Novel irreversible covalent BTK inhibitors discovered using DNA-encoded chemistry.

Libraries of DNA-Encoded small molecules created using combinatorial chemistry and synthetic oligonucleotides are being applied to drug discovery projects across the pharmaceutical industry. The majority of reported projects describe the discovery of reversible, i.e. non-covalent, target modulators. We synthesized multiple DNA-encoded chemical libraries terminated in electrophiles and then used them to discover covalent irreversible inhibitors and report the successful discovery of acrylamide- and epoxide-terminated Bruton's Tyrosine Kinase (BTK) inhibitors. We also demonstrate their selectivity, potency and covalent cysteine engagement using a range of techniques including X-ray crystallography, thermal transition shift assay, reporter displacement assay and intact protein complex mass spectrometry. The epoxide BTK inhibitors described here are the first ever reported to utilize this electrophile for this target.

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

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

Novel Nucleic Acid Binding Small Molecules Discovered Using DNA-Encoded Chemistry.

Inspired by the many reported successful applications of DNA-encoded chemical libraries in drug discovery projects with protein targets, we decided to apply this platform to nucleic acid targets. We used a 120-billion-compound set of 33 distinct DNA-encoded chemical libraries and affinity-mediated selection to discover binders to a panel of DNA targets. Here, we report the successful discovery of small molecules that specifically interacted with DNA G-quartets, which are stable structural motifs found in G-rich regions of genomic DNA, including in the promoter regions of oncogenes. For this study, we chose the G-quartet sequence found in the c-myc promoter as a primary target. Compounds enriched using affinity-mediated selection against this target demonstrated high-affinity binding and high specificity over DNA sequences not containing G-quartet motifs. These compounds demonstrated a moderate ability to discriminate between different G-quartet motifs and also demonstrated activity in a cell-based assay, suggesting direct target engagement in the cell. DNA-encoded chemical libraries and affinity-mediated selection are uniquely suited to discover binders to targets that have no inherent activity outside of a cellular context, and they may also be of utility in other nucleic acid structural motifs.

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

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

Screening Ultra-Large Encoded Compound Libraries Leads to Novel Protein-Ligand Interactions and High Selectivity.

The DNA-encoded library (DEL) discovery platform has emerged as a powerful technology for hit identification in recent years. It has become one of the major parallel workstreams for small molecule drug discovery along with other strategies such as HTS and data mining. For many researchers working in the DEL field, it has become increasingly evident that many hits and leads discovered via DEL screening bind to target proteins with unique and unprecedented binding modes. This Perspective is our attempt to analyze reports of DEL screening with the purpose of providing a rigorous and useful account of the binding modes observed for DEL-derived ligands with a focus on binding mode novelty.

Inhibitors of the Thioesterase Activity of Mycobacterium tuberculosis Pks13 Discovered Using DNA-Encoded Chemical Library Screening.

DNA-encoded chemical library (DEL) technology provides a time- and cost-efficient method to simultaneously screen billions of compounds for their affinity to a protein target of interest. Here we report its use to identify a novel chemical series of inhibitors of the thioesterase activity of polyketide synthase 13 (Pks13) from Mycobacterium tuberculosis (Mtb). We present three chemically distinct series of inhibitors along with their enzymatic and Mtb whole cell potency, the measure of on-target activity in cells, and the crystal structures of inhibitor-enzyme complexes illuminating their interactions with the active site of the enzyme. One of these inhibitors showed a favorable pharmacokinetic profile and demonstrated efficacy in an acute mouse model of tuberculosis (TB) infection. These findings and assay developments will aid in the advancement of TB drug discovery.

Development of Potent Mcl-1 Inhibitors: Structural Investigations on Macrocycles Originating from a DNA-Encoded Chemical Library Screen.

