Computational Prospecting for Novel Peptide Therapeutics: AI-Assisted Discovery of Antimicrobial Peptide Candidates from Metagenomic Data
Published: 1 September 2026| Version 1 | DOI: 10.17632/s8zh59fbhz.1
Contributors:
Samsus Saintloth, connor aamott, leslie fontaine, manjit kaur, theresa millerDescription
the project improves efficiency in candidate identification. Instead of 2 experimentally testing large numbers of random sequences, companies could use the machine learning model and downstream filtering steps, such as similarity analysis and characterization, to focus on the most promising peptides. This reduces time and cost in the earliest stages of development, where attrition is typically high.
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Institutions
- University of Maryland Global CampusMaryland, Adelphi
Categories
Bioinformatics