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.

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.

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.

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.

Partitioning of MLX-Family Transcription Factors to Lipid Droplets Regulates Metabolic Gene Expression.

Lipid droplets (LDs) store lipids for energy and are central to cellular lipid homeostasis. The mechanisms coordinating lipid storage in LDs with cellular metabolism are unclear but relevant to obesity-related diseases. Here we utilized genome-wide screening to identify genes that modulate lipid storage in macrophages, a cell type involved in metabolic diseases. Among ∼550 identified screen hits is MLX, a basic helix-loop-helix leucine-zipper transcription factor that regulates metabolic processes. We show that MLX and glucose-sensing family members MLXIP/MondoA and MLXIPL/ChREBP bind LDs via C-terminal amphipathic helices. When LDs accumulate in cells, these transcription factors bind to LDs, reducing their availability for transcriptional activity and attenuating the response to glucose. Conversely, the absence of LDs results in hyperactivation of MLX target genes. Our findings uncover a paradigm for a lipid storage response in which binding of MLX transcription factors to LD surfaces adjusts the expression of metabolic genes to lipid storage levels.

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.

Genome-wide siRNA screen identifies the retromer as a cellular entry factor for human papillomavirus.

Despite major advances in our understanding of many aspects of human papillomavirus (HPV) biology, HPV entry is poorly understood. To identify cellular genes required for HPV entry, we conducted a genome-wide screen for siRNAs that inhibited infection of HeLa cells by HPV16 pseudovirus. Many retrograde transport factors were required for efficient infection, including multiple subunits of the retromer, which initiates retrograde transport from the endosome to the trans-Golgi network (TGN). The retromer has not been previously implicated in virus entry. Furthermore, HPV16 capsid proteins arrive in the TGN/Golgi in a retromer-dependent fashion during entry, and incoming HPV proteins form a stable complex with retromer subunits. We propose that HPV16 directly engages the retromer at the early or late endosome and traffics to the TGN/Golgi via the retrograde pathway during cell entry. These results provide important insights into HPV entry, identify numerous potential antiviral targets, and suggest that the role of the retromer in infection by other viruses should be assessed.