ArticleBiomolecules2020
Structure-Based Virtual Screening of Ultra-Large Library Yields Potent Antagonists for a Lipid GPCR.
Article in Biomolecules, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 39 citations in OpenAlex.
- Strategies for the drug development of cancer therapeutics.Frontiers in pharmacology · 2025Review
- vScreenML v2.0: Improved Machine Learning Classification for Reducing False Positives in Structure-Based Virtual Screening.International journal of molecular sciences · 2024Article
- Identifying Artifacts from Large Library Docking.Journal of medicinal chemistry · 2024Article
- The Art and Science of Molecular Docking.Annual review of biochemistry · 2024Review
- Identifying Artifacts from Large Library Docking.bioRxiv : the preprint server for biology · 2024Article
- Regression-Based Active Learning for Accessible Acceleration of Ultra-Large Library Docking.Journal of chemical information and modeling · 2024Article
- Protein Structure-Based Organic Chemistry-Driven Ligand Design from Ultralarge Chemical Spaces.ACS central science · 2024Article
- DockOpt: A Tool for Automatic Optimization of Docking Models.Journal of chemical information and modeling · 2024Article
- Docking for EP4R antagonists active against inflammatory pain.Nature communications · 2023Article
- Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries.Journal of chemical information and modeling · 2023Article
- Exploration on learning molecular docking with deep learning models.Quantitative biology (Beijing, China) · 2023Article
- Structure-based discovery of conformationally selective inhibitors of the serotonin transporter.Cell · 2023Article
- Large-Scale Docking in the Cloud.Journal of chemical information and modeling · 2023Article
- Targeting in silico GPCR conformations with ultra-large library screening for hit discovery.Trends in pharmacological sciences · 2023Review
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cysteinyl leukotriene G protein-coupled receptors, CysLT1R and CysLT2R, regulate bronchoconstrictive and pro-inflammatory effects and play a key role in allergic disorders, cardiovascular diseases, and cancer. CysLT1R antagonists have been widely used to treat asthma disorders, while CysLT2R is a potential target against uveal melanoma. However, very few selective antagonist chemotypes for CysLT receptors are available, and the design of such ligands has proved to be challenging. To overcome this obstacle, we took advantage of recently solved crystal structures of CysLT receptors and an ultra-large Enamine REAL library, representing a chemical space of 680 M readily available compounds. Virtual ligand screening employed 4D docking models comprising crystal structures of CysLT1R and CysLT2R and their corresponding ligand-optimized models. Functional assessment of the candidate hits yielded discovery of five novel antagonist chemotypes with sub-micromolar potencies and the best Ki = 220 nM at CysLT1R. One of the hits showed inverse agonism at the L129Q constitutively active mutant of CysLT2R, with potential utility against uveal melanoma.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.