no code implementations • 28 May 2024 • Yuanle Mo, Xin Hong, Bowen Gao, Yinjun Jia, Yanyan Lan
Protein-protein interactions are central mediators in many biological processes.
no code implementations • 4 Mar 2024 • Bowen Gao, Minsi Ren, Yuyan Ni, Yanwen Huang, Bo Qiang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan
In the field of Structure-based Drug Design (SBDD), deep learning-based generative models have achieved outstanding performance in terms of docking score.
no code implementations • 1 Nov 2023 • Minsi Ren, Bowen Gao, Bo Qiang, Yanyan Lan
Structure-based drug design (SBDD) stands at the forefront of drug discovery, emphasizing the creation of molecules that target specific binding pockets.
no code implementations • 11 Oct 2023 • Bowen Gao, Yinjun Jia, Yuanle Mo, Yuyan Ni, WeiYing Ma, ZhiMing Ma, Yanyan Lan
Pocket representations play a vital role in various biomedical applications, such as druggability estimation, ligand affinity prediction, and de novo drug design.
1 code implementation • 10 Oct 2023 • Bowen Gao, Bo Qiang, Haichuan Tan, Minsi Ren, Yinjun Jia, Minsi Lu, Jingjing Liu, WeiYing Ma, Yanyan Lan
Virtual screening, which identifies potential drugs from vast compound databases to bind with a particular protein pocket, is a critical step in AI-assisted drug discovery.
no code implementations • 29 Jul 2023 • Sen Fang, Bowen Gao, Yangjian Wu, Teik Toe Teoh
Multimodal large models have been recognized for their advantages in various performance and downstream tasks.
1 code implementation • 5 May 2023 • Bo Qiang, Yuxuan Song, Minkai Xu, Jingjing Gong, Bowen Gao, Hao Zhou, WeiYing Ma, Yanyan Lan
Generating desirable molecular structures in 3D is a fundamental problem for drug discovery.
no code implementations • 8 Mar 2023 • Sen Fang, Yangjian Wu, Bowen Gao, Jingwen Cai, Teik Toe Teoh
Recently, researchers have gradually realized that in some cases, the self-supervised pre-training on large-scale Internet data is better than that of high-quality/manually labeled data sets, and multimodal/large models are better than single or bimodal/small models.