Exploring new scaffolds for angiotensin II receptor antagonism

Nowadays, AT₁ receptor (AT₁R) antagonists (ARBs) constitute the one of the most prevalent classes of antihypertensive drugs that modulate the renin-angiotensin system (RAS). Their main uses include also treatment of diabetic nephropathy (kidney damage due to diabetes) and congestive heart failure. Towards this direction, our study has been focused on the discovery of novel agents bearing different scaffolds which may evolve as a new class of AT₁ receptor antagonists. To fulfill this aim, a combination of computational approaches and biological assays were implemented. Particularly, a pharmacophore model was established and served as a 3D search query to screen the ChEMBL15 database. The reliability and accuracy of virtual screening results were improved by using molecular docking studies. In total, 4 compounds with completely diverse chemical scaffolds from potential ARBs, were picked and tested for their binding affinity to AT₁ receptor. Results revealed high nanomolar to micromolar affinity (IC₅₀) for all the compounds. Especially, compound 4 exhibited a binding affinity of 199 nM. Molecular dynamics simulations were utilized in an effort to provide a molecular basis of their binding to AT₁R in accordance to their biological activities.     

A genetic and spatial Bayesian analysis of mastitis resistance

A nationwide health card recording system for dairy cattle was introduced in Norway in 1975 (the Norwegian Cattle Health Services). The data base holds information on mastitis occurrences on an individual cow basis. A reduction in mastitis frequency across the population is desired, and for this purpose risk factors are investigated. In this paper a Bayesian proportional hazards model is used for modelling the time to first veterinary treatment of clinical mastitis, including both genetic and environmental covariates. Sire effects were modelled as shared random components, and veterinary district was included as an environmental effect with prior spatial smoothing. A non-informative smoothing prior was assumed for the baseline hazard, and Markov chain Monte Carlo methods (MCMC) were used for inference. We propose a new measure of quality for sires, in terms of their posterior probability of being among the, say 10% best sires. The probability is an easily interpretable measure that can be directly used to rank sires. Estimating these complex probabilities is straightforward in an MCMC setting. The results indicate considerable differences between sires with regards to their daughters disease resistance. A regional effect was also discovered with the lowest risk of disease in the south-eastern parts of Norway.     

Novel Monte Carlo dose calculation algorithm for robotic radiosurgery with multi leaf collimator: Dosimetric evaluation

PurposeAt introduction in 2014, dose calculation for the first MLC on a robotic SRS/SBRT platform was limited to a correction-based Finite-Size Pencil Beam (FSPB) algorithm. We report on the dosimetric accuracy of a novel Monte Carlo (MC) dose calculation algorithm for this MLC, included in the Precision™ treatment planning system.MethodsA phantom was built of one slab (5.0 cm) of lung-equivalent material (0.09…0.29 g/cc) enclosed by 3.5 cm (above) and 5 cm (below) slabs of solid water (1.045 g/cc). This was irradiated using rectangular (15.4 × 15.4 mm² to 53.8 × 53.7 mm²) and two irregular MLC-fields. Radiochromic film (EBT3) was positioned perpendicular to the slabs and parallel to the beam. Calculated dose distributions were compared to film measurements using line scans and 2D gamma analysis.ResultsMeasured and MC calculated percent depth dose curves showed a characteristic dose drop within the low-density region, which was not correctly reproduced by FSPB. Superior average gamma pass rates (2%/1 mm) were found for MC (91.2 ± 1.5%) compared to FSPB (55.4 ± 2.7%). However, MC calculations exhibited localized anomalies at mass density transitions around 0.15 g/cc, which were traced to a simplification in electron transport. Absence of these anomalies was confirmed in a modified build of the MC engine, which increased gamma pass rates to 96.6 ± 1.2%.ConclusionsThe novel MC algorithm greatly improves dosimetric accuracy in heterogeneous tissue, potentially expanding the clinical use of robotic radiosurgery with MLC. In-depth, independent validation is paramount to identify and reduce the residual uncertainties in any software solution.     

The effect of dielectric polarization of the electrode on anomalous temperature effects in the electrical double layer

Monte Carlo simulations and a modified Poisson–Boltzmann (MPB) theory are used to investigate the temperature dependence of the capacitance (around the potential of zero charge) of an electric double layer in the presence of surface polarization due to a dielectric boundary. Within the context of the restricted primitive model planar double layer, whose solvent dielectric constant is ε₂, the cases when the electrode is an insulator (ε₁ = 1), when the electrode and the electrolyte have the same permittivity (ε₁ = ε₂, no polarization), and when the electrode is a conductor (ε₁ → ∞) are studied for the case where the electrolyte concentration is 0.1 M. The simulations reveal a capacitance anomaly, that is, a positive temperature dependence of the capacitance at low temperatures for the former two situations. The MPB theory also shows this effect for these two situations and is in qualitative or better agreement with the simulation data. In these two cases, both the simulations and theory show a dramatic increase of the diffuse layer potential in the temperature regime where capacitance anomaly occurs. However, in the latter situation, where the electrode is metallic, the capacitance always has a negative temperature derivative for the MPB theory and probably also for the simulation data.     

On computational efficiency of the hybrid Monte Carlo method applied to the multicanonical ensemble

Abstract

In the present paper, computational efficiency of the hybrid Monte Carlo (HMC) method applied to the multicanonical ensemble is studied; the HMC is an equation of motion guided Monte Carlo method. As in the standard HMC for the canonical ensemble, the multicanonical HMC calculations with high acceptance ratio show better efficiency; about 60% acceptance yields the best performance for the system examined.     

