Modeling an immune response to influenza A virus infection in alveolar epithelial cells

Influenza A viruses (IAV) have been the cause of several influenza pandemics in history and are a significant threat for the next global pandemic. Hospitalized influenza patients often have excess interferon production and a dysregulated immune response to the IAV infection. Obtaining a better understanding of the mechanisms of IAV infection that induce these harmful effects would help drug developers and health professionals create more effective treatments for IAV infection and improve patient outcomes. IAV stimulates viral sensors and receptors expressed by alveolar epithelial cells, like RIG-I and toll-like receptor 3 (TLR3). These two pathways coordinate with one another to induce expression of type III interferons to combat the infection. Presented here is a queuing theory-based model of these pathways that was designed to analyze the timing and amount of interferons produced in response to IAV single stranded RNA and double-stranded RNA detection. The model accurately represents biological data showing the necessary coordination of the RIG-I and TLR3 pathways for effective interferon production. This model can serve as the framework for future studies of IAV infection and identify new targets for potential treatments.     

Alginate/chitosan hydrogels as perspective transport systems for cefotaxime

This work reports synthesis of pH-responsive alginate/chitosan hydrogel spheres with the average diameter of 2.0 ± 0.05 mm, which contain cefotaxime that is an antibiotic of the cefalosporine group. The spheres provided the cefotaxime encapsulation efficiency of 95 ± 1%. An in vitro release of cefotaxime from the spheres in the media that simulate human biological fluids in peroral delivery conditions was found to be a pH-dependent process. The analysis of cefotaxime release kinetics by the Korsmeyer–Peppas model revealed a non-Fickian mechanism of its diffusion, which may be related to intermolecular interactions occurring between the antibiotic and chitosan. Conductometry, UV spectroscopy, and IR spectroscopy were used to study complexation of chitosan with cefotaxime in aqueous media with varied pH, characterize the composition of the complexes, and calculate their stability constants. The composition of the cefotaxime–chitosan complexes was found to correspond to the 1.0:4.0 and 1.0:2.0 molar ratios of the components at pH 2.0 and 5.6, respectively. Quantum chemical modeling was used to evaluate energy characteristics of chitosan–cefotaxime complexation considering the influence of a solvent.     

Recognition of errors in three-dimensional structures of proteins

A major problem in the determination of the three-dimensional structure of proteins concerns the quality of the structural models obtained from the interpretation of experimental data. New developments in X-ray crystallography and nuclear magnetic resonance spectroscopy have acceleratedd the process of structure determination and the biological community is confronted with a steadily increasing number of experimentally determined protein folds. However, in the recent past several experimentally determined protein structures have been proven to contain major errors, indicating that in some cases the interpretation of experimental data is difficult and may yield incorrect models. Such problems can be avoided when computational methods are employed which complement experimental structure determinations. A prerequisite of such computational tools is that they are independent of the parameters obtained from a particular experiment. In addition such techniques are able to support and accelerate experimental structure determinations. Here we present techniques based on knowledge based mean fields which can be used to judge the quality of protein folds. The methods can be used to identify misfolded structures as well as faulty parts of structural models. The techniques are even applicable in cases where only the C_α trace of a protein conformation is available. The capabilities of the technique are demonstrated using correct and incorrect protein folds. © 1993 Wiley-Liss, Inc.     

TTLL11 gene is associated with sustained attention performance and brain networks: A genome-wide association study of a healthy Chinese sample

Genetic studies on attention have mainly focused on children with attention-deficit/hyperactivity disorder (ADHD), so little systematic research has been conducted on genetic correlates of attention performance and their potential brain mechanisms among healthy individuals. The current study included a genome-wide association study (GWAS, N = 1145 healthy young adults) aimed to identify genes associated with sustained attention and an imaging genetics study (an independent sample of 483 healthy young adults) to examine any identified genes' influences on brain function. The GWAS found that TTLL11 showed genome-wide significant associations with sustained attention, with rs13298112 as the most significant SNP and the GG homozygotes showing more impulsive but also more focused responses than the A allele carriers. A retrospective examination of previously published ADHD GWAS results confirmed an un-reported, small but statistically significant effect of TTLL11 on ADHD. The imaging genetics study replicated this association and showed that the TTLL11 gene was associated with resting state activity and connectivity of the somatomoter network, and can be predicted by dorsal attention network connectivity. Specifically, the GG homozygotes showed lower brain activity, weaker brain network connectivity, and non-significant brain-attention association compared to the A allele carriers. Expression database showed that expression of this gene is enriched in the brain and that the G allele is associated with lower expression level than the A allele. These results suggest that TTLL11 may play a major role in healthy individuals' attention performance and may also contribute to the etiology of ADHD.     

Design,Synthesis, and Biological Evaluation of Novel Indanone Derivatives as Cholinesterase Inhibitors for Potential Use in Alzheimer's Disease

Indanone derivatives containing meta/para-substituted aminopropoxy benzyl/benzylidene moieties were designed based on the structures of donepezil and ebselen analogs as the cholinesterase inhibitors. The designed compounds were synthesized and their acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activities were measured. Inhibitory potencies (IC₅₀ values) for the synthesized compounds ranged from 0.12 to 11.92 μM and 0.04 to 24.36 μM against AChE and BChE, respectively. Compound 5 c showed the highest AChE inhibitory potency with IC₅₀ value of 0.12 μM, whereas the highest BChE inhibition was achieved by structure 7 b (IC₅₀=0.04 μM). Structure-activity relationship (SAR) analysis revealed that there is no significant difference between meta and para-substituted derivatives in AChE and BChE inhibition. However, the most potent AChE inhibitor 5 c belongs to meta-substituted compounds, while the most active BChE inhibitor is para-substituted derivative 7 b . The order of enzyme inhibition potency based on the substituted amine group is dimethyl amine>piperidine>morpholine. Compounds containing C=C linkage are more potent AChE inhibitors than the corresponding saturated structures. Molecular docking studies indicated that 5 c interacts with AChE in a very similar way to that observed experimentally for donepezil. The introduced indanone-aminopropoxy benzylidenes could be used in drug-discovery against Alzheimer's disease.     

Prediction of habitat suitability,connectivity, and corridors in the future to conserve roe deer (Capreolus capreolus) as a locally endangered species in northern Iran

Roe deer is a protected species in Iran as its population and distribution in the country have considerably declined. Roe deer are threatened by several factors such as habitat fragmentation and road mortality, so studying their distribution and movement through the increasing habitat destruction and fragmentation is necessary. This will become increasingly important because climate change will transform the species’ future habitat and connectivity patterns. We evaluated the roe deer’s potential distribution range in northern Iran and, for the first time, developed connectivity models and designed corridors for the present and future to make better conservation plans. We collected 91 points indicating the presence of roe deer in the study region. After developing ensemble models using six species distribution algorithms, we defined high-ranked habitat cores using the concept of landscape suitability prioritization. From these, we designed connectivity and corridors in two time-frames with the help of least-cost paths and circuit theories to predict the potential movement throughout the study area. We estimated that the overall core habitats for roe deer in the present and future periods are, respectively, around 1200 km² and 2600 km², corresponding to 2 and 4 percent of the whole area. This suggests that the habitat core will expand in the future as a result of climate change. Similarly, the connectivity among the cores will strengthen. We also conclude that the temperature-driven and anthropogenic variables significantly affect the distribution of roe deer in northern Iran. It is necessary that conservationists and managers consider the designed corridors in the present study while planning conservation strategies.     

Using Molecular Dynamics to Predict Factors Affecting Binding Strength and Magnetic Relaxivity of MRI Contrast Agents

We demonstrate the use of molecular dynamics and molecular mechanics methods to calculate properties and behavior of metal-chelate complexes that can be used as MRI contrast agents. Static and dynamic properties of several known agents were calculated and compared with experiment. We calculated the static properties such as the q-values (number of inner shell waters) and binding distances of chelate atoms to the metal ion for a set of chelates with known X-ray structure. The dynamic flexibility of the chelate arms was also calculated. These computations were extended to a series of exploratory chelate structures in order to estimate their potential as MRI contrast agents. We have also calculated for the first time the NMR relaxivity of an MRI contrast agent using a long (5 nsec) molecular dynamics simulation. Our predictions are promising enough that the method should prove useful for evaluating novel candidate compounds before they are synthesized. One novel static property, the projected area of chelate atoms onto a virtual surface centered on the metal ion (gnomonic projection), was found to give an effective measure of how well the chelate atoms use the free space around the metal ion.     

Conformational analysis and clustering of short and medium size loops connecting regular secondary structures: a database for modeling and prediction.

