ArticleFrontiers in pharmacology2022
Identification of Potent and Selective JAK1 Lead Compounds Through Ligand-Based Drug Design Approaches.
Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 30 citations in OpenAlex.
- Identification of Novel JAK2 Inhibitors from Amino Derivatives of Epoxyalantolactone: In Silico and In Vitro Studies.International journal of molecular sciences · 2025Article
- Identification of Active Phytochemicals to Inhibit Signal Transducer and Activator of Transcription 5A (STAT5A) Dimerization for Prostate Cancer Therapy: AnAnti-cancer agents in medicinal chemistry · 2025Article
- Identification and Ranking of Binding Sites from Structural Ensembles: Application to SARS-CoV-2.Viruses · 2024Article
- Marine Bioactive Molecules as Inhibitors of the Janus Kinases: A Comparative Molecular Docking and Molecular Dynamics Simulation Approach.Current issues in molecular biology · 2024Article
- Repurposing FDA-approved compounds to target JAK2 for colon cancer treatment.Discover oncology · 2024Article
- Identification of new potent NLRP3 inhibitors by multi-level in-silico approaches.BMC chemistry · 2024Article
- Discovery of novel JAK1 inhibitors through combining machine learning, structure-based pharmacophore modeling and bio-evaluation.Journal of translational medicine · 2023Article
- Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches.Biomolecules · 2023Article
- Modern drug discovery for inflammatory bowel disease: The role of computational methods.World journal of gastroenterology · 2023Review
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6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
JAK1 plays a significant role in the intracellular signaling by interacting with cytokine receptors in different types of cells and is linked to the pathogenesis of various cancers and in the pathology of the immune system. In this study, ligand-based pharmacophore modeling combined with virtual screening and molecular docking methods was incorporated to identify the potent and selective lead compounds for JAK1. Initially, the ligand-based pharmacophore models were generated using a set of 52 JAK1 inhibitors named C-2 methyl/hydroxyethyl imidazopyrrolopyridines derivatives. Twenty-seven pharmacophore models with five and six pharmacophore features were generated and validated using potency and selectivity validation methods. During potency validation, the Guner-Henry score was calculated to check the accuracy of the generated models, whereas in selectivity validation, the pharmacophore models that are capable of identifying selective JAK1 inhibitors were evaluated. Based on the validation results, the best pharmacophore models ADHRRR, DDHRRR, DDRRR, DPRRR, DHRRR, ADRRR, DDHRR, and ADPRR were selected and taken for virtual screening against the Maybridge, Asinex, Chemdiv, Enamine, Lifechemicals, and Zinc database to identify the new molecules with novel scaffold that can bind to JAK1. A total of 4,265 hits were identified from screening and checked for acceptable drug-like properties. A total of 2,856 hits were selected after ADME predictions and taken for Glide molecular docking to assess the accurate binding modes of the lead candidates. Ninety molecules were shortlisted based on binding energy and H-bond interactions with the important residues of JAK1. The docking results were authenticated by calculating binding free energy for protein-ligand complexes using the MM-GBSA calculation and induced fit docking methods. Subsequently, the cross-docking approach was carried out to recognize the selective JAK1 lead compounds. Finally, top five lead compounds that were potent and selective against JAK1 were selected and validated using molecular dynamics simulation. Besides, the density functional theory study was also carried out for the selected leads. Through various computational studies, we observed good potency and selectivity of these lead compounds when compared with the drug ruxolitinib. Compounds such as T5923555 and T5923531 were found to be the best and can be further validated using
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