Uncovering the potential virulence factors of emerging pathogens using AI/ML-based tools: a case study in <i>Emergomyces africanus</i>.

ABSTRACT:

Background

We are currently in the era of artificial intelligence (AI), which has become deeply embedded across nearly all scientific disciplines. Harnessing this revolutionary technology to predict virulence factors of emerging pathogens can improve our understanding of their pathogenicity, especially since the majority of these pathogens' proteomes are composed of hypothetical or uncharacterized proteins. Moreover, emerging orphan proteins were expressed from novel open reading frames. Therefore, this study aimed to develop a pipeline for predicting and annotating the species-specific secreted protein structures of these pathogens, with Emergomyces africanus selected as a model organism.

Methods

The proteome of E. africanus CBS 136260 was retrieved from the N

SUBMITTER: Farag PF 

PROVIDER: S-EPMC12705615 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature