DNA-Encoded Chemical Libraries: A Selection System Based on Endowing Organic Compounds with Amplifiable Information

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

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

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

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

Targeting fusion oncoproteins in childhood cancers: challenges and future opportunities for developing therapeutics

Fusion oncoproteins are associated with childhood cancers and have proven challenging to target, aside from those that include kinases. As part of its efforts for targeting childhood cancers, the National Cancer Institute recently conducted a series on Novel Chemical Approaches for Targeting Fusion Oncoproteins. Key learnings on leading platforms and technologies that can be used to advance the development of molecular therapeutics that target fusion oncoproteins in childhood cancers are described. Recent breakthroughs in medicinal chemistry and chemical biology provide new ground and creative strategies to exploit for the development of targeted agents for improving outcomes against these recalcitrant cancers.

Employing unnatural promiscuity of sortase to construct peptide macrocycle libraries for ligand discovery

With the increasing attention paid to macrocyclic scaffolds in peptide drug development, genetically encoded peptide macrocycle libraries have become invaluable sources for the discovery of high-affinity peptide ligands targeting disease-associated proteins. The traditional phage display technique of constructing disulfide-tethered macrocycles by cysteine oxidation has the inherent drawback of reduction instability of the disulfide bond. Chemical macrocyclization solves the problem of disulfide bond instability, but the involved highly electrophilic reagents are usually toxic to phages and may bring undesirable side reactions. Here, we report a unique Sortase-mediated Peptide Ligation and One-pot Cyclization strategy (SPLOC) to generate peptide macrocycle libraries, avoiding the undesired reactions of electrophiles with phages. The key to this platform is to mine the unnatural promiscuity of sortase on the X residue of the pentapeptide recognition sequence (LPXTG). Low reactive electrophiles are incorporated into the X-residue side chain, enabling intramolecular cyclization with the cysteine residue of the phage-displayed peptide library. Utilizing the genetically encoded peptide macrocycle library constructed by the SPLOC platform, we found a high-affinity bicyclic peptide binding TEAD4 with a nanomolar KD value (63.9 nM). Importantly, the binding affinity of the bicyclic peptide ligand is 102-fold lower than that of the acyclic analogue. To our knowledge, this is the first time to mine the unnatural promiscuity of ligases to generate peptide macrocycles, providing a new avenue for the construction of genetically encoded cyclic peptide libraries.

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.

A detection system using sensing motif-tethered oligodeoxynucleotides for multiplex biomolecular analysis

We developed a system to detect multiple target biomolecules through sensing motif-tethered oligodeoxynucleotides. DNA-based molecular probes gave the primary amine motif upon reaction with the target biomolecules, glutathione (GSH) and H2O2. After labelling with biotin, the product DNAs were selectively collected to be quantified by qPCR.

Hydrophobic Surfactant-DNA Complex (Surf-DNA) Enables DNA-Encoded-Library-Compatible Decarboxylative Arylation under Anhydrous Conditions

DNA-encoded libraries (DELs) are a key technology for identifying small-molecule hits in both the pharmaceutical industry and academia, but their chemical diversity is largely limited to water-compatible reactions to aid in the solubility and integrity of encoding DNA tags. To broaden the DEL chemical space, we present a workflow utilizing DNA-cationic surfactant complexation that enables dissolution and reactions on-DNA in anhydrous organic solvents. We demonstrate its utility by developing DEL-compatible photoredox decarboxylative C(sp2)-C(sp3) coupling under water-free conditions. The workflow is optimized for the 96-well format necessary for large-scale DEL productions, and it enables screening and optimization of DEL-compatible reactions in organic solvents.

Silica Nanowires-Filled Glass Microporous Sensor for the Ultrasensitive Detection of Deoxyribonucleic Acid

DNA carries genetic information and can serve as an important biomarker for the early diagnosis and assessment of the disease prognosis. Here, we propose a bottom-up assembly method for a silica nanowire-filled glass microporous (SiNWs@GMP) sensor and develop a universal sensing platform for the ultrasensitive and specific detection of DNA. The three-dimensional network structure formed by SiNWs provides them with highly abundant and accessible binding sites, allowing for the immobilization of a large amount of capture probe DNA, thereby enabling more target DNA to hybridize with the capture probe DNA to improve detection performance. Therefore, the SiNWs@GMP sensor achieves ultrasensitive detection of target DNA. In the detection range of 1 aM to 100 fM, there is a good linear relationship between the decrease rate of current signal and the concentration of target DNA, and the detection limit is as low as 1 aM. The developed SiNWs@GMP sensor can distinguish target DNA sequences that are 1-, 3-, and 5-mismatched, and specifically recognize target DNA from complex mixed solution. Furthermore, based on this excellent selectivity and specificity, we validate the universality of this sensing strategy by detecting DNA (H1N1 and H5N1) sequences associated with the avian influenza virus. By replacing the types of nucleic acid aptamers, it is expected to achieve a wide range and low detection limit sensitive detection of various biological molecules. The results indicate that the developed universal sensing platform has ultrahigh sensitivity, excellent selectivity, stability, and acceptable reproducibility, demonstrating its potential application in DNA bioanalysis.

Carbohydrate-DNA Conjugation Enabled by Glycosyl Radicals Generated from Glycosyl Sulfinates

Herein, we report a method that enables the synthesis of carbohydrate-DNA conjugates by radical addition. Key to the success is the use of readily available, bench-stable, and unprotected glycosyl sulfinates as precursors to glycosyl radicals. The redox neutral reaction proceeds under mild and simple conditions and tolerates a broad substrate scope. A small library of carbohydrate-DNA conjugates was prepared.

Selection of Leptin Surrogates by a General Phenotypic Screening Method for Receptor Agonists

There is a high demand for agonist biomolecules such as cytokine surrogates in both biological and medicinal research fields. These are typically sourced through natural ligand engineering or affinity-based screening, followed by individual functional validation. However, efficient screening methods for identifying rare hits within immense libraries are very limited. In this research article, we introduce a phenotypic screening method utilizing biological receptor activation-dependent cell survival (BRADS). This method offers a high-throughput, low-background, and cost-effective approach that can be implemented in virtually any biochemical laboratory setting. As a proof-of-concept, we successfully identified a surrogate for human leptin following a two-week cell culture process, without the need for specialized high-throughput equipment or reagents. This surrogate effectively emulates the activity of native human leptin in cell validation assays. Our findings not only underscore the effectiveness of BRADS but also suggest its potential applicability to a broad range of biological receptors, including Notch and GPCRs.

Bioinspired Selenium-Nitrogen Exchange (SeNEx) Click Chemistry Suitable for Nanomole-Scale Medicinal Chemistry and Bioconjugation

Click chemistry is a powerful molecular assembly strategy for rapid functional discovery. The development of click reactions with new connecting linkage is of great importance for expanding the click chemistry toolbox. We report the first selenium-nitrogen exchange (SeNEx) click reaction between benzoselenazolones and terminal alkynes (Se-N to Se-C), which is inspired by the biochemical SeNEx between Ebselen and cysteine (Cys) residue (Se-N to Se-S). The formed selenoalkyne connection is readily elaborated, thus endowing this chemistry with multidimensional molecular diversity. Besides, this reaction is modular, predictable, and high-yielding, features fast kinetics (k2≥14.43 M-1 s-1), excellent functional group compatibility, and works well at miniaturization (nanomole-scale), opening up many interesting opportunities for organo-Se synthesis and bioconjugation, as exemplified by sequential click chemistry (coupled with ruthenium-catalyzed azide-alkyne cycloaddition (RuAAC) and sulfur-fluoride exchange (SuFEx)), selenomacrocycle synthesis, nanomole-scale synthesis of Se-containing natural product library and DNA-encoded library (DEL), late-stage peptide modification and ligation, and multiple functionalization of proteins. These results indicated that SeNEx is a useful strategy for new click chemistry developments, and the established SeNEx chemistry will serve as a transformative platform in multidisciplinary fields such as synthetic chemistry, material science, chemical biology, medical chemistry, and drug discovery.

