Quantitative Comparison of Enrichment from DNA-Encoded Chemical Library Selections

Squaramide Formation for DNA-Encoded Library Synthesis

DNA-encoded libraries (DELs) can be considered as one of the most powerful tools for the discovery of small molecules of biological interest. However, the ability to access large DELs is contingent upon having chemical transformations that work in aqueous phase and generate minimal DNA alterations and the availability of building blocks compatible with on-DNA chemistry. In addition, accessing scaffolds of interest to medicinal chemists can be challenging in a DEL setting because of inherent limitations of DNA-supported chemistry. In this context, a squaramide formation reaction was developed by using a two-step process. The mild and high-yielding reaction tolerates a wide array of functional groups and was shown to be safe for DNA, thereby making this methodology ideal for DELs.

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.

Reversible male contraception by targeted inhibition of serine/threonine kinase 33

Men or mice with homozygous serine/threonine kinase 33 (STK33) mutations are sterile owing to defective sperm morphology and motility. To chemically evaluate STK33 for male contraception with STK33-specific inhibitors, we screened our multibillion-compound collection of DNA-encoded chemical libraries, uncovered potent STK33-specific inhibitors, determined the STK33 kinase domain structure bound with a truncated hit CDD-2211, and generated an optimized hit CDD-2807 that demonstrates nanomolar cellular potency (half-maximal inhibitory concentration = 9.2 nanomolar) and favorable metabolic stability. In mice, CDD-2807 exhibited no toxicity, efficiently crossed the blood-testis barrier, did not accumulate in brain, and induced a reversible contraceptive effect that phenocopied genetic STK33 perturbations without altering testis size. Thus, STK33 is a chemically validated, nonhormonal contraceptive target, and CDD-2807 is an effective tool compound.

Identification of potent pan-ephrin receptor kinase inhibitors using DNA-encoded chemistry technology

EPH receptors (EPHs), the largest family of tyrosine kinases, phosphorylate downstream substrates upon binding of ephrin cell surface-associated ligands. In a large cohort of endometriotic lesions from individuals with endometriosis, we found that EPHA2 and EPHA4 expressions are increased in endometriotic lesions relative to normal eutopic endometrium. Because signaling through EPHs is associated with increased cell migration and invasion, we hypothesized that chemical inhibition of EPHA2/4 could have therapeutic value. We screened DNA-encoded chemical libraries (DECL) to rapidly identify EPHA2/4 kinase inhibitors. Hit compound, CDD-2693, exhibited picomolar/nanomolar kinase activity against EPHA2 (Ki: 4.0 nM) and EPHA4 (Ki: 0.81 nM). Kinome profiling revealed that CDD-2693 bound to most EPH family and SRC family kinases. Using NanoBRET target engagement assays, CDD-2693 had nanomolar activity versus EPHA2 (IC50: 461 nM) and EPHA4 (IC50: 40 nM) but was a micromolar inhibitor of SRC, YES, and FGR. Chemical optimization produced CDD-3167, having picomolar biochemical activity toward EPHA2 (Ki: 0.13 nM) and EPHA4 (Ki: 0.38 nM) with excellent cell-based potency EPHA2 (IC50: 8.0 nM) and EPHA4 (IC50: 2.3 nM). Moreover, CDD-3167 maintained superior off-target cellular selectivity. In 12Z endometriotic epithelial cells, CDD-2693 and CDD-3167 significantly decreased EFNA5 (ligand) induced phosphorylation of EPHA2/4, decreased 12Z cell viability, and decreased IL-1β-mediated expression of prostaglandin synthase 2 (PTGS2). CDD-2693 and CDD-3167 decreased expansion of primary endometrial epithelial organoids from patients with endometriosis and decreased Ewing's sarcoma viability. Thus, using DECL, we identified potent pan-EPH inhibitors that show specificity and activity in cellular models of endometriosis and cancer.

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.

