AI Article Synopsis

  • Recent advancements in structural biology, especially cryoelectron microscopy, have improved our ability to model proteins, but some remain difficult to analyze due to factors like low stability and abundance.
  • The study introduces cross-linking mass spectrometry (XL-MS) as a powerful tool for assessing protein structures, allowing researchers to analyze a large dataset of protein interactions and structures.
  • By presenting the largest XL-MS dataset, this research demonstrates how combining XL-MS data with AlphaFold2 predictions can enhance our understanding of the structural proteome and reveal insights into protein function.

Article Abstract

Significant recent advances in structural biology, particularly in the field of cryoelectron microscopy, have dramatically expanded our ability to create structural models of proteins and protein complexes. However, many proteins remain refractory to these approaches because of their low abundance, low stability, or-in the case of complexes-simply not having yet been analyzed. Here, we demonstrate the power of using cross-linking mass spectrometry (XL-MS) for the high-throughput experimental assessment of the structures of proteins and protein complexes. This included those produced by high-resolution but in vitro experimental data, as well as in silico predictions based on amino acid sequence alone. We present the largest XL-MS dataset to date, describing 28,910 unique residue pairs captured across 4,084 unique human proteins and 2,110 unique protein-protein interactions. We show that models of proteins and their complexes predicted by AlphaFold2, and inspired and corroborated by the XL-MS data, offer opportunities to deeply mine the structural proteome and interactome and reveal mechanisms underlying protein structure and function.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10151615PMC
http://dx.doi.org/10.1073/pnas.2219418120DOI Listing

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