SimTandem

SimTandem identifies peptides from liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectra by similarity searching against theoretical spectra derived from known protein sequences for shotgun proteomics peptide identification.

Key Features:

• Theoretical Mass Spectra Comparison: Compares query LC-MS/MS spectra to theoretical spectra derived from protein sequences using a modified parameterized Hausdorff distance.
• Performance versus OMSSA and X!Tandem: Demonstrates improved identification accuracy relative to OMSSA and X!Tandem, especially for noisy query spectra, and supports identification at q-value thresholds down to 0.001.
• Speed Optimization: Employs a precursor mass filter as a database indexing technique to accelerate searches, yielding faster speeds than OMSSA and comparable speed to X!Tandem when variable modifications are not considered.
• Handling Variable Modifications: Uses a strategy of searching variable modifications separately in multiple runs to increase identified peptides while mitigating false discovery rate inflation from mixing modified and unmodified spectra.
• Implementation Platform: Implemented within the TOPP framework based on OpenMS.

Scientific Applications:

• Shotgun proteomics peptide identification: Determination of peptide composition of complex biological samples from LC-MS/MS data.
• Noisy-spectrum analysis: Improved identification performance on noisy query spectra typical of complex proteomics experiments.
• Post-translational modification searches: Increased peptide identifications via separate searches for variable modifications while controlling false discovery rates.

Methodology:

Similarity search of query LC-MS/MS spectra against a database of theoretical spectra derived from protein sequences; spectrum comparison via a modified parameterized Hausdorff distance; database indexing using a precursor mass filter; separate runs for variable modification searches.