Pincus, D. L. ; Thirumalai, D. Crowding effects on the mechanical stability and unfolding pathways of ubiquitin. J Phys Chem B 113, 359-68.
AbstractThe interiors of cells are crowded, thus making it important to assess the effects of macromolecules on the folding of proteins. Using the self-organized polymer (SOP) model, which is a coarse-grained representation of polypeptide chains, we probe the mechanical stability of ubiquitin (Ub) monomers and trimers ((Ub)(3)) in the presence of monodisperse spherical crowding agents. Crowding increases the volume fraction (Phi(c))-dependent average force (f(u)(Phi(c))), relative to the value at Phi(c) = 0, needed to unfold Ub and the polyprotein. For a given Phi(c), the values of f(u)(Phi(c)) increase as the diameter (sigma(c)) of the crowding particles decreases. The average unfolding force f(u)(Phi(c)) depends on the ratio D/R(g), where D approximately sigma(c)(pi/6Phi(c))(1/3), with R(g) being the radius of gyration of Ub (or (Ub)(3)) in the unfolded state. Examination of the unfolding pathways shows that, relative to Phi(c) = 0, crowding promotes reassociation of ruptured secondary structural elements. Both the nature of the unfolding pathways and f(u)(Phi(c)) for (Ub)(3) are altered in the presence of crowding particles, with the effect being most dramatic for the subunit that unfolds last. We predict, based on SOP simulations and theoretical arguments, that f(u)(Phi(c)) approximately Phi(c)(1/3nu), where nu is the Flory exponent that describes the unfolded (random coil) state of the protein.
crowding-effects-on-the-mechanical-stability-and-unfolding-pathways-of-ubiquitin.pdf Tehver, R. ; Chen, J. ; Thirumalai, D. Allostery wiring diagrams in the transitions that drive the GroEL reaction cycle. J Mol Biol 387, 390-406.
AbstractDetermining the network of residues that transmit allosteric signals is crucial to understanding the function of biological nanomachines. During the course of a reaction cycle, biological machines in general, and Escherichia coli chaperonin GroEL in particular, undergo large-scale conformational changes in response to ligand binding. Normal mode analyses, based on structure-based coarse-grained models where each residue is represented by an alpha carbon atom, have been widely used to describe the motions encoded in the structures of proteins. Here, we propose a new Calpha-side chain elastic network model of proteins that includes information about the physical identity of each residue and accurately accounts for the side-chain topology and packing within the structure. Using the Calpha-side chain elastic network model and the structural perturbation method, which probes the response of a local perturbation at a given site at all other sites in the structure, we determine the network of key residues (allostery wiring diagram) responsible for the T-->R and R''-->T transitions in GroEL. A number of residues, both within a subunit and at the interface of two adjacent subunits, are found to be at the origin of the positive cooperativity in the ATP-driven T-->R transition. Of particular note are residues G244, R58, D83, E209, and K327. Of these, R38, D83, and K327 are highly conserved. G244 is located in the apical domain at the interface between two subunits; E209 and K327 are located in the apical domain, toward the center of a subunit; R58 and D83 are equatorial domain residues. The allostery wiring diagram shows that the network of residues are interspersed throughout the structure. Residues D83, V174, E191, and D359 play a critical role in the R''-->T transition, which implies that mutations of these residues would compromise the ATPase activity. D83 and E191 are also highly conserved; D359 is moderately conserved. The negative cooperativity between the rings in the R''-->T transition is orchestrated through several interface residues within a single ring, including N10, E434, D435, and E451. Signal from the trans ring that is transmitted across the interface between the equatorial domains is responsible for the R''-->T transition. The cochaperonin GroES plays a passive role in the R''-->T transition. Remarkably, the binding affinity of GroES for GroEL is allosterically linked to GroEL residues 350-365 that span helices K and L. The movements of helices K and L alter the polarity of the cavity throughout the GroEL functional cycle and undergo large-scale motions that are anticorrelated with the other apical domain residues. The allostery wiring diagrams for the T-->R and R''-->T transitions of GroEL provide a microscopic foundation for the cooperativity (anticooperativity) within (between) the ring (rings). Using statistical coupling analysis, we extract evolutionarily linked clusters of residues in GroEL and GroES. We find that several substrate protein binding residues as well as sites related to ATPase activity belong to a single functional network in GroEL. For GroES, the mobile loop residues and GroES/GroES interface residues are linked.
allostery-wiring-diagrams-in-the-transitions-that-drive-the-groel-reaction-cycle.pdf Ziv, G. ; Thirumalai, D. ; Haran, G. Collapse transition in proteins. Phys Chem Chem Phys 11, 83-93.
AbstractThe coil-globule transition, a tenet of the physics of polymers, has been identified in recent years as an important unresolved aspect of the initial stages of the folding of proteins. We describe the basics of the collapse transition, starting with homopolymers and continuing with proteins. Studies of denatured-state collapse under equilibrium are then presented. An emphasis is placed on single-molecule fluorescence experiments, which are particularly useful for measuring properties of the denatured state even under conditions of coexistence with the folded state. Attempts to understand the dynamics of collapse, both theoretically and experimentally, are then described. Only an upper limit for the rate of collapse has been obtained so far. Improvements in experimental and theoretical methodology are likely to continue to push our understanding of the importance of the denatured-state thermodynamics and dynamics for protein folding in the coming years.
collapse-transition-in-proteins.pdf Zheng, W. ; Thirumalai, D. Coupling between normal modes drives protein conformational dynamics: illustrations using allosteric transitions in myosin II. Biophys J 96, 2128-37.
AbstractStructure-based elastic network models (ENMs) have been remarkably successful in describing conformational transitions in a variety of biological systems. Low-frequency normal modes are usually calculated from the ENM that characterizes elastic interactions between residues in contact in a given protein structure with a uniform force constant. To explore the dynamical effects of nonuniform elastic interactions, we calculate the robustness and coupling of the low-frequency modes in the presence of nonuniform variations in the ENM force constant. The variations in the elastic interactions, approximated here by Gaussian noise, approximately account for perturbation effects of heterogeneous residue-residue interactions or evolutionary sequence changes within a protein family. First-order perturbation theory provides an efficient and qualitatively correct estimate of the mode robustness and mode coupling for finite perturbations to the ENM force constant. The mode coupling analysis and the mode robustness analysis identify groups of strongly coupled modes that encode for protein functional motions. We illustrate the new concepts using myosin II motor protein as an example. The biological implications of mode coupling in tuning the allosteric couplings among the actin-binding site, the nucleotide-binding site, and the force-generating converter and lever arm in myosin isoforms are discussed. We evaluate the robustness of the correlation functions that quantify the allosteric couplings among these three key structural motifs.
coupling-between-normal-modes-drives-protein-conformational-dynamics-illustrations-using-allosteric-transitions-in-myosin-ii.pdf O'Brien, E. P. ; Morrison, G. ; Brooks, B. R. ; Thirumalai, D. How accurate are polymer models in the analysis of Förster resonance energy transfer experiments on proteins?.
J Chem Phys 130, 124903.
AbstractSingle molecule Förster resonance energy transfer (FRET) experiments are used to infer the properties of the denatured state ensemble (DSE) of proteins. From the measured average FRET efficiency, , the distance distribution P(R) is inferred by assuming that the DSE can be described as a polymer. The single parameter in the appropriate polymer model (Gaussian chain, wormlike chain, or self-avoiding walk) for P(R) is determined by equating the calculated and measured . In order to assess the accuracy of this "standard procedure," we consider the generalized Rouse model (GRM), whose properties [ and P(R)] can be analytically computed, and the Molecular Transfer Model for protein L for which accurate simulations can be carried out as a function of guanadinium hydrochloride (GdmCl) concentration. Using the precisely computed for the GRM and protein L, we infer P(R) using the standard procedure. We find that the mean end-to-end distance can be accurately inferred (less than 10% relative error) using and polymer models for P(R). However, the value extracted for the radius of gyration (R(g)) and the persistence length (l(p)) are less accurate. For protein L, the errors in the inferred properties increase as the GdmCl concentration increases for all polymer models. The relative error in the inferred R(g) and l(p), with respect to the exact values, can be as large as 25% at the highest GdmCl concentration. We propose a self-consistency test, requiring measurements of by attaching dyes to different residues in the protein, to assess the validity of describing DSE using the Gaussian model. Application of the self-consistency test to the GRM shows that even for this simple model, which exhibits an order-->disorder transition, the Gaussian P(R) is inadequate. Analysis of experimental data of FRET efficiencies with dyes at several locations for the cold shock protein, and simulations results for protein L, for which accurate FRET efficiencies between various locations were computed, shows that at high GdmCl concentrations there are significant deviations in the DSE P(R) from the Gaussian model.
how-accurate-are-polymer-models-in-the-analysis-of-forster-resonance-energy-transfer-experiments-on-proteins.pdf