Structural prediction of protein models using distance restraints derived from cross-linking mass spectrometry data
- Resource Type
- Authors
- Thomas Stranzl; Peter Schlögelhofer; Otto Hudecz; Karl Mechtler; Zsuzsanna Orban-Nemeth; David Maria Hollenstein; Johannes Doblmann; Rebecca Beveridge; Evelyn Rampler
- Source
- Subject
- Models, Molecular
0301 basic medicine
Basis (linear algebra)
Computer science
010401 analytical chemistry
Proteins
Experimental data
Mass spectrometry
01 natural sciences
Mass Spectrometry
General Biochemistry, Genetics and Molecular Biology
Article
Protein Structure, Tertiary
0104 chemical sciences
03 medical and health sciences
Search engine
Cross-Linking Reagents
030104 developmental biology
Workflow
Protein structure
DOCK
Computer Simulation
Biological system
Protocol (object-oriented programming)
Forecasting
- Language
- English
This protocol describes a workflow for creating structural models of proteins or protein complexes using distance restraints derived from cross-linking mass spectrometry experiments. The distance restraints are used (i) to adjust preliminary models that are calculated on the basis of a homologous template and primary sequence, and (ii) to select the model that is in best agreement with the experimental data. In the case of protein complexes, the cross-linking data are further used to dock the subunits to one another to generate models of the interacting proteins. Predicting models in such a manner has the potential to indicate multiple conformations and dynamic changes that occur in solution. This modeling protocol is compatible with many cross-linking workflows and uses open-source programs or programs that are free for academic users and do not require expertise in computational modeling. This protocol is an excellent additional application with which to use cross-linking results for building structural models of proteins. The established protocol is expected to take 6-12 d to complete, depending on the size of the proteins and the complexity of the cross-linking data.