The dysregulation of Wnt/β-catenin pathway is often a key reason for cancer and other serious diseases. Wnt signaling is a highly conserved pathway that controls all steps of embryo development^1-6 and tissue maintenance in mature organisms^8-11. Alzheimer's, multiple sclerosis (MS), polycystic kidney disease (PKD), type 2 diabetes, arthritis, colon cancer, lung and breast cancer are some examples of Wnt pathway dysfunction. Recent evidence suggests that activation of Wnt pathway may prevent osteogenesis^17,30,31 and neurodegenerative disorders.^18,32

To create the ultimate Wnt/β-catenin signaling modulators library, we focused on the essential and clinically relevant protein targets. We used all available structural information and activity data for the following targets: CK1α, GSK3α/β, frizzled (Fzd) receptors and Lrp co-receptors (Lrp5/6), zinc and ring finger proteins (Znrf3, Rnf43), DKK1, Dvl-Axin, β-Catenin/TCF4, β-Catenin/Bcl9 and Bcl9/PYGO/His3 interaction inhibitions and Tankyrase to assemble the library.

The library of potential Wnt signaling modulators has been pre-plated for the most convenient and quick access. Using our Wnt library you receive multiple benefits, allowing you to save on time and costs in hit exploration and follow-up optimization:

• Hit confirmation support: Analogs search and hit samples resupply from same batch with strict QC
• Straightforward & affordable synthesis of hit follow-up libraries by parallel chemistry
• Medicinal chemistry support enhanced with on-site broad ADME/T panel

Figure 1. Canonical Wnt/Fz signaling cascade (adopted from Future Med. Chem. (2015), 7(18), 2485–2505) showing specific target-biased focused libraries available from Enamine.

Whereas numerous publications describe both identification and clinical development of Wnt inhibitors as potential anti-tumor therapies,^19,20 limited number of reports deal with the therapeutic utility of Wnt activators and/or potentiators.²¹ These classes of small molecule modulators usually inhibit kinases implicated in stability of β-catenin, namely GSK3β and CK1. For example, CHIR-99021 (CT99021) is a GSK-3α/βinhibitor with IC₅₀ of 10 nM/6.7 nM and > 500-fold selectivity for GSK-3 versus its closest homologs CDC2 and ERK2, as well as other protein kinases. Administration of CHIR-99021 significantly augmented hematopoietic repopulation in recipient mice transplanted with mouse or human hematopoietic stem cells (HSCs).²² This approach induces Wnt target gene expression via affecting the scaffolding proteins APC and Axin. However, GSK3 is involved in numerous signaling events in the cell and may lead to a mechanism-based toxicity. PF-670462 is a potent (IC₅₀ = 7.7 ± 2.2 nM) and selective (>30-fold with respect to 42 additional kinases) inhibitor of CK1ε that phosphorylates Dvl protein in the Wnt signaling.²³

There is the ongoing need for inhibitors, activators and potentiators (i.e. agents that mediate and/or enhance the effect of endogenous Wnt ligands) of Wnt signaling with novel mechanism of action. We combined our novel chemistries and structure-based approach to assemble a library of ca. 10,000 lead-like compounds able to tackle various aspects of Wnt/Fz signaling. Specific targets representing Wnt/Fz cascade include sFRP1, Dkk1, DyrK1A/B and interfaces of β-catenin with several transcription factors including Tcf-4 and Bcl-9. With this library we allow using either target-based, reporter-based or phenotypic assay(s) to test these compounds. Identified hits are expected to be tractable (i.e. feasible SAR and lead generation) and suitable as entry points into developing agents for the treatment of tumors, bone disease, Cardiovasular (CV) /metabolic, gastrointestinal (GI), and CNS/neurodegenerative disorders.