Compositional Deep Probabilistic Models of DNA-Encoded Libraries

DNA-encoded library (DEL) has proven to be a powerful tool that utilizes combinatorially constructed small molecules to facilitate highly efficient screening experiments. These selection experiments, involving multiple stages of washing, elution, and identification of potent binders via unique DNA barcodes, often generate complex data. This complexity can potentially mask the underlying signals, necessitating the application of computational tools, such as machine learning, to uncover valuable insights. We introduce a compositional deep probabilistic model of DEL data, DEL-Compose, which decomposes molecular representations into their monosynthon, disynthon, and trisynthon building blocks and capitalizes on the inherent hierarchical structure of these molecules by modeling latent reactions between embedded synthons. Additionally, we investigate methods to improve the observation models for DEL count data, such as integrating covariate factors to more effectively account for data noise. Across two popular public benchmark data sets (CA-IX and HRP), our model demonstrates strong performance compared to count baselines, enriches the correct pharmacophores, and offers valuable insights via its intrinsic interpretable structure, thereby providing a robust tool for the analysis of DEL data.

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.

Exploiting the Carboxylate-Binding Pocket of β-Lactamase Enzymes Using a Focused DNA-Encoded Chemical Library

β-Lactamase enzymes hydrolyze and thereby provide bacterial resistance to the important β-lactam class of antibiotics. The OXA-48 and NDM-1 β-lactamases cause resistance to the last-resort β-lactams, carbapenems, leading to a serious public health threat. Here, we utilized DNA-encoded chemical library (DECL) technology to discover novel β-lactamase inhibitors. We exploited the β-lactamase enzyme-substrate binding interactions and created a DECL targeting the carboxylate-binding pocket present in all β-lactamases. A library of 106 compounds, each containing a carboxylic acid or a tetrazole as an enzyme recognition element, was designed, constructed, and used to identify OXA-48 and NDM-1 inhibitors with micromolar to nanomolar potency. Further optimization led to NDM-1 inhibitors with increased potencies and biological activities. This work demonstrates that the carboxylate-binding pocket-targeting DECL, designed based on substrate binding information, aids in inhibitor identification and led to the discovery of novel non-β-lactam pharmacophores for the development of β-lactamase inhibitors for enzymes of different structural and mechanistic classes.

DNA-encoded chemical libraries yield non-covalent and non-peptidic SARS-CoV-2 main protease inhibitors

The development of SARS-CoV-2 main protease (Mpro) inhibitors for the treatment of COVID-19 has mostly benefitted from X-ray structures and preexisting knowledge of inhibitors; however, an efficient method to generate Mpro inhibitors, which circumvents such information would be advantageous. As an alternative approach, we show here that DNA-encoded chemistry technology (DEC-Tec) can be used to discover inhibitors of Mpro. An affinity selection of a 4-billion-membered DNA-encoded chemical library (DECL) using Mpro as bait produces novel non-covalent and non-peptide-based small molecule inhibitors of Mpro with low nanomolar Ki values. Furthermore, these compounds demonstrate efficacy against mutant forms of Mpro that have shown resistance to the standard-of-care drug nirmatrelvir. Overall, this work demonstrates that DEC-Tec can efficiently generate novel and potent inhibitors without preliminary chemical or structural information.

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.

Discovery of Highly Potent and BMPR2-Selective Kinase Inhibitors Using DNA-Encoded Chemical Library Screening

The discovery of monokinase-selective inhibitors for patients is challenging because the 500+ kinases encoded by the human genome share highly conserved catalytic domains. Until now, no selective inhibitors unique for a single transforming growth factor β (TGFβ) family transmembrane receptor kinase, including bone morphogenetic protein receptor type 2 (BMPR2), have been reported. This dearth of receptor-specific kinase inhibitors hinders therapeutic options for skeletal defects and cancer as a result of an overactivated BMP signaling pathway. By screening 4.17 billion "unbiased" and "kinase-biased" DNA-encoded chemical library molecules, we identified hits CDD-1115 and CDD-1431, respectively, that were low-nanomolar selective kinase inhibitors of BMPR2. Structure-activity relationship studies addressed metabolic lability and high-molecular-weight issues, resulting in potent and BMPR2-selective inhibitor analogs CDD-1281 (IC50 = 1.2 nM) and CDD-1653 (IC50 = 2.8 nM), respectively. Our work demonstrates that DNA-encoded chemistry technology (DEC-Tec) is reliable for identifying novel first-in-class, highly potent, and selective kinase inhibitors.

Discovery of potent BET bromodomain 1 stereoselective inhibitors using DNA-encoded chemical library selections

BET bromodomain inhibition is therapeutic in multiple diseases; however, pan-BET inhibitors have induced significant myelosuppression and gastrointestinal toxicity, perhaps due to inhibition of both tandem bromodomains (BD) of all BET family members. However, selective inhibition of just the first BD (BD1) phenocopies pan-BET inhibitor activity in preclinical models of cancer, other diseases, and, for BRDT, in the testes for a contraceptive effect. Here, we leveraged our multibillion-molecule collection of DNA-encoded chemical libraries (DECLs) to identify BET BD1-selective inhibitors of specific chirality with high potency, stability, and good cellular activity. Our findings highlight the robustness and efficiency of the DECL platform to identify specific, potent protein binders that have promise as potential anticancer and anti-inflammatory agents and as male contraceptives.

BRDT, BRD2, BRD3, and BRD4 comprise the bromodomain and extraterminal (BET) subfamily which contain two similar tandem bromodomains (BD1 and BD2). Selective BD1 inhibition phenocopies effects of tandem BET BD inhibition both in cancer models and, as we and others have reported of BRDT, in the testes. To find novel BET BD1 binders, we screened >4.5 billion molecules from our DNA-encoded chemical libraries with BRDT-BD1 or BRDT-BD2 proteins in parallel. A compound series enriched only by BRDT-BD1 was resynthesized off-DNA, uncovering a potent chiral compound, CDD-724, with >2,000-fold selectivity for inhibiting BRDT-BD1 over BRDT-BD2. CDD-724 stereoisomers exhibited remarkable differences in inhibiting BRDT-BD1, with the R-enantiomer (CDD-787) being 50-fold more potent than the S-enantiomer (CDD-786). From structure–activity relationship studies, we produced CDD-956, which maintained picomolar BET BD1 binding potency and high selectivity over BET BD2 proteins and had improved stability in human liver microsomes over CDD-787. BROMOscan profiling confirmed the excellent pan-BET BD1 affinity and selectivity of CDD-787 and CDD-956 on BD1 versus BD2 and all other BD-containing proteins. A cocrystal structure of BRDT-BD1 bound with CDD-956 was determined at 1.82 Å and revealed BRDT-BD1–specific contacts with the αZ and αC helices that explain the high affinity and selectivity for BET BD1 versus BD2. CDD-787 and CDD-956 maintain cellular BD1-selectivity in NanoBRET assays and show potent antileukemic activity in acute myeloid leukemia cell lines. These BET BD1-specific and highly potent compounds are structurally unique and provide insight into the importance of chirality to achieve BET specificity.

Recent advances in DNA-encoded dynamic libraries

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

Strategies for developing DNA-encoded libraries beyond binding assays

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

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.

Understanding Data Noise and Uncertainty through Analysis of Replicate Samples in DNA-Encoded Library Selection

By analyzing data sets of replicate DNA-Encoded Library (DEL) selections, an approach for estimating the noise level of the experiment has been developed. Using a logarithm transformation of the number of counts associated with each compound and a subset of compounds with the highest number of counts, it is possible to assess the quality of the data through normalizing the replicates and use this same data to estimate the noise in the experiment. The noise level is seen to be dependent on sequencing depth as well as specific selection conditions. The noise estimation is independent of any cutoff used to remove low frequency compounds from the data analysis. The removal of compounds with only 1-5 read counts greatly reduces some of the challenges encountered in DEL data analysis as it can reduce the data set by greater than 100-fold without impacting the interpretation of the results.

Design and construction of a stereochemically diverse piperazine-based DNA-encoded chemical library

Here we report the successful construction of a novel, stereochemically diverse DNA-Encoded Chemical Library (DECL) by utilizing 24 enantiomerically pure trifunctional 2, 6- di-substituted piperazines as central cores. We introduce the concept of positional diversity by placing the DNA attachment at either of two possible sites on the piperazine scaffold. Using a wide range of building blocks, a diverse library of 77 million compounds was produced. Cheminformatic analysis demonstrates that this library occupies a wide swath of chemical space, and that the piperazine scaffolds confers different shape diversity compared to the commonly used triazine core.

DNA-encoded chemistry technology yields expedient access to SARS-CoV-2 Mpro inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed more than 4 million humans globally, but there is no bona fide Food and Drug Administration-approved drug-like molecule to impede the COVID-19 pandemic. The sluggish pace of traditional therapeutic discovery is poorly suited to producing targeted treatments against rapidly evolving viruses. Here, we used an affinity-based screen of 4 billion DNA-encoded molecules en masse to identify a potent class of virus-specific inhibitors of the SARS-CoV-2 main protease (M^pro) without extensive and time-consuming medicinal chemistry. CDD-1714, the initial three-building-block screening hit (molecular weight [MW] = 542.5 g/mol), was a potent inhibitor (inhibition constant [K _i] = 20 nM). CDD-1713, a smaller two-building-block analog (MW = 353.3 g/mol) of CDD-1714, is a reversible covalent inhibitor of M^pro (K _i = 45 nM) that binds in the protease pocket, has specificity over human proteases, and shows in vitro efficacy in a SARS-CoV-2 infectivity model. Subsequently, key regions of CDD-1713 that were necessary for inhibitory activity were identified and a potent (K _i = 37 nM), smaller (MW = 323.4 g/mol), and metabolically more stable analog (CDD-1976) was generated. Thus, screening of DNA-encoded chemical libraries can accelerate the discovery of efficacious drug-like inhibitors of emerging viral disease targets.

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.

Discovery and characterization of bromodomain 2-specific inhibitors of BRDT

There is no nonhormonal contraceptive pill for men, although hundreds of genes have been identified to play roles during spermatogenesis and fertilization in the male reproductive tract. To address the absence of contraceptive drugs for men, we established a DNA-encoded chemistry technology (DEC-Tec) platform. Our drug discovery campaign on BRDT, a validated spermatogenic-specific contraceptive target, yielded rapid discovery of potent and specific inhibitors of the second bromodomain of BRDT that have unique binding characteristics to BRDT-BD2 relative to BRDT-BD1. Our study emphasizes the robustness and validation of the DEC-Tec platform where the obtained structure–affinity relationship data would allow us to identify specific protein binders immediately without performing exhaustive medicinal chemistry optimization of compounds with potential as male contraceptives.

Bromodomain testis (BRDT), a member of the bromodomain and extraterminal (BET) subfamily that includes the cancer targets BRD2, BRD3, and BRD4, is a validated contraceptive target. All BET subfamily members have two tandem bromodomains (BD1 and BD2). Knockout mice lacking BRDT-BD1 or both bromodomains are infertile. Treatment of mice with JQ1, a BET BD1/BD2 nonselective inhibitor with the highest affinity for BRD4, disrupts spermatogenesis and reduces sperm number and motility. To assess the contribution of each BRDT bromodomain, we screened our collection of DNA-encoded chemical libraries for BRDT-BD1 and BRDT-BD2 binders. High-enrichment hits were identified and resynthesized off-DNA and examined for their ability to compete with JQ1 in BRDT and BRD4 bromodomain AlphaScreen assays. These studies identified CDD-1102 as a selective BRDT-BD2 inhibitor with low nanomolar potency and >1,000-fold selectivity over BRDT-BD1. Structure–activity relationship studies of CDD-1102 produced a series of additional BRDT-BD2/BRD4-BD2 selective inhibitors, including CDD-1302, a truncated analog of CDD-1102 with similar activity, and CDD-1349, an analog with sixfold selectivity for BRDT-BD2 versus BRD4-BD2. BROMOscan bromodomain profiling confirmed the great affinity and selectivity of CDD-1102 and CDD-1302 on all BET BD2 versus BD1 with the highest affinity for BRDT-BD2. Cocrystals of BRDT-BD2 with CDD-1102 and CDD-1302 were determined at 2.27 and 1.90 Å resolution, respectively, and revealed BRDT-BD2 specific contacts that explain the high affinity and selectivity of these compounds. These BD2-specific compounds and their binding to BRDT-BD2 are unique compared with recent reports and enable further evaluation of their nonhormonal contraceptive potential in vitro and in vivo.

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.

Normalization of DNA encoded library affinity selection results driven by high throughput sequencing and HPLC purification

The output of an affinity selection screening results in a huge amount of valuable data that, after conducting the appropriate analysis, lead to the correct identification of the compounds enriched in the target of interest. The approach chosen to perform these analyses has become a key step in the development of a successful DNA Encoded Library platform. In this paper, we describe the combination of High Performance Liquid Chromatography purification during the library production with the Next Generation Sequencing analysis of the libraries to assess the yield of the chemical reactions prior to the affinity selection. This process allows us, apart from achieving higher quality libraries, to enable a normalization analysis of the affinity selection output, thus minimizing the bias induced by the chemical yield of each reaction as a misleading factor within the analysis and subsequent compound short-listing for off-DNA synthesis.

