ArticlePloS one2025
Structure-guided identification of mitogen-activated protein kinase-1 inhibitors towards anticancer therapeutics.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Computational identification of Cucurbitacin S and Kammogenin as bioactive focal adhesion kinase 2 inhibitors for targeted cancer therapy.Molecular diversity · 2026Article
- Data-efficient learning for accurate identification of MAPK1 inhibitors using an active meta-deep learning framework.Journal of cheminformatics · 2026Article
- Computational identification of Moracin G and Isolonchocarpin as potent MELK inhibitors for anticancer drug discovery.Scientific reports · 2025Article
- Deep Sequencing Reveals Novel Mutations inInternational journal of molecular sciences · 2025Article
- MAPK15 PreventsInternational journal of molecular sciences · 2025Article
- Deciphering the Regulatory Potential of Antioxidant and Electron-Shuttling Bioactive Compounds in Oolong Tea.Biology · 2025Article
- SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling andFrontiers in molecular biosciences · 2025Article
- Structure-based identification of Jervine as a potent dual-targeting inhibitor of cell cycle kinases.Frontiers in pharmacology · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
Mitogen-activated protein kinase 1 (MAPK1) is a serine/threonine kinase that plays a crucial role in the MAP kinase signaling transduction pathway. This pathway plays a crucial role in various cellular processes, including cell proliferation, differentiation, adhesion, migration, and survival. Besides, many chemotherapeutic drugs targeting the MAPK pathway are used in clinical practice, and novel inhibitors of MAPK1 with improved specificity and efficacy are required. Hence, targeting MAPK1 can be crucial to control metastasis in cancer therapeutics. In this study, we utilized a structure-guided virtual screening approach to screen a library of thousands of natural compounds from the ZINC database. The Lipinski rule of five (RO5) was used as a criterion for the primary selection of natural compounds. The screened compounds were prioritized based on their binding affinity, docking scores, and specificity towards the kinase domain of MAPK1 during the molecular docking process. Subsequently, the selected hits underwent rigorous screening that included the identification of potential pan-assay interference compounds (PAINS), ADMET evaluation, and prediction of pharmacological activities using PASS analysis. Afterwards, we performed a comprehensive interaction analysis to explore the binding prototypes of the screened molecules with the key residues within the MAPK1 kinase domain. Finally, selected molecules underwent extensive all-atom molecular dynamics (MD) simulations for a time duration of 200 nanoseconds. The study pinpointed three natural compounds with ZINC database IDs ZINC0209285, ZINC02130647, and ZINC02133691 as potential inhibitors of MAPK1. The study highlights that these compounds could be explored further in preclinical and clinical investigations to develop anticancer therapeutics.
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