A conditional denoising VAE-based framework for antimicrobial peptides generation with preserving desirable properties.

ABSTRACT:

Motivation

The widespread use of antibiotics has led to the emergence of resistant pathogens. Antimicrobial peptides (AMPs) combat bacterial infections by disrupting the integrity of cell membranes, making it challenging for bacteria to develop resistance. Consequently, AMPs offer a promising solution to addressing antibiotic resistance. However, the limited availability of natural AMPs cannot meet the growing demand. While deep learning technologies have advanced AMP generation, conventional models often lack stability and may introduce unforeseen side effects.

Results

This study presents a novel denoising VAE-based model guided by desirable physicochemical properties for AMP generation. The model integrates key features (e.g. molecular weight, isoelectric point, hydrophobi

SUBMITTER: Zhao W 

PROVIDER: S-EPMC11850229 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature