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Area of Science:

  • Structural biology
  • Computational biology
  • Protein folding

Background:

  • Understanding the link between protein sequence and structure is crucial for deciphering the protein universe.
  • Sequence capacity, the number of sequences folding to a specific structure, is a key metric for protein designability.
  • Previous studies on sequence capacity relied on theoretical models and lattice simulations, lacking estimates for real protein structures.

Purpose of the Study:

  • To quantitatively estimate the sequence capacity for 10 diverse real protein structures.
  • To investigate the relationship between protein structure, size, contact density, and sequence capacity.
  • To explore the correlation between protein evolutionary age and sequence capacity.

Main Methods:

  • Utilized a statistical model incorporating residue-residue co-evolution to analyze sequence variation within protein families.
  • Applied the model to estimate sequence capacity for 10 proteins across various structural classes.
  • Correlated predicted sequence capacity with protein structural features (size, contact density) and evolutionary age from the CATH database.

Main Results:

  • Sequence capacity for even small protein folds, like the WW domain, exceeds the Avogadro constant.
  • Absolute sequence capacity positively correlates with protein size and contact density, allowing structure-based prediction.
  • Relative sequence capacity is inversely correlated with protein length, indicating increased difficulty in finding foldable sequences for larger proteins.
  • A trade-off was observed between high designability (sequence capacity) and the emergence of novel folds over evolutionary time.

Conclusions:

  • The study provides the first numerical estimates of sequence capacity for real protein structures.
  • Protein structure dictates both the absolute number of foldable sequences and the relative difficulty of finding them.
  • Evolutionary trends suggest a balance between optimizing existing folds (high designability) and the potential for new fold discovery.