Refining near-native protein-protein docking decoys by local resampling and energy minimization

How to refine a near-native structure to make it closer to its native conformation is an unsolved problem in protein-structure and protein-protein complex-structure prediction. In this article, we first test several scoring functions for selecting locally resampled near-native protein-protein docking conformations and then propose a computationally efficient protocol for structure refinement via local resampling and energy minimization. The proposed method employs a statistical energy function based on a Distance-scaled Ideal-gas REference state (DFIRE) as an initial filter and an empirical energy function EMPIRE (EMpirical Protein-InteRaction Energy) for optimization and re-ranking. Significant improvement of final top-1 ranked structures over initial near-native structures is observed in the ZDOCK 2.3 decoy set for Benchmark 1.0 (74% whose global rmsd reduced by 0.5 angstrom or more and only 7% increased by 0.5 angstrom or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed.

Physical mechanism and numerical simulations of surface layer temperature inversion in tropical ocean

The one-dimensional Kraus-Turner mixed layer model improved by Liu is developed to consider the effect of salinity and the equations of temperature and salinity under the mixed layer. On this basis, the processes of growth and death of surface layer temperature inversion is numerically simulated under different environmental parameters. At the same time, the physical mechanism is preliminarily discussed combining the observations at the station of TOGA-COARE 0 degrees N, 156 degrees E. The results indicate that temperature inversion sensitively depends on the mixed layer depth, sea surface wind speed and solar shortwave radiation, etc., and appropriately meteorological and hydrological conditions often lead to the similarly periodical occurrence of this inversion phenomenon.

Factors influencing the climatological mixed layer depth in the South China Sea: numerical simulations

The mixed layer depth (MLD) in the upper ocean is an important physical parameter for describing the upper ocean mixed layer. We analyzed several major factors influencing the climatological mixed layer depth (CMLD), and established a numerical simulation in the South China Sea (SCS) using the Regional Ocean Model System (ROMS) with a high-resolution (1/12A degrees x1/12A degrees) grid nesting method and 50 vertical layers. Several ideal numerical experiments were tested by modifying the existing sea surface boundary conditions. Especially, we analyzed the sensitivity of the results simulated for the CMLD with factors of sea surface wind stress (SSWS), sea surface net heat flux (SSNHF), and the difference between evaporation and precipitation (DEP). The result shows that of the three factors that change the depth of the CMLD, SSWS is in the first place, when ignoring the impact of SSWS, CMLD will change by 26% on average, and its effect is always to deepen the CMLD; the next comes SSNHF (13%) for deepening the CMLD in October to January and shallowing the CMLD in February to September; and the DEP comes in the third (only 2%). Moreover, we analyzed the temporal and spatial characteristics of CMLD and compared the simulation result with the ARGO observational data. The results indicate that ROMS is applicable for studying CMLD in the SCS area.

Docking and molecular dynamics study on the inhibitory activity of coumarins on aldose reductase

In order to explore the inhibitory mechanism of coumarins toward aldose reductase (ALR2), AutoDock and Gromacs software were used for docking and molecular dynamics studies on 14 coumarins (CM) and ALR2 protease. The docking results indicate that residues TYR48, HIS110, and TRP111 construct the active pocket of ALR2 and, besides van der Waals and hydrophobic interaction, CM mainly interact with ALR2 by forming hydrogen bonds to cause inhibitory behavior. Except for CM1, all the other coumarins take the lactone part as acceptor to build up the hydrogen bond network with active-pocket residues. Unlike CM3, which has two comparable binding modes with ALR2, most coumarins only have one dominant orientation in their binding sites. The molecular dynamics calculation, based on the docking results, implies that the orientations of CM in the active pocket show different stabilities. Orientation of CM1 and CM3a take an unstable binding mode with ALR2; their conformations and RMSDs relative to ALR2 change a lot with the dynamic process. While the remaining CM are always hydrogen-bonded with residues TYR48 and HIS110 through the carbonyl O atom of the lactone group during the whole process, they retain the original binding mode and gradually reach dynamic equilibrium.

