SCOPE-DTI: Semi-Inductive Dataset Construction and Framework Optimization for Practical Usability Enhancement in Deep Learning-Based Drug Target Interaction Prediction

• URL: http://arxiv.org/abs/2503.09251v1
• Date: Wed, 12 Mar 2025 10:46:25 GMT
• Title: SCOPE-DTI: Semi-Inductive Dataset Construction and Framework Optimization for Practical Usability Enhancement in Deep Learning-Based Drug Target Interaction Prediction
• Authors: Yigang Chen, Xiang Ji, Ziyue Zhang, Yuming Zhou, Yang-Chi-Dung Lin, Hsi-Yuan Huang, Tao Zhang, Yi Lai, Ke Chen, Chang Su, Xingqiao Lin, Zihao Zhu, Yanggyi Zhang, Kangping Wei, Jiehui Fu, Yixian Huang, Shidong Cui, Shih-Chung Yen, Ariel Warshel, Hsien-Da Huang,
• Abstract summary: SCOPE-DTI is a unified framework combining a large-scale, balanced semi-inductive human DTI dataset with advanced deep learning modeling.<n>The SCOPE dataset expands data volume by up to 100-fold compared to common benchmarks such as the Human dataset.<n>By offering comprehensive data, advanced modeling, and accessible tools, SCOPE-DTI accelerates drug discovery research.
• Score: 15.996998422919111
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Deep learning-based drug-target interaction (DTI) prediction methods have demonstrated strong performance; however, real-world applicability remains constrained by limited data diversity and modeling complexity. To address these challenges, we propose SCOPE-DTI, a unified framework combining a large-scale, balanced semi-inductive human DTI dataset with advanced deep learning modeling. Constructed from 13 public repositories, the SCOPE dataset expands data volume by up to 100-fold compared to common benchmarks such as the Human dataset. The SCOPE model integrates three-dimensional protein and compound representations, graph neural networks, and bilinear attention mechanisms to effectively capture cross domain interaction patterns, significantly outperforming state-of-the-art methods across various DTI prediction tasks. Additionally, SCOPE-DTI provides a user-friendly interface and database. We further validate its effectiveness by experimentally identifying anticancer targets of Ginsenoside Rh1. By offering comprehensive data, advanced modeling, and accessible tools, SCOPE-DTI accelerates drug discovery research.

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