Mimicking the action of GroEL in molecular dynamics simulations: Application to the refinement of protein structures

Bacterial chaperonin, GroEL, together with its co-chaperonin, GroES, facilitates the folding of a variety of polypeptides. Experiments suggest that GroEL stimulates protein folding by multiple cycles of binding and release. Misfolded proteins first bind to an exposed hydrophobic surface on GroEL. GroES then encapsulates the substrate and triggers its release into the central cavity of the GroEL/ES complex for folding. In this work, we investigate the possibility to facilitate protein folding in molecular dynamics simulations by mimicking the effects of GroEL/ES namely, repeated binding and release, together with spatial confinement. During the binding stage, the (metastable) partially folded proteins are allowed to attach spontaneously to a hydrophobic surface within the simulation box. This destabilizes the structures, which are then transferred into a spatially confined cavity for folding. The approach has been tested by attempting to refine protein structural models generated using the ROSETTA procedure for ab initio structure prediction. Dramatic improvements in regard to the deviation of protein models from the corresponding experimental structures were observed. The results suggest that the primary effects of the GroEL/ES system can be mimicked in a simple coarse-grained manner and be used to facilitate protein folding in molecular dynamics simulations. Furthermore, the results Sur port the assumption that the spatial confinement in GroEL/ES assists the folding of encapsulated proteins.

Modelling biological processes under anaerobic conditions through integrating titrimetric and off-gas measurements - applied to EBPR systems

An innovative method for modelling biological processes under anaerobic conditions is presented and discussed. The method is based on titrimetric and off-gas measurements. Titrimetric data is recorded as the addition rate of hydroxyl ions or protons that is required to maintain pH in a bioreactor at a constant level. An off-gas analysis arrangement measures, among other things, the transfer rate of carbon dioxide. The integration of these signals results in a continuous signal which is solely related to the biological reactions. When coupled with a mathematical model of the biological reactions, the signal allows a detailed characterisation of these reactions, which would otherwise be difficult to achieve. Two applications of the method to the enhanced biological phosphorus removal processes are presented and discussed to demonstrate the principle and effectiveness of the method.

Identifying causes for N2O accumulation in a lab-scale sequencing batch reactor performing simultaneous nitrification, denitrification and phosphorus removal

The recently described process of simultaneous nitrification, denitrification and phosphorus removal (SNDPR) has a great potential to save capital and operating costs for wastewater treatment plants. However, the presence of glycogen-accumulating organisms (GAOs) and the accumulation of nitrous oxide (N2O) can severely compromise the advantages of this process. In this study, these two issues were investigated using a lab-scale sequencing batch reactor performing SNDPR over a 5-month period. The reactor was highly enriched in polyphosphate-accumulating organisms (PAOs) and GAOs representing around 70% of the total microbial community. PAOs were the dominant population at all times and their abundance increased, while GAOs population decreased over the study period. Anoxic batch tests demonstrated that GAOs rather than denitrifying PAOs were responsible for denitrification. NO accumulated from denitrification and more than half of the nitrogen supplied in a reactor cycle was released into the atmosphere as NO. After mixing SNDPR sludge with other denitrifying sludge, N2O present in the bulk liquid was reduced immediately if external carbon was added. We therefore suggest that the N2O accumulation observed in the SNDPR reactor is an artefact of the low microbial diversity facilitated by the use of synthetic wastewater with only a single carbon source. (C) 2005 Elsevier B.V. All rights reserved.

