Quantitative Comparison and Clustering of Circular Dichroism Spectra Using a Symmetrized Weighted Spectral Difference

Area of Science:

• Biophysical chemistry
• Structural biology
• Spectroscopic analysis

Background:

• Spectroscopy is crucial for determining macromolecular structures and stability, particularly for protein and nucleic acid-based drugs.
• The Weighted Spectral Difference (WSD) method quantifies spectral dissimilarity but has limitations, including lack of symmetry and reference dependence.

Purpose of the Study:

• To develop a reference-free, symmetrized version of WSD (SWSD) for robust spectral comparison.
• To demonstrate SWSD's utility in group comparisons, kinetic tracking, and hierarchical clustering of spectral data.

Main Methods:

• Development of the symmetrized Weighted Spectral Difference (SWSD) algorithm.
• Application of SWSD to circular dichroism spectra of influenza vaccines and recombinant spike proteins.
• Validation against differential scanning calorimetry (DSC) for protein denaturation studies.

Main Results:

• SWSD achieved perfect clustering of influenza A and B viruses.
• SWSD kinetics accurately identified two denaturation temperatures (Tm) for a spike protein during heating.
• The method demonstrated versatility in analyzing spectral data for biological macromolecules.

Conclusions:

• SWSD is an efficient and versatile tool for quantitative spectral comparison.
• SWSD facilitates spectral kinetics tracking and unsupervised classification of spectra.
• This method enhances the analysis of macromolecular structure and stability using spectroscopy.