A high-speed search engine pLink 2 with systematic evaluation for proteome-scale identification of cross-linked peptides

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Abstract

We describe pLink 2, a search engine with higher speed and reliability for proteome-scale identification of cross-linked peptides. With a two-stage open search strategy facilitated by fragment indexing, pLink 2 is ~40 times faster than pLink 1 and 3~10 times faster than Kojak. Furthermore, using simulated datasets, synthetic datasets, 15N metabolically labeled datasets, and entrapment databases, four analysis methods were designed to evaluate the credibility of ten state-of-the-art search engines. This systematic evaluation shows that pLink 2 outperforms these methods in precision and sensitivity, especially at proteome scales. Lastly, re-analysis of four published proteome-scale cross-linking datasets with pLink 2 required only a fraction of the time used by pLink 1, with up to 27% more cross-linked residue pairs identified. pLink 2 is therefore an efficient and reliable tool for cross-linking mass spectrometry analysis, and the systematic evaluation methods described here will be useful for future software development.

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Most cited references 59

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Identification of cross-linked peptides from complex samples.

Bing Yang, Yan-Jie Wu, Ming Zhu … (2012)

We have developed pLink, software for data analysis of cross-linked proteins coupled with mass-spectrometry analysis. pLink reliably estimates false discovery rate in cross-link identification and is compatible with multiple homo- or hetero-bifunctional cross-linkers. We validated the program with proteins of known structures, and we further tested it on protein complexes, crude immunoprecipitates and whole-cell lysates. We show that it is a robust tool for protein-structure and protein-protein-interaction studies.

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Structure of the voltage-gated calcium channel Cav1.1 at 3.6 Å resolution.

Jianping Wu, Zhen Yan, Zhangqiang Li … (2016)

The voltage-gated calcium (Cav) channels convert membrane electrical signals to intracellular Ca(2+)-mediated events. Among the ten subtypes of Cav channel in mammals, Cav1.1 is specified for the excitation-contraction coupling of skeletal muscles. Here we present the cryo-electron microscopy structure of the rabbit Cav1.1 complex at a nominal resolution of 3.6 Å. The inner gate of the ion-conducting α1-subunit is closed and all four voltage-sensing domains adopt an 'up' conformation, suggesting a potentially inactivated state. The extended extracellular loops of the pore domain, which are stabilized by multiple disulfide bonds, form a windowed dome above the selectivity filter. One side of the dome provides the docking site for the α2δ-1-subunit, while the other side may attract cations through its negative surface potential. The intracellular I-II and III-IV linker helices interact with the β1a-subunit and the carboxy-terminal domain of α1, respectively. Classification of the particles yielded two additional reconstructions that reveal pronounced displacement of β1a and adjacent elements in α1. The atomic model of the Cav1.1 complex establishes a foundation for mechanistic understanding of excitation-contraction coupling and provides a three-dimensional template for molecular interpretations of the functions and disease mechanisms of Cav and Nav channels.

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iProphet: multi-level integrative analysis of shotgun proteomic data improves peptide and protein identification rates and error estimates.

David Shteynberg, Eric W Deutsch, Henry Lam … (2011)

The combination of tandem mass spectrometry and sequence database searching is the method of choice for the identification of peptides and the mapping of proteomes. Over the last several years, the volume of data generated in proteomic studies has increased dramatically, which challenges the computational approaches previously developed for these data. Furthermore, a multitude of search engines have been developed that identify different, overlapping subsets of the sample peptides from a particular set of tandem mass spectrometry spectra. We present iProphet, the new addition to the widely used open-source suite of proteomic data analysis tools Trans-Proteomics Pipeline. Applied in tandem with PeptideProphet, it provides more accurate representation of the multilevel nature of shotgun proteomic data. iProphet combines the evidence from multiple identifications of the same peptide sequences across different spectra, experiments, precursor ion charge states, and modified states. It also allows accurate and effective integration of the results from multiple database search engines applied to the same data. The use of iProphet in the Trans-Proteomics Pipeline increases the number of correctly identified peptides at a constant false discovery rate as compared with both PeptideProphet and another state-of-the-art tool Percolator. As the main outcome, iProphet permits the calculation of accurate posterior probabilities and false discovery rate estimates at the level of sequence identical peptide identifications, which in turn leads to more accurate probability estimates at the protein level. Fully integrated with the Trans-Proteomics Pipeline, it supports all commonly used MS instruments, search engines, and computer platforms. The performance of iProphet is demonstrated on two publicly available data sets: data from a human whole cell lysate proteome profiling experiment representative of typical proteomic data sets, and from a set of Streptococcus pyogenes experiments more representative of organism-specific composite data sets.