Specific targets and nodules of Fz/Wnt signaling cascade used for the library design:

Wnt/sFRP-1 interaction inhibitors. sFRP-1 family of proteins includes endogenous molecules that bind both Wnt ligands and Fz receptors. Inhibition of sFRP-1 may result in vicarious activation of Wnt signaling. In addition, WAY 316606 is a sFRP-1 inhibitor (Ki = 80 nM) that was described to increase total bone area in a murine calvarial organ culture assay at <1 nM concentration²⁴. It was also reported to be an antiosteoporotic agent²⁵. WAY-262611 is a Wnt pathway agonist that increases bone formation rate with EC₅₀ of 0.63 uM in TCF-Luciferase assay. WAY-262611 exhibits good pharmacokinetic properties and a dose-dependent increase in the trabecular bone formation rate in ovariectomized rats following oral administration²⁶. Specific attention needs to be paid to monitoring specific organ toxicity associated with a long-term perturbation of Wnt pathway including neoplasia(s),^27,28 although recent data suggest otherwise²⁹. This selection is represented by ca 1200 compounds.

Figure 2. Multifunctional molecular interactions of sFRP1/2 and their implications in pathological events. A) sFRP1/2 sequester Wnts, thereby antagonizing Wnt/β-catenin signaling; B) Frzb (sFRP3) and Crescent favor the diffusion of Wnts, enhancing their signaling range; C) sFRP1/2 cind to Fz receptors activating intracellular signaling; D) sFRP1 binds RANKL preventing its interaction with RANK receptor; E) sFRP2 binds to and enhances the procollagen proteinase activity of BMP1/Tollpid-like metalloproteinases accelerating the processing of pro-collagen; F) Sizzled binds to and inhibits the Chordinase activity of BMP1/Tolloid-like metalloproteinase; unproteced Chordin binds and sequesters BMPs (from Tohoku J. Exp. Med. 2010, 221, 11-17).

Figure 3. A) Pharmacophore model based on WAY 316606; orange – aromatic/heteroaromatic groups, green-hydrophobic pharmacophore (halogen, CF₃, CHF₂, Me, Et, iPr etc.), blue-positively charged moiety (⁺NH₃Alk, ⁺NH₂Alk₂, ⁺NHAlk₃ etc.); B) Superposition of WAY-316606 and our pharmacophore construct used in (sub) library design

DKK-1 Inhibitors. We used both docking and ligand-based approaches to search for potential DKK-1 binders. Specifically, the DKK1/LRP6 protein-protein interaction (PPI) interface was utilized to select matching ligands from the entire Enamine Screening Collection. The analogs of NCI8642 and other reported DKK-1/LRP6 interaction inhibitors were used for ligand-based search and pharmacophore modeling. In the docking calculation, we focused on topological and charge distribution features of the critical Dkk-1 loop that binds to LRP6. We reasoned that blocking/destabilizing this loop feature of the DKK-1/LRP6 PPI may yield modulators and/or activators of Wnt signaling while maintaining ‘normal’ Wnt-Fz-LRP6 signaling.

Figure 4. Binding interface between LRP6 protein and representative ligand from the focused subset.

We used known DKK-1 inhibitor WAY 262611 and its 3D pharmacophore in the ligand-based approach to identify 3k+ lead-like compounds as potential binders.

Figure 5. A) Pharmacophore model based on WAY-262611; orange – aromatic/heteroaromatic groups, blue – positively charged moiety (⁺NH₃Alk, ⁺NH₂Alk₂, ⁺NHAlk₃ etc.), magenta – aliphatic ring; B) Superposition of WAY-262611 and our pharmacophore construct used in (sub) library design.

Dvl-Axin Inhibitors. Dvl-Axin interaction is mediated by a specific PDZ-domain. Since structural information on this PPI interface is not available, we built a homology model using AlphaFold2 and numerous SBio data on PDZ domains. The resulting model was used to run docking calculation of the entire Screening Collection and identify the most promising ‘hits’. As a result, ~2500 final Dvl-biased compounds were added to the library. A representative example of putative Dvl binder is shown below.

