Spectrum-based Mass-Charge modeling has received significant interest in recent years and is increasingly used in bio-analysis. To explain the statistical phenomenon with positive and negative fluctuations of spike protein sequences from coronaviruses, we propose a calculation-based Mass-Charge modeling. Different from previous Semi-covariance co-efficiency method, this one proposes a normalized derivation with the exact Excel and Matlab tool algorithm involving the separate quadrant extension to normalized covariance, which ends up a Mass-Charge analysis that is still compatible with Pearson covariance co-efficiency. By examining the relative peak and dip of the 11th reverse order string Langlands theory average with spike protein sequences of coronaviruses based on the hydro mass to isoelectric charges of the amino acids, the proposed algorithm provides more clean insights leading to the detail revealing of the underline binding mechanism evolving trends of spike proteins over 1000 years, and to understand which is the viral ancestral source in the nature conditions. The spike proteins from coronaviruses isolated from the Murine(1949) for animal and from Omicron(2020), Delta, Wuhan(2019), IHU(2022), Mu(2021), OC43(1967), 229E, HKU1, NL63 that cause human infections were taken as the representative examples in this study.