Underlying Protein Dynamics Research Articles

Reconciling membrane protein simulations with experimental DEER spectroscopy data.

Spectroscopy experiments are crucial to study membrane proteins for which traditional structure determination methods still prove challenging. Double electron-electron resonance (DEER) spectroscopy experiments provide protein residue-pair distance distributions that are indicative of their conformational heterogeneity. Atomistic molecular dynamics (MD) simulations are another tool that have been proven to be vital to study the structural dynamics of membrane proteins such as to identify inward-open, occluded, and outward-open conformations of transporter membrane proteins, among other partially open or closed states of the protein. Yet, studies have reported that there is no direct consensus between the distributional data from DEER experiments and MD simulations, which has challenged validation of structures obtained from long-timescale simulations and using simulations to design experiments. Current coping strategies for comparisons rely on heuristics, such as mapping the nearest matching peaks between two ensembles or biased simulations. Here we examine the differences in residue-pair distance distributions arising due to the choice of membranes around the protein and covalent modification of a pair of residues to nitroxide spin labels in DEER experiments. Through comparing MD simulations of two proteins, PepTSo and LeuT-both of which have been characterized using DEER experiments previously-we show that the proteins' dynamics are similar despite the choice of the detergent micelle as a membrane mimetic in DEER experiments. On the other hand, covalently modified residues show slight local differences in their dynamics and a huge divergence when the oxygen atom pair distances between spin labeled residues are measured rather than protein backbone distances. Given the computational expense associated with pairwise MTSSL labeled MD simulations, we examine the use of biased simulations to explore the conformational dynamics of the spin labels only to reveal that such simulations alter the underlying protein dynamics. Our study identifies the main cause for the mismatch between DEER experiments and MD simulations and will accelerate the development of potential mitigation strategies to improve the match.

Legionella effector MavC targets the Ube2N~Ub conjugate for noncanonical ubiquitination

The bacterial effector MavC modulates the host immune response by blocking Ube2N activity employing an E1-independent ubiquitin ligation, catalyzing formation of a γ-glutamyl-ε-Lys (Gln40Ub-Lys92Ube2N) isopeptide crosslink using a transglutaminase mechanism. Here we provide biochemical evidence in support of MavC targeting the activated, thioester-linked Ube2N~ubiquitin conjugate, catalyzing an intramolecular transglutamination reaction, covalently crosslinking the Ube2N and Ub subunits effectively inactivating the E2~Ub conjugate. Ubiquitin exhibits weak binding to MavC alone, but shows an increase in affinity when tethered to Ube2N in a disulfide-linked substrate that mimics the charged E2~Ub conjugate. Crystal structures of MavC in complex with the substrate mimic and crosslinked product provide insights into the reaction mechanism and underlying protein dynamics that favor transamidation over deamidation, while revealing a crucial role for the structurally unique insertion domain in substrate recognition. This work provides a structural basis of ubiquitination by transglutamination and identifies this enzyme’s true physiological substrate.

Intrinsic noise in systems with switching environments.

We study individual-based dynamics in finite populations, subject to randomly switching environmental conditions. These are inspired by models in which genes transition between on and off states, regulating underlying protein dynamics. Similarly, switches between environmental states are relevant in bacterial populations and in models of epidemic spread. Existing piecewise-deterministic Markov process approaches focus on the deterministic limit of the population dynamics while retaining the randomness of the switching. Here we go beyond this approximation and explicitly include effects of intrinsic stochasticity at the level of the linear-noise approximation. Specifically, we derive the stationary distributions of a number of model systems, in good agreement with simulations. This improves existing approaches which are limited to the regimes of fast and slow switching.

The Structural Basis for Activation and Inhibition of ZAP-70 Kinase Domain.

