Login / Signup

Structural Isosteres of Phosphate Groups in the Protein Data Bank.

Yuezhou ZhangAlexandre BorrelLeo GhemtioLeslie RegadGustav Boije Af GennäsAnne-Claude CamprouxJari T Yli-KauhaluomaHenri Xhaard
Published in: Journal of chemical information and modeling (2017)
We developed a computational workflow to mine the Protein Data Bank for isosteric replacements that exist in different binding site environments but have not necessarily been identified and exploited in compound design. Taking phosphate groups as examples, the workflow was used to construct 157 data sets, each composed of a reference protein complexed with AMP, ADP, ATP, or pyrophosphate as well other ligands. Phosphate binding sites appear to have a high hydration content and large size, resulting in U-shaped bioactive conformations recurrently found across unrelated protein families. A total of 16 413 replacements were extracted, filtered for a significant structural overlap on phosphate groups, and sorted according to their SMILES codes. In addition to the classical isosteres of phosphate, such as carboxylate, sulfone, or sulfonamide, unexpected replacements that do not conserve charge or polarity, such as aryl, aliphatic, or positively charged groups, were found.
Keyphrases
  • electronic health record
  • protein protein
  • amino acid
  • big data
  • deep learning