Method for rapidly screening high-efficiency alpha-helix antibacterial peptide and application of high-efficiency alpha-helix antibacterial peptide
By extracting characteristic parameters of α-helical antimicrobial peptides and employing a hierarchical screening strategy, the problem of scarce data on plant-derived antimicrobial peptides has been solved. This enables rapid and efficient screening of high-efficiency α-helical antimicrobial peptides on ordinary computers, reducing screening time and costs, and making it suitable for various databases and library design scenarios.
Patent Information
- Application Number
- CN202610822130.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-09
- Publication Date
- 2026-07-10
- Estimated Expiration
- 2046-06-09
AI Technical Summary
Existing technologies struggle to efficiently screen for highly effective α-helical antimicrobial peptides when data on plant-derived antimicrobial peptides are scarce. Furthermore, traditional methods are computationally intensive, time-consuming, and inefficient, failing to meet the demands for rapid screening and reduced research costs.
By extracting characteristic parameters such as the hydrophobic cluster scores HCS3_HF and HCS4_HF of α-helical antimicrobial peptides, and combining them with hydrophobicity Hyd, hydrophobic moment HMom, net charge z, hydrophobic surface HoF, and hydrophilic surface HiF, a programmatic AMPs key feature calculation system written in Python was established for screening. A hierarchical screening strategy was adopted, including physicochemical constraints, confirmation of amphiphilicity, and screening based on hydrophobic cluster score thresholds. The screening process was optimized by using multi-centroid distance sorting.
It achieves efficient screening of billions of sequence spaces on ordinary computers, shortening the screening time to 1-2 hours. The MIC of all screened antimicrobial peptides is controlled within 32μg/mL, which significantly improves screening efficiency and reduces costs. It is suitable for various database and library design scenarios.