Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data

Area of Science:

• Biophysics
• Structural Biology
• Biochemistry

Background:

• Molecular mass (MM) is crucial for protein characterization using small-angle X-ray scattering (SAXS).
• Traditional concentration-dependent MM determination methods often lack accuracy due to reliance on external parameters.
• Concentration-independent methods offer an alternative by directly utilizing scattering data.

Purpose of the Study:

• To compare the performance of various concentration-independent MM determination methods for proteins in solution.
• To develop a novel, accurate, and reliable method for MM estimation from SAXS data.
• To provide a robust tool for assessing sample quality and oligomeric states.

Main Methods:

• Comparative analysis of 165,982 unique scattering profiles derived from high-resolution protein structures.
• Development and application of a Bayesian inference approach for MM estimation.
• Evaluation of concentration-independent methods based on structural parameters and scattering invariants.

Main Results:

• The developed Bayesian inference approach demonstrated superior accuracy compared to individual concentration-independent methods.
• The method provides reliable MM estimates along with a credibility interval.
• Performance was validated across a large dataset of protein structures.

Conclusions:

• The Bayesian approach offers a highly accurate and reliable method for determining protein molecular mass from SAXS data.
• This method can serve as a stand-alone tool or complement existing concentration-dependent techniques.
• It enhances the assessment of protein sample quality and oligomeric composition in solution.