a broad substrate scope and a transition-metal free process. Furthermore, this synthetic methodology, examined by a scale-up reaction test and late-stage precise modification in a mock peptide-like DEL synthesis, will enable its utility for the synthesis of sulfur/selenium-containing DNA-encoded libraries and the discovery of bioactive agents.

Universal encoding of next generation DNA-encoded chemical libraries

DNA-encoded chemical libraries (DELs) are useful tools for the discovery of small molecule ligands to protein targets of pharmaceutical interest. Compared with single-pharmacophore DELs, dual-pharmacophore DELs simultaneously display two chemical moieties on both DNA strands, and allow for the construction of highly diverse and pure libraries, with a potential for targeting larger protein surfaces. Although methods for the encoding of simple, fragment-like dual-display libraries have been established, more complex libraries require a different encoding strategy. Here, we present a robust and convenient "large encoding design" (LED), which facilitates the PCR-amplification of multiple codes distributed among two partially complementary DNA strands. We experimentally implemented multiple coding regions and we compared the new DNA encoding scheme with previously reported dual-display DEL modalities in terms of amplifiability and performance in test selections against two target proteins. With the LED methodology in place, we foresee the construction and screening of DELs of unprecedented sizes and designs.

Macrocyclic DNA-encoded chemical libraries: a historical perspective

While macrocyclic peptides are extensively researched for therapeutically relevant protein targets, DNA-encoded chemical libraries (DELs) are developed at a quick pace to discover novel small molecule binders. The combination of both fields has been explored since 2004 and the number of macrocyclic peptide DELs is steadily increasing. Macrocycles with high affinity and potency were identified for diverse classes of proteins, revealing DEL's huge potential. By giving a historical perspective, we would like to review the methods which permitted the rise of macrocyclic peptide DELs, describe the different DELs which were created and discuss the achievements and challenges of this emerging field.

DEL Selections Against a Soluble Protein Target

Affinity-based DNA-encoded library (DEL) selection is considered a powerful tool for small molecule drug discovery. Such selections are a multi-round process that involves incubation of a target protein with the DEL, capture of the protein and associated DEL compounds on a solid support, separation of bound molecules from the bulk DEL that is unbound, and recovery of bound DEL molecules. Each step is of great importance in order to achieve successful selections. Here we describe the selection process against a soluble target protein in both the immobilized and in-solution modes.

Translation of DNA Sequence to Chemical Structure in DNA-Encoded Libraries

Analysis of DEL selection results requires the generation of large DNA sequence data sets and the conversion of DNA sequence to chemical structure. SAM and BAM formats are the generic formats for storing sequence alignment results. However, such formats are not directly applicable for analysis of DEL selection results due to the lack of reference sequences. In this protocol, reference sequences are constructed from DEL structure files using the central dogma of molecular biology analogy. Enabling the use of SAM and BAM formats drastically facilitates data access while also reducing data storage requirements and permits the efficient translation of DNA sequence to chemical structure of DEL compounds.

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.

Analysis of DNA-Encoded Library Screening Data: Selection of Molecules for Synthesis

DNA-encoded library (DEL) screens are used to discover novel chemical matter capable of modulating the activity of pharmaceutically interesting protein targets. DEL selections are accomplished by immobilizing a target protein on a resin and capturing library molecules that bind to the target. The barcodes of the captured library molecules are then amplified and sequenced. This chapter outlines simple methods for visualizing the resulting screening data (using free open-source software), such that enriched molecules can be selected for synthesis and follow-up activity confirmation. Measures of enrichment and the concept of sub-libraries are also illustrated.

