Constructing high-accuracy theoretical Raman spectra of SARS-CoV-2 spike proteins based on a large fragment method

Area of Science:

• Biophysics
• Spectroscopy
• Computational Chemistry

Background:

• Accurate detection of SARS-CoV-2 is critical for controlling COVID-19.
• Raman spectroscopy can detect SARS-CoV-2 spike proteins, but lacks high-accuracy theoretical spectra for clinical diagnostics.
• Existing theoretical models do not sufficiently capture the complex interactions within spike proteins.

Purpose of the Study:

• To develop a high-precision theoretical Raman spectra prediction method for SARS-CoV-2 spike proteins.
• To establish a reliable spectral standard for clinical diagnostic applications of Raman spectroscopy.
• To improve the accuracy and reduce calculation errors in theoretical Raman spectra of proteins.

Main Methods:

• Proposed a novel 'large fragment method' for constructing theoretical Raman spectra.
• Calculated interactions within large fragments of the spike protein to enhance accuracy.
• Validated the method by comparing theoretical spectra with experimental data.

Main Results:

• Achieved high-precision theoretical Raman spectra for SARS-CoV-2 spike proteins.
• The large fragment method significantly reduced calculation errors and improved spectral accuracy.
• Demonstrated a Pearson correlation coefficient greater than 0.929 between theoretical and experimental spectra.
• Characteristic spectral patterns were clearly visible and easily comparable to experimental data.

Conclusions:

• The large fragment method provides an accurate and reliable detection standard for SARS-CoV-2 spike proteins.
• This advancement facilitates faster and more accurate recognition of SARS-CoV-2 using Raman spectroscopy.
• The findings pave the way for improved clinical diagnostic tools for COVID-19 detection.