Docking and molecular dynamics studies toward the binding of new natural phenolic marine inhibitors and aldose reductase

Phenolic marine natural product is a kind of new potential aldose reductase inhibitors (ARIs). In order to investigate the binding mode and inhibition mechanism, molecular docking and dynamics studies were performed to explore the interactions of six phenolic inhibitors with human aldose reductase (hALR2). Considering physiological environment, all the neutral and other two ionized states of each phenolic inhibitor were adopted in the simulation. The calculations indicate that all the inhibitors are able to form stable hydrogen bonds with the hALR2 active pocket which is mainly constructed by residues TYR48, HIS110 and TRP111, and they impose the inhibition effect by occupying the active space. In all inhibitors, only La and its two ionized derivatives La_ion1 and La_ion2, in which neither of the ortho-hydrogens of 3-hydroxyl is substituted by Br, bind with hALR2 active residues using the terminal 3-hydroxyl. While, all the other inhibitors, at least one of whose ortho-sites of 3- and 6-hydroxyls are substituted by Br substituent which take much electron-withdrawing effect and steric hindrance, bind with hALR2 through the lactone group. This means that the Br substituent can effectively regulate the binding modes of phenolic inhibitors. Although the lactone bound inhibitors have relatively high RMSD values, our dynamics study shows that both binding modes are of high stability. For each inhibitor molecule, the ionization does not change its original binding mode, but it does gradually increase the binding free energy, which reveals that besides hydrogen bonds, the electrostatic effect is also important to the inhibitor–hALR2 interaction.

Parameter sensitivity in simulations of snowmelt

Essery, RLH & P, Etchevers, (2004). Parameter sensitivity in simulations of snowmelt. Journal of Geophysical Research, 109, doi:10. 1029/2004JD005036.

Vegetation and Topographic Control of Wind-blown Snow Distributions in Distributed and Aggregated Simulations for an Arctic Tundra Basin

Essery, RLH & JW, Pomeroy, (2004). Vegetation and topographic control of wind-blown snow distributions in distributed and aggregated simulations. Journal of Hydrometeorology, 5, 735-744.

Simulations of Two-Dimensional Foam under Couette Shear

null Sponsorship: Financial support is acknowledged from the University of Wales Aberystwyth Senate Fund, the Ulysses France-Ireland Exchange Scheme and EPSRC (EP/D014956/1, EP/D048397/1, EP/D071127/1).

X-ray simulations for imaging applications in the agricultural and food industry

R. Zwiggelaar, C.R. Bull, and M.J. Mooney, 'X-ray simulations for imaging applications in the agricultural and food industry', Journal of Agricultural Engineering Research 63(2), 161-170 (1996)

Protein Docking by the Underestimation of Free Energy Funnels in the Space of Encounter Complexes

Similarly to protein folding, the association of two proteins is driven by a free energy funnel, determined by favorable interactions in some neighborhood of the native state. We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of the interface side chains. The method, called semi-definite programming-based underestimation (SDU), employs a general quadratic function to underestimate a set of local energy minima and uses the resulting underestimator to bias further sampling. While SDU effectively minimizes functions with funnel-shaped basins, its application to docking in the rotational and translational space SE(3) is not straightforward due to the geometry of that space. We introduce a strategy that uses separate independent variables for side-chain optimization, center-to-center distance of the two proteins, and five angular descriptors of the relative orientations of the molecules. The removal of the center-to-center distance turns out to vastly improve the efficiency of the search, because the five-dimensional space now exhibits a well-behaved energy surface suitable for underestimation. This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. Results for standard protein docking benchmarks establish that in this space the free energy landscape is a funnel in a reasonably broad neighborhood of the native state and that the SDU strategy can generate docking predictions with less than 5 � ligand interface Ca root-mean-square deviation while achieving an approximately 20-fold efficiency gain compared to Monte Carlo methods.

Simulations of X and Y Retinal Ganglion Cell Behavior with a Nonlinear Push-pull Model of Spatiotemporal Retinal Processing

This article describes a nonlinear model of neural processing in the vertebrate retina, comprising model photoreceptors, model push-pull bipolar cells, and model ganglion cells. Previous analyses and simulations have shown that with a choice of parameters that mimics beta cells, the model exhibits X-like linear spatial summation (null response to contrast-reversed gratings) in spite of photoreceptor nonlinearities; on the other hand, a choice of parameters that mimics alpha cells leads to Y-like frequency doubling. This article extends the previous work by showing that the model can replicate qualitatively many of the original findings on X and Y cells with a fixed choice of parameters. The results generally support the hypothesis that X and Y cells can be seen as functional variants of a single neural circuit. The model also suggests that both depolarizing and hyperpolarizing bipolar cells converge onto both ON and OFF ganglion cell types. The push-pull connectivity enables ganglion cells to remain sensitive to deviations about the mean output level of nonlinear photoreceptors. These and other properties of the push-pull model are discussed in the general context of retinal processing of spatiotemporal luminance patterns.

