33 citations · 43 across the 13 of their papers we have counts for
5 papers · 1 filter
ODesign: A World Model for Biomolecular Interaction Design
Odin Zhang, Xujun Zhang, Haitao Lin +34
Biomolecular interactions underpin almost all biological processes, and their rational design is central to programming new biological functions. Generative AI models have emerged…
BioScore: A Foundational Scoring Function For Diverse Biomolecular Complexes
Yuchen Zhu, Jihong Chen, Yitong Li +9
Structural assessment of biomolecular complexes is vital for translating molecular models into functional insights, shaping our understanding of biology and aiding drug discovery.…
Graph Neural Networks in Modern AI-aided Drug Discovery
Odin Zhang, Haitao Lin, Xujun Zhang +9
Graph neural networks (GNNs), as topology/structure-aware models within deep learning, have emerged as powerful tools for AI-aided drug discovery (AIDD). By directly operating on m…
AutoLoop: a novel autoregressive deep learning method for protein loop prediction with high accuracy
Tianyue Wang, Xujun Zhang, Langcheng Wang +12
Protein structure prediction is a critical and longstanding challenge in biology, garnering widespread interest due to its significance in understanding biological processes. A par…
ProtFlow: Fast Protein Sequence Design via Flow Matching on Compressed Protein Language Model Embeddings
Zitai Kong, Yiheng Zhu, Yinlong Xu +7
The design of protein sequences with desired functionalities is a fundamental task in protein engineering. Deep generative methods, such as autoregressive models and diffusion mode…