ArticleComputers in biology and medicine2025
Evolutionary insights into elongation factor G using AlphaFold and ancestral analysis.
Article in Computers in biology and medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- D81 Mutants Reveal Hidden EF-Tu Diversity while Natural Sequences Preserve Aspartate.Computational and structural biotechnology journal · 2026Article
- EF-G Mutations Reveal Correlation between Power Stroke and Translocation Fidelity in Protein Synthesis.bioRxiv : the preprint server for biology · 2025Article
- SURFS and AlphaFold Reveal Ribosome Footprint Shift Caused by EF-Tu D81 Mutation.bioRxiv : the preprint server for biology · 2025Article
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5 authors.
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Abstract
Elongation factor G (EF-G) is crucial for ribosomal translocation, a fundamental step in protein synthesis. Despite its indispensable role, the conformational dynamics and evolution of EF-G remain elusive. By integrating AlphaFold structural predictions with multiple sequence alignment (MSA)-based sequence analysis, we explored the conformational landscape, sequence-specific patterns, and evolutionary divergence of EF-G. We identified five high-confidence structural states of wild type (WT) EF-G, revealing broader conformational diversity than previously captured by experimental data. Phylogenetic analysis and MSA-embedded sequence patterns demonstrated that single-point mutations in the switch I loop modulate equilibrium between the two dominant conformational states, con1 and con2, which exhibit distinct functional specializations. Reconstructions of two ancestral EF-Gs revealed minimal GTPase activity and reduced translocase function in both forms, suggesting that robust translocase activity emerged after the divergence of con1 and con2. However, ancestral EF-Gs retained the fidelity of three-nucleotide translocation, underscoring the early evolutionary conservation of accurate mRNA movement. These findings establish a framework for understanding how conformational flexibility shapes EF-G function and specialization. Moreover, our computational pipeline can be extended to other translational GTPases, providing broader insights into the evolution of the translational machinery. This study highlights the power of AlphaFold-assisted structural analysis in revealing the mechanistic and evolutionary relationships involved in protein translation.
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