In situ stress tensor measured in an Alaskan glacier

An experimental program at Worthington Glacier, Alaska, U.S.A., has yielded the first in situ measurements of the full stress tensor in glacier ice. Measurements were made with an array of stiff (low-compliance) normal-force sensors frozen into a borehole at 120 m depth. Freezing in temperate ice was accomplished by a down-hole heat exchanger which extracted heat at the rate of 15 W. Under slowly varying stress conditions, relaxation of stress anomalies by viscous creep following drilling of the hole and installation of the sensors allows for equilibration of measured stresses with far-field stresses. Equilibration of local and far-field stresses was confirmed and pressure sensor calibrated in laboratory experiments prior to the field program. Results of the stress measurements show principal axes of the stress tensor oriented in directions consistent with the geometry of the glacier and broadly consistent with measured englacial strain rate. The magnitudes of stress-tensor components are more error-prone and more sensitive to uncertainty in sensor magnitude than uncertainty in sensor orientation. Mean stress determined by pressure measurements agrees with estimated lithostatic overburden with within approximately 15%. Unexpected results include a stress perturbation lasted about 5 days that caused a rotation of the orientations of the principal stress axes of approximately 5 degrees about an axis pointing in the down-flow direction

Influence of conformational fluctuations on enzymatic activity: modelling the functional motion of beta-secretase

Considerable insight into the functional activity of proteins and enzymes can be obtained by studying the low-energy conformational distortions that the biopolymer can sustain. We carry out the characterization of these large scale structural changes for a protein of considerable pharmaceutical interest, the human $\beta$-secretase. Starting from the crystallographic structure of the protein, we use the recently introduced beta-Gaussian model to identify, with negligible computational expenditure, the most significant distortion occurring in thermal equilibrium and the associated time scales. The application of this strategy allows to gain considerable insight into the putative functional movements and, furthermore, helps to identify a handful of key regions in the protein which have an important mechanical influence on the enzymatic activity despite being spatially distant from the active site. The results obtained within the Gaussian model are validated through an extensive comparison against an all-atom Molecular Dynamics simulation.Comment: To be published in a special issue of J. Phys.: Cond. Mat. (Bedlewo Workshop

Using an Augmented Lagrangian Method and block fracturing in the DDA method

This paper presents two extensions to the Discontinuous Deformation Analysis (DDA) method orginally proposed by Shi for modeling the response of blocky rock masses to mechanical loading. The first extension consists of improving the block contact algorithm. An Augmented Lagrangian Method is used to replace the Penalty Method orginally proposed. It allows Lagrange multipliers to be introduced without increasing the number of equations that need to be solved and thus, block contract forces can be calculated more accurately. A block fracturing capability based on a three-parameter Mohr-Coulomb criterion represents the second extension. It allows for shear or tensile fracturing of intact blocks and the formation of smaller blocks

Long range molecular dynamics study of regulation of eukaryotic glucosamine-6-phosphate synthase activity by UDP-GlcNAc

Glucosamine-6-phosphate (GlcN-6-P) synthase catalyses the first and practically irreversible step in hexosamine metabolism. The final product of this pathway, uridine 5’ diphospho N-acetyl-D-glucosamine (UDP-GlcNAc), is an essential substrate for assembly of bacterial and fungal cell walls. Moreover, the enzyme is involved in phenomenon of hexosamine induced insulin resistance in type II diabetes, which makes it a potential target for antifungal, antibacterial and antidiabetic therapy. The crystal structure of the isomerase domain of GlcN-6-P synthase from human pathogenic fungus Candida albicans, in complex with UDP-GlcNAc has been solved recently but it has not revealed the molecular mechanism of inhibition taking place under UDP-GlcNAc influence, the unique feature of the eukaryotic enzyme. UDP-GlcNAc is a physiological inhibitor of GlcN-6-P synthase, binding about 1 nm away from the active site of the enzyme. In the present work, comparative molecular dynamics simulations of the free and UDP-GlcNAc-bounded structures of GlcN-6-P synthase have been performed. The aim was to complete static X-ray structural data and detect possible changes in the dynamics of the two structures. Results of the simulation studies demonstrated higher mobility of the free structure when compared to the liganded one. Several amino acid residues were identified, flexibility of which is strongly affected upon UDP-GlcNAc binding. Importantly, the most fixed residues are those related to the inhibitor binding process and to the catalytic reaction. The obtained results constitute an important step toward understanding of mechanism of GlcN-6-P synthase inhibition by UDP-GlcNAc molecule

A modified empirical criterion for strength of transversely anisotropic rocks with metamorphic origin

A modified empirical criterion is proposed to determine the strength of transversely anisotropic rocks. In this regard, mechanical properties of intact anisotropic slate obtained from three different districts of Iran were taken into consideration. Afterward, triaxial rock strength criterion introduced by Rafiai was modified for transversely anisotropic rocks. The criterion was modified by adding a new parameter α for taking the influence of strength anisotropy into consideration. The results obtained have shown that the parameter α can be considered as the strength reduction parameter due to rock anisotropy. The modified criterion was compared to the modified Hoek–Brown (Saroglou and Tsiambaos) and Ramamurthy criteria for different anisotropic rocks. It was concluded that the criterion proposed in this paper is a more accurate and precise criterion in predicting the strength of anisotropic rocks

The Use of Experimental Structures to Model Protein Dynamics

The number of solved protein structures submitted in the Protein Data Bank (PDB) has increased dramatically in recent years. For some specific proteins, this number is very high—for example, there are over 550 solved structures for HIV-1 protease, one protein that is essential for the life cycle of human immunodeficiency virus (HIV) which causes acquired immunodeficiency syndrome (AIDS) in humans. The large number of structures for the same protein and its variants include a sample of different conformational states of the protein. A rich set of structures solved experimentally for the same protein has information buried within the dataset that can explain the functional dynamics and structural mechanism of the protein. To extract the dynamics information and functional mechanism from the experimental structures, this chapter focuses on two methods—Principal Component Analysis (PCA) and Elastic Network Models (ENM). PCA is a widely used statistical dimensionality reduction technique to classify and visualize high-dimensional data. On the other hand, ENMs are well-established simple biophysical method for modeling the functionally important global motions of proteins. This chapter covers the basics of these two. Moreover, an improved ENM version that utilizes the variations found within a given set of structures for a protein is described. As a practical example, we have extracted the functional dynamics and mechanism of HIV-1 protease dimeric structure by using a set of 329 PDB structures of this protein. We have described, step by step, how to select a set of protein structures, how to extract the needed information from the PDB files for PCA, how to extract the dynamics information using PCA, how to calculate ENM modes, how to measure the congruency between the dynamics computed from the principal components (PCs) and the ENM modes, and how to compute entropies using the PCs. We provide the computer programs or references to software tools to accomplish each step and show how to use these programs and tools. We also include computer programs to generate movies based on PCs and ENM modes and describe how to visualize them

Specialized dynamical properties of promiscuous residues revealed by simulated conformational ensembles

The ability to interact with different partners is one of the most important features in proteins. Proteins that bind a large number of partners (hubs) have been often associated with intrinsic disorder. However, many examples exist of hubs with an ordered structure, and evidence of a general mechanism promoting promiscuity in ordered proteins is still elusive. An intriguing hypothesis is that promiscuous binding sites have specific dynamical properties, distinct from the rest of the interface and pre-existing in the protein isolated state. Here, we present the first comprehensive study of the intrinsic dynamics of promiscuous residues in a large protein data set. Different computational methods, from coarse-grained elastic models to geometry-based sampling methods and to full-atom Molecular Dynamics simulations, were used to generate conformational ensembles for the isolated proteins. The flexibility and dynamic correlations of interface residues with a different degree of binding promiscuity were calculated and compared considering side chain and backbone motions, the latter both on a local and on a global scale. The study revealed that (a) promiscuous residues tend to be more flexible than nonpromiscuous ones, (b) this additional flexibility has a higher degree of organization, and (c) evolutionary conservation and binding promiscuity have opposite effects on intrinsic dynamics. Findings on simulated ensembles were also validated on ensembles of experimental structures extracted from the Protein Data Bank (PDB). Additionally, the low occurrence of single nucleotide polymorphisms observed for promiscuous residues indicated a tendency to preserve binding diversity at these positions. A case study on two ubiquitin-like proteins exemplifies how binding promiscuity in evolutionary related proteins can be modulated by the fine-tuning of the interface dynamics. The interplay between promiscuity and flexibility highlighted here can inspire new directions in protein-protein interaction prediction and design methods. © 2013 American Chemical Society

Combining Optimal Control Theory and Molecular Dynamics for Protein Folding

A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD). In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the atoms of a Coarse-Grained (CG) protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the atoms. In turn, MD simulation provides an all-atom conformation whose positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD) which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization - MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages

Coarse-Graining Protein Structures With Local Multivariate Features from Molecular Dynamics

A multivariate statistical theory, local feature analysis (LFA), extracts functionally relevant domains from molecular dynamics (MD) trajectories. The LFA representations, like those of principal component analysis (PCA), are low dimensional and provide a reduced basis set for collective motions of simulated proteins, but the local features are sparsely distributed and spatially localized, in contrast to global PCA modes. One key problem in the assignment of local features is the coarse-graining of redundant LFA output functions by means of seed atoms. One can solve the combinatorial problem by adding seed atoms one after another to a growing set, minimizing a reconstruction error at each addition. This allows for an efficient implementation, but the sequential algorithm does not guarantee the optimal mutual correlation of the sequentially assigned features. Here, we present a novel coarse-graining algorithm for proteins that directly minimizes the mutual correlation of seed atoms by Monte Carlo (MC) simulations. Tests on MD trajectories of two biological systems, bacteriophage T4 lysozyme and myosin II motor domain S1, demonstrate that the new algorithm provides statistically reproducible results and describes functionally relevant dynamics. The well-known undersampling of large-scale motion by short MD simulations is apparent also in our model, but the new coarse-graining offers a major advantage over PCA; converged features are invariant across multiple windows of the trajectory, dividing the protein into converged regions and a smaller number of localized, undersampled regions. In addition to its use in structure classification, the proposed coarse-graining thus provides a localized measure of MD sampling efficiency