Accommodating Protein Dynamics in the Modeling of Chemical Crosslinks

Abstract

Chemical crosslinking can identify the neighborhood relationships between specific amino-acid residues in proteins. The interpretation of crosslinking data is typically performed using single, static atomic structures. However, proteins are dynamic, undergoing motions spanning from local fluctuations of individual residues to global motions of protein assemblies. Here we demonstrate that failure to explicitly accommodate dynamics when interpreting crosslinks structurally can lead to considerable errors. We present a method and associated software, DynamXL, which is able to account directly for flexibility in the context of crosslinking modeling. Our benchmarking on a large dataset of model structures demonstrates significantly improved rationalization of experimental crosslinking data, and enhanced performance in a protein-protein docking protocol. These advances will provide a considerable increase in the structural insights attainable using chemical crosslinking coupled to mass spectrometry.

Keywords: computational structural biology; crosslinking; mass spectrometry; molecular modeling; protein docking.