The Complex Energy Landscape of the Protein IscU.
Ontology highlight
ABSTRACT:
SUBMITTER: Bothe JR
PROVIDER: S-EPMC4564936 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Here, we reveal a remarkable complexity in the unfolding of giant HEAT-repeat protein PR65/A, a molecular adaptor for the heterotrimeric PP2A phosphatases. The repeat array ruptures at multiple sites, leading to intermediate states with noncontiguous folded subdomains. There is a dominant sequence of unfolding, which reflects a nonuniform stability distribution across the repeat array and can be rationalized by theoretical models accounting for heterogeneous contact density in the folded structure. Unfolding of certain intermediates is, however, competitive, leading to parallel unfolding pathways. The low-stability, central repeats sample unfolded conformations under physiological conditions, suggesting how folding directs function: certain regions present rigid motifs for molecular recognition, whereas others have the flexibility with which to broaden the search area, as in the fly-casting mechanism. Partial unfolding of PR65/A also impacts catalysis by altering the proximity of bound catalytic subunit and substrate. Thus, the repeat array orchestrates the assembly and activity of PP2A.
| S-EPMC4256716 | biostudies-literature
Project description:We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein-protein or protein-ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks.
| S-EPMC4901360 | biostudies-literature
Project description:Recent experiments have conclusively shown that proteins are able to fold from an unknotted, denatured polypeptide to the knotted, native state without the aid of chaperones. These experiments are consistent with a growing body of theoretical work showing that a funneled, minimally frustrated energy landscape is sufficient to fold small proteins with complex topologies. Here, we present a theoretical investigation of the folding of a knotted protein, 2ouf, engineered in the laboratory by a domain fusion that mimics an evolutionary pathway for knotted proteins. Unlike a previously studied knotted protein of similar length, we see reversible folding/knotting and a surprising lack of deep topological traps with a coarse-grained structure-based model. Our main interest is to investigate how evolution might further select the geometry and stiffness of the threading region of the newly fused protein. We compare the folding of the wild-type protein to several mutants. Similarly to the wild-type protein, all mutants show robust and reversible folding, and knotting coincides with the transition state ensemble. As observed experimentally, our simulations show that the knotted protein folds about ten times slower than an unknotted construct with an identical contact map. Simulated folding kinetics reflect the experimentally observed rollover in the folding limbs of chevron plots. Successful folding of the knotted protein is restricted to a narrow range of temperature as compared to the unknotted protein and fits of the kinetic folding data below folding temperature suggest slow, nondiffusive dynamics for the knotted protein.
| S-EPMC3497829 | biostudies-literature
Project description:Energy landscapes have been used to conceptually describe and model protein folding but have been difficult to measure experimentally, in large part because of the myriad of partly folded protein conformations that cannot be isolated and thermodynamically characterized. Here we experimentally determine a detailed energy landscape for protein folding. We generated a series of overlapping constructs containing subsets of the seven ankyrin repeats of the Drosophila Notch receptor, a protein domain whose linear arrangement of modular structural units can be fragmented without disrupting structure. To a good approximation, stabilities of each construct can be described as a sum of energy terms associated with each repeat. The magnitude of each energy term indicates that each repeat is intrinsically unstable but is strongly stabilized by interactions with its nearest neighbors. These linear energy terms define an equilibrium free energy landscape, which shows an early free energy barrier and suggests preferred low-energy routes for folding.
| S-EPMC521126 | biostudies-literature
Project description:Formation of a stereospecific protein complex is favored by specific interactions between two proteins but disfavored by the loss of translational and rotational freedom. Echoing the protein folding process, we have previously proposed a transition state for protein-protein association. Here we clarify the specification of the transition state by working with two types of toy models for protein association. A "hemisphere" model consists of two matching hemispheres as associating proteins, and a "crater" model consists of a spherical protein with a crater to which another spherical protein fits snugly. Short-range pairwise interactions between sites across the interface hold together the bound complex. Small relative translation and rotation between the subunits quickly destroy the interactions, leading to a sharp transition between the bound state with numerous short-range interactions but restricted translation and rotational freedom and the unbound state with, at most, a small number of interactions but expanded configurational freedom. This transition sets the outer boundary of the bound state as well as the transition state for association. The energy landscape is funnel-like, with the deep well of the bound state surrounded by a broad shallow basin. Calculations with the toy models suggest that mutational change in the interaction energy in the x-ray structure of a protein-protein complex, commonly used to approximate the effect on the association constant, overestimates the effect of mutation by 10-20%. With an eye toward specifying the transition states of actual protein complexes, we find that the total number of contacts between the subunits serves as a good surrogate of the interaction energy. This formalism of protein-protein association is applied to the barnase-barstar complex, reproducing the experimental results for the association rate over a wide range of ionic strength.
