Abstract The KCNH2 L532P mutation is an alteration in the I Kr channel that is associated with short QT syndrome and atrial fibrillation in zebrafish. In preliminary studies, the electrophysiological effects of the hERG L532P mutation were investigated using a mathematical model in a single-cell and 2D sheet medium. The objective of this study was to quantify the effects of the KCNH2 L532P mutation on the 3D ventricular electrophysiological behavior and the mechanical pumping responses. We used a realistic three-dimensional ventricular electrophysiological–mechanical model, which was adjusted into two conditions: the wild-type (WT) condition, i.e., the original case of the Tusscher et al. model, and the L532P mutation condition, with modification of the original I Kr equation. The action potential duration (APD) in the mutant ventricle was reduced by 73% owing to the significant increase of the I Kr current density. In the 3D simulation, the L532P mutation maintained the sustainability of reentrant waves; however, the reentry was terminated in the WT condition. The contractility of the ventricle with L532P mutation was significantly reduced compared with that in WT which results in sustain shivering heart during reentry condition. The reduction of the contractility was associated with the shortening APD which simultaneously shortened the duration of the Ca2+ channel opening. In conclusion, the ventricle with KCNH2 L532P mutation is prone to reentry generation with a sustained chaotic condition, and the mutation significantly reduced the pumping performance of the ventricles.

A water distribution network (WDN) is a critical infrastructure that must be maintained, ensuring a proper water supply to widespread customers. A WDN consists of various components, such as pipes, valves, pumps, and tanks, and these elements interact with each other to provide adequate system performance. If the elements fail due to internal or external interruptions, this may adversely impact water service to different degrees depending on the failed elements. To determine an appropriate maintenance priority, the critical elements need to be identified and mapped in the network. To identify and prioritize the critical elements (here, we focus on the pipes only) in the WDN, an element-based simulation approach is proposed, in which all the composing pipes of the WDN are reviewed one at a time. The element-based criticality is measured using several criticality indexes that are newly proposed in this study. The proposed criticality indexes are used to quantify the impacts of element failure to water service degradation. Here, four criticality indexes are developed: supply shortage (SS), economic value loss (EVL), pressure decline (PD), and water age degradation (WAD). Each of these indexes measures different aspects of the consequences, specifically social, economic, hydraulic, and water quality, respectively. The separate values of the indexes from all pipes in a network are then combined into a singular criticality value for assessment. For demonstration, the proposed approach is applied to four real WDNs to identify and prioritize the critical pipes. The proposed element-based simulation approach can be used to identify the critical components and setup maintenance scheduling of WDNs for preparedness of failure events.

A real-time prediction method using a multilayer feedforward neural network is proposed for estimating vertical dynamic displacements of a bridge from the longitudinal strains of the bridge when vehicles pass across it. A numerical model for an existing five-girder bridge spanning 36 m proved by actual experimental values was used to verify the proposed method. To obtain a realistic vehicle distribution for the bridge, vehicle type and actual headways of moving vehicles were taken, and the measured vehicle distribution was generalized using Pearson Type III theory. Twenty-five load scenarios were created with assumed vehicle speeds of 40 km/h, 60 km/h, and 80 km/h. The results indicate that the model can reasonably predict the overall displacements of the bridge (which is difficult to measure) from the strain (which is relatively easy to measure) in the field in real time.

Protein–peptide interactions are involved in a wide range of biological processes and are attractive targets for therapeutic purposes because of their small interfaces. Therefore, effective protein–peptide docking techniques can provide the basis for potential therapeutic applications by enabling an atomic-level understanding of protein interactions. With the increasing number of protein–peptide structures deposited in the protein data bank, the prediction accuracy of protein-peptide docking can be enhanced by utilizing the information provided by the database. The GalaxyPepDock web server, which is freely accessible at http://galaxy.seoklab.org/pepdock, performs similarity-based docking by finding templates from the database of experimentally determined structures and building models using energy-based optimization that allows for structural flexibility. The server can therefore effectively model the structural differences between the template and target protein–peptide complexes. The performance of GalaxyPepDock is superior to those of the other currently available web servers when tested on the PeptiDB set and on recently released complex structures. When tested on the CAPRI target 67, GalaxyPepDock generates models that are more accurate than the best server models submitted during the CAPRI blind prediction experiment.

ABSTRACTProtein structures predicted by state‐of‐the‐art template‐based methods may still have errors when the template proteins are not similar enough to the target protein. Overall target structure may deviate from the template structures owing to differences in sequences. Structural information for some local regions such as loops may not be available when there are sequence insertions or deletions. Those structural aspects that originate from deviations from templates can be dealt with by ab initio structure refinement methods to further improve model accuracy. In the CASP11 refinement experiment, we tested three different refinement methods that utilize overall structure relaxation, loop modeling, and quality assessment of multiple initial structures. From this experiment, we conclude that the overall relaxation method can consistently improve model quality. Loop modeling is the most useful when the initial model structure is high quality, with GDT‐HA >60. The method that used multiple initial structures further refined the already refined models; the minor improvements with this method raise the issue of problem with the current energy function. Future research directions are also discussed. Proteins 2016; 84(Suppl 1):293–301. © 2015 Wiley Periodicals, Inc.

A priori density predictions of 32 molecules were attempted by combining the effective fragment potential version 2 (EFP2) and NPT molecular dynamics (MD) simulations. Our EFP2-MD procedure accurately predicted the density maximum of water as a function of temperature, showing its promising performance in the prediction of molecular density. With the help of a uniform scale factor of 0.9099, the mean absolute deviation and root-mean-square deviation of 32 molecular density predictions as compared to experiments are 0.037 and 0.002 g/cm(3), respectively. They exhibit remarkable accuracy considering the fact that EFP2 is a purely theoretical parameter.

Density functional theory calculations were carried out to study how the position of single-atom doping affects the electronic properties of three graphyne models. We found that the position of the dopant (B, N, or O) plays an important role in tuning the electronic structure of graphynes. For alpha-graphyne, the electronic structure is significantly different for different positions of B and O doping. For beta-graphyne, the electronic structure depends remarkably on the doping position for O doping, but not much for B and N doping, whereas for gamma-graphyne, it depends on the position for B and O doping, but not for N doping. (C) 2016 Elsevier Ltd. All rights reserved.

Histidine state (deprotonated, neutral, and protonated) is considered an important factor influencing the structural properties and aggregation mechanisms in amyloid beta-peptides (A beta), which are associated with the pathogenesis of Alzheimer's disease. Understanding the structural properties and aggregation mechanisms is a great challenge because two forms (the N-epsilon-H or N-delta-H tautomer) can exist in the free neutral state of histidine. Here, replica exchange molecular dynamics simulation was performed to elucidate the changes in structure and the mechanism of aggregation influenced by tautomeric behaviors of histidine in A beta(1-40). Our results show that sheet-dominating conformations can be found in the His6(delta)-His13(delta)-His14(delta) (delta delta delta) isomer with significant antiparallel sheet structures between R5-D7 and L34-G38, as well as between L17-F20 and L34-G38, implying that a new aggregation mechanism may exist to promote the generation of oligomers and/or aggregates. This work fundamental tautomeric behaviors of neutral histidine in the process of aggregation. is helpful in understanding the fundamental tautomeric behaviors of neutral histidine in the process of aggregation.