Evasion of apoptosis is critical for the development and growth of tumors. The pro-survival protein myeloid cell leukemia 1 (Mcl-1) is an antiapoptotic member of the Bcl-2 family, associated with tumor aggressiveness, poor survival, and drug resistance. Development of Mcl-1 inhibitors implies blocking of protein-protein interactions, generally requiring a lengthy optimization process of large, complex molecules. Herein, we describe the use of DNA-encoded chemical library synthesis and screening to directly generate complex, yet conformationally privileged macrocyclic hits that serve as Mcl-1 inhibitors. By applying a conceptual combination of conformational analysis and structure-based design in combination with a robust synthetic platform allowing rapid analoging, we optimized in vitro potency of a lead series into the low nanomolar regime. Additionally, we demonstrate fine-tuning of the physicochemical properties of the macrocyclic compounds, resulting in the identification of lead candidates 57/59 with a balanced profile, which are suitable for future development toward therapeutic use.

Identification and Evaluation of Reversible Covalent Binders to Cys55 of Bfl-1 from a DNA-Encoded Chemical Library Screen.

Bfl-1 is overexpressed in both hematological and solid tumors; therefore, inhibitors of Bfl-1 are highly desirable. A DNA-encoded chemical library (DEL) screen against Bfl-1 identified the first known reversible covalent small-molecule ligand for Bfl-1. The binding was validated through biophysical and biochemical techniques, which confirmed the reversible covalent mechanism of action and pointed to binding through Cys55. This represented the first identification of a cyano-acrylamide reversible covalent compound from a DEL screen and highlights further opportunities for covalent drug discovery through DEL screening. A 10-fold improvement in potency was achieved through a systematic SAR exploration of the hit. The more potent analogue compound 13 was successfully cocrystallized in Bfl-1, revealing the binding mode and providing further evidence of a covalent interaction with Cys55.

Discovery of Small Molecule Interleukin 17A Inhibitors with Novel Binding Mode and Stoichiometry: Optimization of DNA-Encoded Chemical Library Hits to In Vivo Active Compounds.

Dysregulation of IL17A drives numerous inflammatory and autoimmune disorders with inhibition of IL17A using antibodies proven as an effective treatment. Oral anti-IL17 therapies are an attractive alternative option, and several preclinical small molecule IL17 inhibitors have previously been described. Herein, we report the discovery of a novel class of small molecule IL17A inhibitors, identified via a DNA-encoded chemical library screen, and their subsequent optimization to provide in vivo efficacious inhibitors. These new protein-protein interaction (PPI) inhibitors bind in a previously undescribed mode in the IL17A protein with two copies binding symmetrically to the central cavities of the IL17A homodimer.

Discovery of a First-in-Class Small-Molecule Ligand for WDR91 Using DNA-Encoded Chemical Library Selection Followed by Machine Learning.

WD40 repeat-containing protein 91 (WDR91) regulates early-to-late endosome conversion and plays vital roles in endosome fusion, recycling, and transport. WDR91 was recently identified as a potential host factor for viral infection. We employed DNA-encoded chemical library (DEL) selection against the WDR domain of WDR91, followed by machine learning to predict ligands from the synthetically accessible Enamine REAL database. Screening of predicted compounds identified a WDR91 selective compound 1, with a KD of 6 ± 2 µM by surface plasmon resonance. The co-crystal structure confirmed the binding of 1 to the WDR91 side pocket, in proximity to cysteine 487, which led to the discovery of covalent analogues 18 and 19. The covalent adduct formation for 18 and 19 was confirmed by intact mass liquid chromatography-mass spectrometry. The discovery of 1, 18, and 19, accompanying structure-activity relationship, and the co-crystal structures provide valuable insights for designing potent and selective chemical tools against WDR91 to evaluate its therapeutic potential.

Discovery of Nanomolar DCAF1 Small Molecule Ligands.

