Application of encoded library technology (ELT) to a protein–protein interaction target: Discovery of a potent class of integrin lymphocyte function-associated antigen 1 (LFA-1) antagonists

Enhancing the Predictive Power of Machine Learning Models through a Chemical Space Complementary DEL Screening Strategy

DNA-encoded library (DEL) technology is an effective method for small molecule drug discovery, enabling high-throughput screening against target proteins. While DEL screening produces extensive data, it can reveal complex patterns not easily recognized by human analysis. Lead compounds from DEL screens often have higher molecular weights, posing challenges for drug development. This study refines traditional DELs by integrating alternative techniques like photocross-linking screening to enhance chemical diversity. Combining these methods improved predictive performance for small molecule identification models. Using this approach, we predicted active small molecules for BRD4 and p300, achieving hit rates of 26.7 and 35.7%. Notably, the identified compounds exhibit smaller molecular weights and better modification potential compared to traditional DEL molecules. This research demonstrates the synergy between DEL and AI technologies, enhancing drug discovery.

Reversible and Fully Controllable Generation of Organo-Soluble DNA (osDNA)

The present work describes a complete and reversible transformation of DNA's properties allowing solubilization in organic solvents and subsequent chemical modifications that are otherwise not possible in an aqueous medium. Organo-soluble DNA (osDNA) moieties are generated by covalently linking a dsDNA fragment to a polyether moiety with a built-in mechanism, rendering the process perfectly reversible and fully controllable. The precise removal of the polyether moiety frees up the initial DNA fragment, unaltered, both in sequence and nature. The solubility of osDNA was confirmed in six organic solvents of decreasing polarity and six types of osDNAs. As a proof of concept, in the context of DNA-encoded library (DEL) technology, an amidation reaction was successfully performed on osDNA in 100% DMSO. The development of osDNA opens up entirely new avenues for any DNA applications that could benefit from working in nonaqueous solutions, including chemical transformations.

EasyDock: customizable and scalable docking tool

Docking of large compound collections becomes an important procedure to discover new chemical entities. Screening of large sets of compounds may also occur in de novo design projects guided by molecular docking. To facilitate these processes, there is a need for automated tools capable of efficiently docking a large number of molecules using multiple computational nodes within a reasonable timeframe. These tools should also allow for easy integration of new docking programs and provide a user-friendly program interface to support the development of further approaches utilizing docking as a foundation. Currently available tools have certain limitations, such as lacking a convenient program interface or lacking support for distributed computations. In response to these limitations, we have developed a module called EasyDock. It can be deployed over a network of computational nodes using the Dask library, without requiring a specific cluster scheduler. Furthermore, we have proposed and implemented a simple model that predicts the runtime of docking experiments and applied it to minimize overall docking time. The current version of EasyDock supports popular docking programs, namely Autodock Vina, gnina, and smina. Additionally, we implemented a supplementary feature to enable docking of boron-containing compounds, which are not inherently supported by Vina and smina, and demonstrated its applicability on a set of 55 PDB protein-ligand complexes.

CD11a regulates hematopoietic stem and progenitor cells

Integrin αLβ2 (CD11a/CD18, CD11a) is a critical leukocyte adhesion molecule in leukocyte arrest and immunological synapse formation. However, its role in the bone marrow has not been investigated in depth. Here we showed that CD11a was expressed on all subsets of hematopoietic stem and progenitor cells (HPSCs). CD11a deficiency enhanced HSPCs activity under lipopolysaccharide (LPS) stimulation as demonstrated by a higher HSPC cell count along with an increase in cell proliferation. However, our mixed chimera experiment did not support that this phenotype was driven in a cell-intrinsic manner. Rather we found that the production of IL-27, a major cytokine that drives HSPC proliferation, was significantly upregulated both in vivo and in vitro. This adds a novel role of CD11a biology.

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.

