Identification and the molecular mechanism of novel duck liver-derived anti-inflammatory peptides in lipopolysaccharide-induced RAW264.7 cell model

Abstract

In this study, 10 novel anti-inflammatory peptides were identified from duck liver, and their molecular mechanism was demonstrated based on machine learning and molecular docking. Using Sephadex G-15 gel chromatography separation, reversed-phase high-performance liquid chromatography purification, liquid chromatography-tandem mass spectrometry identification, and BIOPEP database comparison, 10 novel anti-inflammatory peptides were initially found. Their splendid angiotensin-converting enzyme (ACE) inhibition and anti-inflammatory properties were confirmed by machine learning. With binding energies less than –20.93 kJ/mol, molecular docking revealed that they could efficiently bind to the active pockets of tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), cyclooxygenase 2 (COX-2), and nuclear factor κB (NF-κB) proteins with efficiency, indicating that the compounds can spontaneously form complexes through hydrogen bonding and hydrophobic interactions with the protein binding pockets. In the lipopolysaccharide-induced RAW264.7 cell model, the release of NO, TNF-α, and IL-6 and the mRNA expression of inflammatory factors (TNF-α, IL-6, COX-2, and NF-κB) were significantly inhibited by these peptides. We concluded it might be due to their anti-inflammatory effects by inhibiting the protein phosphorylation of inhibitor of NF-κB (IκBα) in the cytoplasm and preventing the translocation of NF-κB p65 in the cytoplasm to the nucleus, thereby regulating the NF-κB signaling pathway. This study is essential for the screening of anti-inflammatory peptides and the investigation of the mechanism of action.

Keywords

• peptides
• machine learning
• molecular docking
• inflammation
• liquid chromatography-tandem mass spectrometry