ArticleInternational journal of molecular sciences2022
Identification of Novel Natural Product Inhibitors against Matrix Metalloproteinase 9 Using Quantum Mechanical Fragment Molecular Orbital-Based Virtual Screening Methods.
Article in International journal of molecular sciences, 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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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Identification of Small Molecules as Zika Virus Entry Inhibitors.International journal of molecular sciences · 2025Article
- Matrix Metalloproteinases and Their Inhibitors in the Pathogenesis of Epithelial Differentiation, Vascular Disease, Endometriosis, and Ocular Fibrotic Pterygium.International journal of molecular sciences · 2025Review
- Leveraging the Fragment Molecular Orbital and MM-GBSA Methods in Virtual Screening for the Discovery of Novel Non-Covalent Inhibitors Targeting the TEAD Lipid Binding Pocket.International journal of molecular sciences · 2024Article
- Fragment molecular orbital-based variational quantum eigensolver for quantum chemistry in the age of quantum computing.Scientific reports · 2024Article
- Binding Free Energy Calculation Based on the Fragment Molecular Orbital Method and Its Application in Designing Novel SHP-2 Allosteric Inhibitors.International journal of molecular sciences · 2024Article
- Novel Matrix Metalloproteinase-9 (MMP-9) Inhibitors in Cancer Treatment.International journal of molecular sciences · 2023Review
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Matrix metalloproteinases (MMPs) are calcium-dependent zinc-containing endopeptidases involved in multiple cellular processes. Among the MMP isoforms, MMP-9 regulates cancer invasion, rheumatoid arthritis, and osteoarthritis by degrading extracellular matrix proteins present in the tumor microenvironment and cartilage and promoting angiogenesis. Here, we identified two potent natural product inhibitors of the non-catalytic hemopexin domain of MMP-9 using a novel quantum mechanical fragment molecular orbital (FMO)-based virtual screening workflow. The workflow integrates qualitative pharmacophore modeling, quantitative binding affinity prediction, and a raw material search of natural product inhibitors with the BMDMS-NP library. In binding affinity prediction, we made a scoring function with the FMO method and applied the function to two protein targets (acetylcholinesterase and fibroblast growth factor 1 receptor) from DUD-E benchmark sets. In the two targets, the FMO method outperformed the Glide docking score and MM/PBSA methods. By applying this workflow to MMP-9, we proposed two potent natural product inhibitors (laetanine
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