Determining structural ensembles of flexible multi-domain proteins using small-angle X-ray scattering and molecular dynamics simulations.
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ABSTRACT:
SUBMITTER: Zhang Y
PROVIDER: S-EPMC4506289 | biostudies-literature | 2015 Aug
REPOSITORIES: biostudies-literature
Publications
Determining structural ensembles of flexible multi-domain proteins using small-angle X-ray scattering and molecular dynamics simulations.
Zhang Yonghui Y Wen Bin B Peng Junhui J Zuo Xiaobing X Gong Qingguo Q Zhang Zhiyong Z
Protein & cell 20150801 8
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Project description:Intrinsically disordered proteins and flexible regions in multidomain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modeling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model (i.e., an algorithm to calculate experimental observables from individual conformations or ensembles). In many cases, this involves one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle x-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data but across the entire ensemble. Here, we present a protocol to dissect the effect of the free parameters on the calculated SAXS intensities and to identify a reliable set of values. We have implemented this procedure in our Bayesian/maximum entropy framework for ensemble refinement and demonstrate the results on four intrinsically disordered proteins and a protein with three domains connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects and suggest that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins.
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Project description:Many proteins contain multiple folded domains separated by flexible linkers, and the ability to describe the structure and conformational heterogeneity of such flexible systems pushes the limits of structural biology. Using the three-domain protein TIA-1 as an example, we here combine coarse-grained molecular dynamics simulations with previously measured small-angle scattering data to study the conformation of TIA-1 in solution. We show that while the coarse-grained potential (Martini) in itself leads to too compact conformations, increasing the strength of protein-water interactions results in ensembles that are in very good agreement with experiments. We show how these ensembles can be refined further using a Bayesian/Maximum Entropy approach, and examine the robustness to errors in the energy function. In particular we find that as long as the initial simulation is relatively good, reweighting against experiments is very robust. We also study the relative information in X-ray and neutron scattering experiments and find that refining against the SAXS experiments leads to improvement in the SANS data. Our results suggest a general strategy for studying the conformation of multi-domain proteins in solution that combines coarse-grained simulations with small-angle X-ray scattering data that are generally most easy to obtain. These results may in turn be used to design further small-angle neutron scattering experiments that exploit contrast variation through 1H/2H isotope substitutions.
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Project description:Intrinsic flexibility is closely related to protein function, and a plethora of important regulatory proteins have been found to be flexible, multi-domain or even intrinsically disordered. On the one hand, understanding such systems depends on how these proteins behave in solution. On the other, small-angle X-ray scattering (SAXS) is a technique that fulfills the requirements to study protein structure and dynamics relatively quickly with few experimental limitations. Molecular chaperones from Hsp70 and Hsp90 families are multi-domain proteins containing flexible and/or disordered regions that play central roles in cellular proteostasis. Here, we review the structure and function of these proteins by SAXS. Our general approach includes the use of SAXS data to determine size and shape parameters, as well as protein shape reconstruction and their validation by using accessory biophysical tools. Some remarkable examples are presented that exemplify the potential of the SAXS technique. Protein structure can be determined in solution even at limiting protein concentrations (for example, human mortalin, a mitochondrial Hsp70 chaperone). The protein organization, flexibility and function (for example, the J-protein co-chaperones), oligomeric status, domain organization, and flexibility (for the Hsp90 chaperone and the Hip and Hep1 co-chaperones) may also be determined. Lastly, the shape, structural conservation, and protein dynamics (for the Hsp90 chaperone and both p23 and Aha1 co-chaperones) may be studied by SAXS. We believe this review will enhance the application of the SAXS technique to the study of the molecular chaperones.
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Project description:Wide-angle x-ray scattering (WAXS) experiments of biomolecules in solution have become increasingly popular because of technical advances in light sources and detectors. However, the structural interpretation of WAXS profiles is problematic, partly because accurate calculations of WAXS profiles from structural models have remained challenging. In this work, we present the calculation of WAXS profiles from explicit-solvent molecular dynamics (MD) simulations of five different proteins. Using only a single fitting parameter that accounts for experimental uncertainties because of the buffer subtraction and dark currents, we find excellent agreement to experimental profiles both at small and wide angles. Because explicit solvation eliminates free parameters associated with the solvation layer or the excluded solvent, which would require fitting to experimental data, we minimize the risk of overfitting. We further find that the influence from water models and protein force fields on calculated profiles are insignificant up to q≈15nm(-1). Using a series of simulations that allow increasing flexibility of the proteins, we show that incorporating thermal fluctuations into the calculations significantly improves agreement with experimental data, demonstrating the importance of protein dynamics in the interpretation of WAXS profiles. In addition, free MD simulations up to one microsecond suggest that the calculated profiles are highly sensitive with respect to minor conformational rearrangements of proteins, such as an increased flexibility of a loop or an increase of the radius of gyration by < 1%. The present study suggests that quantitative comparison between MD simulations and experimental WAXS profiles emerges as an accurate tool to validate solution ensembles of biomolecules.
