Computational identification of dual COX-1 and NIK inhibitors from marine microalga Chlorella vulgaris

  • Mahesh Samantaray
  • , Sthitaprajna Sahoo
  • , Durga Prasad Sahoo
  • , Guneswar Sethi
  • , Sarman Singh
  • , Hak Kyo Lee
  • , Biswajita Pradhan*
  • , Donghyun Shin
  • *Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

The search for safe and effective anti-inflammatory agents remains a critical area of research due to the widespread impact of chronic inflammatory diseases. Natural compounds, particularly those derived from marine sources, present a promising avenue for developing novel therapeutics. In this study, we investigated the potential of Chlorella vulgaris, a unicellular green alga with a rich profile of bioactive compounds, as a source of anti-inflammatory agents. Through in silico molecular docking and dynamics simulations, we identified compounds C8 and C4 as potent inhibitors of COX-1 and NIK, key targets in inflammatory pathways. These compounds demonstrated significantly stronger binding affinities than standard inhibitors MXM and OWC. For COX-1, C8 and C4 showed binding affinities of −8.625 and −4.359 kcal/mol, respectively, compared to −3.454 kcal/mol for MXM. Similarly, for NIK, the binding affinities were −6.798 and −3.789 kcal/mol for C8 and C4, respectively, compared to −2.628 kcal/mol for OWC. Molecular dynamics simulations further demonstrated that C8 and C4 formed stable interactions, including hydrogen bonds and hydrophobic contacts, with key residues in the active sites of COX-1 and NIK, suggesting a potential for sustained inhibitory activity. These findings highlight the therapeutic potential of C. vulgaris derived compounds for the treatment of inflammatory conditions. Although further in vitro and in vivo studies are necessary to fully elucidate their efficacy and safety, these results provide a promising foundation for the development of novel, naturally sourced anti-inflammatory therapies.

Original languageEnglish
Article number100531
JournalJournal of Genetic Engineering and Biotechnology
Volume23
Issue number3
DOIs
StatePublished - 2025.09

Keywords

  • Anti-inflammation
  • GC-MS
  • In silico
  • Molecular docking
  • Molecular dynamic simulation

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