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August 20, 2025Proceedings of the National Academy of SciencesOpen Access

Protein functional site annotation using local structure embeddings

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Authors

ADAlexander DerryUniversity of LeedsATAlp TarticiPalo Alto University
Russ B. Altman
Russ B. AltmanStanford University

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Implication

PARSE predicts enzyme catalytic functions in proteins, suggesting local structural features are vital for annotation.

Key Points

  • PARSE achieves over 85% F1 score in predicting enzyme function, showcasing superior precision in residue annotation.
  • The method effectively leverages local structure embeddings while integrating traditional statistical techniques for function prediction.
  • Unsupervised predictions for rare protein functions can be performed, thus extending annotation capabilities beyond common labels.
  • Utilizing the AlphaFold Structure Database, the approach identifies bacterial metalloproteases within the dark proteome, demonstrating functional discovery potential.

Cite This Study

Derry et al. (2025) studied this question.

synapsesocial.com/papers/68af55dead7bf08b1eadc9dbhttps://doi.org/10.1073/pnas.2513219122
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