New therapeutic options are urgently needed to fight drug-resistant and life-threatening infections. In contrast to antibiotics that inhibit the growth pathways of bacteria, the antivirulence strategy is a promising approach to disarm pathogens by interfering with bacterial virulence factors without exerting evolutionary pressure.

Chemical cross-linking, combined with mass spectrometry analysis, is a key source of information for characterizing the structure of large protein assemblies, in the context of molecular modeling. In most approaches, the interpretation is limited to simple spatial restraints, neglecting the physico-chemical interactions between the cross-linker and the protein and of flexibility. Here we present a method, named NRGXL (New Realistic Grid for Cross-Links), which models the flexibility of the cross-linker and the linked side chains, by explicitly sampling many conformations. Also, the method can efficiently deal with overall protein dynamics. This method creates a physical model of the cross-linker and associated energy. A classifier based on it outperforms others, based on Euclidean distance or solvent accessible distance and its efficiency makes it usable for validating 3D models from cross-linking data. NRGXL is freely available as a web server at: https://nrgxl.pasteur.fr.

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