ZAP–70 (Zeta-chain-associated protein kinase 70) is a tyrosine kinase that interacts directly with the activated T-cell receptor to transduce downstream signals, and is hence a major player in the regulation of the adaptive immune response. Dysfunction of ZAP–70 causes selective T cell deficiency that in turn results in persistent infections. ZAP–70 is activated by a variety of signals including phosphorylation of the kinase domain (KD), and binding of its regulatory tandem Src homology 2 (SH2) domains to the T cell receptor. The present study investigates molecular mechanisms of activation and inhibition of ZAP–70 via atomically detailed molecular dynamics simulation approaches. We report microsecond timescale simulations of five distinct states of the ZAP–70 KD, comprising apo, inhibited and three phosphorylated variants. Extensive analysis of local flexibility and correlated motions reveal crucial transitions between the states, thus elucidating crucial steps in the activation mechanism of the ZAP–70 KD. Furthermore, we rationalize previously observed staurosporine-bound crystal structures, suggesting that whilst the KD superficially resembles an “active-like” conformation, the inhibitor modulates the underlying protein dynamics and restricts it in a compact, rigid state inaccessible to ligands or cofactors. Finally, our analysis reveals a novel, potentially druggable pocket in close proximity to the activation loop of the kinase, and we subsequently use its structure in fragment-based virtual screening to develop a pharmacophore model. The pocket is distinct from classical type I or type II kinase pockets, and its discovery offers promise in future design of specific kinase inhibitors, whilst mutations in residues associated with this pocket are implicated in immunodeficiency in humans.

Protein Dynamics and the Diversity of an Antibody Response

The immune system is remarkable in its ability to produce antibodies (Abs) with virtually any specificity from a limited repertoire of germ line precursors. Although the contribution of sequence diversity to this molecular recognition has been studied for decades, recent models suggest that protein dynamics may also broaden the range of targets recognized. To characterize the contribution of protein dynamics to immunological molecular recognition, we report the sequence, thermodynamic, and time-resolved spectroscopic characterization of a panel of eight Abs elicited to the chromophoric antigen 8-methoxypyrene-1,3,6-trisulfonate (MPTS). Based on the sequence data, three of the Abs arose from unique germ line Abs, whereas the remaining five comprise two sets of siblings that arose by somatic mutation of a common precursor. The thermodynamic data indicate that the Abs recognize MPTS via a variety of mechanisms. Although the spectroscopic data reveal small differences in protein dynamics, the anti-MPTS Abs generally show similar levels of flexibility and conformational heterogeneity, possibly representing the convergent evolution of the dynamics necessary for function. However, one Ab is significantly more rigid and conformationally homogeneous than the others, including a sibling Ab from which it differs by only five somatic mutations. This example of divergent evolution demonstrates that point mutations are capable of fixing significant differences in protein dynamics. The results provide unique insight into how high affinity Abs may be produced that bind virtually any target and possibly, from a more general perspective, how new protein functions are evolved.

XPyder: A PyMOL Plugin To Analyze Coupled Residues and Their Networks in Protein Structures.

A versatile method to directly identify and analyze short- or long-range coupled or communicating residues in a protein conformational ensemble is of extreme relevance to achieve a complete understanding of protein dynamics and structural communication routes. Here, we present xPyder, an interface between one of the most employed molecular graphics systems, PyMOL, and the analysis of dynamical cross-correlation matrices (DCCM). The approach can also be extended, in principle, to matrices including other indexes of communication propensity or intensity between protein residues, as well as the persistence of intra- or intermolecular interactions, such as those underlying protein dynamics. The xPyder plugin for PyMOL 1.4 and 1.5 is offered as Open Source software via the GPL v2 license, and it can be found, along with the installation package, the user guide, and examples, at http://linux.btbs.unimib.it/xpyder/.

Detection of viscoelasticity in aggregating dilute protein solutions through dynamic light scattering-based optical microrheology

This study illustrates the applicability of dynamic light scattering (DLS)-based optical microrheology in generating new insights into the rheological response of dilute protein solutions as they start to form insoluble aggregates under the influence of a thermal stress. The technique is also shown to provide a quick method for measuring the viscosity in protein solutions. The optical microrheological technique, which is based on DLS with improved single scattering detection, is shown here to capture the rich dynamics in these systems, where traditional mechanical rheometry cannot be effectively employed due to low torque generation and high sample volume requirements and the more widely known diffusing wave spectroscopy microrheology technique is not desirable due to the required high probe particle concentrations The study illustrates the careful consideration which must be given to the tracer particle surface chemistry, tracer particle concentration and tracer particle size in order to extract out rheological responses that are truly representative of the underlying protein dynamics and microstructure. We outline a procedure for ensuring that the pitfalls inherent to this type of measurement are avoided.

Structural Dynamics of Myosin Investigated by Transient Time Resolved Fluorescence

We are using transient time resolved fluorescence (TR)2F to map conformational transitions in the catalytic domain of Dictyostelium myosin II. The photophysical state of fluorescent probes, site specifically attached to proteins, shadows the underlying protein structure, dynamics and local electrochemical environment. Changes in these underlying constraints, affect the excited state lifetime of the probe. Because the lifetime decays exponentially, different populations of photophysical states in the sample ensemble can be isolated by analyzing the time resolved decay. In a typical experiment, a probe (or pair of probes in the case of a FRET experiment) are innocuously attached to specific sites on myosin and actin. We then measure underlying protein dynamics by time resolved anisotropy and accessibility which reflect the local restricted motion of the probe, and by FRET which reflects the distance (or when κ2 does not = 2/3, distance and the relative dipole orientation) between two probe pairs. When these measurements are performed during a biochemical transient initiated by stopped flow, we gain incite into the millisecond scale “structural kinetics” associated with the transition. These studies are made possible by the recent development of a high throughput time resolved fluorescence spectrometer which can measure a complete, high resolution, time resolved fluorescence decay, in 0.1 ms. The high throughput character of this instrument allows us to measure changes in the time resolved fluorescence decay and thus structural dynamics of a probe during a stopped flow initiated biochemical transient. The added dimensionality afforded by time resolved fluorescence isolates discrete populations of structural states in the ensemble. It also increases the measurement precision. We are using this approach to measure millisecond scale structural transitions that occur in myosin during nucleotide binding, hydrolysis and product dissociation and during actin binding and detachment.

Understanding ligand-based modulation of the Hsp90 molecular chaperone dynamics at atomic resolution

Molecular switching and ligand-based modulation of the 90-kDa heat-shock protein (Hsp90) chaperone activity may ultimately facilitate conformational coupling to the ATPase cycle along with activation and recruitment of the broad range of client proteins. We present an atomic resolution analysis of the Hsp90 N-terminal domain (NTD) binding energy landscape by simulating protein dynamics with a range of binding partners. We show that the activity of the molecular chaperone may be linked to (i) local folding-unfolding transitions and conformational switching of the "active site lid" upon binding and (ii) differences in the underlying protein dynamics as a function of the binding partner. This study suggests that structural plasticity of the Hsp90 NTD can be exploited by the molecular chaperone machinery to modulate enhanced structural rigidity during ATP binding and increased protein flexibility as a consequence of the inhibitor binding. The present study agrees with the experimental structural data and provides a plausible molecular model for understanding mechanisms of modulation of molecular chaperone activities by binding partners.

Structural information content and Lyapunov exponent calculation in protein unfolding

A lattice model with Monte Carlo dynamics is used to carry out computer simulations of protein dynamics on a four α-helix bundle. The interaction energies in the model can be set so that either the helix bundle structure remains relatively stable or changed so that it unfolds. The computer model produces output that simulates experimental measurements relating to the structure. We show how this output can be used with analytical techniques of nonlinear dynamics to obtain important information about the complex underlying protein dynamics. Time-delay reconstruction plots of structural parameters of unfolding bundles resemble strange attractors in a space of dimension 3–4. We calculate Lyapunov exponents for these unfolding runs and find positive Lyapunov exponents implying chaotic dynamics. For stable runs the Lyapunov exponents are close to zero. We use these Lyapunov exponents to calculate the rate of loss of structural information during the unfolding process and show how the approach may be useful for investigating the folding dynamics of proteins. © 1998 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 36: 2761–2769, 1998