Protein-templated ligand discovery via the selection of DNA-encoded dynamic libraries

DNA-encoded chemical libraries (DELs) have become a powerful technology platform in drug discovery. Dual-pharmacophore DELs display two sets of small molecules at the termini of DNA duplexes, thereby enabling the identification of synergistic binders against biological targets, and have been successfully applied in fragment-based ligand discovery and affinity maturation of known ligands. However, dual-pharmacophore DELs identify separate binders that require subsequent linking to obtain the full ligands, which is often challenging. Here we report a protein-templated DEL selection approach that can identify full ligand/inhibitor structures from DNA-encoded dynamic libraries (DEDLs) without the need for subsequent fragment linking. Our approach is based on dynamic DNA hybridization and target-templated in situ ligand synthesis, and it incorporates and encodes the linker structures in the library, along with the building blocks, to be sampled by the target protein. To demonstrate the performance of this method, 4.35-million- and 3.00-million-member DEDLs with different library architectures were prepared, and hit selection was achieved against four therapeutically relevant target proteins.

Catalytic Protein Inhibitors

Many of the highest priority targets in a wide range of disease states are difficult-to-drug proteins. The development of reversible small molecule inhibitors for the active sites of these proteins with sufficient affinity and residence time on-target is an enormous challenge. This has engendered interest in strategies to increase the potency of a given protein inhibitor by routes other than further improvement in gross affinity. Amongst these, the development of catalytic protein inhibitors has garnered the most attention and investment, particularly with respect to protein degraders, which catalyze the destruction of the target protein. This article discusses the genesis of the burgeoning field of catalytic inhibitors, the current state of the art, and exciting future directions.

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.

Asymmetry of Dual-Display DNA-Encoded Chemical Libraries

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

Evolution of chemistry and selection technology for DNA-encoded library

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

Mask and Release Strategy-Enabled Diversity-Oriented Synthesis for DNA-Encoded Library

An ideal DNA-encoded library (DEL) selection requires the library to consist of diverse core skeletons and cover chemical space as much as possible. However, the lack of efficient on-DNA synthetic approaches toward core skeletons has greatly restricted the diversity of DEL. To mitigate this issue, this work disclosed a "Mask & Release" strategy to streamline the challenging on-DNA core skeleton synthesis. N-phenoxyacetamide is used as a masked phenol and versatile directing group to mediate diversified DNA-compatible C-H functionalization, introducing the 1st-dimensional diversity at a defined site, and simultaneously releasing the phenol functionality, which can facilitate the introduction of the 2nd diversity. This work not only provides a set of efficient syntheses toward DNA-conjugated drug-like core skeletons such as ortho-alkenyl/sulfiliminyl/cyclopropyl phenol, benzofuran, dihydrobenzofuran but also provides a paradigm for on-DNA core skeleton synthetic method development.

On-DNA hydroalkylation of N-vinyl heterocycles via photoinduced EDA-complex activation

The emergence of DNA-encoded library (DEL) technology has provided a considerable advantage to the pharmaceutical industry in the pursuit of discovering novel therapeutic candidates for their drug development initiatives. This combinatorial technique not only offers a more economical, spatially efficient, and time-saving alternative to the existing ligand discovery methods, but also enables the exploration of additional chemical space by utilizing novel DNA-compatible synthetic transformations to leverage multifunctional building blocks from readily available substructures. In this report, a decarboxylative-based hydroalkylation of DNA-conjugated N-vinyl heterocycles enabled by single-electron transfer (SET) and subsequent hydrogen atom transfer through electron-donor/electron-acceptor (EDA) complex activation is detailed. The simplicity and robustness of this method permits inclusion of a broad array of alkyl radical precursors and DNA-tethered nitrogenous heterocyles to generate medicinally relevant substituted heterocycles with pendant functional groups. Moreover, a successful telescoped route provides the opportunity to access a broad range of intricate structural scaffolds by employing basic carboxylic acid feedstocks.

ABPP-CoDEL: Activity-Based Proteome Profiling-Guided Discovery of Tyrosine-Targeting Covalent Inhibitors from DNA-Encoded Libraries

DNA-encoded chemical library (DEL) has been extensively used for lead compound discovery for decades in academia and industry. Incorporating an electrophile warhead into DNA-encoded compounds recently permitted the discovery of covalent ligands that selectively react with a particular cysteine residue. However, noncysteine residues remain underexplored as modification sites of covalent DELs. Herein, we report the design and utility of tyrosine-targeting DELs of 67 million compounds. Proteome-wide reactivity analysis of tyrosine-reactive sulfonyl fluoride (SF) covalent probes suggested three enzymes (phosphoglycerate mutase 1, glutathione s-transferase 1, and dipeptidyl peptidase 3) as models of tyrosine-targetable proteins. Enrichment with SF-functionalized DELs led to the identification of a series of tyrosine-targeting covalent inhibitors of the model enzymes. In-depth mechanistic investigation revealed their novel modes of action and reactive ligand-accessible hotspots of the enzymes. Our strategy of combining activity-based proteome profiling and covalent DEL enrichment (ABPP-CoDEL), which generated selective covalent binders against a variety of target proteins, illustrates the potential use of this methodology in further covalent drug discovery.