Studies on evolutionary and selective properties of hypercycles using a Monte Carlo method

Summary The most relevant properties of hypercycles were previously studied mainly from a theoretical point of view. We have developed a Monte Carlo method simulating hypercyclic organization to obtain information about the dynamics of this prebiotic organization. Nucleation, growth, and selective properties have been tested and the results obtained are in good agreement with those of the theoretical predictions. The influence of hypercyclic organization of the error threshold has also been studied. As a consequence of the emergence of a hypercycle, the value of this threshold decreases. The amount of this decrease depends on the population size. Moreover, for some interval of quality factor values, either the hypercycle organization or an error catastrophe can be produced, depending on the initial conditions. The influence of these phenomena on both the dynamic behavior and evolutionary advantages of the hypercycle, as well as their decisive roles on genome size, are discussed.Presented at the FEBS Symposium on Genome Organization and Evolution, held in Crete, Greece, September 1–5, 1986     

Estimation of uncertainties in X-ray refinement results by use of perturbed structures

The uncertainties in the refined parameters for a 1.5-A X-ray structure of carbon-monoxy (FeII) myoglobin are estimated by combining energy minimization with least-squares refinement against the X-ray data. The energy minimizations, done without reference to the X-ray data, provide perturbed structures which are used to restart conventional X-ray refinement. The resulting refined structures have the same, or better, R-factor and stereochemical parameters as the original X-ray structure, but deviate from it by 0.13 A rms for the backbone atoms and 0.31 A rms for the sidechain atoms. Atoms interacting with a disordered sidechain, Arg 45 CD3, are observed to have larger positional uncertainties. The uncertainty in the B-factors, within the isotropic harmonic motion approximation, is estimated to be 15%. The resulting X-ray structures are more consistent with the energy parameters used in simulations.     

Volume estimation of biological objects by systematic sections

The absolute volume of biological objects is often estimated stereologically from an exhaustive set of systematic sections. The usual volume estimator is the sum of the section contents times the distance between sections. For systematic sectioning with a random start, it has been recently shown that is unbiased when m, the ratio between projected object length and section distance, is an integer number (Cruz-Orive 1985). As this quantity is no integer in the real world, we have explored the properties of in the general and realistic situation m . The unbiasedness of under appropriate sampling conditions is demonstrated for the arbitrary compact set in 3 dimensions by a rigorous proof. Exploration of further properties of for the general triaxial ellipsoid leads to a new class of non-elementary real functions with common formal structure which we denote as np-functions. The relative mean square error (CE ²) of in ellipsoids is an oscillating differentiable np-function, which reduces to the known result CE ²= 1/(5m ⁴) for integer m. As a biological example the absolute volumes of 10 left cardiac ventricles and their internal cavities were estimated from systematic sections. Monte Carlo simulation of replicated systematic sectioning is shown to be improved by using m instead of m . In agreement with the geometric model of ellipsoids with some added shape irregularities, mean empirical CE was proportional to m ^–1.36 and m^–1.73 in the cardiac ventricle and its cavity. The considerable variance reduction by systematic sectioning is shown to be a geometric realization of the principle of antithetic variates.     

Aedes aegypti: model for blood finding strategy and prediction of parasite manipulation

Aedes aegypti mosquitoes salivate during intradermal probing of vertebrate prey before ingesting blood (Griffiths and Gordon 1952). Nonsalivating mosquitoes locate blood more slowly; this difference was ascribed to an anti-platelet activity found in the mosquito's saliva (Ribeiro et al. 1984). Mosquitoes infected with Plasmodium gallinaceum suffer pathology that specifically impairs saliva anti-hemostatic activity but without reducing volume of output (Rossignol et al. 1984). The complexity of the feeding apparatus of mosquitoes provides opportunity for a variety of strategies in which pathogens may produce specific lesions that enhance their transmission, but the variables that affect the duration of probing by mosquitoes have not been defined. We sought to resolve this complexity by identifying and quantifying relevant parameters of probing behavior. Mosquitoes thrust their mouthparts repeatedly through their host's skin while searching for blood. Female A. aegypti thrust at 7-sec intervals. If this search results in success, feeding ensues. Alternatively, the mosquito "desists," the mouthparts stylets are withdrawn, and the mosquito attempts to feed at another site. Even after previous desistance, the probability of finding blood remains undiminished. Functions for the probability of feeding success and desistance over time were derived using data from observations on 300 mosquitoes. The probability of feeding success was interpreted as being a function of the density of vessels in the skin, their geometric distribution, and the conditions locally affecting hemostasis. During each probe, the probability of desisting increased linearly with time, and after desisting once, mosquitoes tended to desist more rapidly. A model was developed incorporating Monte Carlo simulation which closely fit observed data. By changing values for the several parameters of the probability functions, we predicted modes in which parasites may manipulate their hosts to enhance transmission, both to and from the vector. In particular, parasite strategies in the vector would include induced salivary pathology; increased duration of probing thrusts; decreased desistance time; and inhibited phagoreception. Predicted parasite strategies in the reservoir host would include increased skin vascular volume and impaired host hemostasis. Our model supports the hypothesis of a mutualistic interaction of malaria and mosquitoes.