DCAF1 is a substrate receptor of two distinct E3 ligases (CRL4DCAF1 and EDVP), plays a critical physiological role in protein degradation, and is considered a drug target for various cancers. Antagonists of DCAF1 could be used toward the development of therapeutics for cancers and viral treatments. We used the WDR domain of DCAF1 to screen a 114-billion-compound DNA encoded library (DEL) and identified candidate compounds using similarity search and machine learning. This led to the discovery of a compound (Z1391232269) with an SPR KD of 11 µM. Structure-guided hit optimization led to the discovery of OICR-8268 (26e) with an SPR KD of 38 nM and cellular target engagement with EC50 of 10 µM as measured by cellular thermal shift assay (CETSA). OICR-8268 is an excellent tool compound to enable the development of next-generation DCAF1 ligands toward cancer therapeutics, further investigation of DCAF1 functions in cells, and the development of DCAF1-based PROTACs.

Chemical Ligation of Oligonucleotide Tags to Support Encoded Chemical Library Synthesis.

Chemical ligation can be used to install encoding tags during the synthesis of DNA-encoded chemical libraries and can present a number of advantages. Here we describe methods to generate polymerase-readable oligonucleotide junctions and for the polymerase-mediated amplification of oligonucleotides ligated with these chemistries, including triazole junctions generated from 2'-ribo-3'-propargyl and 5'-azido oligonucleotides and from 2'-deoxy-3'-propargyl and 5'-azido oligonucleotides. We also present methods for the synthesis of phosphorothioate junctions from 3'-thiophospho and 5'-iodo oligonucleotides and for the synthesis of phosphodiester junctions from both 3'-hydroxy and 5'-phospho- and 3'-phospho and 5'-hydroxy oligonucleotides using 1-cyanoimidazole.

Discovery of 2,4-1H-Imidazole Carboxamides as Potent and Selective TAK1 Inhibitors.

Herein we report the discovery of 2,4-1H-imidazole carboxamides as novel, biochemically potent, and kinome selective inhibitors of transforming growth factor ß-activated kinase 1 (TAK1). The target was subjected to a DNA-encoded chemical library (DECL) screen. After hit analysis a cluster of compounds was identified, which was based on a central pyrrole-2,4-1H-dicarboxamide scaffold, showing remarkable kinome selectivity. A scaffold-hop to the corresponding imidazole resulted in increased biochemical potency. Next, X-ray crystallography revealed a distinct binding mode compared to other TAK1 inhibitors. A benzylamide was found in a perpendicular orientation with respect to the core hinge-binding imidazole. Additionally, an unusual amide flip was observed in the kinase hinge region. Using structure-based drug design (SBDD), key substitutions at the pyrrolidine amide and the glycine resulted in a significant increase in biochemical potency.

Discovery of Novel, Potent Inhibitors of Hydroxy Acid Oxidase 1 (HAO1) Using DNA-Encoded Chemical Library Screening.

Inhibition of hydroxy acid oxidase 1 (HAO1) is a strategy to mitigate the accumulation of toxic oxalate that results from reduced activity of alanine-glyoxylate aminotransferase (AGXT) in primary hyperoxaluria 1 (PH1) patients. DNA-Encoded Chemical Library (DECL) screening provided two novel chemical series of potent HAO1 inhibitors, represented by compounds 3-6. Compound 5 was further optimized via various structure-activity relationship (SAR) exploration methods to 29, a compound with improved potency and absorption, distribution, metabolism, and excretion (ADME)/pharmacokinetic (PK) properties. Since carboxylic acid-containing compounds are often poorly permeable and have potential active glucuronide metabolites, we undertook a brief, initial exploration of acid replacements with the aim of identifying non-acid-containing HAO1 inhibitors. Structure-based drug design initiated with Compound 5 led to the identification of a nonacid inhibitor of HAO1, 31, which has weaker potency and increased permeability.

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.

Generating Selective Leads for Mer Kinase Inhibitors-Example of a Comprehensive Lead-Generation Strategy.

