Protein structure prediction guided by cross-linking restraints - A systematic evaluation of the impact of the cross-linking spacer length

TL;DR

This study systematically evaluates how the length of cross-linkers in XL-MS influences the accuracy of de novo protein structure prediction, identifying optimal lengths that maximize structural information content.

Contribution

It introduces a heuristic for selecting optimal cross-linker lengths based on protein size and demonstrates improved structure prediction accuracy using simulated XL-MS restraints.

Findings

Optimal cross-linker length varies with protein size.

De novo structure prediction accuracy improves with optimal cross-linker length.

XL-MS restraints enhance native-like model selection.

Abstract

Recent development of high-resolution mass spectrometry (MS) instruments enables chemical cross-linking (XL) to become a high-throughput method for obtaining structural information about proteins. Restraints derived from XL-MS experiments have been used successfully for structure refinement and protein-protein docking. However, one formidable question is under which circumstances XL-MS data might be sufficient to determine a protein's tertiary structure de novo? Answering this question will not only include understanding the impact of XL-MS data on sampling and scoring within a de novo protein structure prediction algorithm, it must also determine an optimal cross-linker type and length for protein structure determination. While a longer cross-linker will yield more restraints, the value of each restraint for protein structure prediction decreases as the restraint is consistent with a larger conformational space. In this study, the number of cross-links and their discriminative power was systematically analyzed in silico on a set of 2,055 non-redundant protein folds considering Lys-Lys, Lys-Asp, Lys-Glu, Cys-Cys, and Arg-Arg reactive cross-linkers between 1 {\AA} and 60 {\AA}. Depending on the protein size a heuristic was developed that determines the optimal cross-linker length. Next, simulated restraints of variable length were used to de novo predict the tertiary structure of fifteen proteins using the BCL::Fold algorithm. The results demonstrate that a distinct cross-linker length exists for which information content for de novo protein structure prediction is maximized. The sampling accuracy improves on average by 1.0 {\AA} and up to 2.2 {\AA} in the most prominent example. XL-MS restraints enable consistently an improved selection of native-like models with an average enrichment of 2.1.