Peer-Reviewed Publication
Brief Bioinform2025;26(3)May 1, 2025Journal Article
Rag2Mol: structure-based drug design based on retrieval augmented generation.
Peidong Zhang1,2, Xingang Peng3,4, Rong Han1,2, Ting Chen1,2,5, Jianzhu Ma6,7
1Department of Computer Science and Technology, Tsinghua University, Haidian District, Beijing 100084, China.
2Institute of Artificial Intelligence, Tsinghua University, Haidian District, Beijing 100084, China.
3Institute for Artificial Intelligence, Peking University, Haidian District, Beijing 100084, China.
4School of Intelligence Science and Technology, Peking University, Haidian District, Beijing 100084, China.
5Department of Bioinformatics, School of Medical Technology and Engineering, Fujian Medical University, Taijiang District, Fuzhou 350004, China.
6Department of Electronic Engineering, Tsinghua University, Haidian District, Beijing 100084, China.
7Institute for AI Industry Research (AIR), Tsinghua University, Haidian District, Beijing 100084, China.
Abstract
Artificial intelligence (AI) has brought tremendous progress to drug discovery, yet identifying hit and lead compounds with optimal physicochemical and pharmacological properties remains a significant challenge. Structure-based drug design (SBDD) has emerged as a promising paradigm, but the inherent data biases and ignorance of synthetic accessibility render SBDD models disconnected from practical…
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