Structural Insights into Notum Covalent Inhibition

Designed switch from covalent to non-covalent inhibitors of carboxylesterase Notum activity

N-Acyl indolines 4 are potent, non-covalent Notum inhibitors developed from a covalent virtual screening hit 2a. The lead compounds were simple to synthesise, achieved excellent potency in a biochemical Notum-OPTS assay and restored Wnt signalling in a cell-based TCF/LEF reporter assay. Multiple high resolution X-ray structures established a common binding mode of these inhibitors with the indoline bound centred in the palmiteolate pocket with key interactions being aromatic stacking and a water mediated hydrogen bond to the oxyanion hole. These N-acyl indolines 4 will be useful tools for use in vitro studies to investigate the role of Notum in disease models, especially when paired with a structurally related covalent inhibitor (e.g. 4w and 2a). Overall, this study highlights the designed switch from covalent to non-covalent Notum inhibitors and so illustrates a complementary approach for hit generation and target inhibition.

HyperCys: A Structure- and Sequence-Based Predictor of Hyper-Reactive Druggable Cysteines

The cysteine side chain has a free thiol group, making it the amino acid residue most often covalently modified by small molecules possessing weakly electrophilic warheads, thereby prolonging on-target residence time and reducing the risk of idiosyncratic drug toxicity. However, not all cysteines are equally reactive or accessible. Hence, to identify targetable cysteines, we propose a novel ensemble stacked machine learning (ML) model to predict hyper-reactive druggable cysteines, named HyperCys. First, the pocket, conservation, structural and energy profiles, and physicochemical properties of (non)covalently bound cysteines were collected from both protein sequences and 3D structures of protein-ligand complexes. Then, we established the HyperCys ensemble stacked model by integrating six different ML models, including K-nearest neighbors, support vector machine, light gradient boost machine, multi-layer perceptron classifier, random forest, and the meta-classifier model logistic regression. Finally, based on the hyper-reactive cysteines' classification accuracy and other metrics, the results for different feature group combinations were compared. The results show that the accuracy, F1 score, recall score, and ROC AUC values of HyperCys are 0.784, 0.754, 0.742, and 0.824, respectively, after performing 10-fold CV with the best window size. Compared to traditional ML models with only sequenced-based features or only 3D structural features, HyperCys is more accurate at predicting hyper-reactive druggable cysteines. It is anticipated that HyperCys will be an effective tool for discovering new potential reactive cysteines in a wide range of nucleophilic proteins and will provide an important contribution to the design of targeted covalent inhibitors with high potency and selectivity.

Proteome-Wide Profiling of the Covalent-Druggable Cysteines with a Structure-Based Deep Graph Learning Network

Covalent ligands have attracted increasing attention due to their unique advantages, such as long residence time, high selectivity, and strong binding affinity. They also show promise for targets where previous efforts to identify noncovalent small molecule inhibitors have failed. However, our limited knowledge of covalent binding sites has hindered the discovery of novel ligands. Therefore, developing in silico methods to identify covalent binding sites is highly desirable. Here, we propose DeepCoSI, the first structure-based deep graph learning model to identify ligandable covalent sites in the protein. By integrating the characterization of the binding pocket and the interactions between each cysteine and the surrounding environment, DeepCoSI achieves state-of-the-art predictive performances. The validation on two external test sets which mimic the real application scenarios shows that DeepCoSI has strong ability to distinguish ligandable sites from the others. Finally, we profiled the entire set of protein structures in the RCSB Protein Data Bank (PDB) with DeepCoSI to evaluate the ligandability of each cysteine for covalent ligand design, and made the predicted data publicly available on website.