Pol II docking and pausing at growth and stress genes in C. elegans.

Fluctuations in nutrient availability profoundly impact gene expression. Previous work revealed postrecruitment regulation of RNA polymerase II (Pol II) during starvation and recovery in Caenorhabditis elegans, suggesting that promoter-proximal pausing promotes rapid response to feeding. To test this hypothesis, we measured Pol II elongation genome wide by two complementary approaches and analyzed elongation in conjunction with Pol II binding and expression. We confirmed bona fide pausing during starvation and also discovered Pol II docking. Pausing occurs at active stress-response genes that become downregulated in response to feeding. In contrast, "docked" Pol II accumulates without initiating upstream of inactive growth genes that become rapidly upregulated upon feeding. Beyond differences in function and expression, these two sets of genes have different core promoter motifs, suggesting alternative transcriptional machinery. Our work suggests that growth and stress genes are both regulated postrecruitment during starvation but at initiation and elongation, respectively, coordinating gene expression with nutrient availability.

Evaluating functional network inference using simulations of complex biological systems.

MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological systems from limited data. To overcome this limitation, we propose an approach to evaluate network inference algorithms according to their ability to recover a complex functional network from biologically reasonable simulated data. RESULTS: We designed a simulator to generate data representing a complex biological system at multiple levels of organization: behaviour, neural anatomy, brain electrophysiology, and gene expression of songbirds. About 90% of the simulated variables are unregulated by other variables in the system and are included simply as distracters. We sampled the simulated data at intervals as one would sample from a biological system in practice, and then used the sampled data to evaluate the effectiveness of an algorithm we developed for functional network inference. We found that our algorithm is highly effective at recovering the functional network structure of the simulated system-including the irrelevance of unregulated variables-from sampled data alone. To assess the reproducibility of these results, we tested our inference algorithm on 50 separately simulated sets of data and it consistently recovered almost perfectly the complex functional network structure underlying the simulated data. To our knowledge, this is the first approach for evaluating the effectiveness of functional network inference algorithms at recovering models from limited data. Our simulation approach also enables researchers a priori to design experiments and data-collection protocols that are amenable to functional network inference.

Enhancing the Hodgkin-Huxley Equations: Simulations Based on the First Publication in the Biophysical Journal.

The experiments in the Cole and Moore article in the first issue of the Biophysical Journal provided the first independent experimental confirmation of the Hodgkin-Huxley (HH) equations. A log-log plot of the K current versus time showed that raising the HH variable n to the sixth power provided the best fit to the data. Subsequent simulations using n(6) and setting the resting potential at the in vivo value simplifies the HH equations by eliminating the leakage term. Our article also reported that the K current in response to a depolarizing step to ENa was delayed if the step was preceded by a hyperpolarization. While the interpretation of this phenomenon in the article was flawed, subsequent simulations show that the effect completely arises from the original HH equations.

Numerical Simulations and Coherence Properties of Supercontinuum Generation in Photonic Crystal and Tapered Optical Fibers

Numerical simulations have been used to study broad-band supercontinuum generation in optical fibers with dispersion and nonlinearity characteristics typical and photonic crystal or tapered fibers structures. The simulations include optical shock and Raman nonlinearity terms, with quantum noise taken into account phenomenologically by including in the input field a noise seed of one photon per mode with random phase. For input pulses of 150-fs duration injected in the anomalous dispersion regime, the effect of modulational instability is shown to lead to severe temporal jitter in the output, and associated fluctuations in the spectral amplitude and phase across the generated supercontinuum. The spectral phase fluctuations are quantified by performing multiple simulations and calculating both the standard deviation of the phase and, more rigorously, the degree of first-order coherence as a function of wavelength across the spectrum. By performing simulations over a range of input pulse durations and wavelengths, we can identify the conditions under which coherent supercontinua with a well-defined spectral phase are generated.