SAMPpred-GAT: prediction of antimicrobial peptide by graph attention network and predicted peptide structure.

ABSTRACT:

Motivation

Antimicrobial peptides (AMPs) are essential components of therapeutic peptides for innate immunity. Researchers have developed several computational methods to predict the potential AMPs from many candidate peptides. With the development of artificial intelligent techniques, the protein structures can be accurately predicted, which are useful for protein sequence and function analysis. Unfortunately, the predicted peptide structure information has not been applied to the field of AMP prediction so as to improve the predictive performance.

Results

In this study, we proposed a computational predictor called sAMPpred-GAT for AMP identification. To the best of our knowledge, sAMPpred-GAT is the first approach based on the predicted peptide structures for AMP predictio

SUBMITTER: Yan K 

PROVIDER: S-EPMC9805557 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature