ArticleFrontiers in pharmacology2022
Identification of potential extracellular signal-regulated protein kinase 2 inhibitors based on multiple virtual screening strategies.
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 6 papers.
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6 citing papers in PubMed, 12 citations in OpenAlex.
- A Leakage-Aware Drug Discovery Workflow for PKM2 and MAPK1 Integrating Scaffold Validation, Molecular Docking and Structural Triage.International journal of molecular sciences · 2026Article
- In silico investigation of Toxicodendron succedaneum phytochemicals as extracellular signal-regulated kinase 2 inhibitors for non-small cell lung cancer therapy.Medical oncology (Northwood, London, England) · 2025Article
- Preparation of Acetylcholinesterase Inhibitory Peptides from Yellowfin Tuna Pancreas Using Moderate Ultrasound-Assisted Enzymatic Hydrolysis.Marine drugs · 2025Article
- Metagenomic analysis and bioactive profiling of kombucha fermentation: antioxidant, antibacterial activities, and molecular docking insights into gastric cancer therapeutics.Toxicology research · 2024Article
- AI-based prediction of protein-ligand binding affinity and discovery of potential natural product inhibitors against ERK2.BMC chemistry · 2024Article
- Antiviral activity of chrysin and naringenin against porcine epidemic diarrhea virus infection.Frontiers in veterinary science · 2023Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of multiple virtual screening strategies facilitates the balance of computational efficiency and prediction accuracy. In this study, we constructed an efficient and reliable "multi-stage virtual screening-in vitro biological validation" system to identify potential inhibitors targeting extracellular signal-regulated protein kinase 2 (ERK2). Firstly, we rapidly obtained 10 candidate ERK2 inhibitors with desirable pharmacokinetic characteristics from thousands of named natural products in ZINC database based on machine learning classification models and ADME/T prediction. The structure-based molecular docking approach was then used to obtain four further hits with lower binding free energy compared to the positive control molecule Magnolipin. Subsequently, the two compounds were purchased for
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