Figure 6. A representative example of Dvl/PDZ-domain binding ligand from our focused set.

β-Catenin/TCF4 Protein-Protein Interaction. To model the interaction interface between β-catenin and Tcf-4 we used reported structural data (ACS Chem. Biol. 2014, 9, 193−201) to identify critical contacts including intriguing protonated pyridine (cation) – π-interaction between docked ligand and Arg474/515 tweezers. The topology of the hydrophobic pocket and H-bond of the aromatic NH₂ group with protein’s Lys508 residue allowed construction of a respective pharmacophore model (Figure 7). After docking calculation and scoring cut off, a focused selection of ca. 1800 small molecules was assembled into β-Catenin/TCF4 sublibrary.

Figure 7. Binding interface between β-catenin and representative ligand from the focused subset.

β-Catenin/Bcl9 Protein-Protein Interaction Interface. We focused on the available structural data of the reported helix-helix interaction between the two biological molecules. Specifically, we investigated the key H-bonds between H358, R359 (Bcl9) and D162, D164 (β-catenin) (Figure 8). Following docking and binding poses prioritization, we picked molecules that secured hydrogen bonding with D162/D164 and exhibited a significant π-stacking/hydrophobic interaction area with β-catenin to result in the 1779-compound library.

Figure 8. A) β-catenin/BCL9 helix-helix interaction interface featuring key hydrogen bonds; B) binding of β-catenin and a representative ligand from the focused subset.

Bcl9/PYGO/Histone 3 Interaction Interface. The other option to block Wnt/Fz signaling is disruption of PYGO/Histone 3 interaction (Figure 9A). Notably, it has been shown that small molecules could bind to the PHD domain of PYGO that engages the methylated Histone 3 residue, which leads to disruption of β-catenin/Bcl9 interaction. After docking calculation and scoring prioritization, 318 small molecules were selected as potential PPI inhibitors of this complex. The representative example of a ligand mediating multiple hydrophilic interactions, p-stacking with Phe366 and hydrogen bonds, is shown in Figure 9B.

Figure 9. A) Interaction interface of BCL9/PYGO/Histone 3; B) Representative molecule bound to the key amino acids of H3K4me2.

What Makes this Chemical Compound Library Unique and Valuable?

Most commercial compound libraries cover broad sectors of biology such as GPCRs, kinases, or antibacterials that may include hundreds to thousands of individual proteins. Here we provide targeted libraries, subsets from the Enamine REAL Space, which are designed around common features seen when grouping proteins by their binding properties. These AI-enabled libraries were built around the hundred most promising and clinically relevant drug targets grouped into 10 families.

Development Strategy

As a first step, the human proteome was encoded into binding likelihood vectors through MatchMaker, a neural network model trained on a vast collection of biochemical datasets, to predict interacting protein-ligand pairs, otherwise known as Drug-Target Interactions (DTI). The entire Enamine REAL Space library was then scanned for putative interactions within the proteome, and the resulting pairwise matrix (compound vs protein) of 2.8 quadrillion interactions was aggregated at the synthon level. The emerging space is rich in chemical and biological information. It can be navigated to identify chemo-proteomic clusters: small, focused target sets predicted to bind with structurally and chemically similar compounds.

• Targeted libraries are designed starting from a list of seed targets relevant to biological pathways of interest and expanded to relevant chemo-proteomic clusters.
• Compounds were ranked against targets in each cluster according to their MatchMaker DTI prediction score.
• The final library set was selected to maximize diversity in drug-like, synthesizable chemical space, through the application of a range of classical medicinal chemistry, DMSO stability and synthesizability filters.
• 15 000 new compounds were synthesized to deliver highly focused AI-driven libraries

Breast cancer remains one of the major health problems among the women’s population. This disease frightens millions of women around the world. The tremendous efforts of researchers and drug developers in this field have made significant progress in treatment and early diagnostics. Breast cancer is often fueled by hormones and most commonly uses estrogen to grow. Treatment with anti-estrogen therapy can effectively block the growth of the cancer cells. Thus, Estrogen Receptor (ER) remains the most important target for the development of new effective drugs against breast cancer.

