Beyond protein binding: recent advances in screening DNA-encoded libraries

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

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

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.

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.

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.

Building Block-Based Binding Predictions for DNA-Encoded Libraries

DNA-encoded libraries (DELs) provide the means to make and screen millions of diverse compounds against a target of interest in a single experiment. However, despite producing large volumes of binding data at a relatively low cost, the DEL selection process is susceptible to noise, necessitating computational follow-up to increase signal-to-noise ratios. In this work, we present a set of informatics tools to employ data from prior DEL screen(s) to gain information about which building blocks are most likely to be productive when designing new DELs for the same target. We demonstrate that similar building blocks have similar probabilities of forming compounds that bind. We then build a model from the inference that the combined behavior of individual building blocks is predictive of whether an overall compound binds. We illustrate our approach on a set of three-cycle OpenDEL libraries screened against soluble epoxide hydrolase (sEH) and report performance of more than an order of magnitude greater than random guessing on a holdout set, demonstrating that our model can serve as a baseline for comparison against other machine learning models on DEL data. Lastly, we provide a discussion on how we believe this informatics workflow could be applied to benefit researchers in their specific DEL campaigns.

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.

Synthesis of 6-Alkynylated Purine-Containing DNA via On-Column Sonogashira Coupling and Investigation of Their Base-Pairing Properties

Synthetic unnatural base pairs have been proven to be attractive tools for the development of DNA-based biotechnology. Our group has very recently reported on alkynylated purine-pyridazine pairs, which exhibit selective and stable base-pairing via hydrogen bond formation between pseudo-nucleobases in the major groove of duplex DNA. In this study, we attempted to develop an on-column synthesis methodology of oligodeoxynucleotides (ODNs) containing alkynylated purine derivatives to systematically explore the relationship between the structure and the corresponding base-pairing ability. Through Sonogashira coupling of the ethynyl pseudo-nucleobases and CPG-bound ODNs containing 6-iodopurine, we have demonstrated the synthesis of the ODNs containing three ^NPu derivatives (^NPu1, ^NPu2, ^NPu3) as well as three ^OPu derivatives (^OPu1, ^OPu2, ^OPu3). The base-pairing properties of each alkynylated purine derivative revealed that the structures of pseudo-nucleobases influence the base pair stability and selectivity. Notably, we found that ^OPu1 bearing 2-pyrimidinone exhibits higher stability to the complementary ^NPz than the original ^OPu, thereby demonstrating the potential of the on-column strategy for convenient screening of the alkynylated purine derivatives with superior pairing ability.

Recent advances in DNA-encoded dynamic libraries

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

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

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

Selective and stable base pairing by alkynylated nucleosides featuring a spatially-separated recognition interface

Unnatural base pairs (UBPs) which exhibit a selectivity against pairing with canonical nucleobases provide a powerful tool for the development of nucleic acid-based technologies. As an alternative strategy to the conventional UBP designs, which involve utility of different recognition modes at the Watson–Crick interface, we now report that the exclusive base pairing can be achieved through the spatial separation of recognition units. The design concept was demonstrated with the alkynylated purine (^NPu, ^OPu) and pyridazine (^NPz, ^OPz) nucleosides endowed with nucleobase-like 2-aminopyrimidine or 2-pyridone (‘pseudo-nucleobases’) on their major groove side. These alkynylated purines and pyridazines exhibited exclusive and stable pairing properties by the formation of complementary hydrogen bonds between the pseudo-nucleobases in the DNA major groove as revealed by comprehensive T_m measurements, 2D-NMR analyses, and MD simulations. Moreover, the alkynylated purine-pyridazine pairs enabled dramatic stabilization of the DNA duplex upon consecutive incorporation while maintaining a high sequence-specificity. The present study showcases the separation of the recognition interface as a promising strategy for developing new types of UBPs.