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Project description:The combination of molecular dynamics (MD) simulations and small-angle X-ray scattering (SAXS), called the MD-SAXS method, is efficient for investigating protein dynamics. To overcome the time-scale limitation of all-atom MD simulations, coarse-grained (CG) representations are often utilized for biomolecular simulations. In this study, we propose a method to combine CG MD simulations with SAXS, termed the CG-MD-SAXS method. In the CG-MD-SAXS method, the scattering factors of CG particles for proteins and nucleic acids are evaluated using high-resolution structural data in the Protein Data Bank, and the excluded volume and the hydration shell are modeled using two adjustable parameters to incorporate solvent effects. To avoid overfitting, only the two parameters are adjusted for an entire structure ensemble. To verify the developed method, theoretical SAXS profiles for various proteins, DNA/RNA, and a protein-RNA complex are compared with both experimental profiles and theoretical profiles obtained by the all-atom representation. In the present study, we applied the CG-MD-SAXS method to the Swi5-Sfr1 complex and three types of nucleosomes to obtain reliable ensemble models consistent with the experimental SAXS data.
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Project description:Speckle-type POZ protein (SPOP) is a substrate adaptor in the ubiquitin proteasome system, and plays important roles in cell-cycle control, development, and cancer pathogenesis. SPOP forms linear higher-order oligomers following an isodesmic self-association model. Oligomerization is essential for SPOP's multivalent interactions with substrates, which facilitate phase separation and localization to biomolecular condensates. Structural characterization of SPOP in its oligomeric state and in solution is, however, challenging due to the inherent conformational and compositional heterogeneity of the oligomeric species. Here, we develop an approach to simultaneously and self-consistently characterize the conformational ensemble and the distribution of oligomeric states of SPOP by combining small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations. We build initial conformational ensembles of SPOP oligomers using coarse-grained molecular dynamics simulations, and use a Bayesian/maximum entropy approach to refine the ensembles, along with the distribution of oligomeric states, against a concentration series of SAXS experiments. Our results suggest that SPOP oligomers behave as rigid, helical structures in solution, and that a flexible linker region allows SPOP's substrate-binding domains to extend away from the core of the oligomers. Additionally, our results are in good agreement with previous characterization of the isodesmic self-association of SPOP. In the future, the approach presented here can be extended to other systems to simultaneously characterize structural heterogeneity and self-assembly.
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Project description:Solving structural ensembles of flexible biomolecules is a challenging research area. Here, we propose a method to obtain possible structural ensembles of a biomolecule based on small-angle X-ray scattering (SAXS) and molecular dynamics simulations. Our idea is to clip a time series that matches a SAXS profile from a simulation trajectory. To examine its practicability, we applied our idea to a multi-domain protein ER-60 and successfully extracted time series longer than 1 micro second from trajectories of coarse-grained molecular dynamics simulations. In the extracted time series, the domain conformation was distributed continuously and smoothly in a conformational space. Preferred domain conformations were also observed. Diversity among scattering curves calculated from each ER-60 structure was interpreted to reflect an open-close motion of the protein. Although our approach did not provide a unique solution for the structural ensemble of the biomolecule, each extracted time series can be an element of the real behavior of ER-60. Considering its low computational cost, our approach will play a key role to identify biomolecular dynamics by integrating SAXS, simulations, and other experiments.
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Project description:Proteins and protein complexes with high conformational flexibility participate in a wide range of biological processes. These processes include genome maintenance, gene expression, signal transduction, cell cycle regulation, and many others. Gaining a structural understanding of conformationally flexible proteins and protein complexes is arguably the greatest problem facing structural biologists today. Over the last decade, some progress has been made toward understanding the conformational flexibility of such systems using hybrid approaches. One particularly fruitful strategy has been the combination of small-angle X-ray scattering (SAXS) and molecular simulations. In this article, we provide a brief overview of SAXS and molecular simulations and then discuss two general approaches for combining SAXS data and molecular simulations: minimal ensemble approaches and full ensemble approaches. In minimal ensemble approaches, one selects a minimal ensemble of structures from the simulations that best fit the SAXS data. In full ensemble approaches, one validates a full ensemble of structures from the simulations using SAXS data. We argue that full ensemble models are more realistic than minimal ensemble searches models and that full ensemble approaches should be used wherever possible.
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