On the Use of low-resolution Data to Improve Structure Prediction of Proteins and Protein Complexes

Conformational effects in protein electrospray-ionization mass spectrometry

Electrospray-ionization mass spectrometry (ESI-MS) is a key tool of structural biology, complementing the information delivered by conventional biochemical and biophysical methods. Yet, the mechanism behind the conformational effects in protein ESI-MS is an object of debate. Two parameters-solvent-accessible surface area (As) and apparent gas-phase basicity (GBapp)-are thought to play a role in controlling the extent of protein ionization during ESI-MS experiments. This review focuses on recent experimental and theoretical investigations concerning the influence of these parameters on ESI-MS results and the structural information that can be derived. The available evidence supports a unified model for the ionization mechanism of folded and unfolded proteins. These data indicate that charge-state distribution (CSD) analysis can provide valuable structural information on normally folded, as well as disordered structures.

A computational model for protein ionization by electrospray based on gas-phase basicity

Identifying the key factor(s) governing the overall protein charge is crucial for the interpretation of electrospray-ionization mass spectrometry data. Current hypotheses invoke different principles for folded and unfolded proteins. Here, first we investigate the gas-phase structure and energetics of several proteins of variable size and different folds. The conformer and protomer space of these proteins ions is explored exhaustively by hybrid Monte-Carlo/molecular dynamics calculations, allowing for zwitterionic states. From these calculations, the apparent gas-phase basicity of desolvated protein ions turns out to be the unifying trait dictating protein ionization by electrospray. Next, we develop a simple, general, adjustable-parameter-free model for the potential energy function of proteins. The model is capable to predict with remarkable accuracy the experimental charge of folded proteins and its well-known correlation with the square root of protein mass.

Structural characterization of protein-protein complexes by integrating computational docking with small-angle scattering data

X-ray crystallography and NMR can provide detailed structural information of protein-protein complexes, but technical problems make their application challenging in the high-throughput regime. Other methods such as small-angle X-ray scattering (SAXS) are more promising for large-scale application, but at the cost of lower resolution, which is a problem that can be solved by complementing SAXS data with theoretical simulations. Here, we propose a novel strategy that combines SAXS data and accurate protein-protein docking simulations. The approach has been benchmarked on a large pool of known structures with synthetic SAXS data, and on three experimental examples. The combined approach (pyDockSAXS) provided a significantly better success rate (43% for the top 10 predictions) than either of the two methods alone. Further analysis of the influence of different docking parameters made it possible to increase the success rates for specific cases, and to define guidelines for improving the data-driven protein-protein docking protocols.