Discovery of SARS-CoV-2 main protease covalent inhibitors from a DNA-encoded library selection

Covalent inhibitors targeting the main protease (M^pro, or 3CLpro) of SARS-CoV-2 have shown promise in preclinical investigations. Herein, we report the discovery of two new series of molecules that irreversibly bind to SARS-CoV-2 M^pro. These acrylamide containing molecules were discovered using our covalent DNA-encoded library (DEL) screening platform. Following selection against SARS-CoV-2 M^pro, off-DNA compounds were synthesized and investigated to determine their inhibitory effects, the nature of their binding, and to generate preliminary structure-activity relationships. LC-MS analysis indicates a 1:1 (covalent) binding stoichiometry between our hit molecules and SARS-CoV-2 M^pro. Fluorescent staining assay for covalent binding in the presence of cell lysate suggests reasonable selectivity for SARS-CoV-2 M^pro. And lastly, inhibition of enzymatic activity was also observed against a panel of 3CLpro enzymes from different coronavirus strains, with IC₅₀ values ranging from inactive to single digit micromolar. Our results indicate that DEL selection is a useful approach for identifying covalent inhibitors of cysteine proteases.

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.

Universal encoding of next generation DNA-encoded chemical libraries

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

Evolution of the Selection Methods of DNA-Encoded Chemical Libraries

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

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

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

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.

Massively Parallel Optimization of the Linker Domain in Small Molecule Dimers Targeting a Toxic r(CUG) Repeat Expansion

RNA contributes to disease pathobiology and is an important therapeutic target. The downstream biology of disease-causing RNAs can be short-circuited with small molecules that recognize structured regions. The discovery and optimization of small molecules interacting with RNA is, however, challenging. Herein, we demonstrate a massively parallel one-bead-one-compound methodology, employed to optimize the linker region of a dimeric compound that binds the toxic r(CUG) repeat expansion [r(CUG)exp] causative of myotonic dystrophy type 1 (DM1). Indeed, affinity selection on a 331,776-member library allowed the discovery of a compound with enhanced potency both in vitro (10-fold) and in DM1-patient-derived myotubes (5-fold). Molecular dynamics simulations revealed additional interactions between the optimized linker and the RNA, resulting in ca. 10 kcal/mol lower binding free energy. The compound was conjugated to a cleavage module, which directly cleaved the transcript harboring the r(CUG)exp and alleviated disease-associated defects.

Scanning Protein Surfaces with DNA-Encoded Libraries

Understanding the ligandability of a target protein, defined as the capability of a protein to bind drug-like compounds on any site, can give important stimuli to drug-development projects. For instance, inhibition of protein-protein interactions usually depends on the identification of protein surface binders. DNA-encoded chemical libraries (DELs) allow scanning of protein surfaces with large chemical space. Encoded library selection screens uncovered several protein-protein interaction inhibitors and compounds binding to the surface of G protein-coupled receptors (GPCRs) and kinases. The protein surface-binding chemotypes from DELs are predominantly chemically modified and cyclized peptides, and functional small-molecule peptidomimetics. Peptoid libraries and structural peptidomimetics have been less studied in the DEL field, hinting at hitherto less populated chemical space and suggesting alternative library designs. Roughly a third of bioactive molecules evolved from smaller, target-focused libraries. They showcase the potential of encoded libraries to identify more potent molecules from weak, for example, fragment-like, starting points.

Proteolysis targeting chimeras (PROTACs) come of age: entering the third decade of targeted protein degradation

With the discovery of PROteolysis TArgeting Chimeras (PROTACs) twenty years ago, targeted protein degradation (TPD) has changed the landscape of drug development. PROTACs have evolved from cell-impermeable peptide-small molecule chimeras to orally bioavailable clinical candidate drugs that degrade oncogenic proteins in humans. As we move into the third decade of TPD, the pace of discovery will only accelerate. Improved technologies are enabling the development of ligands for "undruggable" proteins and the recruitment of new E3 ligases. Moreover, enhanced computing power will expedite identification of active degraders. Here we discuss the strides made in these areas and what advances we can look forward to as the next decade in this exciting field begins.

G protein-coupled receptors: structure- and function-based drug discovery

As one of the most successful therapeutic target families, G protein-coupled receptors (GPCRs) have experienced a transformation from random ligand screening to knowledge-driven drug design. We are eye-witnessing tremendous progresses made recently in the understanding of their structure-function relationships that facilitated drug development at an unprecedented pace. This article intends to provide a comprehensive overview of this important field to a broader readership that shares some common interests in drug discovery.

Direct ligand screening against membrane proteins on live cells enabled by DNA-programmed affinity labelling

DNA-programmed affinity labelling (DPAL) enables the screening of chemical compounds against membrane proteins directly on live cells.

