Designer artificial environments for membrane protein synthesis.

Journal: Nature communications
PMID: 40348791

Abstract

Protein synthesis in natural cells involves intricate interactions between chemical environments, protein-protein interactions, and protein machinery. Replicating such interactions in artificial and cell-free environments can control the precision of protein synthesis, elucidate complex cellular mechanisms, create synthetic cells, and discover new therapeutics. Yet, creating artificial synthesis environments, particularly for membrane proteins, is challenging due to the poorly defined chemical-protein-lipid interactions. Here, we introduce MEMPLEX (Membrane Protein Learning and Expression), which utilizes machine learning and a fluorescent reporter to rapidly design artificial synthesis environments of membrane proteins. MEMPLEX generates over 20,000 different artificial chemical-protein environments spanning 28 membrane proteins. It captures the interdependent impact of lipid types, chemical environments, chaperone proteins, and protein structures on membrane protein synthesis. As a result, MEMPLEX creates new artificial environments that successfully synthesize membrane proteins of broad interest but previously intractable. In addition, we identify a quantitative metric, based on the hydrophobicity of the membrane-contacting amino acids, that predicts membrane protein synthesis in artificial environments. Our work allows others to rapidly study and resolve the "dark" proteome using predictive generation of artificial chemical-protein environments. Furthermore, the results represent a new frontier in artificial intelligence-guided approaches to creating synthetic environments for protein synthesis.

Authors

  • Conary Meyer
    Department of Biomedical Engineering, University of California, Davis, Davis, CA, 95616, USA.
  • Alessandra Arizzi
    Department of Biomedical Engineering, University of California, Davis, Davis, CA, 95616, USA.
  • Tanner Henson
    Department of Biomedical Engineering, University of California, Davis, Davis, CA, 95616, USA.
  • Sharon Aviran
    Department of Biomedical Engineering, University of California, Davis, Davis, CA, 95616, USA.
  • Marjorie L Longo
    Department of Chemical Engineering, University of California, Davis, Davis, CA, 95616, USA.
  • Aijun Wang
    Department of Biomedical Engineering, University of California, Davis, Davis, CA, 95616, USA.
  • Cheemeng Tan
    Department of Biomedical Engineering, University of California, Davis, Davis, CA, 95616, USA. cmtan@ucdavis.edu.

Keywords

External Resources

Popular Topics
Recent Journals