Triaging of DNA-Encoded Library Selection Results by High-Throughput Resynthesis of DNA-Conjugate and Affinity Selection Mass Spectrometry

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

Toward the assembly and characterization of an encoded library hit confirmation platform: Bead-Assisted Ligand Isolation Mass Spectrometry (BALI-MS)

The ability to predict chemical structure from DNA sequence has to date been a necessary cornerstone of DNA-encoded library technology. DNA-encoded libraries (DELs) are typically screened by immobilized affinity selection and enriched library members are identified by counting the number of times an individual compound's sequence is observed in the resultant dataset. Those with high signal reads (DEL hits) are subsequently followed up through off-DNA synthesis of the predicted small molecule structures. However, hits followed-up in this manner often fail to translate to confirmed ligands. To address this low conversion rate of DEL hits to off-DNA ligands, we have developed an approach that eliminates the reliance on chemical structure prediction from DNA sequence. Here we describe our method of combining non-combinatorial resynthesis on-DNA following library procedures as a rapid means to assess the probable molecules attached to the DNA barcode. Furthermore, we apply our Bead-Assisted Ligand Isolation Mass Spectrometry (BALI-MS) technique to identify the true binders found within the mixtures of on-DNA synthesis products. Finally, we describe a Normalized Enrichment (NE) metric that allows for the quantitative assessment of affinity selection in these studies. We exemplify how this combined approach enables the identification of putative hit matter against a clinically relevant therapeutic target bisphosphoglycerate mutase, BPGM.

Bispecific Estrogen Receptor α Degraders Incorporating Novel Binders Identified Using DNA-Encoded Chemical Library Screening

Bispecific degraders (PROTACs) of ERα are expected to be advantageous over current inhibitors of ERα signaling (aromatase inhibitors/SERMs/SERDs) used to treat ER+ breast cancer. Information from DNA-encoded chemical library (DECL) screening provides a method to identify novel PROTAC binding features as the linker positioning, and binding elements are determined directly from the screen. After screening ∼120 billion DNA-encoded molecules with ERα WT and 3 gain-of-function (GOF) mutants, with and without estradiol to identify features that enrich ERα competitively, the off-DNA synthesized small molecule exemplar 7 exhibited nanomolar ERα binding, antagonism, and degradation. Click chemistry synthesis on an alkyne E3 ligase engagers panel and an azide variant of 7 rapidly generated bispecific nanomolar degraders of ERα, with PROTACs 18 and 21 inhibiting ER+ MCF7 tumor growth in a mouse xenograft model of breast cancer. This study validates this approach toward identifying novel bispecific degrader leads from DECL screening with minimal optimization.

Synthetic Studies toward DNA-Encoded Heterocycles Based on the On-DNA Formation of α,β-Unsaturated Ketones

Taking advantage of the diversity-oriented synthesis strategy with α,β-unsaturated carbonyl compounds, we have successfully established the DNA-compatible transformations for various heterocyclic scaffolds. The ring-closure reactions for pyrrole, pyrrolidine, pyrazole, pyrazoline, isoxazoline, pyridine, piperidine, cyclohexenone, and 5,8-dihydroimidazo[1,2-a]pyrimidine were elegantly demonstrated in a DNA-compatible format. These efforts paved the way for preparing DNA-encoded libraries with more extensive chemical space.

Selecting Approaches for Hit Identification and Increasing Options by Building the Efficient Discovery of Actionable Chemical Matter from DNA-Encoded Libraries

Over the past 20 years, the toolbox for discovering small-molecule therapeutic starting points has expanded considerably. Pharmaceutical researchers can now choose from technologies that, in addition to traditional high-throughput knowledge-based and diversity screening, now include the screening of fragment and fragment-like libraries, affinity selection mass spectrometry, and selection against DNA-encoded libraries (DELs). Each of these techniques has its own unique combination of advantages and limitations that makes them more, or less, suitable for different target classes or discovery objectives, such as desired mechanism of action. Layered on top of this are the constraints of the drug-hunters themselves, including budgets, timelines, and available platform capacity; each of these can play a part in dictating the hit identification strategy for a discovery program. In this article, we discuss some of the factors that we use to govern our building of a hit identification roadmap for a program and describe the increasing role that DELs are playing in our discovery strategy. Furthermore, we share our learning during our initial exploration of DEL and highlight the approaches we have evolved to maximize the value returned from DEL selections. Topics addressed include the optimization of library design and production, reagent validation, data analysis, and hit confirmation. We describe how our thinking in these areas has led us to build a DEL platform that has begun to deliver tractable matter to our global discovery portfolio.