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

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

PROTACs to address the challenges facing small molecule inhibitors

Small molecule inhibitors of proteins represent important medicines and critical chemical tools to investigate the biology of the target proteins. Advances in various -omics technologies have fueled the pace of discovery of disease-relevant proteins. Translating these discoveries into human benefits requires us to develop specific chemicals to inhibit the proteins. However, traditional small molecule inhibitors binding to orthosteric or allosteric sites face significant challenges. These challenges include drug selectivity, therapy resistance as well as drugging undruggable proteins and multi-domain proteins. To address these challenges, PROteolysis TArgeting Chimera (PROTAC) has been proposed. PROTACs are heterobifunctional molecules containing a binding ligand for a protein of interest and E3 ligase-recruiting ligand that are connected through a chemical linker. Binding of a PROTAC to its target protein will bring a E3 ligase in close proximity to initiate polyubiquitination of the target protein ensuing its proteasome-mediated degradation. Unlike small molecule inhibitors, PROTACs achieve target protein degradation in its entirety in a catalytical fashion. In this review, we analyze recent advances in PROTAC design to discuss how PROTACs can address the challenges facing small molecule inhibitors to potentially deliver next-generation medicines and chemical tools with high selectivity and efficacy. We also offer our perspectives on the future promise and potential limitations facing PROTACs. Investigations to overcome these limitations of PROTACs will further help realize the promise of PROTACs for human benefits.

Acid-Stable Ester Linkers for the Solid-Phase Synthesis of Immobilized Peptides

A series of N-terminally Fmoc-protected linkers of the general formula Fmoc-X-CO-O-Y-COOH have been prepared, where X is -NH-CH₂ -CH₂ - or -p-(aminomethyl)phenyl- and Y is -(CH₂ )_n - (n is 1 or 4) or -p-(methyl)phenyl-. These linkers can easily be covalently attached via their C-terminal carboxyl group to a resin bearing a free amino group. After cleavage of the N-terminal Fmoc group, the linkers can be extended by standard solid-phase peptide synthesis techniques. These ester linkers are acid-stable and resistant to the base-mediated diketopiperazine formation that often occurs during the synthesis of ester-bound peptides; they are stable at neutral pH in aqueous buffers for days but can be effectively cleaved with 0.1 m NaOH or aq. ammonia within minutes or hours, respectively. These properties make these ester handles well suited for use as linkers for the solid-phase peptide synthesis of immobilized peptides when the stable on-resin immobilization of the peptides and the testing of their biological properties in aqueous buffers at neutral pH are necessary.

Selection of DNA-Encoded Dynamic Chemical Libraries for Direct Inhibitor Discovery

Dynamic combinatorial libraries (DCLs) is a powerful tool for ligand discovery in biomedical research; however, the application of DCLs has been hampered by their low diversity. Recently, the concept of DNA encoding has been employed in DCLs to create DNA-encoded dynamic libraries (DEDLs); however, all current DEDLs are limited to fragment identification, and a challenging process of fragment linking is required after selection. We report an anchor-directed DEDL approach that can identify full ligand structures from large-scale DEDLs. This method is also able to convert unbiased libraries into focused ones targeting specific protein classes. We demonstrated this method by selecting DEDLs against five proteins, and novel inhibitors were identified for all targets. Notably, several selective BD1/BD2 inhibitors were identified from the selections against bromodomain 4 (BRD4), an important anti-cancer drug target. This work may provide a broadly applicable method for inhibitor discovery.

Psoralen as an interstrand DNA crosslinker in the selection of DNA-Encoded dynamic chemical library

DNA-encoded chemical library (DEL) has emerged as a powerful technology for ligand discovery in biomedical research. Recently, we have developed a DNA-encoded dynamic library (DEDL) approach by incorporating the concept of dynamic combinatorial library (DCL) with DELs. DEDL has shown excellent potential in ligand discovery towards a variety of protein targets. However, the requirement of having a pair of unnatural p-stilbazoles as the interstrand DNA crosslinker has limited the chemical diversity of DEDLs. Here, we replaced p-stilbazole with psoralen (PS) and tested the feasibility of psoralen as the crosslinker in DEDL selection. Since psoralen is commercially available and does not require any special crosslinking partner, existing DELs may be directly used to create high-diversity DEDLs. This study is expected to greatly facilitate the development of DEDLs as a versatile tool in drug discovery.