Comparative Study of DNA Barcode Integrity Evaluation Approaches in the Early-Stage Development of DNA-Compatible Chemical Transformation

DNA-encoded libraries (DEL) have emerged as an important drug discovery technical platform for target-based compound library selection. The success rate of DEL depends on both the chemical diversity of combinatorial libraries and the accuracy of DNA barcoding. Therefore, it is critical that the chemistry applied to library construction should efficiently transform on a wide range of substrates while preserving the integrity of DNA tags. Although several analytical methods have been developed to measure DNA damage caused by DEL chemical reactions, efficient and cost-effective evaluation criteria for DNA damage detection are still demanding. Herein, we set standards for evaluating the DNA compatibility of chemistry development at the laboratory level. Based on four typical DNA damage models of three different DEL formats, we evaluated the detection capabilities of four analytical methods, including ultraperformance liquid chromatography (UPLC-MS), electrophoresis, quantitative polymerase chain reaction (qPCR), and Sanger sequencing. This work systematically revealed the scope and capability of different analytical methods in assessing DNA damages caused by chemical transformation. Based on the results, we recommended UPLC-MS and qPCR as efficient methods for DNA barcode integrity analysis in the early-stage development of DNA-compatible chemistry. Meanwhile, we identified that Sanger sequencing was unreliable to assess DNA damage in this application.

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

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

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

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

Precision Oncology Comes of Age: Designing Best-in-Class Small Molecules by Integrating Two Decades of Advances in Chemistry, Target Biology, and Data Science

Small-molecule drugs have enabled the practice of precision oncology for genetically defined patient populations since the first approval of imatinib in 2001. Scientific and technology advances over this 20-year period have driven the evolution of cancer biology, medicinal chemistry, and data science. Collectively, these advances provide tools to more consistently design best-in-class small-molecule drugs against known, previously undruggable, and novel cancer targets. The integration of these tools and their customization in the hands of skilled drug hunters will be necessary to enable the discovery of transformational therapies for patients across a wider spectrum of cancers.

SIGNIFICANCE

Target-centric small-molecule drug discovery necessitates the consideration of multiple approaches to identify chemical matter that can be optimized into drug candidates. To do this successfully and consistently, drug hunters require a comprehensive toolbox to avoid following the "law of instrument" or Maslow's hammer concept where only one tool is applied regardless of the requirements of the task. Combining our ever-increasing understanding of cancer and cancer targets with the technological advances in drug discovery described below will accelerate the next generation of small-molecule drugs in oncology.

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

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

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

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

Small-molecule discovery through DNA-encoded libraries

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

DNA-Compatible Copper/TEMPO Oxidation for DNA-Encoded Libraries

Aldehydes are important synthons for DNA-encoded library (DEL) construction, but the development of a DNA-compatible method for the oxidation of alcohols to aldehydes remains a significant challenge in the field of DEL chemistry. We report that a copper/TEMPO catalyst system enables the solution-phase DNA-compatible oxidation of DNA-linked primary activated alcohols to aldehydes. The semiaqueous, room-temperature reaction conditions afford oxidation of benzylic, heterobenzylic, and allylic alcohols in high yield, with DNA compatibility verified by mass spectrometry, qPCR, Sanger sequencing, and ligation assays. Subsequent transformations of the resulting aldehydes demonstrate the potential of this method for robust library diversification.

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

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

Enolate-Azide [3 + 2]-Cycloaddition Reaction Suitable for DNA-Encoded Library Synthesis

The DNA-encoded chemical library (DEL) is a powerful hit selection technique in either basic science or innovative drug discovery. With the aim to circumvent the issue concerning DNA barcode damage in a conventional on-DNA copper-catalyzed azide-alkyne cycloaddition reaction (CuAAC), we have successfully developed the first DNA-compatible enolate-azide [3 + 2] cycloaddition reaction. The merits of this DEL chemistry include metal-free reaction and high DNA fidelity, high conversions and easy operation, broad substrate scope, and ready access to the highly substituted 1,4,5-trisubstituted triazoles. Thus, it will not only further enrich the DEL chemistry toolbox but also will have great potential in practical DEL synthesis.

