Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: Meeting new challenges

© 2014 Elsevier Ltd All rights reserved. Despite tremendous successes of GPCR crystallography, the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to maximize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor the progress in molecular modeling and ligand docking for GPCRs. The four targets in the present third assessment round presented new and diverse challenges for modelers, including prediction of allosteric ligand interaction and activation states in 5-hydroxytryptamine receptors 1B and 2B, and modeling by extremely distant homology for smoothened receptor. Forty-four modeling groups participated in the assessment. State-of-the-art modeling approaches achieved close-to-experimental accuracy for small rigid orthosteric ligands and models built by close homology, and they correctly predicted protein fold for distant homology targets. Predictions of long loops and GPCR activation states remain unsolved problems

Numerical modelling of aeolian coastal landform development

Coastal dunes serve as a first line of protection against flooding by the sea. In the recent past, the interest in secondary services provided by coastal dunes has increased. These services include ecological values and recreation. In order to manage and maintain the coast as an attractive area that combines coastal protection and ecological values, the natural dynamics have to be understood. In view of this, numerical models with quantitative predictive capabilities on the development of coastal dunes can give a lot of insight. A model is developed with the aim to improve the current aeolian modeling by implementing biological and physical processes adapted from different existing models, developing a modular aeolian transport model with quantitative predictive capabilities for dune development. The current version of the model is capable of simulating barchan dunes and the initial stage of coastal dune formation: Embryo dunes. Potentially the model can be used to determine the influence of tidal ranges, storm frequencies, armoring, salinity and precipitation on dune building processes. This will result in a greater insight in the general behavior of coastal systems, including the evolution of embryonal dune fields as well as foredune characteristics like maximum height and autocyclic formation of transverse dunes. On the other hand the model can also be used during more practical situations such as computing recovery times of coastal dunes after extreme events or for the creation of artificial blowouts

RESEARCH ARTICLE Proteochemometric modeling in a Bayesian framework Open Access

Proteochemometrics (PCM) is an approach for bioactivity predictive modeling which models the relationship between protein and chemical information. Gaussian Processes (GP), based on Bayesian inference, provide the most objective estimation of the uncertainty of the predictions, thus permitting the evaluation of the applicability domain (AD) of the model. Furthermore, the experimental error on bioactivity measurements can be used as input for this probabilistic model. In this study, we apply GP implemented with a panel of kernels on three various (and multispecies) PCM datasets. The first dataset consisted of information from 8 human and rat adenosine receptors with 10,999 small molecule ligands and their binding affinity. The second consisted of the catalytic activity of four dengue virus NS3 proteases on 56 small peptides. Finally, we have gathered bioactivity information of small molecule ligands on 91 aminergic GPCRs from 9 different species, leading to a dataset of 24,593 datapoints with a matrix completeness of only 2.43%. GP models trained on these datasets are statistically sound, at the same level of statistical significance as Support Vector Machines (SVM), with R2 0 values on the external dataset ranging from 0.68 to 0.92, and RMSEP values close to the experimental error. Furthermore, the best GP models obtained with the normalized polynomial and radial kernels provide intervals of confidence for the predictions in agreement with the cumulative Gaussian distribution. GP models were also interpreted on the basis of individual targets and of ligand descriptors. In the dengue dataset, the model interpretation in terms of the amino-acid positions in the tetra-peptide ligands gave biologically meaningful results

Predicting marine and aeolian contributions to the Sand Engine's evolution using coupled modelling

Quantitative predictions of marine and aeolian sediment transport in the nearshore–beach–dune system are important for designing Nature-Based Solutions (NBS) in coastal environments. To quantify the impact of the marine-aeolian interactions on shaping NBS, we present a framework coupling three existing process-based models: Delft3D Flexible Mesh, SWAN and AeoLiS. This framework facilitates the continuous exchange of bed levels, water levels and wave properties between numerical models focussing on the aeolian and marine domain. The coupled model is used to simulate the morphodynamic evolution of the Sand Engine mega-nourishment. Results display good agreement with the observed aeolian and marine volumetric developments, showing similar marine-driven erosion from the main peninsula and aeolian-driven infilling of the dune lake. To estimate the magnitude of the interactions between aeolian and marine processes, a comparison between the simulated morphological development by the coupled and stand-alone models was made. This comparison shows that aeolian sediment transport to the foredune, i.e. 214,000 m3 over 5 years, extracts sediment from the marine domain. As a result, the alongshore redistribution of sediment from the main peninsula by marine-driven processes decreased by 70,000 m3, representing 1.7% of the total marine-driven dispersion. From the aeolian perspective, marine-driven deposition and erosion reshape the cross-shore profile, controlling the supply-limited aeolian sediment transport and the magnitude of sediment deposition in the foredunes. In the region with persistent accretion along the Sand Engine's southern flank, a higher than average foredune deposition was predicted due to morphological development of the region where sediment is picked up by aeolian transport. Including these marine processes in the coupled model resulted in an increase of 1.3% in foredune growth in year 1 and up to 6.7% in year 5 along this accretive section. At the northern flank, where the developing lagoon and tidal channel provided increased shelter to the supratidal beach, predicted foredune deposition reduced up to −11.5% over the evaluation period. Our findings show that both aeolian and marine transports impact reshaping the nourished sand, where developments in one domain affect the other. The study findings echo that the interplay between aeolian- and marine-driven morphodynamics could play a relevant role when predicting sandy NBS.</p

The association between body temperature and electrocardiographic parameters in normothermic healthy volunteers

Background: Previous studies reported that hypo- and hyperthermia are associated with several atrial and ventricular electrocardiographical parameters, including corrected QT (QTc) interval. Enhanced characterization of variations in QTc interval and normothermic body temperature aids in better understanding the underlying mechanism behind drug induced QTc interval effects. The analysis’ objective was to investigate associations between body temperature and electrocardiographical parameters in normothermic healthy volunteers. Methods: Data from 3023 volunteers collected at our center were retrospectively analyzed. Subjects were considered healthy after review of collected data by a physician, including a normal tympanic body temperature (35.5-37.5°C) and in sinus rhythm. A linear multivariate model with body temperature as a continuous was performed. Another multivariate analysis was performed with only the QT subintervals as independent variables and body temperature as dependent variable. Results: Mean age was 33.8 ± 17.5 years and mean body temperature was 36.6 ± 0.4°C. Body temperature was independently associated with age (standardized coefficient [SC] = −0.255, P <.001), female gender (SC = +0.209, P <.001), heart rate (SC = +0.231, P <.001), P-wave axis (SC = −0.051, P <.001), J-point elevation in lead V4 (SC = −0.121, P <.001), and QTcF duration (SC = −0.061, P =.002). In contrast, other atrial and atrioventricular (AV) nodal parameters were not independently associated with body temperature. QT subinterval analysis revealed that only QRS duration (SC = −0.121, P <.001) was independently associated with body temperature. Conclusion: Body temperature in normothermic healthy volunteers was associated with heart rate, P-wave axis, J-point amplitude in lead V4, and ventricular conductivity, the latter primarily through prolongation of the QRS duration