Applying forces to elastic network models of large biomolecules using a haptic feedback device

Elastic network models of biomolecules have proved to be relatively good at predicting global conformational changes particularly in large systems. Software that facilitates rapid and intuitive exploration of conformational change in elastic network models of large biomolecules in response to externally applied forces would therefore be of considerable use, particularly if the forces mimic those that arise in the interaction with a functional ligand. We have developed software that enables a user to apply forces to individual atoms of an elastic network model of a biomolecule through a haptic feedback device or a mouse. With a haptic feedback device the user feels the response to the applied force whilst seeing the biomolecule deform on the screen. Prior to the interactive session normal mode analysis is performed, or pre-calculated normal mode eigenvalues and eigenvectors are loaded. For large molecules this allows the memory and number of calculations to be reduced by employing the idea of the important subspace, a relatively small space of the first M lowest frequency normal mode eigenvectors within which a large proportion of the total fluctuation occurs. Using this approach it was possible to study GroEL on a standard PC as even though only 2.3% of the total number of eigenvectors could be used, they accounted for 50% of the total fluctuation. User testing has shown that the haptic version allows for much more rapid and intuitive exploration of the molecule than the mouse version

Investigation of sequence features of hinge-bending regions in proteins with domain movements using kernel logistic regression

Background: Hinge-bending movements in proteins comprising two or more domains form a large class of functional movements. Hinge-bending regions demarcate protein domains and collectively control the domain movement. Consequently, the ability to recognise sequence features of hinge-bending regions and to be able to predict them from sequence alone would benefit various areas of protein research. For example, an understanding of how the sequence features of these regions relate to dynamic properties in multi-domain proteins would aid in the rational design of linkers in therapeutic fusion proteins. Results: The DynDom database of protein domain movements comprises sequences annotated to indicate whether the amino acid residue is located within a hinge-bending region or within an intradomain region. Using statistical methods and Kernel Logistic Regression (KLR) models, this data was used to determine sequence features that favour or disfavour hinge-bending regions. This is a difficult classification problem as the number of negative cases (intradomain residues) is much larger than the number of positive cases (hinge residues). The statistical methods and the KLR models both show that cysteine has the lowest propensity for hinge-bending regions and proline has the highest, even though it is the most rigid amino acid. As hinge-bending regions have been previously shown to occur frequently at the terminal regions of the secondary structures, the propensity for proline at these regions is likely due to its tendency to break secondary structures. The KLR models also indicate that isoleucine may act as a domain-capping residue. We have found that a quadratic KLR model outperforms a linear KLR model and that improvement in performance occurs up to very long window lengths (eighty residues) indicating long-range correlations. Conclusion: In contrast to the only other approach that focused solely on interdomain hinge-bending regions, the method provides a modest and statistically significant improvement over a random classifier. An explanation of the KLR results is that in the prediction of hinge-bending regions a long-range correlation is at play between a small number amino acids that either favour or disfavour hinge-bending regions. The resulting sequence-based prediction tool, HingeSeek, is available to run through a webserver at hingeseek.cmp.uea.ac.uk

Interacting with the biomolecular solvent accessible surface via a haptic feedback device

Background: From the 1950s computer based renderings of molecules have been produced to aid researchers in their understanding of biomolecular structure and function. A major consideration for any molecular graphics software is the ability to visualise the three dimensional structure of the molecule. Traditionally, this was accomplished via stereoscopic pairs of images and later realised with three dimensional display technologies. Using a haptic feedback device in combination with molecular graphics has the potential to enhance three dimensional visualisation. Although haptic feedback devices have been used to feel the interaction forces during molecular docking they have not been used explicitly as an aid to visualisation. Results: A haptic rendering application for biomolecular visualisation has been developed that allows the user to gain three-dimensional awareness of the shape of a biomolecule. By using a water molecule as the probe, modelled as an oxygen atom having hard-sphere interactions with the biomolecule, the process of exploration has the further benefit of being able to determine regions on the molecular surface that are accessible to the solvent. This gives insight into how awkward it is for a water molecule to gain access to or escape from channels and cavities, indicating possible entropic bottlenecks. In the case of liver alcohol dehydrogenase bound to the inhibitor SAD, it was found that there is a channel just wide enough for a single water molecule to pass through. Placing the probe coincident with crystallographic water molecules suggests that they are sometimes located within small pockets that provide a sterically stable environment irrespective of hydrogen bonding considerations. Conclusion: By using the software, named HaptiMol ISAS (available from http://​www.​haptimol.​co.​uk), one can explore the accessible surface of biomolecules using a three-dimensional input device to gain insights into the shape and water accessibility of the biomolecular surface that cannot be so easily attained using conventional molecular graphics software

Competition Between Charge-Density Waves and Superconductivity in Striped Systems

Switching on interchain coupling in a system of one-dimensional strongly interacting chains often leads to an ordered state. Quite generally, there is a competition between an insulating charge-density-wave and a superconducting state. In the case of repulsive interactions, charge-density wave usually wins over superconductivity. Here, we show that a suitable modulation in the form of a period 4 bond-centered stripe can reverse this balance even in the repulsive case and produce a superconducting state with relatively high temperature.Comment: Proceedings of SCES 04, 2 page

Moral Formation in a Culture of Relativism: Correlates of Universalism and Relativism in the Moral Outlooks of Emerging Adults