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.

Denoising DNA Encoded Library Screens with Sparse Learning

DNA-encoded libraries (DELs) are large, pooled collections of compounds in which every library member is attached to a stretch of DNA encoding its complete synthetic history. DEL-based hit discovery involves affinity selection of the library against a protein of interest, whereby compounds retained by the target are subsequently identified by next-generation sequencing of the corresponding DNA tags. When analyzing the resulting data, one typically assumes that sequencing output (i.e., read counts) is proportional to the binding affinity of a given compound, thus enabling hit prioritization and elucidation of any underlying structure-activity relationships (SAR). This assumption, though, tends to be severely confounded by a number of factors, including variable reaction yields, presence of incomplete products masquerading as their intended counterparts, and sequencing noise. In practice, these confounders are often ignored, potentially contributing to low hit validation rates, and universally leading to loss of valuable information. To address this issue, we have developed a method for comprehensively denoising DEL selection outputs. Our method, dubbed "deldenoiser", is based on sparse learning and leverages inputs that are commonly available within a DEL generation and screening workflow. Using simulated and publicly available DEL affinity selection data, we show that "deldenoiser" is not only able to recover and rank true binders much more robustly than read count-based approaches but also that it yields scores, which accurately capture the underlying SAR. The proposed method can, thus, be of significant utility in hit prioritization following DEL screens.

Discovery of potent thrombin inhibitors from a protease-focused DNA-encoded chemical library

To rapidly identify small-molecule lead compounds to target healthcare-associated proteases, we constructed a unique 9.8-million-membered protease-focused DNA-encoded chemical library. Affinity selection of this library with a healthcare-relevant protease (i.e., thrombin, a key protein necessary for blood coagulation) revealed potent inhibitors in the first screening attempt. Our results emphasize the utility of a structurally focused DNA-encoded chemical library approach to rapidly uncover hits for healthcare targets (e.g., proteases) where no drug exists (e.g., male contraception) and for emerging diseases (e.g., coronavirus disease 2019).

DNA-encoded chemical libraries are collections of compounds individually coupled to unique DNA tags serving as amplifiable identification barcodes. By bridging split-and-pool combinatorial synthesis with the ligation of unique encoding DNA oligomers, million- to billion-member libraries can be synthesized for use in hundreds of healthcare target screens. Although structural diversity and desirable molecular property ranges generally guide DNA-encoded chemical library design, recent reports have highlighted the utility of focused DNA-encoded chemical libraries that are structurally biased for a class of protein targets. Herein, a protease-focused DNA-encoded chemical library was designed that utilizes chemotypes known to engage conserved catalytic protease residues. The three-cycle library features functional moieties such as guanidine, which interacts strongly with aspartate of the protease catalytic triad, as well as mild electrophiles such as sulfonamide, urea, and carbamate. We developed a DNA-compatible method for guanidinylation of amines and reduction of nitriles. Employing these optimized reactions, we constructed a 9.8-million-membered DNA-encoded chemical library. Affinity selection of the library with thrombin, a common protease, revealed a number of enriched features which ultimately led to the discovery of a 1 nM inhibitor of thrombin. Thus, structurally focused DNA-encoded chemical libraries have tremendous potential to find clinically useful high-affinity hits for the rapid discovery of drugs for targets (e.g., proteases) with essential functions in infectious diseases (e.g., severe acute respiratory syndrome coronavirus 2) and relevant healthcare conditions (e.g., male contraception).

Solution-Phase DNA-Compatible Pictet-Spengler Reaction Aided by Machine Learning Building Block Filtering

The application of machine learning toward DNA encoded library (DEL) technology is lacking despite obvious synergy between these two advancing technologies. Herein, a machine learning algorithm has been developed that predicts the conversion rate for the DNA-compatible reaction of a building block with a model DNA-conjugate. We exemplify the value of this technique with a challenging reaction, the Pictet-Spengler, where acidic conditions are normally required to achieve the desired cyclization between tryptophan and aldehydes to provide tryptolines. This is the first demonstration of using a machine learning algorithm to cull potential building blocks prior to their purchase and testing for DNA-encoded library synthesis. Importantly, this allows for a challenging reaction, with an otherwise very low building block pass rate in the test reaction, to still be used in DEL synthesis. Furthermore, because our protocol is solution phase it is directly applicable to standard plate-based DEL synthesis.

Identifying Oxacillinase-48 Carbapenemase Inhibitors Using DNA-Encoded Chemical Libraries

Bacterial resistance to β-lactam antibiotics is largely mediated by β-lactamases, which catalyze the hydrolysis of these drugs and continue to emerge in response to antibiotic use. β-Lactamases that hydrolyze the last resort carbapenem class of β-lactam antibiotics (carbapenemases) are a growing global health threat. Inhibitors have been developed to prevent β-lactamase-mediated hydrolysis and restore the efficacy of these antibiotics. However, there are few inhibitors available for problematic carbapenemases such as oxacillinase-48 (OXA-48). A DNA-encoded chemical library approach was used to rapidly screen for compounds that bind and potentially inhibit OXA-48. Using this approach, a hit compound, CDD-97, was identified with submicromolar potency (Ki = 0.53 ± 0.08 μM) against OXA-48. X-ray crystallography showed that CDD-97 binds noncovalently in the active site of OXA-48. Synthesis and testing of derivatives of CDD-97 revealed structure-activity relationships and informed the design of a compound with a 2-fold increase in potency. CDD-97, however, synergizes poorly with β-lactam antibiotics to inhibit the growth of bacteria expressing OXA-48 due to poor accumulation into E. coli. Despite the low in vivo activity, CDD-97 provides new insights into OXA-48 inhibition and demonstrates the potential of using DNA-encoded chemistry technology to rapidly identify β-lactamase binders and to study β-lactamase inhibition, leading to clinically useful inhibitors.

Comparative evaluation of DNA-encoded chemical selections performed using DNA in single-stranded or double-stranded format

DNA-encoded chemical libraries (DEL) are increasingly being used for the discovery and optimization of small organic ligands to proteins of biological or pharmaceutical interest. The DNA fragments, that serve as amplifiable identification barcodes for individual compounds in the library, are typically used in double-stranded DNA format. To the best of our knowledge, a direct comparison of DEL selections featuring DNA in either single- or double-stranded DNA format has not yet been reported. In this article, we describe a comparative evaluation of selections with two DEL libraries (named GB-DEL and NF-DEL), based on different chemical designs and produced in both single- and double-stranded DNA format. The libraries were selected in identical conditions against multiple protein targets, revealing comparable and reproducible fingerprints for both types of DNA formats. Surprisingly, selections performed with single-stranded DNA barcodes exhibited improved enrichment factors compared to double-stranded DNA. Using high-affinity ligands to carbonic anhydrase IX as benchmarks for selection performance, we observed an improved selectivity for the NF-DEL library (on average 2-fold higher enrichment factors) in favor of single-stranded DNA. The enrichment factors were even higher for the GB-DEL selections (approximately 5-fold), compared to the same library in double-stranded DNA format. Collectively, these results indicate that DEL libraries can conveniently be synthesized and screened in both single- and double-stranded DNA format, but single-stranded DNA barcodes typically yield enhanced enrichment factors.

Serine protease inhibitor disrupts sperm motility leading to reduced fertility in female mice†

Inhibition of the sperm transport process in the female reproductive tract could lead to infertility. We previously showed that a pan-serine protease inhibitor, 4-(2-aminoethyl)benzenesulfonyl fluoride (AEBSF), blocked semen liquefaction in vivo and resulted in a drastic decrease in the number of sperm in the oviduct of female mice. In this study, we used a mouse model to test the efficacy of AEBSF as a reversible contraceptive, a sperm motility inhibitor, and a spermicide. Additionally, this study evaluated the toxicity of AEBSF on mouse vaginal tissues in vivo and human endocervical cells in vitro. We found that female mice treated with AEBSF had significantly less pups born per litter as well as fertilization rates in vivo compared to the vehicle control. We then showed that AEBSF reduced sperm motility and fertilization capability in vitro in a dose-dependent manner. Furthermore, AEBSF also exhibited spermicidal effects. Lastly, AEBSF treatment in female mice for 10 min or 3 consecutive days did not alter vaginal cell viability in vivo, similar to that of the vehicle and non-treated controls. However, AEBSF decreased cell viability of human ectocervical (ECT) cell line in vitro, suggesting that cells in the lower reproductive tract in mice and humans responded differently to AEBSF. In summary, our study showed that AEBSF can be used as a prototype compound for the further development of novel non-hormonal contraceptives for women by targeting sperm transport in the female reproductive tract.

