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.

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.

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.

Agonists and Antagonists of Protease-Activated Receptor 2 Discovered within a DNA-Encoded Chemical Library Using Mutational Stabilization of the Target.

The discovery of ligands via affinity-mediated selection of DNA-encoded chemical libraries is driven by the quality and concentration of the protein target. G-protein-coupled receptors (GPCRs) and other membrane-bound targets can be difficult to isolate in their functional state and at high concentrations, and therefore have been challenging for affinity-mediated selection. Here, we report a successful selection campaign against protease-activated receptor 2 (PAR2). Using a thermo-stabilized mutant of PAR2, we conducted affinity selection using our >100-billion-compound DNA-encoded library. We observed a number of putative ligands enriched upon selection, and subsequent cellular profiling revealed these ligands to comprise both agonists and antagonists. The agonist series shared structural similarity with known agonists. The antagonists were shown to bind in a novel allosteric binding site on the PAR2 protein. This report serves to demonstrate that cell-free affinity selection against GPCRs can be achieved with mutant stabilized protein targets.

Correction to "Structure Based Design of Non-Natural Peptidic Macrocyclic Mcl-1 Inhibitors".

[This corrects the article DOI: 10.1021/acsmedchemlett.6b00464.].

Isoform-Selective ATAD2 Chemical Probe with Novel Chemical Structure and Unusual Mode of Action.

ATAD2 (ANCCA) is an epigenetic regulator and transcriptional cofactor, whose overexpression has been linked to the progress of various cancer types. Here, we report a DNA-encoded library screen leading to the discovery of BAY-850, a potent and isoform selective inhibitor that specifically induces ATAD2 bromodomain dimerization and prevents interactions with acetylated histones in vitro, as well as with chromatin in cells. These features qualify BAY-850 as a chemical probe to explore ATAD2 biology.

Structure Based Design of Non-Natural Peptidic Macrocyclic Mcl-1 Inhibitors.

Mcl-1 is a pro-apoptotic BH3 protein family member similar to Bcl-2 and Bcl-xL. Overexpression of Mcl-1 is often seen in various tumors and allows cancer cells to evade apoptosis. Here we report the discovery and optimization of a series of non-natural peptide Mcl-1 inhibitors. Screening of DNA-encoded libraries resulted in hit compound 1, a 1.5 µM Mcl-1 inhibitor. A subsequent crystal structure demonstrated that compound 1 bound to Mcl-1 in a ß-turn conformation, such that the two ends of the peptide were close together. This proximity allowed for the linking of the two ends of the peptide to form a macrocycle. Macrocyclization resulted in an approximately 10-fold improvement in binding potency. Further exploration of a key hydrophobic interaction with Mcl-1 protein and also with the moiety that engages Arg256 led to additional potency improvements. The use of protein-ligand crystal structures and binding kinetics contributed to the design and understanding of the potency gains. Optimized compound 26 is a <3 nM Mcl-1 inhibitor, while inhibiting Bcl-2 at only 5 µM and Bcl-xL at >99 µM, and induces cleaved caspase-3 in MV4-11 cells with an IC50 of 3 µM after 6 h.

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.

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.

Encoded Library Synthesis Using Chemical Ligation and the Discovery of sEH Inhibitors from a 334-Million Member Library.

A chemical ligation method for construction of DNA-encoded small-molecule libraries has been developed. Taking advantage of the ability of the Klenow fragment of DNA polymerase to accept templates with triazole linkages in place of phosphodiesters, we have designed a strategy for chemically ligating oligonucleotide tags using cycloaddition chemistry. We have utilized this strategy in the construction and selection of a small molecule library, and successfully identified inhibitors of the enzyme soluble epoxide hydrolase.