School of Computer Science & Technology, Soochow University, Suzhou 215000, China.
Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210000, China.
Int J Mol Sci. 2023 Feb 7;24(4):3255. doi: 10.3390/ijms24043255.
The emergence of numerous variants of SARS-CoV-2 has presented challenges to the global efforts to control the COVID-19 pandemic. The major mutation is in the SARS-CoV-2 viral envelope spike protein that is responsible for virus attachment to the host, and is the main target for host antibodies. It is critically important to study the biological effects of the mutations to understand the mechanisms of how mutations alter viral functions. Here, we propose a protein co-conservation weighted network (PCCN) model only based on the protein sequence to characterize the mutation sites by topological features and to investigate the mutation effects on the spike protein from a network view. Frist, we found that the mutation sites on the spike protein had significantly larger centrality than the non-mutation sites. Second, the stability changes and binding free energy changes in the mutation sites were positively significantly correlated with their neighbors' degree and the shortest path length separately. The results indicate that our PCCN model provides new insights into mutations on spike proteins and reflects the mutation effects on protein function alternations.
众多 SARS-CoV-2 变异株的出现给全球控制 COVID-19 大流行的努力带来了挑战。主要突变发生在 SARS-CoV-2 病毒包膜刺突蛋白上,该蛋白负责病毒与宿主的附着,是宿主抗体的主要靶标。研究突变的生物学效应对于了解突变如何改变病毒功能的机制至关重要。在这里,我们仅基于蛋白质序列提出了一种蛋白质共保守加权网络(PCCN)模型来通过拓扑特征来描述突变位点,并从网络角度研究突变对刺突蛋白的影响。首先,我们发现刺突蛋白上的突变位点的中心性显著大于非突变位点。其次,突变位点的稳定性变化和结合自由能变化与它们的邻居的度和最短路径长度分别呈正显著相关。结果表明,我们的 PCCN 模型为刺突蛋白上的突变提供了新的见解,并反映了突变对蛋白质功能改变的影响。