Loops are regions of nonrepetitive conformation connecting regular secondary structures. We identified 2,024 loops of one to eight residues in length, with acceptable main-chain bond lengths and peptide bond angles, from a database of 223 protein and protein-domain structures. Each loop is characterized by its sequence, main-chain conformation, and relative disposition of its bounding secondary structures as described by the separation between the tips of their axes and the angle between them. Loops, grouped according to their length and type of their bounding secondary structures, were superposed and clustered into 161 conformational classes, corresponding to 63% of all loops. Of these, 109 (51% of the loops) were populated by at least four nonhomologous loops or four loops sharing a low sequence identity. Another 52 classes, including 12% of the loops, were populated by at least three loops of low sequence similarity from three or fewer nonhomologous groups. Loop class suprafamilies resulting from variations in the termini of secondary structures are discussed in this article. Most previously described loop conformations were found among the classes. New classes included a 2:4 type IV hairpin, a helix-capping loop, and a loop that mediates dinucleotide-binding. The relative disposition of bounding secondary structures varies among loop classes, with some classes such as beta-hairpins being very restrictive. For each class, sequence preferences as key residues were identified; those most frequently at these conserved positions than in proteins were Gly, Asp, Pro, Phe, and Cys. Most of these residues are involved in stabilizing loop conformation, often through a positive phi conformation or secondary structure capping. Identification of helix-capping residues and beta-breakers among the highly conserved positions supported our decision to group loops according to their bounding secondary structures. Several of the identified loop classes were associated with specific functions, and all of the member loops had the same function; key residues were conserved for this purpose, as is the case for the parvalbumin-like calcium-binding loops. A significant number, but not all, of the member loops of other loop classes had the same function, as is the case for the helix-turn-helix DNA-binding loops. This article provides a systematic and coherent conformational classification of loops, covering a broad range of lengths and all four combinations of bounding secondary structure types, and supplies a useful basis for modelling of loop conformations where the bounding secondary structures are known or reliably predicted.     

Ligand recognition in μ opioid receptor: experimentally based modeling of μ opioid receptor binding sites and their testing by ligand docking

For three-dimensional understanding of the mechanisms that control potency and selectivity of the ligand binding at the atomic level, we have analysed opioid receptor-ligand interaction based on the receptor's 3D model. As a first step, we have constructed molecular models for the multiple opioid receptor subtypes using bacteriorhodopsin as a template. The S-activated dihydromorphine derivatives should serve as powerful tools in mapping the three-dimensional structure of the μ opioid receptor, including the nature of the agonist-mediated conformational change that permits G protein-coupling to ‘second messenger’ effector molecules, and in identifying specific ligand-binding contacts with the μ opioid receptor. The analyses of the interactions of some opioid ligands with the predicted ligand binding sites are consistent with the results of the affinity labeling experiments.     

Coding of odor intensity in a steady-state deterministic model of an olfactory receptor neuron

The coding of odor intensity by an olfactory receptor neuron model was studied under steady-state stimulation. Our model neuron is an elongated cylinder consisting of the following three components: a sensory dendritic region bearing odorant receptors, a passive region consisting of proximal dendrite and cell body, and an axon. First, analytical solutions are given for the three main physiological responses: (1) odorant-dependent conductance change at the sensory dendrite based on the Michaelis-Menten model, (2) generation and spreading of the receptor potential based on a new solution of the cable equation, and (3) firing frequency based on a Lapicque model. Second, the magnitudes of these responses are analyzed as a function of odorant concentration. Their dependence on chemical, electrical, and geometrical parameters is examined. The only evident gain in magnitude results from the activation-to-conductance conversion. An optimal encoder neuron is presented that suggests that increasing the length of the sensory dendrite beyond about 0.3 space constant does not increase the magnitude of the receptor potential. Third, the sensivities of the responses are examined as functions of (1) the concentration at half-maximum response, (2) the lower and upper concentrations actually discriminated, and (3) the width of the dynamic range. The overall gain in sensitivity results entirely from the conductance-to-voltage conversion. The maximum conductance at the sensory dendrite appears to be the main tuning constant of the neuron because it determines the shift toward low concentrations and the increase in dynamic range. The dynamic range of the model cannot exceed 5.7 log units, for a sensitivity increase at low odor concentration is compensated by a sensitivity decrease at high odor concentration.