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The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database
Qian-Yuan Tang1, Weitong Ren2, Jun Wang3
1Laboratory for Neural Computation and Adaptation, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0106, Japan.
Molecular Biology and Evolution
|September 15, 2022
Summary
Artificial intelligence reveals that complex organisms have proteins with distinct structural and dynamic properties. This suggests protein evolution parallels organism evolution, impacting functional diversity and dynamics.
Area of Science:
- Evolutionary Biology
- Structural Biology
- Computational Biology
Background:
- Artificial intelligence (AI) offers novel tools for investigating organism and protein evolution.
- The AlphaFold Protein Structure Database (AlphaFold DB) provides extensive protein structure data for comparative analysis.
Purpose of the Study:
- To explore the relationship between organismal complexity and the structural/dynamic properties of proteins.
- To uncover the sequence and topological underpinnings of these correlations.
- To investigate if protein structural proximity reflects phylogenetic relationships.
Main Methods:
- Comparative analysis of proteins from diverse organisms using AlphaFold DB data.
- Normal mode analysis and scaling analyses to study protein dynamics.
- Analysis of residue contact networks and sequence properties (hydrophilic-hydrophobic segregation).
- Comparison of proteome-wide structural proximity with phylogenetic trees.
Main Results:
- Higher organismal complexity correlates with proteins having larger radii of gyration, higher coil fractions, and slower vibrations.
- Increased organismal complexity is linked to lower fractal dimensions in protein structure and dynamics, suggesting functional specialization.
- Protein residue contact networks become more assortative, and hydrophilic-hydrophobic segregation increases with organismal complexity.
- Statistical structural proximity across proteomes may reflect phylogenetic proximity, indicating parallel evolution.
Conclusions:
- Organismal complexity drives specific changes in protein structure and dynamics, correlating with functional specialization.
- Protein evolution appears to occur in parallel with organism evolution, influencing protein function diversity and dynamics.
- AI-driven structural analysis provides new insights into the fundamental principles of life's evolution.
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