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Updates every hour. Last Updated: 30-Apr-2025 20:08 ET (1-May-2025 00:08 GMT/UTC)
Researchers have developed a powerful tool that can detect variants of SARS-CoV-2 with high transmission potential before they become widespread. This approach could significantly support public health efforts to control outbreaks and help identify new variants that need closer monitoring.
Researchers from Zhejiang University and HKUST (Guangzhou) have introduced ProtET, an innovative AI-powered multi-modal protein editing model published in Health Data Science. ProtET leverages advanced transformer-structured encoders and a hierarchical training paradigm to align protein sequences with natural language instructions, enabling precise and controllable protein editing.
The model was trained on over 67 million protein-biotext pairs from Swiss-Prot and TrEMBL databases and demonstrated significant improvements across key benchmarks, including 16.9% enhanced protein stability, optimized enzyme catalytic activity, and improved antibody-antigen binding affinity. ProtET’s zero-shot capabilities successfully designed SARS-CoV antibodies with stable 3D structures, highlighting its real-world biomedical applications.
This research represents a major advancement in AI-driven protein engineering, offering a scalable and interactive tool for scientific discovery, synthetic biology, and therapeutic development.