Abstract
The fundamental aim of structural analyses in biophysics is to reveal a mutual relation between a molecule’s dynamic structure and its physiological function. Small-angle X-ray scattering (SAXS) is an experimental technique for structural characterization of macromolecules in solution and enables time-resolved analysis of conformational changes under physiological conditions. As such experiments measure spatially averaged low-resolution scattering intensities only, the sparse information obtained is not sufficient to uniquely reconstruct a three-dimensional atomistic model. Here, we integrate the information from SAXS into molecular dynamics simulations using computationally efficient native structure-based models. Dynamically fitting an initial structure towards a scattering intensity, such simulations produce atomistic models in agreement with the target data. In this way, SAXS data can be rapidly interpreted while retaining physico-chemical knowledge and sampling power of the underlying force field. We demonstrate our method’s performance using the example of three protein systems. Simulations are faster than full molecular dynamics approaches by more than two orders of magnitude and consistently achieve comparable accuracy. Computational demands are reduced sufficiently to run the simulations on commodity desktop computers instead of high-performance computing systems. These results underline that scattering-guided structure-based simulations provide a suitable framework for rapid early-stage refinement of structures towards SAXS data with particular focus on minimal computational resources and time.
Highlights
Protein structure determination is a key challenge in modern biophysics and aims at revealing a fundamental relation between biomolecular structure and function
We considered minimum target root-mean-square deviation (RMSD) as a primary indicator to assess whether a simulation converges sufficiently close towards the target to provide a real chance to observe the conformations of interest despite the structure-based models (SBMs)’s strong bias towards the Theoretical difference curves of simulated structures almost perfectly match the target data and were plotted with small offsets. (C) Initial and target RMSD and bias energy versus simulated time. (D) Best structures as measured by target and bias energy
A fundamental paradigm in protein biophysics is the interdependency of macromolecular structure and function
Summary
Protein structure determination is a key challenge in modern biophysics and aims at revealing a fundamental relation between biomolecular structure and function. Experimental data is typically processed in form of difference curves, where the initial intensity serves as a reference and is subtracted from that of a certain time point Such curves reflect a difference in pair distribution functions and structural change during the molecular reaction. In particular with large structural rearrangements being involved, such methods do not yield reliable results Other approaches such as rigid body refinement [15, 16], simulated annealing of dummy atom collections [13, 17], and targeted selection of suitable frames from biomolecular simulations [10, 18, 19] rely on sequential sampling and comparison with experimental data by generating candidate structures and calculating their respective scattering patterns.
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