Dataset Information

Ultra-large scale virtual screening identifies a small molecule inhibitor of the Wnt transporter Wntless.

ABSTRACT: Wnts are lipid-modified glycoproteins that play key roles in both embryonic development and adult homeostasis. Wnt signaling is dysregulated in many cancers and preclinical data shows that targeting Wnt biosynthesis and secretion can be effective in Wnt-addicted cancers. An integral membrane protein known as Wntless (WLS/Evi) is essential for Wnt secretion. However, WLS remains undrugged thus far. The cryo-EM structure of WLS in complex with WNT8A shows that WLS has a druggable G-protein coupled receptor (GPCR) domain. Using Active Learning/Glide, we performed an ultra-large scale virtual screening from Enamine's REAL 350/3 Lead-Like library containing nearly 500 million compounds. 68 hits were examined after on-demand synthesis in cell-based Wnt reporter and other functional assays. ETC-451 emerged as a potential first-in-class WLS inhibitor. ETC-451 blocked WLS-WNT3A interaction and decreased Wnt-addicted pancreatic cancer cell line proliferation. The current hit provides a starting chemical scaffold for further structure or ligand-based drug discovery targeting WLS.

SUBMITTER: Yu J

PROVIDER: S-EPMC11298631 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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Ultra-large scale virtual screening identifies a small molecule inhibitor of the Wnt transporter Wntless.

Yu Jia J Liao Pei-Ju PJ Keller Thomas H TH Cherian Joseph J Virshup David M DM Xu Weijun W

iScience 20240705 8

Wnts are lipid-modified glycoproteins that play key roles in both embryonic development and adult homeostasis. Wnt signaling is dysregulated in many cancers and preclinical data shows that targeting Wnt biosynthesis and secretion can be effective in Wnt-addicted cancers. An integral membrane protein known as Wntless (WLS/Evi) is essential for Wnt secretion. However, WLS remains undrugged thus far. The cryo-EM structure of WLS in complex with WNT8A shows that WLS has a druggable G-protein coupled ...[more]

PMID: 39104418

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Project description:BACKGROUND: In ligand-based screening, as well as in other chemoinformatics applications, one seeks to effectively search large repositories of molecules in order to retrieve molecules that are similar typically to a single molecule lead. However, in some case, multiple molecules from the same family are available to seed the query and search for other members of the same family.Multiple-molecule query methods have been less studied than single-molecule query methods. Furthermore, the previous studies have relied on proprietary data and sometimes have not used proper cross-validation methods to assess the results. In contrast, here we develop and compare multiple-molecule query methods using several large publicly available data sets and background. We also create a framework based on a strict cross-validation protocol to allow unbiased benchmarking for direct comparison in future studies across several performance metrics. RESULTS: Fourteen different multiple-molecule query methods were defined and benchmarked using: (1) 41 publicly available data sets of related molecules with similar biological activity; and (2) publicly available background data sets consisting of up to 175,000 molecules randomly extracted from the ChemDB database and other sources. Eight of the fourteen methods were parameter free, and six of them fit one or two free parameters to the data using a careful cross-validation protocol. All the methods were assessed and compared for their ability to retrieve members of the same family against the background data set by using several performance metrics including the Area Under the Accumulation Curve (AUAC), Area Under the Curve (AUC), F1-measure, and BEDROC metrics.Consistent with the previous literature, the best parameter-free methods are the MAX-SIM and MIN-RANK methods, which score a molecule to a family by the maximum similarity, or minimum ranking, obtained across the family. One new parameterized method introduced in this study and two previously defined methods, the Exponential Tanimoto Discriminant (ETD), the Tanimoto Power Discriminant (TPD), and the Binary Kernel Discriminant (BKD), outperform most other methods but are more complex, requiring one or two parameters to be fit to the data. CONCLUSION: Fourteen methods for multiple-molecule querying of chemical databases, including novel methods, (ETD) and (TPD), are validated using publicly available data sets, standard cross-validation protocols, and established metrics. The best results are obtained with ETD, TPD, BKD, MAX-SIM, and MIN-RANK. These results can be replicated and compared with the results of future studies using data freely downloadable from http://cdb.ics.uci.edu/.

Dataset Information

Ultra-large scale virtual screening identifies a small molecule inhibitor of the Wnt transporter Wntless.

Publications

Ultra-large scale virtual screening identifies a small molecule inhibitor of the Wnt transporter Wntless.

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