Improvement of 3D protein models using multiple templates guided by single-template model quality assessment

Motivation: Modelling the 3D structures of proteins can often be enhanced if more than one fold template is used during the modelling process. However, in many cases, this may also result in poorer model quality for a given target or alignment method. There is a need for modelling protocols that can both consistently and significantly improve 3D models and provide an indication of when models might not benefit from the use of multiple target-template alignments. Here, we investigate the use of both global and local model quality prediction scores produced by ModFOLDclust2, to improve the selection of target-template alignments for the construction of multiple-template models. Additionally, we evaluate clustering the resulting population of multi- and single-template models for the improvement of our IntFOLD-TS tertiary structure prediction method. Results: We find that using accurate local model quality scores to guide alignment selection is the most consistent way to significantly improve models for each of the sequence to structure alignment methods tested. In addition, using accurate global model quality for re-ranking alignments, prior to selection, further improves the majority of multi-template modelling methods tested. Furthermore, subsequent clustering of the resulting population of multiple-template models significantly improves the quality of selected models compared with the previous version of our tertiary structure prediction method, IntFOLD-TS.

The ModFOLD4 server for the quality assessment of 3D protein models

Once you have generated a 3D model of a protein, how do you know whether it bears any resemblance to the actual structure? To determine the usefulness of 3D models of proteins, they must be assessed in terms of their quality by methods that predict their similarity to the native structure. The ModFOLD4 server is the latest version of our leading independent server for the estimation of both the global and local (per-residue) quality of 3D protein models. The server produces both machine readable and graphical output, providing users with intuitive visual reports on the quality of predicted protein tertiary structures. The ModFOLD4 server is freely available to all at: http://www.reading.ac.uk/bioinf/ModFOLD/.

Synthesis and structure-activity relationship studies of CD4 down-modulating cyclotriazadisulfonamide (CADA) analogues

HIV attachment via the CD4 receptor is an important target for developing novel approaches to HIV chemotherapy. Cyclotriazadisulfonamide (CADA) inhibits HIV at submicromolar levels by specifically down-modulating cell-surface and intracellular CD4. An effective five-step synthesis of CADA in 30% overall yield is reported. This synthesis has also been modified to produce more than 50 analogues. Many tail-group analogues have been made by removing the benzyl tail of CADA and replacing it with various alkyl, acyl, alkoxycarbonyl and aminocarbonyl substituents. A series of sidearm analogues, including two unsymmetrical compounds, have also been prepared by modifying the CADA synthesis, replacing the toluenesulfonyl sidearms with other sulfonyl groups. Testing 30 of these compounds in MT-4 cells shows a wide range of CD4 down-modulation potency, which correlates with ability to inhibit HIV-1. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The X-ray crystal structures of four compounds, including CADA, show the same major conformation of the central 12-membered ring. The solid-state structure of CADA was energy minimized and used to generate the remaining 29 structures, which were similarly minimized and aligned to produce the 3D-QSAR models. Both models indicate that steric bulk of the tail group, and, to a lesser extent, the sidearms mainly determine CD4 down-modulation potency in this series of compounds.

3D scanning by multiple fan beam X-ray sources and sensors

*** Purpose – Computer tomography (CT) for 3D reconstruction entails a huge number of coplanar fan-beam projections for each of a large number of 2D slice images, and excessive radiation intensities and dosages. For some applications its rate of throughput is also inadequate. A technique for overcoming these limitations is outlined. *** Design methodology/approach – A novel method to reconstruct 3D surface models of objects is presented, using, typically, ten, 2D projective images. These images are generated by relative motion between this set of objects and a set of ten fanbeam X-ray sources and sensors, with their viewing axes suitably distributed in 2D angular space. *** Findings – The method entails a radiation dosage several orders of magnitude lower than CT, and requires far less computational power. Experimental results are given to illustrate the capability of the technique *** Practical implications – The substantially lower cost of the method and, more particularly, its dramatically lower irradiation make it relevant to many applications precluded by current techniques *** Originality/value – The method can be used in many applications such as aircraft hold-luggage screening, 3D industrial modelling and measurement, and it should also have important applications to medical diagnosis and surgery.

Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 floods in Tewkesbury, UK

Two-dimensional flood inundation modelling is a widely used tool to aid flood risk management. In urban areas, where asset value and population density are greatest, the model spatial resolution required to represent flows through a typical street network (i.e. < 10m) often results in impractical computational cost at the whole city scale. Explicit diffusive storage cell models become very inefficient at such high resolutions, relative to shallow water models, because the stable time step in such schemes scales as a quadratic of resolution. This paper presents the calibration and evaluation of a recently developed new formulation of the LISFLOOD-FP model, where stability is controlled by the Courant–Freidrichs–Levy condition for the shallow water equations, such that, the stable time step instead scales linearly with resolution. The case study used is based on observations during the summer 2007 floods in Tewkesbury, UK. Aerial photography is available for model evaluation on three separate days from the 24th to the 31st of July. The model covered a 3.6 km by 2 km domain and was calibrated using gauge data from high flows during the previous month. The new formulation was benchmarked against the original version of the model at 20 m and 40 m resolutions, demonstrating equally accurate performance given the available validation data but at 67x faster computation time. The July event was then simulated at the 2 m resolution of the available airborne LiDAR DEM. This resulted in a significantly more accurate simulation of the drying dynamics compared to that simulated by the coarse resolution models, although estimates of peak inundation depth were similar.

Neuroinflammation and its modulation by flavonoids

There is increasing evidence to suggest that neuroinflammatory processes contribute to the cascade of events that lead to the progressive neuronal damage observed in neurodegenerative disorders such as Parkinson’s disease and Alzheimer’s disease. Therefore, treatment regimes aimed at modulating neuroinflammatory processes may act to slow the progression of these debilitating brain disorders. Recently, a group of dietary polyphenols known as flavonoids have been shown to exert neuroprotective effects in vivo and in neuronal cell models. In this review we discuss the evidence relating to the modulation of neuroinflammation by flavonoids. We highlight the evidence which suggests their mechanism of action involves: 1) attenuation of the release of cytokines, such as interleukin-1β (IL-1β) and tumor necrosis factor-alpha (TNF-α); 2) an inhibitory action against inducible nitric oxide synthase (iNOS) induction and subsequent nitric oxide (NO•) production; 3) inhibition of the activation of NADPH oxidase and subsequent reactive oxygen species generation; 4) a capacity to down-regulate the activity of pro-inflammatory transcription factors such as nuclear factor-κB (NF-κB); and 5) the potential to modulate signalling pathways such as mitogen-activated protein kinase (MAPK) cascade. We also consider the potential of these dietary compounds to represent novel therapeutic agents by considering their metabolism in the body and their ability to access the brain via the blood brain barrier. Finally, we discuss future areas of study which are necessary before dietary flavonoids can be established as therapeutic agents against neuroinflammation.

Green tea (Camellia sinensis) catechins and vascular function

The health benefits of green tea (Camellia sinensis) catechins are becoming increasingly recognised. Amongst the proposed benefits are the maintenance of endothelial function and vascular homeostasis and an associated reduction in atherogenesis and CVD risk. The mounting evidence for the influential effect of green tea catechins on vascular function from epidemiological, human intervention and animal studies is subject to review together with exploration of the potential mechanistic pathways involved. Epigallocatechin-3-gallate, one of the most abundant and widely studied catechin found in green tea, will be prominent in the present review. Since there is a substantial inconsistency in the published data with regards to the impact of green tea catechins on vascular function, evaluation and interpretation of the inter- and intra-study variability is included. In conclusion, a positive effect of green tea catechins on vascular function is becoming apparent. Further studies in animal and cell models using physiological concentrations of catechins and their metabolites are warranted in order to gain some insight into the physiology and molecular basis of the observed beneficial effects.

Enhanced sensitivity to rapamycin following long-term oestrogen deprivation in MCF-7, T-47-D and ZR-75-1 human breast cancer cells

Human breast cancer cells (MCF-7, T-47-D and ZR-75-1) can adapt to circumvent any reduced growth rate during long-term oestrogen deprivation, and this provides three model systems to investigate mechanisms of endocrine resistance in breast cancer. In this paper we report consistent differences in the effects of three growth inhibitors following long-term oestrogen deprivation in all three cell models. Long-term oestrogen deprivation of MCF-7, T-47-D and ZR-75-1 cells resulted in reduced growth inhibition by PD98059 (2–10 µg/ml), implying a loss of dependence on mitogen-activated protein kinase pathways for growth. The growth inhibitor LY294002 (2–10 µM) inhibited growth of both oestrogen-maintained and oestrogen-deprived cells with similar dose–responses, implying continued similar dependence on phosphoinositide 3-kinase (PI3K) pathways with no alteration after adaptation to oestrogen independent growth. However, by contrast, long-term oestrogen deprivation resulted in an increased sensitivity to growth inhibition by rapamycin, which was not reduced by readdition of oestradiol. The enhanced inhibition of long-term oestrogen-deprived MCF-7-ED, T-47-D-ED and ZR-75-1-ED cell growth by combining rapamycin with LY294002 at concentrations where each alone had little effect, offers preclinical support to the development of therapeutic combinations of rapamycin analogues with other PI3K inhibitors in endocrine-resistant breast cancer.

