AMPFinder

AMPFinder identifies antimicrobial peptides (AMPs; host defense peptides of 5 to 100 amino acids) and predicts their functional types from sequence-derived information to support discovery and characterization of AMPs active against mycobacteria, enveloped viruses, bacteria, fungi, and cancerous cells.

Key Features:

• High-Throughput Identification: AMPFinder enables rapid identification of AMPs from sequence data, facilitating large-scale screening efforts.
• Function Prediction: AMPFinder predicts the functional types of AMPs, providing insights into their potential biological roles and applications.
• Advanced Computational Model: The tool employs a cascaded computational approach that integrates sequence-derived information with life language embedding techniques to enhance prediction accuracy.
• Performance Metrics: AMPFinder demonstrates improved performance over existing methods with gains in F1-score (1.45%-6.13%), Matthews Correlation Coefficient (MCC) (2.92%-12.86%), Area Under the Curve (AUC) (5.13%-8.56%), and Average Precision (AP) (9.20%-21.07%).
• Reduced Bias: The model achieves lower bias in R² on public datasets via 10-fold cross-validation, with improvements of (18.82%-19.46%).

Scientific Applications:

• Antimicrobial discovery and characterization: Identification and functional prediction of AMPs to support antimicrobial research, drug development, and biotechnological efforts against antibiotic resistance.

Methodology:

Two-tiered computational strategy using sequence-derived analysis to detect candidate AMPs and life language embedding in a cascaded approach to refine functional predictions, with 10-fold cross-validation used to assess bias.