Multi-label classification and features investigation of antimicrobial peptides with various functional classes

Chia Ru Chung, Jhen Ting Liou, Li Ching Wu, Jorng Tzong Horng, Tzong Yi Lee

研究成果: 雜誌貢獻期刊論文同行評審

摘要

The challenge of drug-resistant bacteria to global public health has led to increased attention on antimicrobial peptides (AMPs) as a targeted therapeutic alternative with a lower risk of resistance. However, high production costs and limitations in functional class prediction have hindered progress in this field. In this study, we used multi-label classifiers with binary relevance and algorithm adaptation techniques to predict different functions of AMPs across a wide range of pathogen categories, including bacteria, mammalian cells, fungi, viruses, and cancer cells. Our classifiers attained promising AUC scores varying from 0.8492 to 0.9126 on independent testing data. Forward feature selection identified sequence order and charge as critical, with specific amino acids (C and E) as discriminative. These findings provide valuable insights for the design of antimicrobial peptides (AMPs) with multiple functionalities, thus contributing to the broader effort to combat drug-resistant pathogens.

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文章編號108250
期刊iScience
26
發行號12
DOIs
出版狀態已出版 - 15 12月 2023

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