CARS-AMP: A Simple and Efficient Deep Learning Model for Antimicrobial Peptide Prediction
peptides. In addition, we further test the ability of the model to distinguish similar sequences by comparing it with the experimental results of the ZXR-2 series of peptides, and the results suggest that the model may need improvement to discern the differences in side chain size and sequence length. The CARS-AMP model provides a simple predictor with high efficiency and could be further improved to achieve better performance and wider application in identifying AMPs.
Authors
- Xinyao Guan
- Pengfei Pei (ORCID: https://orcid.org/0009-0005-6710-1089)
- L Chen
- Huangzi Yan
- Shi-Zhong Luo
- Ruichen Lin
Institutions
- Wuhan Donghu University (CN)
- Green Chemistry (PL)
- Beijing University of Chemical Technology (CN)
Publication Details
- Journal
- Journal of Chemical Information and Modeling
- Published
- 2026-05-01
- DOI
- https://doi.org/10.1021/acs.jcim.6c00362
- Primary Topic
- Antimicrobial Peptides and Activities
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Beijing University of Chemical Technology
- Beijing Municipal Natural Science Foundation
- National Key Research and Development Program of China
- China-Japan Friendship Hospital