Diversity-oriented synthesis encoded by deoxyoligonucleotides

Diversity-oriented synthesis (DOS) is a powerful strategy to prepare molecules with underrepresented features in commercial screening collections, resulting in the elucidation of novel biological mechanisms. In parallel to the development of DOS, DNA-encoded libraries (DELs) have emerged as an effective, efficient screening strategy to identify protein binders. Despite recent advancements in this field, most DEL syntheses are limited by the presence of sensitive DNA-based constructs. Here, we describe the design, synthesis, and validation experiments performed for a 3.7 million-member DEL, generated using diverse skeleton architectures with varying exit vectors and derived from DOS, to achieve structural diversity beyond what is possible by varying appendages alone. We also show screening results for three diverse protein targets. We will make this DEL available to the academic scientific community to increase access to novel structural features and accelerate early-phase drug discovery.

Fragment expansion with NUDELs - poised DNA-encoded libraries

Optimisation of the affinity of lead compounds is a critical challenge in the identification of drug candidates and chemical probes and is a process that takes many years. Fragment-based drug discovery has become established as one of the methods of choice for drug discovery starting with small, low affinity compounds. Due to their low affinity, the evolution of fragments to desirable levels of affinity is often a key challenge. The accepted best method for increasing the potency of fragments is by iterative fragment growing, which can be very time consuming and complex. Here, we introduce a paradigm for fragment hit optimisation using poised DNA-encoded chemical libraries (DELs). The synthesis of a poised DEL, a partially constructed library that retains a reactive handle, allows the coupling of any active fragment for a specific target protein, allowing rapid discovery of potent ligands. This is illustrated for bromodomain-containing protein 4 (BRD4), in which a weakly binding fragment was coupled to a 42-member poised DEL via Suzuki-Miyaura cross coupling resulting in the identification of an inhibitor with 51 nM affinity in a single step, representing an increase in potency of several orders of magnitude from an original fragment. The potency of the compound was shown to arise from the synergistic combination of substructures, which would have been very difficult to discover by any other method and was rationalised by X-ray crystallography. The compound showed attractive lead-like properties suitable for further optimisation and demonstrated BRD4-dependent cellular pharmacology. This work demonstrates the power of poised DELs to rapidly optimise fragments, representing an attractive generic approach to drug discovery.

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.

Identification of small-molecule protein-protein interaction inhibitors for NKG2D

NKG2D (natural-killer group 2, member D) is a homodimeric transmembrane receptor that plays an important role in NK, γδ+, and CD8+ T cell-mediated immune responses to environmental stressors such as viral or bacterial infections and oxidative stress. However, aberrant NKG2D signaling has also been associated with chronic inflammatory and autoimmune diseases, and as such NKG2D is thought to be an attractive target for immune intervention. Here, we describe a comprehensive small-molecule hit identification strategy and two distinct series of protein-protein interaction inhibitors of NKG2D. Although the hits are chemically distinct, they share a unique allosteric mechanism of disrupting ligand binding by accessing a cryptic pocket and causing the two monomers of the NKG2D dimer to open apart and twist relative to one another. Leveraging a suite of biochemical and cell-based assays coupled with structure-based drug design, we established tractable structure-activity relationships with one of the chemical series and successfully improved both the potency and physicochemical properties. Together, we demonstrate that it is possible, albeit challenging, to disrupt the interaction between NKG2D and multiple protein ligands with a single molecule through allosteric modulation of the NKG2D receptor dimer/ligand interface.

Computational approaches streamlining drug discovery

Computer-aided drug discovery has been around for decades, although the past few years have seen a tectonic shift towards embracing computational technologies in both academia and pharma. This shift is largely defined by the flood of data on ligand properties and binding to therapeutic targets and their 3D structures, abundant computing capacities and the advent of on-demand virtual libraries of drug-like small molecules in their billions. Taking full advantage of these resources requires fast computational methods for effective ligand screening. This includes structure-based virtual screening of gigascale chemical spaces, further facilitated by fast iterative screening approaches. Highly synergistic are developments in deep learning predictions of ligand properties and target activities in lieu of receptor structure. Here we review recent advances in ligand discovery technologies, their potential for reshaping the whole process of drug discovery and development, as well as the challenges they encounter. We also discuss how the rapid identification of highly diverse, potent, target-selective and drug-like ligands to protein targets can democratize the drug discovery process, presenting new opportunities for the cost-effective development of safer and more effective small-molecule treatments.