Identification and Validation of New Interleukin-2 Ligands Using DNA-Encoded Libraries

Interleukin-2 (IL2) is a pro-inflammatory cytokine that plays a crucial role in immunity, which is increasingly being used for therapeutic applications. There is growing interest in developing IL2-based therapeutics which do not interact with the alpha subunit of the IL2 receptor (CD25) as this protein is primarily found on immunosuppressive regulatory T cells (T_regs). Screenings of a new DNA-encoded library, comprising 669,240 members, provided a novel series of IL2 ligands, subsequently optimized by medicinal chemistry. One of these molecules (compound 18) bound to IL2 with a dissociation constant of 0.34 μM was able to form a kinetically stable complex with IL2 in size-exclusion chromatography and recognized the CD25-binding site as evidenced by competition experiments with the NARA1 antibody. Compound 18 and other members of the series may represent the starting point for the discovery of potent small-molecule modulators of IL2 activity, abrogating the binding to CD25.

Specific Inhibitor of Placental Alkaline Phosphatase Isolated from a DNA-Encoded Chemical Library Targets Tumor of the Female Reproductive Tract

Placental alkaline phosphatase (PLAP) is an abundant surface antigen in the malignancies of the female reproductive tract. Nevertheless, the discovery of PLAP-specific small organic ligands for targeting applications has been hindered by ligand cross-reactivity with the ubiquitous tissue non-specific alkaline phosphatase (TNAP). In this study, we used DNA-encoded chemical libraries to discover a potent (IC₅₀ = 32 nM) and selective PLAP inhibitor, with no detectable inhibition of TNAP activity. Subsequently, the PLAP ligand was conjugated to fluorescein; it specifically bound to PLAP-positive tumors in vitro and targeted cervical cancer in vivo in a mouse model of the disease. Ultimately, the fluorescent derivative of the PLAP inhibitor functioned as a bispecific engager redirecting the killing of chimeric antigen receptor-T cells specific to fluorescein on PLAP-positive tumor cells.

Sequential DNA-Encoded Building Block Fusion for the Construction of Polysubstituted Pyrazoline Core Libraries

The construction of chemical libraries containing polysubstituted pyrazoline scaffolds is highly desirable for the discovery of novel chemical ligands for biological targets. Herein, we report a sequential DNA-encoded synthesis strategy for polysubstituted pyrazoline heterocycles, which fuses a broad panel of aldehydes, aryl amines, and alkenes as building blocks. Furthermore, mock library synthesis and selection demonstrated the ability of the method to produce DNA-encoded focused libraries with highly functionalized pyrazoline cores.

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.

DNA-Encoded Chemical Libraries: A Comprehensive Review with Succesful Stories and Future Challenges

DNA-encoded chemical libraries (DELs) represent a versatile and powerful technology platform for the discovery of small-molecule ligands to protein targets of biological and pharmaceutical interest. DELs are collections of molecules, individually coupled to distinctive DNA tags serving as amplifiable identification barcodes. Thanks to advances in DNA-compatible reactions, selection methodologies, next-generation sequencing, and data analysis, DEL technology allows the construction and screening of libraries of unprecedented size, which has led to the discovery of highly potent ligands, some of which have progressed to clinical trials. In this Review, we present an overview of diverse approaches for the generation and screening of DEL molecular repertoires. Recent success stories are described, detailing how novel ligands were isolated from DEL screening campaigns and were further optimized by medicinal chemistry. The goal of the Review is to capture some of the most recent developments in the field, while also elaborating on future challenges to further improve DEL technology as a therapeutic discovery platform.

Recent Advances on the Selection Methods of DNA-Encoded Libraries

DNA-encoded libraries (DEL) have come of age and become a major technology platform for ligand discovery in both academia and the pharmaceutical industry. Technological maturation in the past two decades and the recent explosive developments of DEL-compatible chemistries have greatly improved the chemical diversity of DELs and fueled its applications in drug discovery. A relatively less-covered aspect of DELs is the selection method. Typically, DEL selection is considered as a binding assay and the selection is conducted with purified protein targets immobilized on a matrix, and the binders are separated from the non-binding background via physical washes. However, the recent innovations in DEL selection methods have not only expanded the target scope of DELs, but also revealed the potential of the DEL technology as a powerful tool in exploring fundamental biology. In this Review, we first cover the "classic" DEL selection methods with purified proteins on solid phase, and then we discuss the strategies to realize DEL selections in solution phase. Finally, we focus on the emerging approaches for DELs to interrogate complex biological targets.

