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Characterize direct protein interactions with enrichable, cleavable and latent bioreactive unnatural amino acids.

Dan-Dan LiuWenlong DingJin-Tao ChengQiushi WeiYinuo LinTian-Yi ZhuJing TianKe SunJisheng LiuPeilong LuFan YangChao LiuShibing TangBing Yang
Published in: Nature communications (2024)
Latent bioreactive unnatural amino acids (Uaas) have been widely used in the development of covalent drugs and identification of protein interactors, such as proteins, DNA, RNA and carbohydrates. However, it is challenging to perform high-throughput identification of Uaa cross-linking products due to the complexities of protein samples and the data analysis processes. Enrichable Uaas can effectively reduce the complexities of protein samples and simplify data analysis, but few cross-linked peptides were identified from mammalian cell samples with these Uaas. Here we develop an enrichable and multiple amino acids reactive Uaa, eFSY, and demonstrate that eFSY is MS cleavable when eFSY-Lys and eFSY-His are the cross-linking products. An identification software, AixUaa is developed to decipher eFSY mass cleavable data. We systematically identify direct interactomes of Thioredoxin 1 (Trx1) and Selenoprotein M (SELM) with eFSY and AixUaa.
Keyphrases
  • amino acid
  • data analysis
  • high throughput
  • protein protein
  • multiple sclerosis
  • binding protein
  • stem cells
  • ms ms
  • circulating tumor
  • machine learning
  • electronic health record
  • cell free
  • mesenchymal stem cells