Abstract
Spectrum-based Mass-Charge modeling is increasingly used in biological analysis. To explain statistical phenomenon with positive and negative fluctuations of amino-acid charges in spike proteins from coronaviruses, we propose calculation-based Mass-Charge modeling. This model provides normalized derivation algorithm with exact Excel or MATLAB tools involving separate quadrant extensions to normalized covariance, which is still compatible with Pearson covariance coefficiency. The number of amino acids, amino-acid composition, charges, molecular weight, isoelectric point, hydropathicity, and mass-charge ratio of the proteins were taken into consideration. Spike proteins from SARSCoV- 2 variants, seasonal and murine coronaviruses were analyzed as the representative examples. The analyses with the algorithm provide insights of evolving trends of the viral proteins and demonstrate that the Mass-Charge covariance co-efficiency can distinguish subtle differences between biological properties of spike proteins and correlate well with viral infectivity and virulence. This modeling may also be used in analyzing other proteins from pathogens.
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