| S-EPMC1796829 | biostudies-literature
Project description:A variety of coarse-grained (CG) models exists for simulation of proteins. An outstanding problem is the construction of a CG model with physically accurate conformational energetics rivaling all-atom force fields. In the present work, atomistic simulations of peptide folding and aggregation equilibria are force-matched using multiscale coarse-graining to develop and test a CG interaction potential of general utility for the simulation of proteins of arbitrary sequence. The reduced representation relies on multiple interaction sites to maintain the anisotropic packing and polarity of individual sidechains. CG energy landscapes computed from replica exchange simulations of the folding of Trpzip, Trp-cage and adenylate kinase resemble those of other reduced representations; non-native structures are observed with energies similar to those of the native state. The artifactual stabilization of misfolded states implies that non-native interactions play a deciding role in deviations from ideal funnel-like cooperative folding. The role of surface tension, backbone hydrogen bonding and the smooth pairwise CG landscape is discussed. Ab initio folding aside, the improved treatment of sidechain rotamers results in stability of the native state in constant temperature simulations of Trpzip, Trp-cage, and the open to closed conformational transition of adenylate kinase, illustrating the potential value of the CG force field for simulating protein complexes and transitions between well-defined structural states.
| S-EPMC2891700 | biostudies-literature
Project description:Effective locomotion in nature happens by transitioning across multiple modes (e.g., walk, run, climb). Despite this, far more mechanistic understanding of terrestrial locomotion has been on how to generate and stabilize around near-steady-state movement in a single mode. We still know little about how locomotor transitions emerge from physical interaction with complex terrain. Consequently, robots largely rely on geometric maps to avoid obstacles, not traverse them. Recent studies revealed that locomotor transitions in complex three-dimensional (3D) terrain occur probabilistically via multiple pathways. Here, we show that an energy landscape approach elucidates the underlying physical principles. We discovered that locomotor transitions of animals and robots self-propelled through complex 3D terrain correspond to barrier-crossing transitions on a potential energy landscape. Locomotor modes are attracted to landscape basins separated by potential energy barriers. Kinetic energy fluctuation from oscillatory self-propulsion helps the system stochastically escape from one basin and reach another to make transitions. Escape is more likely toward lower barrier direction. These principles are surprisingly similar to those of near-equilibrium, microscopic systems. Analogous to free-energy landscapes for multipathway protein folding transitions, our energy landscape approach from first principles is the beginning of a statistical physics theory of multipathway locomotor transitions in complex terrain. This will not only help understand how the organization of animal behavior emerges from multiscale interactions between their neural and mechanical systems and the physical environment, but also guide robot design, control, and planning over the large, intractable locomotor-terrain parameter space to generate robust locomotor transitions through the real world.
| S-EPMC7334479 | biostudies-literature
Project description:We report the free-energy landscape and thermodynamics of the protein-protein association responsible for the drug-induced multimerization of HIV-1 integrase (IN). Allosteric HIV-1 integrase inhibitors promote aberrant IN multimerization by bridging IN-IN intermolecular interactions. However, the thermodynamic driving forces and kinetics of the multimerization remain largely unknown. Here, we explore the early steps in the IN multimerization by using umbrella sampling and unbiased molecular dynamics simulations in explicit solvent. In direct simulations, the two initially separated dimers spontaneously associate to form near-native complexes that resemble the crystal structure of the aberrant tetramer. Most strikingly, the effective interaction of the protein-protein association is very short-ranged: the two dimers associate rapidly within tens of nanoseconds when their binding surfaces are separated by d ≤ 4.3 Å (less than two water diameters). Beyond this distance, the oligomerization kinetics appears to be diffusion controlled with a much longer association time. The free-energy profile also captured the crucial role of allosteric IN inhibitors in promoting multimerization and explained why several C-terminal domain mutations are remarkably resistant to the drug-induced multimerization. The results also show that at small separation, the protein-protein binding process contains two consecutive phases with distinct thermodynamic signatures. First, interprotein water molecules are expelled to the bulk, resulting in a small increase in entropy, as the solvent entropy gain from the water release is nearly cancelled by the loss of side-chain entropies as the two proteins approach each other. At shorter distances, the two dry binding surfaces adapt to each other to optimize their interaction energy at the expense of further protein configurational entropy loss. Although the binding interfaces feature clusters of hydrophobic residues, overall, the protein-protein association in this system is driven by enthalpy and opposed by entropy.
| S-EPMC7499063 | biostudies-literature
Project description:Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes.
| S-EPMC3443792 | biostudies-literature
Project description:In the realm of protein-protein interactions, the assembly process of homooligomers plays a fundamental role because the majority of proteins fall into this category. A comprehensive understanding of this multistep process requires the characterization of the driving molecular interactions and the transient intermediate species. The latter are often short-lived and thus remain elusive to most experimental investigations. Molecular simulations provide a unique tool to shed light onto these complex processes complementing experimental data. Here we combine advanced sampling techniques, such as metadynamics and parallel tempering, to characterize the oligomerization landscape of fibritin foldon domain. This system is an evolutionarily optimized trimerization motif that represents an ideal model for experimental and computational mechanistic studies. Our results are fully consistent with previous experimental nuclear magnetic resonance and kinetic data, but they provide a unique insight into fibritin foldon assembly. In particular, our simulations unveil the role of nonspecific interactions and suggest that an interplay between thermodynamic bias toward native structure and residual conformational disorder may provide a kinetic advantage.
| S-EPMC3856838 | biostudies-literature