5 papers
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…
A Generalist Cross-Domain Molecular Learning Framework for Structure-Based Drug Discovery
Yiheng Zhu, Mingyang Li, Junlong Liu +7
Structure-based drug discovery (SBDD) is a systematic scientific process that develops new drugs by leveraging the detailed physical structure of the target protein. Recent advance…
ProtCLIP: Function-Informed Protein Multi-Modal Learning
Hanjing Zhou, Mingze Yin, Wei Wu +5
Multi-modality pre-training paradigm that aligns protein sequences and biological descriptions has learned general protein representations and achieved promising performance in var…
SALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning
Mingze Yin, Hanjing Zhou, Jialu Wu +8
Antibodies safeguard our health through their precise and potent binding to specific antigens, demonstrating promising therapeutic efficacy in the treatment of numerous diseases, i…
Bridge-IF: Learning Inverse Protein Folding with Markov Bridges
Yiheng Zhu, Jialu Wu, Qiuyi Li +7
Inverse protein folding is a fundamental task in computational protein design, which aims to design protein sequences that fold into the desired backbone structures. While the deve…