AI Proteomics: From Protein Identification to Virtual Cells

Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells. These include improving peptide and protein identification and quantification, which is critical for understanding protein function and regulation. AI algorithms can analyze large datasets and identify patterns that may not be apparent to human researchers, leading to more accurate and efficient protein identification. Another area of focus is characterizing protein-protein interactions and protein complexes, which is essential for understanding cellular function and behavior. AI can help analyze large datasets of protein interactions and identify new interactions that may not have been previously known. Additionally, AI is advancing spatial and perturbation proteomics, which involves studying protein behavior in specific cellular contexts. This can provide valuable insights into protein function and regulation. Integrating multi-omics data is another area where AI is making significant contributions. By combining data from different omics fields, such as genomics, transcriptomics, and proteomics, AI can provide a more comprehensive understanding of cellular function and behavior. Ultimately, the goal is to enable AI virtual cells, which are computational models of cellular behavior that can be used to simulate and predict cellular responses to different stimuli. This has the potential to revolutionize our understanding of cellular function and behavior. However, to achieve this goal, we need a global collaboration among data producers, data consumers, and other stakeholders to establish an AI-friendly ecosystem for MS-based proteomics. This collaboration will be critical for laying the foundation for transformative advancements in proteomics driven by AI. Due to the research-use-only nature of the peptides provided by this supplier, the results of this research should not be used for clinical applications or to make any claims about the efficacy of the peptides. The peptides provided are for laboratory use only and should be used in accordance with all applicable laws and regulations. The supplier makes no claims about the results of this research or the efficacy of the peptides provided.