Nothing about protein structure classification makes sense except in the light of evolution

Area of Science:

• Evolutionary biology
• Structural bioinformatics
• Biochemistry

Background:

• Protein structure classification traditionally relies on homologous sequence relationships.
• Protein structure is more conserved than amino acid sequence.
• This conservation offers opportunities for deeper evolutionary analysis.

Purpose of the Study:

• To propose a novel protein structure classification scheme based on evolutionary principles.
• To leverage the conserved nature of protein structure for classifying distant evolutionary relationships.
• To differentiate between ancestral and derived protein structures.

Main Methods:

• Revisiting protein structure classification from an evolutionary perspective.
• Utilizing conserved structural features beyond sequence homology.
• Developing an iterative classification approach to identify distant evolutionary links.

Main Results:

• Demonstrated that protein structure is a more robust indicator of evolutionary relationships than sequence alone.
• Proposed a classification system where folds are considered semantic, and structures are categorized as ancestral or derived.
• Enabled the identification of deeper evolutionary connections between protein structures.

Conclusions:

• An evolutionary perspective enhances protein structure classification.
• Classifying structures as ancestral or derived reveals deeper evolutionary history.
• This approach refines our understanding of protein evolution and relationships.