Stereo- and regiodefined DNA-encoded chemical libraries enable efficient tumour-targeting applications

The encoding of chemical compounds with amplifiable DNA tags facilitates the discovery of small-molecule ligands for proteins. To investigate the impact of stereo- and regiochemistry on ligand discovery, we synthesized a DNA-encoded library of 670,752 derivatives based on 2-azido-3-iodophenylpropionic acids. The library was selected against multiple proteins and yielded specific ligands. The selection fingerprints obtained for a set of protein targets of pharmaceutical relevance clearly showed the preferential enrichment of ortho-, meta- or para-regioisomers, which was experimentally verified by affinity measurements in the absence of DNA. The discovered ligands included novel selective enzyme inhibitors and binders to tumour-associated antigens, which enabled conditional chimeric antigen receptor T-cell activation and tumour targeting.

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

DNA-encoded chemical libraries are typically screened against purified protein targets. Recently, cell-based selections with encoded chemical libraries have been described, commonly revealing suboptimal performance due to insufficient recovery of binding molecules. We used carbonic anhydrase IX (CAIX)-expressing tumor cells as a model system to optimize selection procedures with code-specific quantitative polymerase chain reaction (qPCR) as selection readout. Salt concentration and performing PCR on cell suspension had the biggest impact on selection performance, leading to 15-fold enrichment factors for high-affinity monovalent CAIX binders (acetazolamide; K_D =8.7 nM). Surprisingly, the homobivalent display of acetazolamide at the extremities of both complementary DNA strands led to a substantial improvement of both ligand recovery and enrichment factors (above 100-fold). The optimized procedures were used for selections with a DNA-encoded chemical library comprising 1 million members against tumor cell lines expressing CAIX, leading to a preferential recovery of known and new ligands against this validated tumor-associated target. This work may facilitate future affinity selections on cells against target proteins which might be difficult to express otherwise.

Diversity-oriented synthesis as a tool to expand the chemical space of DNA-encoded libraries

DNA-encoded libraries (DEL) represent a powerful technology for generating compound collections for drug discovery campaigns, that have allowed for the selection of many hit compounds over last three decades. However, the application of split-and-pool combinatorial methodologies, as well as the limitation imposed by DNA-compatible chemistry, has often brought to a limited exploration of the chemical space, with an over-representation of flat aromatic or peptide-like structures, whereas a higher scaffold complexity is generally associated with a more successful biological activity of the library. In this context, the application of Diversity-Oriented Synthesis, capable of creating sp³-rich molecular entities even starting from simple flat building blocks, can represent an efficient strategy to significantly broaden the chemical space explored by DELs. In this review, we present selected examples of DNA-compatible complexity-generating reactions that can be applied for the generation of DNA-encoded DOS libraries, including: (i) multicomponent reactions; (ii) C-H/C-X functionalization; (iii) tandem approaches; (iv) cycloadditions; (v) reactions introducing privileged elements. Also, selected case studies on the generation of DELs with high scaffold diversity are discussed, reporting their application in drug discovery programs.

A DNA-Encoded Chemical Library Based on Peptide Macrocycles

The synthesis and characterization of a novel DNA-encoded library of macrocyclic peptide derivatives are described; the macrocycles are based on three sets of proteinogenic and non-proteinogenic amino acid building blocks and featuring the use of copper(I)-catalyzed alkyne-azide cycloaddition (CuAAC) reaction for ring closure. The library (termed YO-DEL) which contains 1 254 838 compounds, was encoded with DNA in single-stranded format and was screened against target proteins of interest using affinity capture procedures and photocrosslinking. YO-DEL selections yielded specific binders against serum albumins, carbonic anhydrases and NKp46, a marker of activated Natural Killer cells.