2. Academic Validation
  3. A dual-view deep learning-driven discovery of cinnamoyl anthranilic acid derivatives against orthopoxvirus through targeting host ITGB3

A dual-view deep learning-driven discovery of cinnamoyl anthranilic acid derivatives against orthopoxvirus through targeting host ITGB3

  • Eur J Med Chem. 2025 Nov 15:298:118002. doi: 10.1016/j.ejmech.2025.118002.
Mengyi Xu 1,  Fan Liu 2,  Xiaosa Zhao 3,  Jing Pang 4,  Xixi Guo 5,  Shijiao Feng 1,  Zhiwen Li 5,  Yanan Ni 4,  Yinghong Li 4,  Minghao Yin 3,  Weijin Huang 6,  Danqing Song 7,  Yanxiang Wang 8
Affiliations

Affiliations

  • 1 Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China; Institute of Health and Medicine, Hefei Comprehensive National Science Center, Hefei, 230601, Anhui, China.
  • 2 Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, 102629, China.
  • 3 School of Information Science and Technology, Northeast Normal University, Changchun, 130117, China.
  • 4 Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
  • 5 Institute of Health and Medicine, Hefei Comprehensive National Science Center, Hefei, 230601, Anhui, China.
  • 6 Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, 102629, China. Electronic address: huangweijin@nifdc.org.cn.
  • 7 Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China. Electronic address: songdanqing@imb.pumc.edu.cn.
  • 8 Institute of Health and Medicine, Hefei Comprehensive National Science Center, Hefei, 230601, Anhui, China. Electronic address: wangyanxiang@ihm.ac.cn.
PMID: 40749255 DOI: 10.1016/j.ejmech.2025.118002
Abstract

The Orthopoxvirus genus, particularly the monkeypox virus (MPXV), continues to pose a significant global public health threat. Therefore, the development of novel anti-orthopoxvirus agents remains an urgent priority. Machine learning has proven to be an effective approach for identifying potential drug candidates. In this study, we implemented a dual-view deep learning model that combines BERT and a graph neural network to analyze molecular sequences and structural graphs. The model was trained following a pre-training-then-fine-tuning paradigm and was subsequently applied to identify new molecules with potential anti-orthopoxvirus activity. Notably, a cinnamoyl anthranilic acid derivative (compound 6) was successfully predicted and demonstrated potent anti-orthopoxvirus effects both in vitro and in vivo. Furthermore, Integrin subunit beta 3 (ITGB3) has been validated as one of the direct target protein of 6. In conclusion, we established a robust dual-view deep learning model for the discovery of novel anti-orthopoxvirus agents, and compound 6 is a promising candidate for Orthopoxvirus treatment via ITGB3 targeting.

Keywords

Anti-orthopoxvirus; Dual-view deep learning; Integrin beta 3; Photoaffinity probe; Target identification.

Figures
Products
嗨！很高兴为您提供帮助！

尊敬的 MCE 客户您好，
请您选择所在区域，我们将转接对应客服为您服务！

热门区域

A

B

C

F

G

H

J

L

N

Q

S

T

X

Y

Z

热 A B C F G H J L N Q S T X Y Z