Suppr超能文献

2019新型冠状病毒刺突蛋白突变体对病毒感染性的协同作用。

Collaborative effects of 2019-nCoV-Spike mutants on viral infectivity.

作者信息

Fang Senbiao, Lei Chuqi, Li Meng, Ming Yongfan, Liu Liren, Zhou Xuming, Li Min

机构信息

Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 410083, China.

Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.

出版信息

Comput Struct Biotechnol J. 2023 Oct 17;21:5125-5135. doi: 10.1016/j.csbj.2023.10.030. eCollection 2023.

Abstract

BACKGROUND

The emerging mutants of the 2019-nCoV coronavirus are posing unprecedented challenges to the pandemic prevention. A thorough, understanding of the mutational characterization responsible for the pathogenic mechanisms of mutations in 2019-nCoV-Spike is indispensable for developing effective drugs and new vaccines.

METHODS

We employed computational methods and viral infection assays to examine the interaction pattern and binding affinity between ACE2 and both single- and multi-mutants of the Spike proteins.

RESULTS

Using data from the CNCB-NGDC databank and analysis of the 2019-nCoV-Spike/ACE2 interface crystal structure, we identified 31 amino acids that may significantly contribute to viral infectivity. Subsequently, we performed molecular dynamics simulations for 589 single-mutants that emerged from the nonsynonymous substitutions of the aforementioned 31 residues. Ultimately, we discovered 8 single-mutants that exhibited significantly higher binding affinities (<-65.00 kcal/mol) to ACE2 compared with the wild-type Spike protein (-55.07 kcal/mol). The random combination of these 8 single-mutants yielded 184 multi-mutants, of which 60 multi-mutants exhibit markedly enhanced binding affinities (<-65.00 kcal/mol). Moreover, the binding free energy analyses of all 773 mutants (including 589 single- and 184 multi-mutants) revealed that Y449R and S494R had a synergistic effect on the binding affinity with other mutants, which were confirmed by virus infection assays of six randomly selected multi-mutants. More importantly, the findings of virus infection assay further validated a strong association between the binding free energy of Spike/ACE2 complex and the viral infectivity.

CONCLUSIONS

These findings will greatly contribute to the future surveillance of viruses and rational design of therapeutics.

摘要

背景

2019 - 新型冠状病毒(2019 - nCoV)不断出现的突变体给疫情防控带来了前所未有的挑战。全面了解2019 - nCoV刺突蛋白(Spike)突变的致病机制对于开发有效的药物和新型疫苗至关重要。

方法

我们采用计算方法和病毒感染实验来研究血管紧张素转换酶2(ACE2)与刺突蛋白单突变体和多突变体之间的相互作用模式及结合亲和力。

结果

利用中国国家微生物科学数据中心(CNCB - NGDC)数据库的数据并分析2019 - nCoV刺突蛋白/ACE2界面晶体结构,我们确定了31个可能对病毒感染性有显著影响的氨基酸。随后,我们对上述31个残基非同义替换产生的589个单突变体进行了分子动力学模拟。最终,我们发现8个单突变体与野生型刺突蛋白(-55.07千卡/摩尔)相比,对ACE2表现出显著更高的结合亲和力(<-65.00千卡/摩尔)。这8个单突变体的随机组合产生了184个多突变体,其中60个多突变体表现出明显增强的结合亲和力(<-65.00千卡/摩尔)。此外,对所有773个突变体(包括589个单突变体和184个多突变体)的结合自由能分析表明,Y449R和S494R对与其他突变体的结合亲和力具有协同作用,这通过对6个随机选择的多突变体进行病毒感染实验得到了证实。更重要的是,病毒感染实验结果进一步验证了刺突蛋白/ACE2复合物结合自由能与病毒感染性之间的紧密关联。

结论

这些发现将极大地有助于未来的病毒监测和治疗药物的合理设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cec/10618117/13df7f48aa68/ga1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验