We combined different approaches in the design of ER focused library to bring the most promising and convenient for follow-up starting points in your screening campaign. The library has been carefully reviewed in the context of MedChem tractability and intrinsic high diversity. Additionally, compounds were reviewed for sufficient solubility and stability in DMSO solution to ensure the high quality of the library.

Library design

The database of activities related to SERMs (Selective Estrogen Receptor Modulators) was collected from the public domain (ChEMBL and Reaxys) and analyzed by the activity range. In total, about 15k activities were found, analyzed, and then separated by chemotypes. The most interesting from medchem prospective scaffolds were used for substructure searches, while the most active molecules were assembled into a validation set for in silico models – 3D pharmacophore and docking.

In addition, all available RE structures in PDB were combined and analyzed. Over 200 co-crystallized ligands with ER-alpha were extracted and superimposed to identify the most important interaction points and common structural motifs.

Superposition of all ER-alpha co-crystalized ligands, www.rcsb.org:

• All ligands share a similar binding mode which aligns with Estradiol binding.
• Two hydroxy groups from different/opposite parts of the binding pocket.
• One hydroxy group (H-bond donor) is well conserved among all extracted ligands.
• The conserved H-bond interaction with the OH-group is essential for activity when another can be replaced with different bioisosteres and H-bond donors.

About 15 distinct pharmacophores were identified with the four most common interaction maps selected for the in silico models:

• Estrogen receptor alpha 7 clusters based on PDB ID: 1sj0, 2iog, 2qxm, 3os8, 5aau, 5dwi, 5krj.
• Estrogen receptor beta 5 clusters based on PDB ID: 1nde, 1qkm, 2fsz, 2giu2yly.

Three 3D-pharmacophore models with exclusion volume were built, validated, and then used for the search of potential new ER ligands. As a result, over 10k compounds were identified as potential hits for ER-alpha, and 7k+ potentially active compounds were identified for ER-beta. The final library of potential estrogen receptor modulators passed through a manual review of predicted binding poses and was filtered using extended MedChem filters.

Examples of the pharmacophore models with reference molecules and predicted hits

Hydrophobic features are marked as orange spheres; Hydroxy group function is highlighted with purple.

Covalent chemical probes have become a valuable tool in drug discovery within the last few years. New technologies and development of fast mass spectrometric screening and imaging open a new horizon for proteome-wide screening and proteomics discoveries. The impressive number of successful applications brought aspiration to the discovery and synthesis of new covalent probes. Previously developed by Cravatt research group mapping of the ligandable proteome using fully functionalized enantiomeric probe pairs makes this field especially attractive for further investigations.

To support further research of the stereoselective interaction of proteins with chiral covalent small-molecules we designed and specially synthesized two sets of fragments with the most robust covalent warheads – acrylamides and chloroacetamides.

More than 6000 chiral building blocks with enantiomeric excess (ee) purity of 90%+ were analyzed and triaged for further synthesis of covalent binder pairs. The resulting set of over 2000 of the most diverse novel covalent modifiers has been synthesized. The enantiomeric purity of the corresponding enantiomeric pairs was analyzed by chiral chromatography. Compounds that passed rigorous QC and selection based on the diversity and Ro3 criteria were assembled into the Covalent Enantiomeric Pairs Library.

Key features

• Stereoselective interaction of target with enantiomeric covalent binder provides evidence of ligand-protein interaction
• Information about “correct” stereochemistry of hit on early stage
• Most common and well-validated warheads

Enatiomeric Pairs Fragment Library is plated at 100 mM concentration and is available for fast supply in different formats. The Library consists of two sublibraries, which can be acquired separately.