Exploring Artesunate and Dihydroartemisinin for Mechanism on MMP-3 and MMP-13 via Molecular Docking and Molecular Dynamics
Year: 2025
Type: article
Abstract: The application of natural products has drawn increasing attention in recent times. Artesunate (ART) and Dihydroartemisinin (DHA), being natural products with anti-inflammatory and cartilage protective capabilities, have shown potential in osteoarthritis (OA) treatment. OA is a highly prevalent degenerative joint disease globally, leading to a diminished quality of life and is a major cause of disability. Matrix metalloproteinase 3 (MMP-3) and MMP-13 play crucial roles in OA progression. Although ART and DHA have been found to downregulate the protein levels of MMP-3 and MMP-13 and suppress the activity of inflammatory factors in chondrocytes, their interaction mechanisms with MMP-3 and MMP-13 remain unclear. This study aimed to conduct an in-silico exploration of the binding affinity, action mode, and stability of ART and DHA to the active sites of MMP-3 and MMP-13 using molecular docking and molecular dynamics simulation techniques. The results demonstrated that ART and DHA possess favorable binding affinities (≤−7.0 kcal/mol) for MMP-3 and MMP-13, establish hydrogen bonds and hydrophobic interactions with amino acid residues in the active sites, and form interactions with Zn2+. During the 50 ns simulation, the root mean square deviation (RMSD) of ART and DHA on MMP-3 was less than 2Å. The binding free energies were all negative, indicating a stable binding state. These findings disclose a novel function of ART and DHA as potential inhibitors of MMP-3 and MMP-13, presenting valuable insights and research directions for the development of novel OA therapeutics. However, further in vitro and in vivo investigations are required to validate the biological activities of these molecules.
Source: Molecular Modeling Connect
Authors: Yi Wang, Xiushan Chen
Institution: Shandong Academy of Chinese Medicine
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409968349