Protein-protein interfaces in molecular glue-induced ternary complexes: classification, characterization, and prediction

Molecular glues are a class of small molecules that stabilize the interactions between proteins. Naturally occurring molecular glues are present in many areas of biology where they serve as central regulators of signaling pathways. Importantly, several clinical compounds act as molecular glue degraders that stabilize interactions between E3 ubiquitin ligases and target proteins, leading to their degradation. Molecular glues hold promise as a new generation of therapeutic agents, including those molecular glue degraders that can redirect the protein degradation machinery in a precise way. However, rational discovery of molecular glues is difficult in part due to the lack of understanding of the protein-protein interactions they stabilize. In this review, we summarize the structures of known molecular glue-induced ternary complexes and the interface properties. Detailed analysis shows different mechanisms of ternary structure formation. Additionally, we also review computational approaches for predicting protein-protein interfaces and highlight the promises and challenges. This information will ultimately help inform future approaches for rational molecular glue discovery.

Abiotic peptides as carriers of information for the encoding of small-molecule library synthesis

Encoding small-molecule information in DNA has been leveraged to accelerate the discovery of ligands for therapeutic targets such as proteins. However, oligonucleotide-based encoding is hampered by inherent limitations of information stability and density. In this study, we establish abiotic peptides for next-generation information storage and apply them for the encoding of diverse small-molecule synthesis. The chemical stability of the peptide-based tag allows the use of palladium-mediated reactions to efficiently synthesize peptide-encoded libraries (PELs) with broad chemical diversity and high purity. We demonstrate the successful de novo discovery of small-molecule protein ligands from PELs by affinity selection against carbonic anhydrase IX and the oncogenic protein targets BRD4(1) and MDM2. Collectively, this work establishes abiotic peptides as carriers of information for the encoding of small-molecule synthesis, leveraged herein for the discovery of protein ligands.

DNA-Encoded Libraries: Towards Harnessing their Full Power with Darwinian Evolution

DNA-encoded library (DEL) technologies are transforming the drug discovery process, enabling the identification of ligands at unprecedented speed and scale. DEL makes use of libraries that are orders of magnitude larger than traditional high-throughput screens. While a DNA tag alludes to a genotype-phenotype connection that is exploitable for molecular evolution, most of the work in the field is performed with libraries where the tag serves as an amplifiable barcode but does not allow "translation" into the synthetic product it is linked to. In this Review, we cover technologies that enable the "translation" of the genetic tag into synthetic molecules, both biochemically and chemically, and explore how it can be used to harness Darwinian evolutionary pressure.

The Application of High-Throughput Approaches in Identifying Novel Therapeutic Targets and Agents to Treat Diabetes

During the past decades, unprecedented progress in technologies has revolutionized traditional research methodologies. Among these, advances in high-throughput drug screening approaches have permitted the rapid identification of potential therapeutic agents from drug libraries that contain thousands or millions of molecules. Moreover, high-throughput-based therapeutic target discovery strategies can comprehensively interrogate relationships between biomolecules (e.g., gene, RNA, and protein) and diseases and significantly increase the authors' knowledge of disease mechanisms. Diabetes is a chronic disease primarily characterized by the incapacity of the body to maintain normoglycemia. The prevalence of diabetes in modern society has become a severe public health issue that threatens the well-being of millions of patients. Although a number of pharmacological treatments are available, there is no permanent cure for diabetes, and discovering novel therapeutic targets and agents continues to be an urgent need. The present review discusses the technical details of high-throughput screening approaches in drug discovery, followed by introducing the applications of such approaches to diabetes research. This review aims to provide an example of the applicability of high-throughput technologies in facilitating different aspects of disease research.