Structural Analysis and Development of Notum Fragment Screening Hits

The Wnt signaling suppressor Notum is a promising target for osteoporosis, Alzheimer's disease, and colorectal cancers. To develop novel Notum inhibitors, we used an X-ray crystallographic fragment screen with the Diamond-SGC Poised Library (DSPL) and identified 59 fragment hits from the analysis of 768 data sets. Fifty-eight of the hits were found bound at the enzyme catalytic pocket with potencies ranging from 0.5 to >1000 μM. Analysis of the fragments' diverse binding modes, enzymatic inhibitory activities, and chemical properties led to the selection of six hits for optimization, and five of these resulted in improved Notum inhibitory potencies. One hit, 1-phenyl-1,2,3-triazole 7, and its related cluster members, have shown promising lead-like properties. These became the focus of our fragment development activities, resulting in compound 7d with IC50 0.0067 μM. The large number of Notum fragment structures and their initial optimization provided an important basis for further Notum inhibitor development.

Design of a Potent, Selective, and Brain-Penetrant Inhibitor of Wnt-Deactivating Enzyme Notum by Optimization of a Crystallographic Fragment Hit

Notum is a carboxylesterase that suppresses Wnt signaling through deacylation of an essential palmitoleate group on Wnt proteins. There is a growing understanding of the role Notum plays in human diseases such as colorectal cancer and Alzheimer's disease, supporting the need to discover improved inhibitors, especially for use in models of neurodegeneration. Here, we have described the discovery and profile of 8l (ARUK3001185) as a potent, selective, and brain-penetrant inhibitor of Notum activity suitable for oral dosing in rodent models of disease. Crystallographic fragment screening of the Diamond-SGC Poised Library for binding to Notum, supported by a biochemical enzyme assay to rank inhibition activity, identified 6a and 6b as a pair of outstanding hits. Fragment development of 6 delivered 8l that restored Wnt signaling in the presence of Notum in a cell-based reporter assay. Assessment in pharmacology screens showed 8l to be selective against serine hydrolases, kinases, and drug targets.

Computational Analysis of the Inhibition Mechanism of NOTUM by the ONIOM Method

Notum is a member of serine hydrolyses that cleaves the palmitoleate moiety from Wingless-related integration site (Wnt) ligands. This enzyme plays crucial functions through modulating the Wnt signaling pathway. Inhibition of Notum carries therapeutic effects against a number of maladies including osteoporosis, cancer, and Alzheimer's disease. Recently, a class of irreversible inhibitors based on esters of 4-(indolin-1-yl)-4-oxobutanoic acid have been reported. Using the crystal structures of enzyme-4-(indolin-1-yl)-4-oxobutanoate adduct and 4-(indolin-1-yl)-4-oxobutanoic acid-enzyme complex, we studied computationally the proposed inhibition mechanism using model systems based on the own n-layered integrated molecular orbital and molecular mechanics (ONIOM) method. In the first place, model systems were formulated to investigate the transesterification between the catalytic serine residue, Ser-232, and the methyl ester of 4-(indolin-1-yl)-4-oxobutanoate. In the second place, the hydrolysis mechanism of the resultant enzyme-inhibitor adduct was studied. The energetics of these steps were analyzed using a density functional theory functional in the ONIOM method. In addition, the roles of active-site residues during these steps were highlighted. It was found that the hydrolysis of the covalent adduct is highly endergonic corroborating the irreversible inhibition mechanism. These results will shed light not only on the inhibition mechanism but also on the catalytic mechanism.

Virtual Screening Directly Identifies New Fragment-Sized Inhibitors of Carboxylesterase Notum with Nanomolar Activity

Notum is a negative regulator of Wnt signaling acting through the hydrolysis of a palmitoleoylate ester, which is required for Wnt activity. Inhibitors of Notum could be of use in diseases where dysfunctional Notum activity is an underlying cause. A docking-based virtual screen (VS) of a large commercial library was used to shortlist 952 compounds for experimental validation as inhibitors of Notum. The VS was successful with 31 compounds having an IC50 < 500 nM. A critical selection process was then applied with two clusters and two singletons (1-4d) selected for hit validation. Optimization of 4d guided by structural biology identified potent inhibitors of Notum activity that restored Wnt/β-catenin signaling in cell-based models. The [1,2,4]triazolo[4,3-b]pyradizin-3(2H)-one series 4 represent a new chemical class of Notum inhibitors and the first to be discovered by a VS campaign. These results demonstrate the value of VS with well-designed docking models based on X-ray structures.