Stoichiometric insights into SARS-CoV-2 spike-ACE2 binding across variants.

IF 4.1 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-07-24 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.07.034
Ishola Abeeb Akinwumi, Sneha Bheemireddy, Laurent Chaloin, Serge Perez, Hamed Khakzad, Bernard Maigret, Yasaman Karami
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引用次数: 0

Abstract

The SARS-CoV-2 spike protein binds to the angiotensin-converting enzyme 2 (ACE2) receptor to mediate viral entry, with mutations in different variants influencing binding affinity and conformational dynamics. Using large-scale molecular dynamics simulations, we analyzed the Spike-ACE2 complex in the wild-type (WT), Beta, and Delta variants. Our findings reveal significant conformational rearrangements at the interface in Beta and Delta compared to WT, leading to distinct interaction networks and changes in complex stability. Binding free energy analysis further highlights variant-specific differences in ACE2 affinity, with alternative binding modes emerging over the simulation. The results enhance our understanding of spike-ACE2 stoichiometry across variants, providing implications for viral infectivity and therapeutic targeting.

SARS-CoV-2刺突- ace2跨变体结合的化学计量学见解。
SARS-CoV-2刺突蛋白与血管紧张素转换酶2 (ACE2)受体结合介导病毒进入,不同变异的突变影响结合亲和力和构象动力学。利用大规模分子动力学模拟,我们分析了野生型(WT)、Beta和Delta变体中的Spike-ACE2复合体。我们的研究结果显示,与WT相比,β和δ的界面有显著的构象重排,导致不同的相互作用网络和复杂稳定性的变化。结合自由能分析进一步强调了ACE2亲和力的变异特异性差异,在模拟过程中出现了不同的结合模式。研究结果增强了我们对不同变异的acei - 2化学计量学的理解,为病毒感染性和治疗靶向性提供了启示。
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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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