Search

It is not an understatement to say that the interplay between water and protein is a fundamental aspect of life. The vitality of an organism depends on the functionality of its biological machinery, and this, in turn, is mediated in water. Yet, we understand surprisingly little about the nature of the interface between bulk water and the protein. On the one hand, we know that the nature of the bulk water is dominated by the existence of H-bonding and H-bonded networks. On the other hand, the protein surface, where much of the bioactivity is centered, is a complex landscape of hydrophilic and hydrophobic elements. So how does the interface between these two entities work and how do they influence each other? The question is important because if one understands how a particular protein interface influences the dynamics of the water, it then becomes an easily accessible marker for similar behavior in other protein systems. The dielectric relaxation of hydrated proteins with different structures, lysozyme, collagen, and phycocyanin, has been reviewed in this paper. The dynamics of hydrated water was analyzed in terms of orientation and the ionic defect migration model. This approach enables to characterize the microscopic relaxation mechanism of the dynamics of hydration water on the different structures of the protein. In addition, our model is also capable of characterizing not only hydrated proteins but also polymer-water systems. [ABSTRACT FROM AUTHOR]

Recently, dynamic analysis methods in signal processing have been applied to the analysis of molecular dynamics (MD) trajectories of biopolymers. In the context of a relaxation mode analysis (RMA) method, based on statistical physics, it is explained why the signal-processing methods work well for the simulation trajectories of biopolymers. A distinctive difference between the RMA method and the signal-processing methods is the introduction of an additional parameter, called an evolution time parameter. This parameter enables us to better estimate the relaxation modes and rates, although it increases computational difficulty. In this paper, we propose a simple and effective extension of the RMA method, which is referred to as the positive definite RMA method, to introduce the evolution time parameter robustly. In this method, an eigenvalue problem for the time correlation matrix of physical quantities relevant to slow relaxation in a system is first solved to find the subspace in which the matrix is numerically positive definite. Then, we implement the RMA method in the subspace. We apply the method to the analysis of a 3-μs MD trajectory of a heterotrimer of an erythropoietin protein and two of its receptor proteins, and we demonstrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

The biological function of proteins is encoded in their structure and expressed through the mediation of their dynamics. This paper presents a study on the correlation between local fluctuations, binding, and biological function for two sample proteins, starting from the Langevin Equation for Protein Dynamics (LE4PD). The LE4PD is a microscopic and residue-specific coarse-grained approach to protein dynamics, which starts from the static structural ensemble of a protein and predicts the dynamics analytically. It has been shown to be accurate in its prediction of NMR relaxation experiments and Debye-Waller factors. The LE4PD is solved in a set of diffusive modes which span a vast range of time scales of the protein dynamics, and provides a detailed picture of the mode-dependent localization of the fluctuation as a function of the primary structure of the protein. To investigate the dynamics of protein complexes, the theory is implemented here to treat the coarse-grained dynamics of interacting macromolecules. As an example, calculations of the dynamics of monomeric and dimerized HIV protease and the free Insulin Growth Factor II Receptor (IGF2R) domain 11 and its IGF2R:IGF2 complex are presented. Either simulation-derived or experimentally measured NMR conformers are used as input structural ensembles to the theory. The picture that emerges suggests a dynamical heterogeneous protein where biologically active regions provide energetically comparable conformational states that are trapped by a reacting partner in agreement with the conformationselection mechanism of binding. [ABSTRACT FROM AUTHOR]

Erratum: "Biotin-painted proteins have thermodynamic stability switched by kinetic folding routes" [J. Chem. Phys. The correction appropriately cites the paper in which the FKBP3 structure deposition is described. II D "FKBP3 biotin painting progressively increases the folding temperature" in the article[1] incorrectly describes the full FKBP3 structure (PDB code 2MPH[2]) as being an x-ray crystallographic structure. [Extracted from the article]

The Histone-like Nucleoid Structuring protein (H-NS) is a nucleoid-associated protein, which is involved in both gene regulation and DNA compaction. Although it is a key player in genome organization by forming bridges between DNA duplexes, the precise structure of complexes of DNA and H-NS proteins is still not well understood. In particular, it is not clear whether the structure of DNA/H-NS complexes in the living cell is similar to that of complexes deposited on mica surfaces, which may be observed by AFM microscopy. A coarse-grained model, which helps getting more insight into this question, is described and analyzed in the present paper. This model is able of describing both the bridging of bacterial DNA by H-NS in the bulk and the deposition and equilibration of the complex on a charged surface. Simulations performed with the model reveal that a slight attraction between DNA and the charged surface is sufficient to let DNA/H-NS complexes reorganize from 3D coils to planar plasmids bridged by H-NS proteins similar to those observed by AFM microscopy. They furthermore highlight the antagonistic effects of the interactions between DNA and the surface. Indeed, increasing these interactions slows down the equilibration of naked plasmids on the surface but, on the other hand, enables a faster equilibration of DNA/H-NS complexes. Based on the distribution of the lifetimes of H-NS bridges and the time evolution of the number of trans-binding protein dimers during equilibration of the complexes on the surface, it is argued that the decrease of the equilibration time of the complex upon increase of the interaction strength between DNA and the surface is ascribable to the associated decrease of the probability to form new bridges between DNA and the proteins. [ABSTRACT FROM AUTHOR]

In this paper, the second in a series devoted to molecular modeling of protein aggregation, a mesoscale model of proteins together with extensive discontinuous molecular dynamics simulation is used to study the phenomenon in a confined medium. The medium, as a model of a crowded cellular environment, is represented by a spherical cavity, as well as cylindrical tubes with two aspect ratios. The aggregation process leads to the formation of β sheets and eventually fibrils, whose deposition on biological tissues is believed to be a major factor contributing to many neuro-degenerative diseases, such as Alzheimer’s, Parkinson’s, and amyotrophic lateral sclerosis diseases. Several important properties of the aggregation process, including dynamic evolution of the total number of the aggregates, the mean aggregate size, and the number of peptides that contribute to the formation of the β sheets, have been computed. We show, similar to the unconfined media studied in Paper I [S. Zheng et al., J. Chem. Phys. 145, 134306 (2016)], that the computed properties follow dynamic scaling, characterized by power laws. The existence of such dynamic scaling in unconfined media was recently confirmed by experiments. The exponents that characterize the power-law dependence on time of the properties of the aggregation process in spherical cavities are shown to agree with those in unbounded fluids at the same protein density, while the exponents for aggregation in the cylindrical tubes exhibit sensitivity to the geometry of the system. The effects of the number of amino acids in the protein, as well as the size of the confined media, have also been studied. Similarities and differences between aggregation in confined and unconfined media are described, including the possibility of no fibril formation, if confinement is severe. [ABSTRACT FROM AUTHOR]