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FunTree: advances in a resource for exploring and contextualising protein function evolution.

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The FunTree database now integrates protein sequence, structure, and function for over 2300 superfamilies, including non-enzymatic proteins. This expanded resource aids in analyzing functional evolution and trends across diverse protein families.

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Area of Science:

  • Bioinformatics
  • Structural Biology
  • Evolutionary Biology

Background:

  • The FunTree database originally focused on 276 enzyme superfamilies, integrating protein sequence, structure, and functional data.
  • Expanding functional and structural information is crucial for understanding protein evolution and diversity.

Purpose of the Study:

  • To present an updated version of FunTree with a significantly expanded scope.
  • To enable the investigation of functional evolution within structurally defined superfamilies for both enzymes and non-enzymes.
  • To provide new tools for analyzing functional trends and relationships across a broader range of proteins.

Main Methods:

  • Integrated 2340 superfamilies, including enzymes and non-enzymatic proteins annotated with Gene Ontology (GO) terms.
  • Developed new functional similarity measures for enzymes (reaction centers, bond changes, metabolite similarity) and non-enzymes (GO semantic similarity).
  • Incorporated ancestral character estimation to track functional changes throughout evolution.

Main Results:

  • The updated FunTree database now encompasses a much larger and more diverse set of protein superfamilies.
  • Novel methods for quantifying functional similarity provide deeper insights into enzyme and non-enzyme functions.
  • Ancestral character estimations highlight evolutionary trajectories of protein functions.

Conclusions:

  • The expanded FunTree resource facilitates comprehensive analysis of protein function evolution.
  • The integration of diverse functional data and new analytical tools enhances our understanding of protein superfamily dynamics.
  • The redesigned web interface offers improved accessibility for exploring protein sequence, structure, and function relationships.