This study explores some of the demographic, personal, and experiential factors of emerging adults that correlate to a spectrum of moral outlooks ranging from moral universalism to moral relativism. Data was gathered from 466 volunteer undergraduate students. Respondents’ demographic, experiential, and personal factors served as independent variables. The relativism index score form Forsyth’s Ethics Position Questionnaire (1980) served as the dependent variable. Results suggest several conclusions: First, adults in the life of youth are a significant factor in moral outlook, exerting influence in both universalistic and relativistic directions. Second, religious practice and involvement contribute to a universal moral outlook. Third, the personal characteristics of grit and spiritual transcendence contribute to a universal moral outlook. Fourth, engaging in sexual activity outside of marriage contributes to a relative moral outlook. Fifth, a Catholic school education at both the grade and high school levels contributes to a universal moral outlook

Quantitative method for the assignment of hinge and shear mechanism in protein domain movements

Motivation: A popular method for classification of protein domain movements apportions them into two main types: those with a ‘hinge’ mechanism and those with a ‘shear’ mechanism. The intuitive assignment of domain movements to these classes has limited the number of domain movements that can be classified in this way. Furthermore, whether intended or not, the term ‘shear’ is often interpreted to mean a relative translation of the domains. Results: Numbers of occurrences of four different types of residue contact changes between domains were optimally combined by logistic regression using the training set of domain movements intuitively classified as hinge and shear to produce a predictor for hinge and shear. This predictor was applied to give a 10-fold increase in the number of examples over the number previously available with a high degree of precision. It is shown that overall a relative translation of domains is rare, and that there is no difference between hinge and shear mechanisms in this respect. However, the shear set contains significantly more examples of domains having a relative twisting movement than the hinge set. The angle of rotation is also shown to be a good discriminator between the two mechanisms. Availability and implementation: Results are free to browse at http:// www.cmp.uea.ac.uk/dyndom/interface/. Supplementary information: Supplementary data are available at Bioinformatics online

Multi-strand β-sheet of Alzheimer Aβ(1-40) folds to β-strip helix: Implication for protofilament formation

X-ray fiber diffraction experiments on Alzheimer Aβ(1–40) fibrils formed in an assembly process thought to simulate a portion of the pathophysiological process in Alzheimer's disease, indicated protofilaments with tilted β-strands rather than strands oriented perpendicular to the fibril axis as is usually interpreted from cross-β patterns. The protofilament width and tilt angle determined by these experiments were used to predict a β-strip helix model–a β-helix-like structure in which multiple identical polypeptide molecules assemble in-register to form a helical sheet structure such that the outer strands 1 and m join with a register shift t–with m = 11 and t = 22. Starting from untwisted β-sheets comprising 10, 11, and 12 strands, multiple explicit solvent molecular dynamics (MD) simulations were performed to determine whether the sheets form β-strip helices matching the dimensions of the experimentally measured protofilament. In the simulations, the predicted 11-strand sheets curled up to form a closed β-strip helix-like structure with dimensions matching experimental values, whereas the 10- and 12-strand sheets did not form a closed helical structure. The 12-strand structure did, however, show similarity to a cross-β structure determined by a solid-state NMR experiment. The 11-strand β-strip helix resembles a trans-membrane β-barrel which could explain the ability of small oligomers of Aβ(1–40) to form toxic ion channels. A further consequence of opposite sides of the 11-strand strip coming together at a register shift of 22 is end-to-end joins between neighboring β-strip helices, resulting in a protofilament that keeps growing in both directions. Communicated by Ramaswamy H. Sarma

Free Energy Profile of Domain Movement in Ligand-Free Citrate Synthase

Citrate synthase plays a fundamental role in the metabolic cycle of the cell. Its catalytic mechanism is complex involving the binding of two substrates that cause a domain movement. In this paper, we used classical molecular dynamics simulations and umbrella sampling simulations to determine the potential of mean force along a reaction coordinate for the domain movement in ligand-free citrate synthase from pig (Sus Scrofa). The results show that at 293 K, the closed-domain conformation has a ~4 kbT higher energy than the open-domain conformation. In a simple two-state model, this difference means that the enzyme spends 98% of the time in the open-domain conformation ready to receive the substrate, oxaloacetate, rather than the closed-domain conformation where the binding site would be inaccessible to the substrate. Given that experimental evidence indicates that the binding of oxaloacetate induces at least partial closure, this would imply an induced-fit mechanism which we argue is applicable to all enzymes with a functional domain movement for reasons of catalytic efficiency. A barrier of 4 kbT gives an estimation of the mean first passage time in the range 1-10 microseconds

Methodological improvements for the analysis of domain movements in large biomolecular complexes

Domain movements play a prominent role in the function of many biomolecules such as the ribosome and F0F1-ATP synthase. As more structures of large biomolecules in different functional states become available as experimental techniques for structure determination advance, there is a need to develop methods to understand the conformational changes that occur. DynDom and DynDom3D were developed to analyse two structures of a biomolecule for domain movements. They both used an original method for domain recognition based on clustering of “rotation vectors”. Here we introduce significant improvements in both the methodology and implementation of a tool for the analysis of domain movements in large multimeric biomolecules. The main improvement is in the recognition of domains by using all six degrees of freedom required to describe the movement of a rigid body. This is achieved by way of Chasles’ theorem in which a rigid-body movement can be described as a screw movement about a unique axis. Thus clustering now includes, in addition to rotation vector data, screw-axis location data and axial climb data. This improves both the sensitivity of domain recognition and performance. A further improvement is the recognition and annotation of interdomain bending regions, something not done for multimeric biomolecules in DynDom3D. This is significant as it is these regions that collectively control the domain movement. The new stand-alone, platform-independent implementation, DynDom6D, can analyse biomolecules comprising protein, DNA and RNA, and employs an alignment method to automatically achieve the required equivalence of atoms in the two structures