Privileged heterocycles for DNA-encoded library design and hit-to-lead optimization

It is well known that heterocyclic compounds play a key role in improving drug activity, target selectivity, physicochemical properties as well as reducing toxicity. In this review, we summarized the representative heterocyclic structures involved in hit compounds which were obtained from DNA-encoded library from 2013 to 2021. In some examples, the state of the art in heterocycle-based DEL synthesis and hit-to-lead optimization are highlighted. We hope that more and more novel heterocycle-based DEL toolboxes and in-depth pharmaceutical research on these lead compounds can be developed to accelerate the discovery of new drugs.

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.

Opportunities for Expanding Encoded Chemical Diversification and Improving Hit Enrichment in mRNA-Displayed Peptide Libraries

DNA-encoded small-molecule libraries and mRNA displayed peptide libraries both use numerically large pools of oligonucleotide-tagged molecules to identify potential hits for protein targets. They differ dramatically, however, in the 'drug-likeness' of the molecules that each can be used to discover. We give here an overview of the two techniques, comparing some advantages and disadvantages of each, and suggest areas where particularly mRNA display can benefit from adopting advances developed with DNA-encoded small molecule libraries. We outline cases where chemical modification of the peptide library has already been used in mRNA display, and survey opportunities to expand this using examples from DNA-encoded small molecule libraries. We also propose potential opportunities for encoding such reactions within the mRNA/cDNA tag of an mRNA-displayed peptide library to allow a more diversity-oriented approach to library modification. Finally, we outline alternate approaches for enriching target-binding hits from a pooled and tagged library, and close by detailing several examples of how an adjusted mRNA-display based approach could be used to discover new 'drug-like' modified small peptides.

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.

Library Synthesis: Building Block Selection, Handling, and Tracking

Careful selection and manipulation of small molecule building blocks is crucial to the success of a DNA-encoded library. Building block selection impacts the quality of the hits arising out of a selection assay, while proper sample handling and tracking ensure follow-up synthetic work is done with the appropriate synthetic map in mind. In this chapter, possible strategies for building block selection are outlined, as well as best practices for handling and tracking samples to be used for validation and library synthesis.

Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction

We present results on the extent to which physics-based simulation (exemplified by FEP⁺) and focused machine learning (exemplified by QuanSA) are complementary for ligand affinity prediction. For both methods, predictions of activity for LFA-1 inhibitors from a medicinal chemistry lead optimization project were accurate within the applicable domain of each approach. A hybrid model that combined predictions by both approaches by simple averaging performed better than either method, with respect to both ranking and absolute pK_i values. Two publicly available FEP⁺ benchmarks, covering 16 diverse biological targets, were used to test the generality of the synergy. By identifying training data specifically focused on relevant ligands, accurate QuanSA models were derived using ligand activity data known at the time of the original series publications. Results across the 16 benchmark targets demonstrated significant improvements both for ranking and for absolute pK_i values using hybrid predictions that combined the FEP⁺ and QuanSA predicted affinity values. The results argue for a combined approach for affinity prediction that makes use of physics-driven methods as well as those driven by machine learning, each applied carefully on appropriate compounds, with hybrid prediction strategies being employed where possible.

Antibacterial Discovery via Phenotypic DNA-Encoded Library Screening

The global rise of multidrug resistant infections poses an imminent, existential threat. Numerous pipelines have failed to convert biochemically active molecules into bona fide antibacterials, owing to a lack of chemical material with antibacterial-like physical properties in high-throughput screening compound libraries. Here, we demonstrate scalable design and synthesis of an antibacterial-like solid-phase DNA-encoded library (DEL, 7488 members) and facile hit deconvolution from whole-cell Escherichia coli and Bacillus subtilis cytotoxicity screens. The screen output identified two low-micromolar inhibitors of B. subtilis growth and recapitulated known structure-activity relationships of the fluoroquinolone antibacterial class. This phenotypic DEL screening strategy is also potentially applicable to adherent cells and will broadly enable the discovery and optimization of cell-active molecules.

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.

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.

DNA-Encoded Chemistry: Drug Discovery from a Few Good Reactions

Click chemistry, proposed nearly 20 years ago, promised access to novel chemical space by empowering combinatorial library synthesis with a "few good reactions". These click reactions fulfilled key criteria (broad scope, quantitative yield, abundant starting material, mild reaction conditions, and high chemoselectivity), keeping the focus on molecules that would be easy to make, yet structurally diverse. This philosophy bears a striking resemblance to DNA-encoded library (DEL) technology, the now-dominant combinatorial chemistry paradigm. This review highlights the similarities between click and DEL reaction design and deployment in combinatorial library settings, providing a framework for the design of new DEL synthesis technologies to enable next-generation drug discovery.

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.

Modulating Target Protein Biology Through the Re-mapping of Conformational Distributions Using Small Molecules

Over the last 10 years considerable progress has been made in the application of small molecules to modulating protein-protein interactions (PPIs), and the navigation from "undruggable" to a host of candidate molecules in clinical trials has been well-charted in recent, comprehensive reviews. Structure-based design has played an important role in this scientific journey, with three dimensional structures guiding medicinal chemistry efforts. However, the importance of two additional dimensions: movement and time is only now being realised, as increasing computing power, closely aligned with wet lab validation, is applied to the challenge. Protein dynamics are fundamental to biology and disease, and application to PPI drug discovery has massively widened the scope for new chemical entities to influence function from allosteric, and previously unreported, sites. In this forward-looking perspective we highlight exciting, new opportunities for small molecules to modulate disease biology, by adjusting the frequency profile of natural conformational sampling, through the stabilisation of clinically desired conformers of target proteins.

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.

Irisin supports integrin-mediated cell adhesion of lymphocytes

Irisin, a myokine released from skeletal muscle, has recently been found to act as a ligand for the integrins αVβ5, αVβ1, and α5β1 expressed on mesenchymal cells, thereby playing an important role in the metabolic remodeling of the bone, skeletal muscle and adipose tissues. Although the immune-modulatory effects of irisin in chronic inflammation have been documented, its interactions with lymphocytic integrins have yet to be elucidated. Here, we show that irisin supports the cell adhesion of human and mouse lymphocytes. Cell adhesion assays using a panel of inhibitory antibodies to integrins have shown that irisin-mediated lymphocyte adhesion involves multiple integrins including not only α4β1 and α5β1, but also leukocyte-specific αLβ2 and α4β7. Importantly, mouse lymphocytic TK-1 cells that lack the expression of β1 integrins have exhibited αLβ2- and α4β7-mediated cell adhesion to irisin. Irisin has also been demonstrated to bind to purified recombinant integrin αLβ2 and α4β7 proteins. Thus, irisin represents a novel ligand for integrin αLβ2 and α4β7, capable of supporting lymphocyte cell adhesion independently of β1 integrins. These results suggest that irisin may play an important role in regulating lymphocyte adhesion and migration in the inflamed vasculature.

•

Irisin, a myokine released from skeletal muscle, binds to integrins αLβ2 and α4β7 in addition to integrins α4β1 and α5β1.

•

Irisin acts as an integrin ligand capable of supporting cell adhesion of human and mouse lymphocytes.

•

The results of this study significantly expand upon the role of irisin as a contributor to metabolic regulation.

•

Irisin deposited on the inflamed vasculature may participate in the metabolic regulation of lymphocyte migration.

The maturation of DNA encoded libraries: opportunities for new users

DNA-encoded combinatorial libraries (DECLs) represent an exciting new technology for high-throughput screening, significantly increasing its capacity and cost-effectiveness. Historically, DECLs have been the domain of specialized academic groups and industry; however, there has recently been a shift toward more drug discovery academic centers and institutes adopting this technology. Key to this development has been the simplification, characterization and standardization of various DECL subprotocols, such as library design, affinity screening and data analysis of hits. This review examines the feasibility of implementing DECL screening technology as a first-time user, particularly in academia, exploring the some important considerations for this, and outlines some applications of the technology that academia could contribute to the field.

Selection of DNA-encoded chemical libraries against endogenous membrane proteins on live cells

Membrane proteins on the cell surface perform a myriad of biological functions; however, ligand discovery for membrane proteins is highly challenging, because a natural cellular environment is often necessary to maintain protein structure and function. DNA-encoded chemical libraries (DELs) have emerged as a powerful technology for ligand discovery, but they are mainly limited to purified proteins. Here we report a method that can specifically label membrane proteins with a DNA tag, and thereby enable target-specific DEL selections against endogenous membrane proteins on live cells without overexpression or any other genetic manipulation. We demonstrate the generality and performance of this method by screening a 30.42-million-compound DEL against the folate receptor, carbonic anhydrase 12 and the epidermal growth factor receptor on live cells, and identify and validate a series of novel ligands for these targets. Given the high therapeutic significance of membrane proteins and their intractability to traditional high-throughput screening approaches, this method has the potential to facilitate membrane-protein-based drug discovery by harnessing the power of DEL.

TEAD-YAP Interaction Inhibitors and MDM2 Binders from DNA-Encoded Indole-Focused Ugi Peptidomimetics

DNA-encoded combinatorial synthesis provides efficient and dense coverage of chemical space around privileged molecular structures. The indole side chain of tryptophan plays a prominent role in key, or "hot spot", regions of protein-protein interactions. A DNA-encoded combinatorial peptoid library was designed based on the Ugi four-component reaction by employing tryptophan-mimetic indole side chains to probe the surface of target proteins. Several peptoids were synthesized on a chemically stable hexathymidine adapter oligonucleotide "hexT", encoded by DNA sequences, and substituted by azide-alkyne cycloaddition to yield a library of 8112 molecules. Selection experiments for the tumor-relevant proteins MDM2 and TEAD4 yielded MDM2 binders and a novel class of TEAD-YAP interaction inhibitors that perturbed the expression of a gene under the control of these Hippo pathway effectors.

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.

DNA-Encoded Library Screening as Core Platform Technology in Drug Discovery: Its Synthetic Method Development and Applications in DEL Synthesis

DNA-encoded library technology (DELT) was introduced to our medicinal chemistry society more than 20 years ago. The application of DELT in the development of clinical candidates has been actively reported in the literature recently. A few representative examples include RIP1K inhibitors for inflammatory diseases and sEH inhibitors for endothelial dysfunction or abnormal tissue repair, among many others. Here, the authors would like to recall the recent developments in on-DNA synthetic methodologies for DEL construction and to analyze recent examples in the literature of DELT-based drug development efforts pursued in both the academic and industrial sectors. With this perspective, we hope to provide a useful summary of recent DELT-based drug discovery research and to discuss the future scope of DELT in medicinal chemistry.

Off-DNA DNA-Encoded Library Affinity Screening

DNA-encoded library (DEL) technology is emerging as a key element of the small molecule discovery toolbox. Conventional DEL screens (i.e., on-DNA screening) interrogate large combinatorial libraries via affinity selection of DNA-tagged library members that are ligands of a purified and immobilized protein target. In these selections, the DNA tags can materially and undesirably influence target binding and, therefore, the experiment outcome. Here, we use a solid-phase DEL and droplet-based microfluidic screening to separate the DEL member from its DNA tag (i.e., off-DNA screening), for subsequent in-droplet laser-induced fluorescence polarization (FP) detection of target binding, obviating DNA tag interference. Using the receptor tyrosine kinase (RTK) discoidin domain receptor 1 (DDR1) as a proof-of-concept target in a droplet-scale competition-binding assay, we screened a 67 100-member solid-phase DEL of drug-like small molecules for competitive ligands of DDR1 and identified several known RTK inhibitor pharmacophores, including azaindole- and quinazolinone-containing monomers. Off-DNA DEL affinity screening with FP detection is potentially amenable to a wide array of target classes, including nucleic acid binding proteins, proteins that are difficult to overexpress and purify, or targets with no known activity assay.

Exploring the Lower Limit of Individual DNA-Encoded Library Molecules in Selection

DNA-encoded library (DEL) technology has been used as an ultra-high-throughput screening approach for hit identification of drug targets. This process is an affinity-based selection and requires incubation of DEL molecules with the target. Currently, in most reported cases, the input (i.e., the copy number) of individual DEL molecules varies from 105 to 107. With the ever-increasing DEL size and screening cost, lowering the input of DEL molecules while maintaining an appropriate signal-to-noise ratio in a selection is of paramount importance. In this article, we varied the input of DEL ranging from 103 to 105 in selections with two different protein targets to explore the lower limit of DEL molecule input. The results could facilitate the optimization of the DEL selection process and reduce costs related to library consumption.

DNA Barcoding a Complete Matrix of Stereoisomeric Small Molecules

It is challenging to incorporate stereochemical diversity and topographic complexity into DNA-encoded libraries (DELs) because DEL syntheses cannot fully exploit the capabilities of modern synthetic organic chemistry. Here, we describe the design, construction, and validation of DOS-DEL-1, a library of 107 616 DNA-barcoded chiral 2,3-disubsituted azetidines and pyrrolidines. We used stereospecific C-H arylation chemistry to furnish complex scaffolds primed for DEL synthesis, and we developed an improved on-DNA Suzuki reaction to maximize library quality. We then studied both the structural diversity of the library and the physicochemical properties of individual compounds using Tanimoto multifusion similarity analysis, among other techniques. These analyses revealed not only that most DOS-DEL-1 members have "drug-like" properties, but also that the library more closely resembles compound collections derived from diversity synthesis than those from other sources (e.g., commercial vendors). Finally, we performed validation screens against horseradish peroxidase and carbonic anhydrase IX, and we developed a novel, Poisson-based statistical framework to analyze the results. A set of assay positives were successfully translated into potent carbonic anhydrase inhibitors (IC₅₀ = 20.1-68.7 nM), which confirmed the success of the synthesis and screening procedures. These results establish a strategy to synthesize DELs with scaffold-based stereochemical diversity and complexity that does not require the development of novel DNA-compatible chemistry.

Activity-Based DNA-Encoded Library Screening

Robotic high-throughput compound screening (HTS) and, increasingly, DNA-encoded library (DEL) screening are driving bioactive chemical matter discovery in the postgenomic era. HTS enables activity-based investigation of highly complex targets using static compound libraries. Conversely, DEL grants efficient access to novel chemical diversity, although screening is limited to affinity-based selections. Here, we describe an integrated droplet-based microfluidic circuit that directly screens solid-phase DELs for activity. An example screen of a 67 100-member library for inhibitors of the phosphodiesterase autotaxin yielded 35 high-priority structures for nanomole-scale synthesis and validation (20 active), guiding candidate selection for synthesis at scale (5/5 compounds with IC₅₀ values of 4-10 μM). We further compared activity-based hits with those of an analogous affinity-based DEL selection. This miniaturized screening platform paves the way toward applying DELs to more complex targets (signaling pathways, cellular response) and represents a distributable approach to small molecule discovery.

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.

DNA-encoded libraries - an efficient small molecule discovery technology for the biomedical sciences

DNA-encoded compound libraries are a highly attractive technology for the discovery of small molecule protein ligands. These compound collections consist of small molecules covalently connected to individual DNA sequences carrying readable information about the compound structure. DNA-tagging allows for efficient synthesis, handling and interrogation of vast numbers of chemically synthesized, drug-like compounds. They are screened on proteins by an efficient, generic assay based on Darwinian principles of selection. To date, selection of DNA-encoded libraries allowed for the identification of numerous bioactive compounds. Some of these compounds uncovered hitherto unknown allosteric binding sites on target proteins; several compounds proved their value as chemical biology probes unraveling complex biology; and the first examples of clinical candidates that trace their ancestry to a DNA-encoded library were reported. Thus, DNA-encoded libraries proved their value for the biomedical sciences as a generic technology for the identification of bioactive drug-like molecules numerous times. However, large scale experiments showed that even the selection of billions of compounds failed to deliver bioactive compounds for the majority of proteins in an unbiased panel of target proteins. This raises the question of compound library design.

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.

Efficient copper-catalyzed amination of DNA-conjugated aryl iodides under mild aqueous conditions

Herein, we describe the development of copper-catalyzed cross-coupling of DNA-conjugated aryl iodides with aliphatic amines. This protocol leverages a novel ligand, 2-((2,6-dimethoxyphenyl)amino)-2-oxoacetic acid, to effect the transformation in aqueous DMSO, under mild conditions and in air, making it an ideal candidate for the synthesis of DNA-encoded libraries.

Kinetically guided radical-based synthesis of C(sp3)-C(sp3) linkages on DNA

DNA-encoded libraries (DEL)-based discovery platforms have recently been widely adopted in the pharmaceutical industry, mainly due to their powerful diversity and incredible number of molecules. In the two decades since their disclosure, great strides have been made to expand the toolbox of reaction modes that are compatible with the idiosyncratic aqueous, dilute, and DNA-sensitive parameters of this system. However, construction of highly important C(sp³)-C(sp³) linkages on DNA through cross-coupling remains unexplored. In this article, we describe a systematic approach to translating standard organic reactions to a DEL setting through the tactical combination of kinetic analysis and empirical screening with information captured from data mining. To exemplify this model, implementation of the Giese addition to forge high value C-C bonds on DNA was studied, which represents a radical-based synthesis in DEL.

Integration of Lead Discovery Tactics and the Evolution of the Lead Discovery Toolbox

There has been much debate around the success rates of various screening strategies to identify starting points for drug discovery. Although high-throughput target-based and phenotypic screening has been the focus of this debate, techniques such as fragment screening, virtual screening, and DNA-encoded library screening are also increasingly reported as a source of new chemical equity. Here, we provide examples in which integration of more than one screening approach has improved the campaign outcome and discuss how strengths and weaknesses of various methods can be used to build a complementary toolbox of approaches, giving researchers the greatest probability of successfully identifying leads. Among others, we highlight case studies for receptor-interacting serine/threonine-protein kinase 1 and the bromo- and extra-terminal domain family of bromodomains. In each example, the unique insight or chemistries individual approaches provided are described, emphasizing the synergy of information obtained from the various tactics employed and the particular question each tactic was employed to answer. We conclude with a short prospective discussing how screening strategies are evolving, what this screening toolbox might look like in the future, how to maximize success through integration of multiple tactics, and scenarios that drive selection of one combination of tactics over another.

Design and Application of a DNA-Encoded Macrocyclic Peptide Library

A DNA-encoded macrocyclic peptide library was designed and synthesized with 2.4 × 10¹² members composed of 4-20 natural and non-natural amino acids. Affinity-based selection was performed against two therapeutic targets, VHL and RSV N protein. On the basis of selection data, some peptides were selected for resynthesis without a DNA tag, and their activity was confirmed.

Prioritizing multiple therapeutic targets in parallel using automated DNA-encoded library screening

The identification and prioritization of chemically tractable therapeutic targets is a significant challenge in the discovery of new medicines. We have developed a novel method that rapidly screens multiple proteins in parallel using DNA-encoded library technology (ELT). Initial efforts were focused on the efficient discovery of antibacterial leads against 119 targets from Acinetobacter baumannii and Staphylococcus aureus. The success of this effort led to the hypothesis that the relative number of ELT binders alone could be used to assess the ligandability of large sets of proteins. This concept was further explored by screening 42 targets from Mycobacterium tuberculosis. Active chemical series for six targets from our initial effort as well as three chemotypes for DHFR from M. tuberculosis are reported. The findings demonstrate that parallel ELT selections can be used to assess ligandability and highlight opportunities for successful lead and tool discovery.

Encoded Library Technology (ELT) has streamlined the identification of chemical ligands for protein targets in drug discovery. Here, the authors optimize the ELT approach to screen multiple proteins in parallel and identify promising targets and antibacterial compounds for S. aureus, A. baumannii and M. tuberculosis.

