In silico analysis of Arbacia lixula-derived peptides and plasmid construction for recombinant anti-aging therapies

Skin aging is one of the degenerative processes influenced by tyrosinase, elastase, collagenase, hyaluronidase, and matrix metalloproteinase-9 (MMP9) activity. One promising avenue for discovering antiaging therapeutics is the peptides from the Arbacia lixula spine. The aim of this study was to explore the potential of peptides from A. lixula spine as a multitarget inhibitor for recombinant antiaging therapies through in silico approaches. The crystal structure of peptides previously identified in A. lixula spine was visualized using the UCSF Chimera. The protein data bank (PDB) database was used to obtain the crystal structures of protein targets. The webservers Innovagen, AllerTop, and ToxinPred were utilized to predict the peptide's water solubility, toxicity, and allergenicity. MOE application was used to prepare all ligands and proteins, molecular docking, and visualization. Molecular dynamics simulations were carried out on the protein-ligand complexes on Yasara Dynamics application. The Benchling website was used to perform virtual electrophoresis and reconstruct the recombinant plasmid (Psb1c3). Based on the molecular docking results, peptide REGSPDLLE has the potential as a multitarget inhibitor of tyrosinase (-9.07 kcal/mol), hyaluronidase (-10.57 kcal/mol), elastase (-9.32 kcal/mol), collagenase (-10.57 kcal/mol), and MMP9 (-10.43 kcal/mol). Peptide REGSPDLLE was selected due to its strong binding affinity on the active site of each target protein and exhibits non-toxic, non-allergenic, and good water-soluble as indicated by Support Vector Machine score <0. Molecular dynamics simulations confirmed stable interactions with receptor proteins. Peptide REGSPDLLE was successfully inserted into the recombinant pSB1C3 plasmid, confirmed by virtual electrophoresis with bands at ∼2000bp and ∼150 bp. Further in vitro and in vivo studies are necessary to verify the anti- aging efficacy of peptide REGSPDLLE.