Protein Language Models and Machine Learning Facilitate the Identification of Antimicrobial Peptides.

ABSTRACT: Peptides are bioactive molecules whose functional versatility in living organisms has led to successful applications in diverse fields. In recent years, the amount of data describing peptide sequences and function collected in open repositories has substantially increased, allowing the application of more complex computational models to study the relations between the peptide composition and function. This work introduces AMP-Detector, a sequence-based classification model for the detection of peptides' functional biological activity, focusing on accelerating the discovery and de novo design of potential antimicrobial peptides (AMPs). AMP-Detector introduces a novel sequence-based pipeline to train binary classification models, integrating protein language models and machine learning algor

SUBMITTER: Medina-Ortiz D 

PROVIDER: S-EPMC11487388 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature