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Conserved Binding Sites01:49

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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Lineage-specific mutational clustering in protein structures predicts evolutionary shifts in function.

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We developed a method to detect spatially clustered mutations in protein evolution, identifying over 19,000 lineages with significant clusters. This approach reveals functional shifts and new candidates for experimental study in protein families.

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Area of Science:

  • Evolutionary biology
  • Structural biology
  • Bioinformatics

Background:

  • Spatially clustered mutations in proteins often indicate positive selection for new functions, particularly in cancer oncoproteins.
  • Previous methods focused on pairwise comparisons, leaving the utility for phylogenetic analysis unexplored.

Purpose of the Study:

  • To adapt and extend spatial substitution clustering methods for phylogenetic branch analysis.
  • To investigate the capacity of this approach to identify historical functional shifts in protein families.

Main Methods:

  • Implemented and enhanced the P3D statistic for detecting spatially clustered substitutions on phylogenetic branches.
  • Analyzed 423,690 vertebrate protein family branches from 9,261 families.
  • Examined enrichment of clusters in ligand-binding sites and specific protein families (e.g., C2H2 transcription factors, protein kinases).

Main Results:

  • Identified 19,607 lineages across 5,362 protein families with significant spatial substitution clustering (P3D < 0.01).
  • Spatially clustered substitutions were enriched in ligand-binding residues and specific protein families.
  • Detected functional shifts and new interactions in ancient adaptations of proteins like SLC7A2, PTEN, and SNAP25.

Conclusions:

  • Lineage-specific, spatially clustered substitutions are valuable indicators of functional shifts in protein evolution.
  • The developed method successfully identifies historical functional changes and provides new candidates for experimental validation.