Analysis of Current DNA Encoded Library Screening Data Indicates Higher False Negative Rates for Numerically Larger Libraries

To optimize future DNA-encoded library design, we have attempted to quantify the library size at which the signal becomes undetectable. To accomplish this we (i) have calculated that percent yields of individual library members following a screen range from 0.002 to 1%, (ii) extrapolated that ∼1 million copies per library member are required at the outset of a screen, and (iii) from this extrapolation predict that false negative rates will begin to outweigh the benefit of increased diversity at library sizes >10⁸. The above analysis is based upon a large internal data set comprising multiple screens, targets, and libraries; we also augmented our internal data with all currently available literature data. In theory, high false negative rates may be overcome by employing larger amounts of library; however, we argue that using more than currently reported amounts of library (≫10 nmoles) is impractical. The above conclusions may be generally applicable to other DNA encoded library platforms, particularly those platforms that do not allow for library amplification.

Discovery of a Potent BTK Inhibitor with a Novel Binding Mode by Using Parallel Selections with a DNA-Encoded Chemical Library

We have identified and characterized novel potent inhibitors of Bruton's tyrosine kinase (BTK) from a single DNA-encoded library of over 110 million compounds by using multiple parallel selection conditions, including variation in target concentration and addition of known binders to provide competition information. Distinct binding profiles were observed by comparing enrichments of library building block combinations under these conditions; one enriched only at high concentrations of BTK and was competitive with ATP, and another enriched at both high and low concentrations of BTK and was not competitive with ATP. A compound representing the latter profile showed low nanomolar potency in biochemical and cellular BTK assays. Results from kinetic mechanism of action studies were consistent with the selection profiles. Analysis of the co-crystal structure of the most potent compound demonstrated a novel binding mode that revealed a new pocket in BTK. Our results demonstrate that profile-based selection strategies using DNA-encoded libraries form the basis of a new methodology to rapidly identify small molecule inhibitors with novel binding modes to clinically relevant targets.

DNA-encoded chemistry: enabling the deeper sampling of chemical space

DNA-encoded chemical library technologies are increasingly being adopted in drug discovery for hit and lead generation. DNA-encoded chemistry enables the exploration of chemical spaces four to five orders of magnitude more deeply than is achievable by traditional high-throughput screening methods. Operation of this technology requires developing a range of capabilities including aqueous synthetic chemistry, building block acquisition, oligonucleotide conjugation, large-scale molecular biological transformations, selection methodologies, PCR, sequencing, sequence data analysis and the analysis of large chemistry spaces. This Review provides an overview of the development and applications of DNA-encoded chemistry, highlighting the challenges and future directions for the use of this technology.

Recent advances on the encoding and selection methods of DNA-encoded chemical library

DNA-encoded chemical library (DEL) has emerged as a powerful and versatile tool for ligand discovery in chemical biology research and in drug discovery. Encoding and selection methods are two of the most important technological aspects of DEL that can dictate the performance and utilities of DELs. In this digest, we have summarized recent advances on the encoding and selection strategies of DEL and also discussed the latest developments on DNA-encoded dynamic library, a new frontier in DEL research.

Discovery of cofactor-specific, bactericidal Mycobacterium tuberculosis InhA inhibitors using DNA-encoded library technology

Millions of individuals are infected with and die from tuberculosis (TB) each year, and multidrug-resistant (MDR) strains of TB are increasingly prevalent. As such, there is an urgent need to identify novel drugs to treat TB infections. Current frontline therapies include the drug isoniazid, which inhibits the essential NADH-dependent enoyl-acyl-carrier protein (ACP) reductase, InhA. To inhibit InhA, isoniazid must be activated by the catalase-peroxidase KatG. Isoniazid resistance is linked primarily to mutations in the katG gene. Discovery of InhA inhibitors that do not require KatG activation is crucial to combat MDR TB. Multiple discovery efforts have been made against InhA in recent years. Until recently, despite achieving high potency against the enzyme, these efforts have been thwarted by lack of cellular activity. We describe here the use of DNA-encoded X-Chem (DEX) screening, combined with selection of appropriate physical properties, to identify multiple classes of InhA inhibitors with cell-based activity. The utilization of DEX screening allowed the interrogation of very large compound libraries (10¹¹ unique small molecules) against multiple forms of the InhA enzyme in a multiplexed format. Comparison of the enriched library members across various screening conditions allowed the identification of cofactor-specific inhibitors of InhA that do not require activation by KatG, many of which had bactericidal activity in cell-based assays.