Distance matrices for nitrogenous bases and amino acids of SARS-CoV-2 via structural metric.

COVID-19 pandemic has caused a global health crisis. Developing vaccines would need a good knowledge of genetic properties of SARS-CoV-2. The most fundamental approach is to look into the structures of its RNA, in particular, the nucleotides and amino acids. This motivates our research on this topic. We study the occurrence structures of nitrogenous bases and amino acids. To this aim, we devise a structural metric which could measure the structure differences for bases or amino acids. By analyzing various SARS-CoV-2 samples, we calculate the distance matrices for nitrogenous bases and amino acids. Based on the distance matrices, we find the average distance matrices for them, respectively. Then we identify the relations of all the minimal distances between bases and amino acids. The results also show that different substructures would yield much more diversified distances between amino acids. In the end, we also conduct the comparison of our structural metric with other frequently used metrics, in particular, Hausdorff metrics.