Mer is a member of the TAM (Tyro3, Axl, Mer) kinase family that has been associated with cancer progression, metastasis, and drug resistance. Their essential function in immune homeostasis has prompted an interest in their role as modulators of antitumor immune response in the tumor microenvironment. Here we illustrate the outcomes of an extensive lead-generation campaign for identification of Mer inhibitors, focusing on the results from concurrent, orthogonal high-throughput screening approaches. Data mining, HT (high-throughput), and DECL (DNA-encoded chemical library) screens offered means to evaluate large numbers of compounds. We discuss campaign strategy and screening outcomes, and exemplify series resulting from prioritization of hits that were identified. Concurrent execution of HT and DECL screening successfully yielded a large number of potent, selective, and novel starting points, covering a range of selectivity profiles across the TAM family members and modes of kinase binding, and offered excellent start points for lead development.

Discovery of Novel UDP-N-Acetylglucosamine Acyltransferase (LpxA) Inhibitors with Activity against Pseudomonas aeruginosa.

This study describes a novel series of UDP-N-acetylglucosamine acyltransferase (LpxA) inhibitors that was identified through affinity-mediated selection from a DNA-encoded compound library. The original hit was a selective inhibitor of Pseudomonas aeruginosa LpxA with no activity against Escherichia coli LpxA. The biochemical potency of the series was optimized through an X-ray crystallography-supported medicinal chemistry program, resulting in compounds with nanomolar activity against P. aeruginosa LpxA (best half-maximal inhibitory concentration (IC50) <5 nM) and cellular activity against P. aeruginosa (best minimal inhibitory concentration (MIC) of 4 µg/mL). Lack of activity against E. coli was maintained (IC50 > 20 µM and MIC > 128 µg/mL). The mode of action of analogues was confirmed through genetic analyses. As expected, compounds were active against multidrug-resistant isolates. Further optimization of pharmacokinetics is needed before efficacy studies in mouse infection models can be attempted. To our knowledge, this is the first reported LpxA inhibitor series with selective activity against P. aeruginosa.

Novel Autotaxin Inhibitor for the Treatment of Idiopathic Pulmonary Fibrosis: A Clinical Candidate Discovered Using DNA-Encoded Chemistry.

The activity of the secreted phosphodiesterase autotaxin produces the inflammatory signaling molecule LPA and has been associated with a number of human diseases including idiopathic pulmonary fibrosis (IPF). We screened a single DNA-encoded chemical library (DECL) of 225 million compounds and identified a series of potent inhibitors. Optimization of this series led to the discovery of compound 1 (X-165), a highly potent, selective, and bioavailable small molecule. Cocrystallization of compound 1 with human autotaxin demonstrated that it has a novel binding mode occupying both the hydrophobic pocket and a channel near the autotaxin active site. Compound 1 inhibited the production of LPA in human and mouse plasma at nanomolar levels and showed efficacy in a mouse model of human lung fibrosis. After successfully completing IND-enabling studies, compound 1 was approved by the FDA for a Phase I clinical trial. These results demonstrate that DECL hits can be readily optimized into clinical candidates.

Machine Learning on DNA-Encoded Libraries: A New Paradigm for Hit Finding.

DNA-encoded small molecule libraries (DELs) have enabled discovery of novel inhibitors for many distinct protein targets of therapeutic value. We demonstrate a new approach applying machine learning to DEL selection data by identifying active molecules from large libraries of commercial and easily synthesizable compounds. We train models using only DEL selection data and apply automated or automatable filters to the predictions. We perform a large prospective study (∼2000 compounds) across three diverse protein targets: sEH (a hydrolase), ERα (a nuclear receptor), and c-KIT (a kinase). The approach is effective, with an overall hit rate of ∼30% at 30 µM and discovery of potent compounds (IC50 < 10 nM) for every target. The system makes useful predictions even for molecules dissimilar to the original DEL, and the compounds identified are diverse, predominantly drug-like, and different from known ligands. This work demonstrates a powerful new approach to hit-finding.