DISC: DISulfide linkage Characterization from tandem mass spectra

Area of Science:

• Proteomics
• Computational Biology
• Biochemistry

Background:

• Mass spectrometry is the primary method for disulfide bond analysis.
• Automating the interpretation of large mass spectral datasets is crucial.
• Existing methods often overlook internal ion fragments and lack robust quality control.

Purpose of the Study:

• To develop a computational approach for automated disulfide bond identification.
• To improve the accuracy and reliability of disulfide bond analysis from MS/MS spectra.

Main Methods:

• Introduced DISC (DISulfide bond Characterization), a novel computational approach.
• Incorporated various ion types, including internal ions, for matching spectra to structures.
• Developed a two-layer scoring scheme and a target-decoy strategy for quality control and false discovery rate reporting.

Main Results:

• DISC effectively matches MS/MS spectra with hypothetical disulfide linkage structures.
• The method demonstrated efficiency in identifying disulfide bonds from both low and high-complexity datasets.
• Showcased potential for characterizing disulfide bonds at the proteome scale.

Conclusions:

• DISC offers an effective solution for automated disulfide bond identification.
• The inclusion of internal ions and advanced scoring enhances accuracy.
• The method is applicable to large-scale proteomic studies.