Unfolding dynamics of proteins under applied force

Understanding the mechanisms of protein folding is a major challenge that is being addressed effectively by collaboration between researchers in the physical and life sciences. Recently, it has become possible to mechanically unfold proteins by pulling on their two termini using local force probes such as the atomic force microscope. Here, we present data from experiments in which synthetic protein polymers designed to mimic naturally occurring polyproteins have been mechanically unfolded. For many years protein folding dynamics have been studied using chemical denaturation, and we therefore firstly discuss our mechanical unfolding data in the context of such experiments and show that the two unfolding mechanisms are not the same, at least for the proteins studied here. We also report unexpected observations that indicate a history effect in the observed unfolding forces of polymeric proteins and explain this in terms of the changing number of domains remaining to unfold and the increasing compliance of the lengthening unstructured polypeptide chain produced each time a domain unfolds

Optimizing the calculation of energy landscape parameters from single-molecule protein unfolding experiments

Single-molecule force spectroscopy using an atomic force microscope (AFM) can be used to measure the average unfolding force of proteins in a constant velocity experiment. In combination with Monte Carlo simulations and through the application of the Zhurkov-Bell model, information about the parameters describing the underlying unfolding energy landscape of the protein can be obtained. Using this approach, we have completed protein unfolding experiments on the polyprotein (I27) 5 over a range of pulling velocities. In agreement with previous work, we find that the observed number of protein unfolding events observed in each approach-retract cycle varies between one and five, due to the nature of the interactions between the polyprotein, the AFM tip, and the substrate, and there is an unequal unfolding probability distribution. We have developed a Monte Carlo simulation that incorporates the impact of this unequal unfolding probability distribution on the median unfolding force and the calculation of the protein unfolding energy landscape parameters. These results show that while there is a significant, unequal unfolding probability distribution, the unfolding energy landscape parameters obtained from use of the Zhurkov-Bell model are not greatly affected. This result is important because it demonstrates that the minimum acceptance criteria typically used in force extension experiments are justified and do not skew the calculation of the unfolding energy landscape parameters. We further validate this approach by determining the error in the energy landscape parameters for two extreme cases, and we provide suggestions for methods that can be employed to increase the level of accuracy in single-molecule experiments using polyproteins

Cooperative folding of intrinsically disordered domains drives assembly of a strong elongated protein.

Bacteria exploit surface proteins to adhere to other bacteria, surfaces and host cells. Such proteins need to project away from the bacterial surface and resist significant mechanical forces. SasG is a protein that forms extended fibrils on the surface of Staphylococcus aureus and promotes host adherence and biofilm formation. Here we show that although monomeric and lacking covalent cross-links, SasG maintains a highly extended conformation in solution. This extension is mediated through obligate folding cooperativity of the intrinsically disordered E domains that couple non-adjacent G5 domains thermodynamically, forming interfaces that are more stable than the domains themselves. Thus, counterintuitively, the elongation of the protein appears to be dependent on the inherent instability of its domains. The remarkable mechanical strength of SasG arises from tandemly arrayed 'clamp' motifs within the folded domains. Our findings reveal an elegant minimal solution for the assembly of monomeric mechano-resistant tethers of variable length.This research was supported by Biotechnology and Biological Research Council Grants BB/J006459/1 (D.T.G. and J.C.), BB/J005029/1 (F.W. and J.R.P), BB/G019452/1 (O.E.F and D.J.B) and BB/G020671/1 (C.G.B. and J.R.P.). H.K.H.F. is supported by a studentship from a Wellcome Trust 4-year PhD programme (WT095024MA). C.M.J. is supported by the German Federal Ministry of Education and Research (BMBF), grant BIOSCAT (contract N° 05K12YE1). J.C. is a Wellcome Trust Senior Research Fellow (WT/095195). J.R.P holds a British Heart Foundation Senior Basic Science Fellowship (FS/12/36/29588). The authors acknowledge the use of EMBL SAXS beamline P12 at Petra-3 (DESY, Hamburg, Germany) and Maxim Petoukhov (EMBL) for providing a modified version of SASR EF. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under BioStruct-X (grant agreement N°283570). The authors would like to thank Diamond Light Source for beamtime (proposal mx-7864) and Johan Turkenburg and Sam Hart for assistance with crystal testing and data collection.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/ncomms827

Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Data for 'Structural and Thermodynamic Classification of Amyloid Polymorphs'

Over 500 amyloid structures have been solved to date to near-atomic resolution. This has highlighted an enormous diversity of fibril structures conforming to the canonical cross-β amyloid fold. Using α-synuclein and tau amyloid structures as models, we show that they can be hierarchically clustered into topologically distinct fold families. Despite their different topologies, fibrils display remarkably similar energy profiles, as determined by FoldX, with the same regions providing stability among different polymorphs. We found that the regions that stabilise the amyloid core pair in different ways to generate distinct topologies. The results provide a framework to classify newly solved fibril structures as belonging to an existing class or forming a new topological cross-β fold. Furthermore, the analysis facilitates comparisons between fibrils found in disease and those formed in vitro, including their nearest structural neighbours. The workflow has been automated, enabling users to interrogate new amyloid structures as they emerge

Skp is a multivalent chaperone of outer membrane proteins

The trimeric chaperone Skp sequesters outer-membrane proteins (OMPs) within a hydrophobic cage, thereby preventing their aggregation during transport across the periplasm in Gram-negative bacteria. Here, we studied the interaction between Escherichia coli Skp and five OMPs of varying size. Investigations of the kinetics of OMP folding revealed that higher Skp/OMP ratios are required to prevent the folding of 16-stranded OMPs compared with their 8-stranded counterparts. Ion mobility spectrometry–mass spectrometry (IMS–MS) data, computer modeling and molecular dynamics simulations provided evidence that 10- to 16-stranded OMPs are encapsulated within an expanded Skp substrate cage. For OMPs that cannot be fully accommodated in the expanded cavity, sequestration is achieved by binding of an additional Skp trimer. The results suggest a new mechanism for Skp chaperone activity involving the coordination of multiple copies of Skp in protecting a single substrate from aggregation

Extraction of Accurate Biomolecular Parameters from Single-Molecule Force Spectroscopy Experiments

The atomic force microscope (AFM) is able to manipulate biomolecules and their complexes with exquisite force sensitivity and distance resolution. This capability, complemented by theoretical models, has greatly improved our understanding of the determinants of mechanical strength in proteins and revealed the diverse effects of directional forces on the energy landscape of biomolecules. In unbinding experiments, the interacting partners are usually immobilized on their respective substrates via extensible linkers. These linkers affect both the force and contour length (Lc) of the complex at rupture. Surprisingly, while the former effect is well understood, the latter is largely neglected, leading to incorrect estimations of Lc, a parameter that is often used as evidence for the detection of specific interactions and remodeling events and for the inference of interaction regions. To address this problem, a model that predicts contour length measurements from single-molecule forced-dissociation experiments is presented that considers attachment position on the AFM tip, geometric effects, and polymer dynamics of the linkers. Modeled data are compared with measured contour length distributions from several different experimental systems, revealing that current methods underestimate contour lengths. The model enables nonspecific interactions to be identified unequivocally, allows accurate determination of Lc, and, by comparing experimental and modeled distributions, enables partial unfolding events before rupture to be identified unequivocally

Outer membrane protein folding from an energy landscape perspective

The cell envelope is essential for the survival of Gram-negative bacteria. This specialised membrane is densely packed with outer membrane proteins (OMPs), which perform a variety of functions. How OMPs fold into this crowded environment remains an open question. Here, we review current knowledge about OFMP folding mechanisms in vitro and discuss how the need to fold to a stable native state has shaped their folding energy landscapes. We also highlight the role of chaperones and the β-barrel assembly machinery (BAM) in assisting OMP folding in vivo and discuss proposed mechanisms by which this fascinating machinery may catalyse OMP folding

Symbiotic Effectiveness of Rhizobial Mutualists Varies in Interactions with Native Australian Legume Genera

Peer reviewe

The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio