AI4AVP: an antiviral peptides predictor in deep learning approach with generative adversarial network data augmentation

Tzu-Tang Lin; Yih-Yun Sun; Ching-Tien Wang; Wen-Chih Cheng; I-Hsuan Lu; Chung-Yen Lin; Shu-Hwa Chen

doi:10.1093/bioadv/vbac080

AI4AVP: an antiviral peptides predictor in deep learning approach with generative adversarial network data augmentation

Bioinform Adv. 2022 Oct 26;2(1):vbac080. doi: 10.1093/bioadv/vbac080. eCollection 2022.

Authors

Tzu-Tang Lin¹, Yih-Yun Sun^{1

2}, Ching-Tien Wang¹, Wen-Chih Cheng¹, I-Hsuan Lu¹, Chung-Yen Lin^{1

3

4}, Shu-Hwa Chen⁵

Affiliations

¹ Institute of Information Science, Academia Sinica, Taipei 115, Taiwan.
² Graduate Institute of Biomedical Electronics and Bioinformatics, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei 106, Taiwan.
³ Institute of Fisheries Science, National Taiwan University, Taipei 106, Taiwan.
⁴ Genome and Systems Biology Degree Program, National Taiwan University, Taipei 106, Taiwan.
⁵ TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei 110, Taiwan.

Abstract

Motivation: Antiviral peptides (AVPs) from various sources suggest the possibility of developing peptide drugs for treating viral diseases. Because of the increasing number of identified AVPs and the advances in deep learning theory, it is reasonable to experiment with peptide drug design using in silico methods.

Results: We collected the most up-to-date AVPs and used deep learning to construct a sequence-based binary classifier. A generative adversarial network was employed to augment the number of AVPs in the positive training dataset and enable our deep learning convolutional neural network (CNN) model to learn from the negative dataset. Our classifier outperformed other state-of-the-art classifiers when using the testing dataset. We have placed the trained classifiers on a user-friendly web server, AI4AVP, for the research community.

Availability and implementation: AI4AVP is freely accessible at http://axp.iis.sinica.edu.tw/AI4AVP/; codes and datasets for the peptide GAN and the AVP predictor CNN are available at https://github.com/lsbnb/amp_gan and https://github.com/LinTzuTang/AI4AVP_predictor.

Supplementary information: Supplementary data are available at Bioinformatics Advances online.