CMMSCL-DPI: cross-modal multi-structural contrastive learning for predicting drug-protein interactions

This case study not only confirms the predictive accuracy of CMMSCL-DPI but also underscores its potential in discovering novel protein-ligand interactions.

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Publication Details

Journal
BMC Biology
Published
2026-02-09
DOI
https://doi.org/10.1186/s12915-026-02533-7
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

CMMSCL-DPI: cross-modal multi-structural contrastive learning for predicting drug-protein interactions

Xingyue Gu, Junkai Liu, Pengfeng Xiao, Xiaoyi Guo et al.
BMC Biology
Computational Drug Discovery Methods
article

CMMSCL-DPI: cross-modal multi-structural contrastive learning for predicting drug-protein interactions

Xingyue Gu, Junkai Liu, Pengfeng Xiao, Xiaoyi Guo, Xin Zhang, Yijie Ding, Quan Zou, Yue Yu
article en

Abstract

This case study not only confirms the predictive accuracy of CMMSCL-DPI but also underscores its potential in discovering novel protein-ligand interactions.

BMC BiologyVol. 24(1)
University of Electronic Science and Technology of China (CN), Harbin Institute of Technology (CN), Yang-En University (CN), University College Birmingham (GB), Quzhou City People's Hospital (CN), Southeast University (BD), Quzhou University (CN), Wuxi Vocational Institute of Commerce (CN), Heilongjiang Institute of Technology (CN), Wuxi Vocational College of Science and Technology, State Key Laboratory of Digital Medical Engineering (CN), Southeast University (CN), University of Birmingham (GB)
Quality Education
Openalex Percentile: Top 60%
Computational Drug Discovery Methods
DOIOpen Access PDFOpenAlex
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CMMSCL-DPI: cross-modal multi-structural contrastive learning for predicting drug-protein interactions — Xingyue Gu, Junkai Liu, et al. · BMC Biology (2026) | TGRS Research Map | TGRS