Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides.

ABSTRACT:

Introduction

Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics, possess a variety of potent biological activities and exhibit immunomodulatory effects that alleviate difficult-to-treat infections. Clarifying the structure-activity relationships of AMPs can direct the synthesis of desirable peptide therapeutics.

Objectives

In this study, the lipopolysaccharide-binding domain (LBD) was identified through machine learning-guided directed evolution, which acts as a functional domain of the anti-lipopolysaccharide factor family of AMPs identified from Marsupenaeus japonicus.

Methods

LBD_A-D was identified as an output of this algorithm, in which the original LBD_Mj sequence was the input, and the three-dimensional soluti

SUBMITTER: Zhang H 

PROVIDER: S-EPMC11785909 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature