Accurate sequence-to-affinity models for SH2 domains from multi-round peptide binding assays coupled with free-energy regression
2024

Improving SH2 Domain Binding Predictions

publication

Author Information

Author(s): Gagoski Dejan, Rube Tomas, Rastogi Chaitanya, Melo Lucas, Li Xiaoting, Voleti Rashmi, Shah Neel H., Bussemaker Harmen J.

Primary Institution: Cold Spring Harbor Laboratory

Hypothesis

Can we enhance the predictive power of SH2 domain specificity profiling using multi-round peptide binding assays and computational models?

Conclusion

The study developed a method that significantly improves the prediction of SH2 domain binding affinities.

Supporting Evidence

  • SH2 domains are crucial for cell signaling and bind specifically to tyrosine-phosphorylated proteins.
  • Recent advancements in protein display technologies have enabled profiling of SH2 domain binding across many ligands.
  • The developed models can predict the effects of genetic variants on SH2 binding.

Takeaway

This study helps scientists better understand how certain proteins interact, which is important for cell signaling.

Methodology

The researchers used multi-round affinity selection and deep sequencing with large randomized phosphopeptide libraries to gather data for training a binding free energy model.

Digital Object Identifier (DOI)

10.1101/2024.12.23.630085

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