Nonspecific cross-linker can provide distance restraints between surface residues of any type, which could be used to investigate protein structure construction and protein–protein interaction (PPI). However, the vast number of potential combinations of cross-linked residues or sites obtained with such a cross-linker makes the data challenging to analyze, especially for the proteome-wide applications. Here, we developed SpotLink software for identifying site nonspecific cross-links at the proteome scale. Contributed by the dual pointer dynamic pruning algorithm and the quality control of cross-linking sites, SpotLink identified > 3000 cross-links from human cell samples within a short period of days. We demonstrated that SpotLink outperformed other approaches in terms of sensitivity and precision on the datasets of the simulated succinimidyl 4,4′-azipentanoate dataset and the condensin complexes with known structures. In addition, some valuable PPI were discovered in the datasets of the condensin complexes and the HeLa dataset, indicating the unique identification advantages of site nonspecific cross-linking. These findings reinforce the importance of SpotLink as a fundamental characteristic of site nonspecific cross-linking technologies.

Data-dependent liquid chromatography–tandem mass spectrometry (LC–MS/MS) is widely used in proteomic analyses. A well-performed LC–MS/MS workflow, which involves multiple procedures and interdependent metrics, is a prerequisite for deep proteome profiling. Researchers have previously evaluated LC–MS/MS performance mainly based on the number of identified peptides and proteins. However, this is not a comprehensive approach. This motivates us to develop MSRefine, which aims to evaluate and optimize the performance of the LC–MS/MS workflow for data-dependent acquisition (DDA) proteomics. It extracts 47 kinds of metrics, scores the metrics, and reports visual results, assisting users in evaluating the workflow, locating problems, and providing optimizing strategies. In this study, we compared and analyzed multiple pairs of datasets spanning different samples, methods, and instruments and demonstrated that the comprehensive visual metrics and scores in MSRefine enable us to evaluate the performance of the various experiments and provide optimal strategies for the identification of more peptides and proteins.

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We developed SpotLink software for identifying site non-specific cross-links at the proteome scale. Contributed by the dual pointer dynamic pruning (DPDP) algorithm and the quality control of cross-linking sites, SpotLink identified more than 3000 cross-links from human proteome database with rich site information in a few days. We demonstrated that SpotLink outperformed other approaches in terms of sensitivity and precision on a simulated dataset and a protein complexes dataset with known structures. Additionally, we discovered some valuable protein-protein interaction (PPI) information contained in the protein complexes dataset and HeLa dataset, indicating the unique identification advantages of site non-specific cross-linking. The excellent performance of SpotLink will increase the usage of site non-specific cross-linking in the near future. SpotLink is publicly available on GitHub [https://github.com/DICP1810/SpotLink].