Discovery of bioactive peptides from Arbacia lixula as dipeptidyl peptidase-IV inhibitors: An in silico approach

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BSTRACT

Dipeptidyl peptidase-IV (DPP-IV) inhibition is a validated therapeutic mechanism for type 2 diabetes mellitus. Marine-derived bioactive peptides offer a diverse array of potential inhibitors but often exhibit pharmacokinetic limitations that impede clinical translation. This study aimed to identify and evaluate candidate peptides from Arbacia lixula as potential DPP-IV inhibitors using an integrated in silico approach. A total of twenty peptides were evaluated in silico for absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles using SwissADME, pkCSM, and ProTox. Molecular docking against DPP-IV was performed in MOE v2022.02 with linagliptin as the reference ligand; docking poses were evaluated by predicted binding energy and root mean square deviation (RMSD). Top-ranked peptide–DPP-IV complexes were subjected to 50 ns molecular dynamics (MD) simulations in YASARA Dynamics v4.3.13 to assess conformational stability. ADMET predictions showed low gastrointestinal absorption in most peptides, whereas Peptides 17, 18, and 20 showed high predicted absorption. No target-organ or endpoint-specific toxicity was predicted. Peptides 7, 15, and 18 were prioritized based on favorable docking scores, RMSD <2.0 Å, and relevant DPP-IV residue interactions. Docking scores were interpreted cautiously, not as direct quantitative comparisons with linagliptin. During 50 ns MD simulations, RMSD, root mean square fluctuation, radius of gyration, and solvent-accessible surface area profiles supported the stability, compactness, and dynamic consistency of selected peptide–DPP-IV complexes. Peptides 7, 15, and 18 showed favorable in silico predicting binding, relevant DPP-IV interactions, and acceptable preliminary safety profiles as potential DPP-IV inhibitory candidates. These findings should be interpreted as computational leads that require further in vitro and in vivo validation.