Molecular recognition of an RNA trafficking element by heterogeneous nuclear ribonucleoprotein A2

Heterogeneous nuclear ribonucleoprotein (hnRNP) A2 is a multitasking protein involved in RNA packaging, alternative splicing of pre-mRNA. telomere maintenance, cytoplasmic RNA trafficking, and translation. It binds short segments of single-stranded nucleic acids, including the A2RE11 RNA element that is necessary and sufficient for cytoplasmic transport of a subset of rnRNAs in oligodendrocytes and neurons. We have explored the structures of hnRNP A2, its RNA recognition motifs (RRMs) and Gly-rich module, and the RRM complexes with A2RE11. Circular dichroism spectroscopy showed that the secondary structure of the first 189 residues of hnRNP A2 parallels that of the tandem beta alpha beta beta alpha beta RRMs of its paralogue, hnRNP A1, previously deduced from X-ray diffraction studies. The unusual GRD was shown to have substantial beta-sheet and beta-turn structure. Sedimentation equilibrium and circular dichroism results were consistent with the tandem RRM region being monomeric and supported earlier evidence for the binding of two A2RE11 oligoribonucleotides to this domain, in contrast to the protein dimer formed by the complex of hnRNP A1 with the telomeric ssDNA repeat. A three-dimensional structure for the N-terminal, two-RRM-containing segment of hnRNP A2 was derived by homology modeling. This structure was used to derive a model for the complex with A2RE11 using the previously described interaction of pairs of stacked nucleotides with aromatic residues on the RRM beta-sheet platforms, conserved in other RRM-RNA complexes, together with biochemical data and molecular dynamics-based observations of inter-RRM mobility.

Optical Bloch equations and enhanced decay of Rabi oscillations in strong driving fields

Optical Bloch equations are widely used for describing dynamics in a system consisting molecules, electromagnetic waves, and a thermal bath. We analyze applicability of these equations to a single molecule imbedded in a solid matrix. Classical Bloch equations and the limits of their applicability are derived from more general master equations. Simple and intuitively appealing picture based on stochastic Bloch equations shows that at low temperatures, contrary to common believes, a strong driving field can not only suppress but can also increase decay rates of Rabi oscillations. A physical system where predicted effects can be observed experimentally is suggested. (c) 2005 Elsevier B.V. All rights reserved.

Oscillatory regulation of hes1: Discrete stochastic delay modelling and simulation

Discrete stochastic simulations are a powerful tool for understanding the dynamics of chemical kinetics when there are small-to-moderate numbers of certain molecular species. In this paper we introduce delays into the stochastic simulation algorithm, thus mimicking delays associated with transcription and translation. We then show that this process may well explain more faithfully than continuous deterministic models the observed sustained oscillations in expression levels of hes1 mRNA and Hes1 protein.

Phase behavior of a phospholipid/fatty acid/water mixture studied in atomic detail

Molecular dynamics simulations have been used to study the phase behavior of a dipalmitoylphosphatidylcholine (DPPC)/palmitic acid (PA)/water 1:2:20 mixture in atomic detail. Starting from a random solution of DPPC and PA in water, the system adopts either a gel phase at temperatures below similar to 330 K or an inverted hexagonal phase above similar to 330 K in good agreement with experiment. It has also been possible to observe the direct transformation from a gel to an inverted hexagonal phase at elevated temperature (similar to 390 K). During this transformation, a metastable fluid lamellar intermediate is observed. Interlamellar connections or stalks form spontaneously on a nanosecond time scale and subsequently elongate, leading to the formation of an inverted hexagonal phase. This work opens the possibility of studying in detail how the formation of nonlamellar phases is affected by lipid composition and (fusion) peptides and, thus, is an important step toward understanding related biological processes, such as membrane fusion.

Polyenylpyrroles and polyenylfurans from an Australian isolate of the soil ascomycete Gymnoascus reessii

An Australian isolate of the soil ascomycete Gymnoascus reessii yielded a series of cytotoxic metabolites, including the known polyenylpyrroles rumbrin (1) and auxarconjugatin A (2), and the new rumbrin stereoisomer 12E-isorumbrin (3), as well as an unprecedented class of polyenylfurans exemplified by gymnoconjugatins A (4) and B (5). Structures were assigned with detailed spectroscopic analysis.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Procedure compilation in the refinement calculus

High-level language program compilation strategies can be proven correct by modelling the process as a series of refinement steps from source code to a machine-level description. We show how this can be done for programs containing recursively-defined procedures in the well-established predicate transformer semantics for refinement. To do so the formalism is extended with an abstraction of the way stack frames are created at run time for procedure parameters and variables.

