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Statistical mechanics of the denatured state of a protein using replica-averaged metadynamics
No full textThe characterization of denatured states of proteins is challenging because the lack of permanent structure in these states makes it difficult to apply to them standard methods of structural biology. In this work we use all-atom replica-averaged metadynamics (RAM) simulations with NMR chemical shift restraints to determine an ensemble of structures representing an acid-denatured state of the 86-residue protein ACBP. This approach has enabled us to reach convergence in the free energy landscape calculations, obtaining an ensemble of structures in relatively accurate agreement with independent experimental data used for validation. By observing at atomistic resolution the transient formation of native and non-native structures in this acid-denatured state of ACBP, we rationalize the effects of single-point mutations on the folding rate, stability, and transition-state structures of this protein, thus characterizing the role of the unfolded state in determining the folding process
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Assessment of the use of NMR chemical shifts as replica-averaged structural restraints in molecular dynamics simulations to characterize the dynamics of proteins
No full textIt has been recently proposed that NMR chemical shifts can be used as replica-averaged structural restraints in molecular dynamics simulations to determine the conformational fluctuations of proteins. In this work, we assess the accuracy of this approach by considering its application to the case of ribonuclease A. We found that the agreement between experimental and calculated chemical shifts improves on average when the chemical shifts are used as replica-averaged restraints with respect to the cases in which X-ray structures or ensembles of structures obtained by standard molecular dynamics simulations are considered. These results indicate that the use of chemical shifts as structural restraints enables a bias of the conformational sampling to be introduced in a system-specific manner to reproduce accurately the conformational fluctuations of proteins
Determination of the conformational states of strychnine in solution using NMR residual dipolar couplings in a tensor-free approach
No full textSmall molecules with rotatable bonds can occupy different conformational states in solution as a consequence of their thermal fluctuations. The accurate determination of the structures of such states, as well as of their statistical weights, has been challenging because of the technical difficulties in extracting information from experimental measurements, which are normally averaged over the conformational space available. Here, to achieve this objective, we present an approach based on a recently proposed tensor-free method for incorporating NMR residual dipolar couplings as structural restraints in replica-averaged molecular dynamics simulations. This approach enables the information provided by the experimental data to be used in the spirit of the maximum entropy principle to determine the structural ensembles of small molecules. Furthermore, in order to enhance the sampling of the conformational space we incorporated the metadynamics method in the simulations. We illustrate the method in the case of strychnine, determining the three major conformational states of this small molecule and their associated occupation probabilities
A tensor-free method for the structural and dynamical refinement of proteins using residual dipolar couplings
No full textResidual dipolar couplings (RDCs) are parameters measured in nuclear magnetic resonance spectroscopy that can provide exquisitely detailed information about the structure and dynamics of biological macromolecules. We describe here a method of using RDCs for the structural and dynamical refinement of proteins that is based on the observation that the RDC between two atomic nuclei depends directly on the angle ∂ between the internuclear vector and the external magnetic field. For every pair of nuclei for which an RDC is available experimentally, we introduce a structural restraint to minimize the deviation from the value of the angle ∂ derived from the measured RDC and that calculated in the refinement protocol. As each restraint involves only the calculation of the angle ∂ of the corresponding internuclear vector, the method does not require the definition of an overall alignment tensor to describe the preferred orientation of the protein with respect to the alignment medium. Application to the case of ubiquitin demonstrates that this method enables an accurate refinement of the structure and dynamics of this protein to be obtained
Lymphotactin: How a protein can adopt two folds
No full textMetamorphic proteins such as lymphotactin are a notable exception of the empirical principle that structured natural proteins possess a unique three-dimensional structure. In particular, the human chemokine lymphotactin protein exists in two distinct conformations (one monomeric and one dimeric) under physiological conditions. In this work, we use a Cα G ō model to show how this very peculiar behavior can be reproduced. From the study of the thermodynamics and of the kinetics, we characterize the interconversion mechanism. In particular, this takes place through the docking of the two chains living in a third monomeric, partially unfolded, state which shows a residual structure involving a set of local contacts common to the two native conformations. The main feature of two fold proteins appears to be the sharing of a common set of local contacts between the two distinct folds as confirmed by the study of two designed two fold proteins. Metamorphic proteins may be more common than expected. © 2009 American Institute of Physics
From A to B : a ride in the free energy surfaces of protein G domains suggests how new folds arise
No full textMetamorphic proteins are an extremely intriguing case of protein evolution and a golden opportunity to challenge the current simplified models. In a recent work, we showed that a coarse-grained Go model can be used to study the thermodynamics of lymphotactin, a naturally occurring metamorphic protein. Here, we extend such model by including the necessary atomic detail to study the effects of the single mutations that artificially bring the GA domain of protein G to fold into the GB domain of the same protein. The results of this all-atom Go model show how the residual structure of the denatured state is an early indicator of a forthcoming fold and function switch. These findings reconcile the results of previous studies on similar systems highlighting the different role played by secondary and tertiary interactions and suggesting a possible way for new folds to arise
Ratcheted molecular-dynamics simulations identify efficiently the transition state of protein folding
No full textThe atomistic characterization of the transition state (TS) is a fundamental step to improve the understanding of the folding mechanism and the function of proteins. From a computational point of view, the identification of the conformations that build out the transition state is particularly cumbersome, mainly because of the large computational cost of generating a statistically sound set of folding trajectories. Here we show that a biasing algorithm, based on the physics of the ratchet-and-pawl, can be used to approximate efficiently the transition state. The basic idea is that the algorithmic ratchet exerts a force on the protein when it is climbing the free-energy barrier, while it is inactive when it is descending. The transition state can be identified as the point of the trajectory where the ratchet changes regime. Besides discussing this strategy in general terms, we test it within a protein model whose transition state can be studied independently by plain molecular dynamics simulations. Finally, we show its power in explicit-solvent simulations, obtaining and characterizing a set of transition-state conformations for Acyl-Coenzyme A-Binding Protein (ACBP) and Chymotrypsin Inhibitor 2 (CI2)
Properties of low-dimensional collective variables in the molecular dynamics of biopolymers
Full text linkThe description of the dynamics of a complex, high-dimensional system in terms of a low-dimensional set of collective variables Y can be fruitful if the low-dimensional representation satisfies a Langevin equation with drift and diffusion coefficients that depend only on Y . We present a computational scheme to evaluate whether a given collective variable provides a faithful low-dimensional representation of the dynamics of a high-dimensional system. The scheme is based on the framework of a finite-difference Langevin equation, similar to that used for molecular-dynamics simulations. This allows one to calculate the drift and diffusion coefficients in any point of the full-dimensional system. The width of the distribution of drift and diffusion coefficients in an ensemble of microscopic points at the same value of Y indicates to what extent the dynamics of Y is described by a simple Langevin equation. Using a simple protein model, we show that collective variables often used to describe biopolymers display a non-negligible width both in the drift and in the diffusion coefficients. We also show that the associated effective force is compatible with the equilibrium free energy calculated from a microscopic sampling, but it results in markedly different dynamical properties
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