Prediction of the synergistic effect of antimicrobial peptides and antimicrobial agents via supervised machine learning.

ABSTRACT:

Background

Infectious diseases not only cause severe health problems but also burden the healthcare system. Therefore, the effective treatment of those diseases is crucial. Both conventional approaches, such as antimicrobial agents, and novel approaches, like antimicrobial peptides (AMPs), are used to treat infections. However, due to the drawbacks of current approaches, new solutions are still being investigated. One recent approach is the use of AMPs and antimicrobial agents in combination, but determining synergism is with a huge variety of AMPs time-consuming and requires multiple experimental studies. Machine learning (ML) algorithms are widely used to predict biological outcomes, particularly in the field of AMPs, but no previous research reported on predicting the synergisti

SUBMITTER: Olcay B 

PROVIDER: S-EPMC10792927 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature