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Advances in Computational and Data-driven Methodologies for Accelerating Antimicrobial Peptide Design and Discovery
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DOI：10.1016/j.progpolymsci.2026.102119.png)
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Abstract
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• Reviewed computational strategies for antimicrobial peptide discovery. • Summarized how machine learning accelerates peptide design and selection. • Highlighted integration of simulation, robotic synthesis, and rapid screening. • Showed the promise of autonomous antimicrobial discovery platforms. • Provided an outlook on smart systems to combat resistant pathogens.
Keywords:
Antimicrobial peptide design
drug resistance
high throughput molecular simulations
machine learning
statistical optimization
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