  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.