Optimization of PROTAC Ternary Complex Using DNA Encoded Library Approach

The proteolysis targeting chimera (PROTAC) strategy results in the down-regulation of unwanted protein(s) for disease treatment. In the PROTAC process, a heterobifunctional degrader forms a ternary complex with a target protein of interest (POI) and an E3 ligase, which results in ubiquitination and proteasomal degradation of the POI. While ternary complex formation is a key attribute of PROTAC degraders, modification of the PROTAC molecule to optimize ternary complex formation and protein degradation can be a labor-intensive and tedious process. In this study, we take advantage of DNA-encoded library (DEL) technology to efficiently synthesize a vast number of possible PROTAC molecules and describe a parallel screening approach that utilizes DNA barcodes as reporters of ternary complex formation and cooperative binding. We use a designed PROTAC DEL against BRD4 and CRBN to describe a dual protein affinity selection method and the direct discovery of novel, potent BRD4 PROTACs that importantly demonstrate clear SAR. Such an approach evaluates all the potential PROTACs simultaneously, avoids the interference of PROTAC solubility and permeability, and uses POI and E3 ligase proteins in an efficient manner.

Photoredox-Mediated Deoxygenative Alkylation of DNA-Tagged Alkenes with Activated Alcohols

DNA-encoded library (DEL) screens have become a key technology to find small molecule binders to biological targets for drug discovery applications. The development of new DNA-compatible chemistries to expand the accessible DEL chemical space is imperative to enhance screen success across broad target classes and modalities. Additionally, reactions that use commonly available building blocks as well as those that enable the fsp³ of library members to be increased would have high impact for accessing diverse drug-like structures. Herein, we report a DNA-compatible Giese-type addition of nonstabilized C-centered radicals generated by the deoxygenation of preactivated alcohols into on-DNA olefins. Although alcohols have been historically underused as a building block class within DEL synthesis, their activation to a xanthate enables Csp³-Csp³ coupling to furnish sp³-rich products. This reaction is compatible with multiple classes of functional groups, does not damage the DNA tag, and is suitable for use in DEL productions.

Current strategies and progress for targeting the "undruggable" transcription factors

Transcription factors (TFs) specifically bind to DNA, recruit cofactor proteins and modulate target gene expression, rendering them essential roles in the regulation of numerous biological processes. Meanwhile, mutated or dysregulated TFs are involved in a variety of human diseases. As multiple signaling pathways ultimately converge at TFs, targeting these TFs directly may prove to be more specific and cause fewer side effects, than targeting the upfront conventional targets in these pathways. All these features together endue TFs with great potential and high selectivity as therapeutic drug targets. However, TFs have been historically considered "undruggable", mainly due to their lack of structural information, especially about the appropriate ligand-binding sites and protein-protein interactions, leading to relatively limited choices in the TF-targeting drug design. In this review, we summarize the recent progress of TF-targeting drugs and highlight certain strategies used for targeting TFs, with a number of representative drugs that have been approved or in the clinical trials as examples. Various approaches in targeting TFs directly or indirectly have been developed. Common direct strategies include aiming at defined binding pockets, proteolysis-targeting chimaera (PROTAC), and mutant protein reactivation. In contrast, the indirect ones comprise inhibition of protein-protein interactions between TF and other proteins, blockade of TF expression, targeting the post-translational modifications, and targeting the TF-DNA interactions. With more comprehensive structural information about TFs revealed by the powerful cryo-electron microscopy technology and predicted by machine-learning algorithms, plus more efficient compound screening platforms and a deeper understanding of TF-disease relationships, the development of TF-targeting drugs will certainly be accelerated in the near future.

Forty years of combinatorial technology

Combinatorial technology has been facilitating the synthesis and screening of large molecular libraries containing millions of organic compounds ever since its introduction 40 years ago. It has changed the paradigms of pharmaceutical research from focusing on single compounds to focusing on immense collections of compounds. It inspired the development of dynamic combinatorial libraries, fragment-based drug discovery and virtual library screening. Combinatorial technology was revitalized by the development of DNA encoding. Amplification of DNA oligomers plus next-generation sequencing has made it possible to successfully screen billions of compounds in a single process.

DNA Compatible Oxidization and Amidation of Terminal Alkynes

Through a modified Kinugasa reaction, a novel method of amidation on terminal oligo alkyne conjugates by copper-promoted oxidation with nitrones has been developed. Unprotected bifunctional carboxylic acid-amine reagents can be transformed directly to the respective amide products under these edited Kinugasa reaction conditions. 3-Cycle DNA-encoded libraries (DELs) can be built in three steps of chemical conversion.

Nonlinear manipulation and analysis of large DNA datasets

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

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

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