Antiprotozoal peptide prediction using machine learning with effective feature selection techniques.

ABSTRACT:

Background

Protozoal pathogens pose a considerable threat, leading to notable mortality rates and the ongoing challenge of developing resistance to drugs. This situation underscores the urgent need for alternative therapeutic approaches. Antimicrobial peptides stand out as promising candidates for drug development. However, there is a lack of published research focusing on predicting antimicrobial peptides specifically targeting protozoal pathogens. In this study, we introduce a successful machine learning-based framework designed to predict potential antiprotozoal peptides effective against protozoal pathogens.

Objective

The primary objective of this study is to classify and predict antiprotozoal peptides using diverse negative datasets.

Methods

A comprehensive liter

SUBMITTER: Periwal N 

PROVIDER: S-EPMC11380031 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature