Rahaman Shawonur, Steele Jacob H, Zeng Yi, Xu Shoujun, Wang Yuhong
Department of Chemistry, University of Houston, Houston, TX, 77204, USA.
Department of Biology and Biochemistry, University of Houston, Houston, TX, 77204, USA.
Comput Biol Med. 2025 Jun;191:110188. doi: 10.1016/j.compbiomed.2025.110188. Epub 2025 Apr 12.
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.
延伸因子G(EF-G)对于核糖体转位至关重要,而核糖体转位是蛋白质合成中的一个基本步骤。尽管EF-G起着不可或缺的作用,但其构象动力学和进化仍不清楚。通过将AlphaFold结构预测与基于多序列比对(MSA)的序列分析相结合,我们探索了EF-G的构象景观、序列特异性模式和进化差异。我们确定了野生型(WT)EF-G的五个高置信度结构状态,揭示了比以前实验数据所捕捉到的更广泛的构象多样性。系统发育分析以及嵌入MSA的序列模式表明,开关I环中的单点突变调节了两种主要构象状态con1和con2之间的平衡,这两种状态表现出不同的功能特化。对两个祖先EF-G的重建显示,两种形式的GTPase活性都很低,转位酶功能也有所降低,这表明强大的转位酶活性在con1和con2分化之后才出现。然而,祖先EF-G保留了三核苷酸转位的保真度,强调了准确的mRNA移动在早期进化中的保守性。这些发现建立了一个框架,用于理解构象灵活性如何塑造EF-G的功能和特化。此外,我们的计算流程可以扩展到其他翻译GTPases,为翻译机制的进化提供更广泛的见解。这项研究突出了AlphaFold辅助结构分析在揭示蛋白质翻译中所涉及的机制和进化关系方面的强大作用。