Crosslink FDR validation with advanced entrapment database

[z3rone]

aim of the new module

Robust error control in crosslink mass spectrometry (MS) data analysis remains an ongoing challenge[1][2][3][4]. As the field rapidly evolves with new software, a universal standard for quality control is urgently needed. This module provides a comprehensive method to validate error control across crosslink MS workflows, specifically targeting biases introduced by integrating external information during data analysis. For instance, filtering heteromeric links based on self-links without maintaining corresponding decoy proteins heavily underestimates the FDR[1][2]. To address this, we introduce a protein FASTA file with fused proteins, building on prior entrapment strategies[2][5]. Unlike separate entrapment proteins—which suffer from the same filtering vulnerabilities as standard decoys—our fused-protein approach reliably captures these downstream errors. Ultimately, the broader objective of this module is to provide the field with a standardized framework to rigorously test novel database search algorithms and FDR estimation approaches, ensuring that any new methodology can be systematically vetted for unintended side effects on statistical accuracy.

full description of the new module

1. What file would be available for download on the module website?
   • A set of RAW spectra files to be searched.
   • A FASTA file to be used for the search. The FASTA file will contain the target proteins fused to the entrapment proteins. This will serve as a decoy-independent error control.
2. What would users need to do?
   Run a complete CLMS workflow, from spectra search to residue link identification, with 5% target FDR, the specified
   crosslinker and (at most) the specified allowed number of miscleavages.
3. What would be the type/format of files used as input for the module?
   A result file containing the reported residue links. To make the submission most accessible, we will accept the industry standard mzIdentML format and a more basic custom CSV format.
4. What metrics would be calculated and how?
   For the submitted aggregation levels we will calculate the estimated False Discovery Proportion (eFDP) using the formula $eFDP=\frac{2*TE}{TT}$ where TE are the target-entrapment matches among the non-decoy matches. This value will be compared to the requested FDR of 5%.
5. Propose a plot for metrics visualisation
   Bar plots of the eFDP (entrapment based) with a mark where the expected FDR (decoy based) is.

potential external expert(s)

No response

Will you be able to work on the implementation (coding) yourself, with additional help from the ProteoBench maintainers?

• yes
• no

any other information

To prevent search software from selectively identifying, altering, or bypassing the control metrics, the entrapment sequences must be hidden within the target protein sequences. However, embedding these sequences introduces structural artifacts that can distort the relative search spaces of both target and entrapment proteins. The core design principle of this module is to maintain strict search space parity. In scenarios where absolute parity is mathematically or biochemically unattainable, the module systematically prioritizes giving the software under investigation the benefit of the doubt, selecting optimization strategies that shrink the entrapment search space rather than the target search space.

When evaluating where to integrate the entrapment sequence, terminal additions were rejected due to disproportionate search space distortions. Prepending the entrapment sequence at the N-terminus of the target sequence disproportionately shrinks the target search space by disrupting native N-terminal crosslinks and preventing natural N-terminal methionine elimination. Conversely, appending the entrapment sequence at the C-terminus permanently introduces an artificial lysine/arginine to the final peptide of the target protein (assuming it natively terminates on a different amino acid), which alters its native digestion profile. To avoid these terminal artifacts, the module utilizes an internal insertion approach where the entrapment sequence is placed directly following an existing lysine/arginine residue within the target protein.

To ensure these internally conjoined sequences accurately mimic native sequences during in silico digestion, a multi-tiered mitigation strategy is implemented for a workflow allowing $n$ missed cleavages. First, to minimize target-entrapment overlapping peptides during tryptic digestion, the inserted entrapment sequence is insulated from the target sequence by a spacer of $n+1$ arginines. Second, because internal insertion inherently destroys miscleaved target peptides that span across the insertion site, the $n$ peptides immediately preceding the insertion point are duplicated directly after the entrapment sequence to recover this lost target search space. Finally, introducing duplicated peptides creates positional ambiguity that some software pipelines may penalize or discard entirely. To prevent this behavior from artificially altering the target search space accuracy, a symmetric control bias is introduced by duplicating $n$ peptides within the middle of the entrapment sequence itself. This ensures that any software-specific handling of ambiguous peptides impacts both target and entrapment spaces equally.

Figure 1: Principle of fused target-entrapment sequences.

References

[1] Rescuing error control in crosslinking mass spectrometry
[2] A synthetic peptide library for benchmarking crosslinking-mass spectrometry search engines for proteins and protein complexes
[3] Enhancing Inter-link Coverage in Cross-Linking Mass Spectrometry through Context-Sensitive Subgrouping and Decoy Fusion
[4] Assessment of Reported Error Rates in Crosslinking Mass Spectrometry
[5] Adaptation of Decoy Fusion Strategy for Existing Multi-Stage Search Workflows

[rodvrees]

Hi @z3rone

Thank you for submitting this module request! It looks very interesting and potentially a great addition to ProteoBench!
Would you be willing to present the idea in one of our weekly meetings? We meet every week on Friday at 10:00 CET. That way we can more easily discuss the module development plan. Feel free to get in touch with proteobench@eubic-ms.org to plan further!

Thanks!