Using SIM-XL to identify and annotate cross-linked peptides analyzed by mass spectrometry
State-of-the-art structural mass spectrometry-based proteomics is often accomplished by using cross-linkers to covalently bind two or more amino-acid groups. This strategy is complementary to classical structural biology and therefore broadens the toolset for analyzing protein and protein-protein complex structures. One of the greatest challenges in identifying cross-linked peptides in complex protein mixtures is computationally dealing with the large search space, which grows quadratically with each peptide included in the sequence database. The **Spectrum Identification Machine for Cross-Linked Peptides \(SIM-XL)** software uses an algorithm that overcomes this limitation by capitalizing on experimental features that allow it to effectively address the massive combinatorial problem at hand, and presents the results in a user-friendly manner. Thus, SIM-XL is recommended for studies dealing with protein structure and protein-protein interaction in either simple or complex protein mixtures. SIM-XL also allows the sharing of results through PRIDE by exporting them in the mzIdentML format.
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Posted 13 Feb, 2015
Using SIM-XL to identify and annotate cross-linked peptides analyzed by mass spectrometry
Posted 13 Feb, 2015
State-of-the-art structural mass spectrometry-based proteomics is often accomplished by using cross-linkers to covalently bind two or more amino-acid groups. This strategy is complementary to classical structural biology and therefore broadens the toolset for analyzing protein and protein-protein complex structures. One of the greatest challenges in identifying cross-linked peptides in complex protein mixtures is computationally dealing with the large search space, which grows quadratically with each peptide included in the sequence database. The **Spectrum Identification Machine for Cross-Linked Peptides \(SIM-XL)** software uses an algorithm that overcomes this limitation by capitalizing on experimental features that allow it to effectively address the massive combinatorial problem at hand, and presents the results in a user-friendly manner. Thus, SIM-XL is recommended for studies dealing with protein structure and protein-protein interaction in either simple or complex protein mixtures. SIM-XL also allows the sharing of results through PRIDE by exporting them in the mzIdentML format.
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