Core Insights - The article discusses the development of a novel protein language model (PLM) called Saprot, which integrates one-dimensional amino acid sequences with three-dimensional structural information to enhance protein structure and function prediction [2][9][19] - The launch of the open-source platform SaprotHub aims to democratize access to advanced PLMs for researchers in the life sciences, bridging the gap between AI developers and biologists [3][8][19] Group 1: Challenges in Protein Research - Protein research faces significant challenges due to the technical expertise required for training and deploying advanced AI models, which creates a barrier for biologists engaged in experimental research [5][19] - The complexity of programming environments, data preprocessing, and model training limits the widespread adoption of AI technologies in fields like medicine and biotechnology [5] Group 2: SaprotHub and Its Components - SaprotHub is a comprehensive ecosystem that combines cutting-edge AI model technology, open-source tools, and a global community to facilitate collaboration in protein research [8][19] - The core engine, Saprot, has been trained using millions of protein structures predicted by AlphaFold2, utilizing 64 NVIDIA A100 GPUs, and has demonstrated superior performance in various protein function prediction tasks [9][19] Group 3: Open-Source Tools and Global Collaboration - The ColabSaprot platform simplifies the training of protein language models, allowing researchers without programming backgrounds to easily engage with advanced AI tools [10][19] - The Open Protein Modeling Consortium (OPMC) is a collaborative initiative that includes top research institutions worldwide, aiming to foster the development of the protein field through shared resources and knowledge [11][19] Group 4: Validation and Real-World Applications - The effectiveness of SaprotHub has been validated through user studies and various biological experiments, showing that non-AI researchers can achieve results comparable to AI experts [12][19] - Successful applications include enhancing the activity of an industrial enzyme by 2.55 times, optimizing gene editing tools for doubled efficiency, and designing a new fluorescent protein with over eight times the brightness of the original [18][19]