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严重急性呼吸综合征冠状病毒2(SARS-CoV-2)变体分子适应性的预测与演变:介绍SpikePro

Prediction and Evolution of the Molecular Fitness of SARS-CoV-2 Variants: Introducing SpikePro.

作者信息

Pucci Fabrizio, Rooman Marianne

机构信息

Computational Biology and Bioinformatics, Université Libre de Bruxelles, 1050 Brussels, Belgium.

Interuniversity Institute of Bioinformatics in Brussels, 1050 Brussels, Belgium.

出版信息

Viruses. 2021 May 18;13(5):935. doi: 10.3390/v13050935.

Abstract

The understanding of the molecular mechanisms driving the fitness of the SARS-CoV-2 virus and its mutational evolution is still a critical issue. We built a simplified computational model, called SpikePro, to predict the SARS-CoV-2 fitness from the amino acid sequence and structure of the spike protein. It contains three contributions: the inter-human transmissibility of the virus predicted from the stability of the spike protein, the infectivity computed in terms of the affinity of the spike protein for the ACE2 receptor, and the ability of the virus to escape from the human immune response based on the binding affinity of the spike protein for a set of neutralizing antibodies. Our model reproduces well the available experimental, epidemiological and clinical data on the impact of variants on the biophysical characteristics of the virus. For example, it is able to identify circulating viral strains that, by increasing their fitness, recently became dominant at the population level. SpikePro is a useful, freely available instrument which predicts rapidly and with good accuracy the dangerousness of new viral strains. It can be integrated and play a fundamental role in the genomic surveillance programs of the SARS-CoV-2 virus that, despite all the efforts, remain time-consuming and expensive.

摘要

对驱动SARS-CoV-2病毒适应性及其突变进化的分子机制的理解仍然是一个关键问题。我们构建了一个简化的计算模型,称为SpikePro,用于根据刺突蛋白的氨基酸序列和结构预测SARS-CoV-2的适应性。它包含三个因素:根据刺突蛋白的稳定性预测的病毒人际传播能力、根据刺突蛋白对ACE2受体的亲和力计算的感染性,以及基于刺突蛋白对一组中和抗体的结合亲和力的病毒逃避免疫反应的能力。我们的模型很好地再现了关于变体对病毒生物物理特性影响的现有实验、流行病学和临床数据。例如,它能够识别通过提高适应性最近在人群水平上占主导地位的循环病毒株。SpikePro是一种有用的、免费可用的工具,能够快速且准确地预测新病毒株的危险性。它可以被整合,并在SARS-CoV-2病毒的基因组监测计划中发挥重要作用,尽管已经付出了所有努力,但该计划仍然耗时且昂贵。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae04/8158131/dc4bccd15e63/viruses-13-00935-g001.jpg

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