Using intrinsic X-ray absorption spectral differences to identify and map peptides and proteins

Area of Science:

• Biophysical Chemistry
• Spectroscopy
• Proteomics

Background:

• Near-edge X-ray absorption fine structure (NEXAFS) spectra exhibit intrinsic variations across peptides and proteins.
• These spectral differences offer potential for label-free identification and mapping in biological settings.
• Amino acid-specific spectral signatures suggest distinguishability between peptides and proteins based on sequence.

Purpose of the Study:

• To develop a computational tool (X-SpecSim) for predicting C, N, and O 1s NEXAFS spectra of peptides and proteins from their amino acid sequences.
• To validate the prediction methodology through comparisons with experimental spectra of known peptides and proteins.
• To demonstrate the practical application of sequence-based NEXAFS spectral prediction for identifying and mapping biomolecules.

Main Methods:

• Development of X-SpecSim software for quantitative prediction of NEXAFS spectra based on peptide/protein sequences.
• Acquisition and interpretation of C 1s, N 1s, and O 1s NEXAFS spectra for specific peptides (Indolicidin, Sub6) and proteins (human serum albumin, fibrinogen).
• Application of scanning transmission X-ray microscopy (STXM) to visualize and quantify an antimicrobial peptide within a protein mixture.

Main Results:

• X-SpecSim successfully predicts NEXAFS spectra, showing good precision when compared to experimental data.
• Distinct spectral features were observed and interpreted for Indolicidin, Sub6, human serum albumin, and fibrinogen.
• Successful identification and quantitative mapping of the antimicrobial peptide Sub6 against a background of albumin was achieved using STXM.

Conclusions:

• Sequence-based NEXAFS spectral prediction is a viable approach for label-free characterization of peptides and proteins.
• X-SpecSim provides a powerful tool for understanding and predicting biomolecular spectra.
• This methodology holds promise for identifying, differentiating, and spatially mapping peptides and proteins in complex biological environments.