The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database

Abstract

The recent development of artificial intelligence provides us with new and powerful tools for studying the mysterious relationship between organism evolution and protein evolution. In this work, based on the AlphaFold Protein Structure Database (AlphaFold DB), we perform comparative analyses of the proteins of different organisms. The statistics of AlphaFold-predicted structures show that, for organisms with higher complexity, their constituent proteins will have larger radii of gyration, higher coil fractions, and slower vibrations, statistically. By conducting normal mode analysis and scaling analyses, we demonstrate that higher organismal complexity correlates with lower fractal dimensions in both the structure and dynamics of the constituent proteins, suggesting that higher functional specialization is associated with higher organismal complexity. We also uncover the topology and sequence bases of these correlations. As the organismal complexity increases, the residue contact networks of the constituent proteins will be more assortative, and these proteins will have a higher degree of hydrophilic–hydrophobic segregation in the sequences. Furthermore, by comparing the statistical structural proximity across the proteomes with the phylogenetic tree of homologous proteins, we show that, statistical structural proximity across the proteomes may indirectly reflect the phylogenetic proximity, indicating a statistical trend of protein evolution in parallel with organism evolution. This study provides new insights into how the diversity in the functionality of proteins increases and how the dimensionality of the manifold of protein dynamics reduces during evolution, contributing to the understanding of the origin and evolution of lives.

Evolutionary Tinkering Enriches the Hierarchical and Interlaced Structures in Amino Acid Sequences

“…We also confirmed using shuffling methods that this complexity does not stem from content differences (e.g., the so-called C-value paradox or enigma [61]) but arises from internal sequential patterns. From the perspective of protein structure, studies have shown that species with higher complexity possess more proteins with larger radii of gyration (signifying increased flexibility) and a higher degree of modularity [62]. On the other hand, our analysis from the sequential perspective implies that the more complex a species is, the higher the tendency for sequence complexity.…”

“…On the other hand, our analysis from the sequential perspective implies that the more complex a species is, the higher the tendency for sequence complexity. (It is worth noting that although the definition of species complexity remains debated, in practice, biologists often employ varied metrics like the total cell types, genome size, or proteome size to gauge species complexity, whereas these metrics are often interrelated [62,63].) Collectively, these results hint at positive correlations between amino acid sequence complexity, protein structural modularity, and overall species complexity.…”

Limitations of Protein Structure Prediction Algorithms in Therapeutic Protein Development

“…had higher prediction scores, directing that both AF2 and ESMF perform well on multi-domain proteins, making single-and multiple-domain molecules equally likely to have lower scores. Multi-domain molecules with longer sequence lengths tend to have larger radii of gyration, resulting in increased complexity [83,84]. Generally, a larger radius of gyration indicates a more extended or less compact structure; therefore, it might add up to the challenge of structure prediction for prediction tools to model a structure accurately, resulting in lower scores.…”

Protein structure and folding pathway prediction based on remote homologs recognition using PAthreader

“…It is well known that templates play a critical role in the protein structure modelling 4 . Meanwhile, the evolutionary relationship implicitly contained in templates are probably favorable for study of protein folding 6 .…”