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2026-06-18 PubMed

DeepAngio AI model identifies novel ACE-inhibitory peptides LLRP, LHWPR, RFLR from tuna hydrolysate

ACE Inhibitory Peptide Tailored Preparation, Screening, and Interaction Mechanism via Computer-Assisted Experimental Studies.

Background

Conventional methods for discovering angiotensin-converting enzyme (ACE) inhibitory peptides are often inefficient, yielding suboptimal activity and requiring extensive optimization. Hypertension, a major global health concern, is frequently managed by ACE inhibitors, which block the conversion of angiotensin I to angiotensin II, a potent vasoconstrictor. While synthetic ACE inhibitors are effective, there's growing interest in natural, food-derived peptides as safer alternatives with fewer side effects. The challenge lies in efficiently identifying and producing these bioactive peptides, addressing a critical gap in developing functional foods and nutraceuticals for blood pressure management.

Study Design

Researchers developed DeepAngio, a novel computational model, to streamline the preparation and screening of ACE-inhibitory peptides. The model's performance was validated using 10-fold cross-validation. Following computational screening, DeepAngio guided the directional preparation of tuna meat hydrolysates. From these hydrolysates, three specific peptides – LLRP, LHWPR, and RFLR – were isolated and their ACE inhibitory activity was experimentally confirmed. The mechanism of ACE inhibition for each peptide was characterized using spectroscopic analysis and molecular docking simulations to understand their binding modes.

Results

The DeepAngio model demonstrated high predictive performance, achieving 98.80% accuracy, 99.63% precision, and 96.44% specificity in screening ACE-inhibitory peptides. For classification tasks, it showed 88.24% accuracy, 86.76% precision, and 95.16% specificity. The tuna meat hydrolysates, prepared with DeepAngio's guidance, exhibited notable ACE inhibitory activity with an IC50 of 31.27 ± 0.72 µg/mL. Three novel potent ACE inhibitory peptides were successfully screened and isolated:

LLRP (IC50, 3.44 ± 0.19 µM), LHWPR (IC50, 17.67 ± 1.53 µM), and RFLR (IC50, 42.52 ± 7.50 µM). These peptides inhibited ACE activity through distinct mechanisms: LLRP and RFLR showed mixed-competitive inhibition, while LHWPR exhibited competitive inhibition, forming stable complexes with the enzyme, as confirmed by spectroscopic and molecular docking analyses.

Key Findings

  • DeepAngio model achieved 98.80% accuracy in screening ACE-inhibitory peptides.
  • Tuna meat hydrolysates prepared using DeepAngio guidance showed an IC50 of 31.27 ± 0.72 µg/mL.
  • Novel peptide LLRP demonstrated potent ACE inhibition with an IC50 of 3.44 ± 0.19 µM.
  • Peptides LLRP and RFLR exhibited mixed-competitive ACE inhibition, while LHWPR was competitive.

Why It Matters

This study introduces a powerful, AI-driven approach that significantly accelerates the discovery and targeted production of bioactive peptides. DeepAngio could revolutionize the development of functional foods and nutraceuticals for managing hypertension. By efficiently identifying potent ACE-inhibitory peptides like LLRP, LHWPR, and RFLR from common food sources like tuna, this technology paves the way for cost-effective and natural alternatives to synthetic drugs. The ability to predict and then directionally prepare hydrolysates means that future peptide-based interventions for blood pressure regulation could be developed with unprecedented speed and precision, moving closer to personalized nutritional strategies. This method offers a practical pathway to translate computational insights into tangible, active compounds.


ace-inhibitor hypertension peptide-discovery computational-biology tuna functional-food
Source: pubmed:42313066 · Ingested 2026-06-18 · Digest: gemini-2.5-flash