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

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

Discovery of PqsE Thioesterase Inhibitors for Pseudomonas aeruginosa Using DNA-Encoded Small Molecule Library Screening

Pseudomonas aeruginosa is a leading cause of hospital-acquired infections in the United States. PqsE, a thioesterase enzyme, is vital for virulence of P. aeruginosa, making PqsE an attractive target for inhibition. Neither the substrate nor the product of PqsE catalysis has been identified. A library of 550 million DNA-encoded drug-like small molecules was screened for those that bind to the purified PqsE protein. The structures of the bound molecules were identified by high throughput sequencing of the attached DNA barcodes. Putative PqsE binders with the strongest affinity features were examined for inhibition of PqsE thioesterase activity in vitro. The most potent inhibitors were resynthesized off DNA and examined for the ability to alter PqsE thermal melting and for PqsE thioesterase inhibition. Here, we report the synthesis, biological activity, mechanism of action, and early structure-activity relationships of a series of 2-(phenylcarbamoyl)benzoic acids that noncompetitively inhibit PqsE. A small set of analogs designed to probe initial structure-activity relationships showed increases in potency relative to the original hits, the best of which has an IC₅₀ = 5 μM. Compound refinement is required to assess their in vivo activities as the current compounds do not accumulate in the P. aeruginosa cytosol. Our strategy validates DNA-encoded compound library screening as a rapid and effective method to identify catalytic inhibitors of the PqsE protein, and more generally, for discovering binders to bacterial proteins revealed by genetic screening to have crucial in vivo activities but whose biological functions have not been well-defined.

Evolving a Peptide: Library Platforms and Diversification Strategies

Peptides are widely used in pharmaceutical industry as active pharmaceutical ingredients, versatile tools in drug discovery, and for drug delivery. They find themselves at the crossroads of small molecules and proteins, possessing favorable tissue penetration and the capability to engage into specific and high-affinity interactions with endogenous receptors. One of the commonly employed approaches in peptide discovery and design is to screen combinatorial libraries, comprising a myriad of peptide variants of either chemical or biological origin. In this review, we focus mainly on recombinant peptide libraries, discussing different platforms for their display or expression, and various diversification strategies for library design. We take a look at well-established technologies as well as new developments and future directions.

On-DNA Decarboxylative Arylation: Merging Photoredox with Nickel Catalysis in Water

A new catalytic manifold that merges photoredox with nickel catalysis in aqueous solution is presented. Specifically, the combination of a highly active, yet air-stable, nickel precatalyst with a new electron-deficient pyridyl carboxamidine ligand was key to the development of a water-compatible nickel catalysis platform, which is a crucial requirement for the preparation of DNA-encoded libraries (DELs). Together with an iridium-based photocatalyst and a powerful light source, this dual catalysis approach enabled the efficient decarboxylative arylation of α-amino acids with DNA-tagged aryl halides. This C(sp²)-C(sp³) coupling tolerates a wide variety of functional groups on both the amino acid and the aryl halide substrates. Due to the mild and DNA-compatible reaction conditions, the presented transformation holds great potential for the construction of DELs. This was further evidenced by showing that well plate-compatible LED arrays can serve as competent light sources to facilitate parallel synthesis. Lastly, we demonstrate that this procedure can serve as a blueprint toward the adaptation of other established nickel metallaphotoredox transformations to the idiosyncratic requirements of a DEL.

Palladium-Catalyzed Hydroxycarbonylation of (Hetero)aryl Halides for DNA-Encoded Chemical Library Synthesis

A strategy for DNA-compatible, palladium-catalyzed hydroxycarbonylation of (hetero)aryl halides on DNA–chemical conjugates has been developed. This method generally provided the corresponding carboxylic acids in moderate to very good conversions for (hetero)aryl iodides and bromides, and in poor to moderate conversions for (hetero)aryl chlorides. These conditions were further validated by application within a DNA-encoded chemical library synthesis and subsequent discovery of enriched features from the library in selection experiments against two protein targets.

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.

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.

A Mild, DNA-Compatible Nitro Reduction Using B2(OH)4

A hypodiboric acid system for the reduction of nitro groups on DNA–chemical conjugates has been developed. This transformation provided good to excellent yields of the reduced amine product for a variety of functionalized aromatic, heterocyclic, and aliphatic nitro compounds. DNA tolerance to reaction conditions, extension to decigram scale reductions, successful use in a DNA-encoded chemical library synthesis, and subsequent target selection are also described.