Pose Refinement of Active Models using Forces in 3D

A new algorithm is described for refining the pose of a model of a rigid object, to conform more accurately to the image structure. Elemental 3D forces are considered to act on the model. These are derived from directional derivatives of the image local to the projected model features. The convergence properties of the algorithm is investigated and compared to a previous technique. Its use in a video sequence of a cluttered outdoor traffic scene is also illustrated and assessed.

A Newton method for pose refinement of 3D models

Different optimization methods can be employed to optimize a numerical estimate for the match between an instantiated object model and an image. In order to take advantage of gradient-based optimization methods, perspective inversion must be used in this context. We show that convergence can be very fast by extrapolating to maximum goodness-of-fit with Newton's method. This approach is related to methods which either maximize a similar goodness-of-fit measure without use of gradient information, or else minimize distances between projected model lines and image features. Newton's method combines the accuracy of the former approach with the speed of convergence of the latter.

Ocean acoustic models for low frequency propagation in 2D and 3D environments

In this paper we are mainly concerned with the development of efficient computer models capable of accurately predicting the propagation of low-to-middle frequency sound in the sea, in axially symmetric (2D) and in fully 3D environments. The major physical features of the problem, i.e. a variable bottom topography, elastic properties of the subbottom structure, volume attenuation and other range inhomogeneities are efficiently treated. The computer models presented are based on normal mode solutions of the Helmholtz equation on the one hand, and on various types of numerical schemes for parabolic approximations of the Helmholtz equation on the other. A new coupled mode code is introduced to model sound propagation in range-dependent ocean environments with variable bottom topography, where the effects of an elastic bottom, of volume attenuation, surface and bottom roughness are taken into account. New computer models based on finite difference and finite element techniques for the numerical solution of parabolic approximations are also presented. They include an efficient modeling of the bottom influence via impedance boundary conditions, they cover wide angle propagation, elastic bottom effects, variable bottom topography and reverberation effects. All the models are validated on several benchmark problems and versus experimental data. Results thus obtained were compared with analogous results from standard codes in the literature.

Learning enhanced 3D models for vehicle tracking

This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic object-centred and appearance-based representations in computer vision giving improved hypothesis verification under iconic matching. The "appearance" of a 3D object is learnt using an eigenspace representation obtained as it is tracked through a scene. The feature representation implicitly models the background and the objects observed enabling the segmentation of the objects from the background. The method is shown to enhance model-based tracking, particularly in the presence of clutter and occlusion, and to provide a basis for identification. The unified approach is discussed in the context of the traffic surveillance domain. The approach is demonstrated on real-world image sequences and compared to previous (edge-based) iconic evaluation techniques.

Classifying general nonlinear force laws in cell-based models via the continuum limit

though discrete cell-based frameworks are now commonly used to simulate a whole range of biological phenomena, it is typically not obvious how the numerous different types of model are related to one another, nor which one is most appropriate in a given context. Here we demonstrate how individual cell movement on the discrete scale modeled using nonlinear force laws can be described by nonlinear diffusion coefficients on the continuum scale. A general relationship between nonlinear force laws and their respective diffusion coefficients is derived in one spatial dimension and, subsequently, a range of particular examples is considered. For each case excellent agreement is observed between numerical solutions of the discrete and corresponding continuum models. Three case studies are considered in which we demonstrate how the derived nonlinear diffusion coefficients can be used to (a) relate different discrete models of cell behavior; (b) derive discrete, intercell force laws from previously posed diffusion coefficients, and (c) describe aggregative behavior in discrete simulations.

Influence of substrate on corneal epithelial cell viability within ocular surface models

Corneal tissue engineering has improved dramatically over recent years. It is now possible to apply these technological advancements to the development of superior in vitro ocular surface models to reduce animal testing. We aim to show the effect different substrates can have on the viability of expanded corneal epithelial cells and that those which more accurately mimic the stromal surface provide the most protection against toxic assault. Compressed collagen gel as a substrate for the expansion of a human epithelial cell line was compared against two well-known substrates for modeling the ocular surface (polycarbonate membrane and conventional collagen gel). Cells were expanded over 10 days at which point cell stratification, cell number and expression of junctional proteins were assessed by electron microscopy, immunohistochemistry and RT-PCR. The effect of increasing concentrations of sodium lauryl sulphate on epithelial cell viability was quantified by MTT assay. Results showed improvement in terms of stratification, cell number and tight junction expression in human epithelial cells expanded upon either the polycarbonate membrane or compressed collagen gel when compared to a the use of a conventional collagen gel. However, cell viability was significantly higher in cells expanded upon the compressed collagen gel. We conclude that the more naturalistic composition and mechanical properties of compressed collagen gels produces a more robust corneal model.