Putative glycogen-accumulating organisms belonging to the Alphaproteobacteria identified through rRNA-based stable isotope probing

Deterioration of enhanced biological phosphorus removal (EBPR) has been linked to the proliferation of glycogen-accumulating organisms (GAOs), but few organisms possessing the GAO metabolic phenotype have been identified. An unidentified GAO was highly enriched in a laboratory-scale bioreactor and attempts to identify this organism using conventional 16S rRNA gene cloning had failed. Therefore, rRNA-based stable isotope probing followed by full-cycle rRNA analysis was used to specifically identify the putative GAOs based on their characteristic metabolic phenotype. The study obtained sequences from a group of Alphaproteobacteria not previously shown to possess the GAO phenotype, but 90% identical by 16S rRNA gene analysis to a phylogenetic clade containing cloned sequences from putative GAOs and the isolate Defluvicoccus vanus. Fluorescence in situ hybridization (FISH) probes (DF988 and DF1020) were designed to target the new group and post-FISH chemical staining demonstrated anaerobic-aerobic cycling of polyhydroxyalkanoates, as per the GAO phenotype. The successful use of probes DF988 and DF1020 required the use of unlabelled helper probes which increased probe signal intensity up to 6.6-fold, thus highlighting the utility of helper probes in FISH. The new group constituted 33% of all Bacteria in the lab-scale bioreactor from which they were identified and were also abundant (51 and 55% of Bacteria) in two other similar bioreactors in which phosphorus removal had deteriorated. Unlike the previously identified Defluvicoccus-related organisms, the group identified in this study were also found in two full-scale treatment plants performing EBPR, suggesting that this group may be industrially relevant.

Quantum effects on adsorption and diffusion of hydrogen and deuterium in microporous materials

Monte Carlo and molecular dynamics simulations and neutron scattering experiments are used to study the adsorption and diffusion of hydrogen and deuterium in zeolite Rho in the temperature range of 30-150 K. In the molecular simulations, quantum effects are incorporated via the Feynman-Hibbs variational approach. We suggest a new set of potential parameters for hydrogen, which can be used when Feynman-Hibbs variational approach is used for quantum corrections. The dynamic properties obtained from molecular dynamics simulations are in excellent agreement with the experimental results and show significant quantum effects on the transport at very low temperature. The molecular dynamics simulation results show that the quantum effect is very sensitive to pore dimensions and under suitable conditions can lead to a reverse kinetic molecular sieving with deuterium diffusing faster than hydrogen.

Secondary metabolites from the wood bark of Durio zibethinus and Durio kutejensis

Phytochemical exploration of a wood bark extract from Durio zibethinus afforded two new triterpenoids, namely, methyl 27-O-trans-caffeoylcylicodiscate (1) and methyl 27-O-cis-caffeoylcylicodiscate (2), a new phenolic, 1,2-diarylpropane-3- ol (3), and seven known compounds, fraxidin, eucryphin, boehmenan, threo-carolignan E, (-)-(3R, 4S)-4-hydroxymellein, methyl protocatechuate, and (+)-(R)-de-O-methyllasiodiplodin (4). In addition, chemical analysis of a wood bark extract from Durio kutejensis yielded the new triterpenes 3 beta-O-trans-caffeoyl-2R-hydroxyolean-12-en-28-oic acid (5) and 3 beta-trans-caffeoyl-2R-hydroxytaraxest-12-en-28-oic acid (6) together with four known compounds, maslinic acid, arjunolic acid, 2,6-dimethoxy-p-benzoquinone, and fraxidin. The structures of all compounds were determined on the basis of spectroscopic data.