The Manila subduction zone is identified as one of the most hazardous tsunami source regions, and the countries around the South China Sea are under threat from tsunami hazard. However, the number of early-warning tsunami buoys being deployed in this area is far fewer than that in the Pacific Ocean. This study investigates a feasible approach for establishing a tsunami early warning system in the South China Sea without deploying buoys. The idea is to integrate existing earthquake early warning systems with a fast computing system for estimating tsunami threats. This study presents an efficient and low-cost tsunami fast computing system for early warning. The widely validated tsunami model, COMCOT is chosen as the kernel. The COMCOT source code has been optimized and parallelized in order to meet the requirements of real-time simulation. The optimized model, iCOMCOT performs at least 10 times faster than the original COMCOT. In addition, a flexible and user-friendly grid/cloud-based portal service has been built, which is also made available for mobile devices. As for the automatic generation of the tsunami sources, a new Source-Scaling relationship, which has been validated by recent mega-earthquakes, is implemented. The 2011 Tohoku tsunami is adopted as a case for validation and demonstration. The modelling results of Manila trench, chosen to demonstrate the application of iCOMCOT, show that the western coast of the Philippines is prone to get tsunami attacks. Furthermore, tsunami from the north segment of Manila trench tend to strike southern Taiwan, Hong Kong and Macau area; tsunami from the middle segment, Vietnam.
The discovery of potent therapeutic compounds against dengue virus is urgently needed. The NS2B-NS3 protease (NS2B-NS3pro) of dengue fever virus carries out all enzymatic activities needed for polyprotein processing and is considered to be amenable to antiviral inhibition by analogy. Virtual screening of 300,000 compounds using Autodock 3 on the GVSS platform was conducted to identify novel inhibitors against the NS2B-NS3pro. Thirty-six compounds were selected for in vitro assay against NS2B-NS3pro expressed in Pichia pastoris. Seven novel compounds were identified as inhibitors with IC50 values of 3.9 ± 0.6–86.7 ± 3.6 μM. Three strong NS2B-NS3pro inhibitors were further confirmed as competitive inhibitors with Ki values of 4.0 ± 0.4, 4.9 ± 0.3, and 3.4 ± 0.1 μM, respectively. Hydrophobic and hydrogen bond interactions between amino acid residues in the NS3pro active site with inhibition compounds were also identified.
Experience from the 1994 giant Sumatra earthquake, seismic and tsunami hazard have been considered as important issues in the South China Sea and its surrounding region, and attracted many seismologist's interesting. Currently, more than 25 broadband seismic instruments are currently operated by Institute of Earth Sciences, Academia Sinica in northern Vietnam to study the geodynamic evolution of the Red river fracture zone and rearranged to distribute to southern Vietnam recently to study the geodynamic evolution and its deep structures of the South China Sea. Similar stations are planned to deploy in Philippines in near future. In planning, some high quality stations may be left as permanent stations and added continuous GPS observations, and instruments to be maintained and operated by several cooperation institutes, for instance, Institute of Geophysics, Vietnamese Acadamy of Sciences and Technology in Vietnam and Philippine Institute of Volcanology and Seismology in Philippines. Finally, those stations will be planed to upgrade as real time transmission stations for earthquake monitoring and tsunami warning. However, high speed data transfer within different agencies is always a critical issue for successful network operation. By taking advantage of both EGEE and EUAsiaGrid e-Infrastructure, Academia Sinica Grid Computing Centre coordinates researchers from various Asian countries to construct a platform to high performance data transfer for huge parallel computation. Efforts from this data service and a newly build earthquake data centre for data management may greatly improve seismic network performance. Implementation of Grid infrastructure and e-science issues in this region may assistant development of earthquake research, monitor and natural hazard reduction: In the near future, we will search for new cooperation continually from the surrounding countries of the South China Sea to install new seismic stations to construct a complete. seismic network of the South China Sea and encourage studies for earthquake sciences and natural hazard reductions.
Agent-based simulation models provide a way to investigate social phenomena that complement existing social science methods. Recent advances in computing hardware such as the wide availability of multi-core CPUs and increased main memory capacities make it possible to investigate population-scale phenomena using commodity compute resources. This paper describes experiences made in the development of an example model that utilises multiple CPU cores and an investigation of the scalability of the resulting code. We argue that commodity compute resources and commoditised simulation frameworks can now be used to simulate real-world populations and to use these simulations to investigate social phenomena such as migration.
In the study of Biomedicines, molecular docking simulation is a common method for predicting potential interacting complexes of small molecules in protein binding sites. However, it is a time-consuming process to search exhaustively all correct conformations of a compound. This study demonstrates how massive molecular docking benefit from state-of-the-art Grid technology. Providing intensive computing power and effective data management, the production e-infrastructure (such as EGEE and EUAsiaGrid) enables opportunities for in-silico drug discovery on the neglected and emerging diseases, for instance, avian influenza and dengue fever. In this study, Grid Application Platform (GAP) and GAP-enabled Virtual Screening Service (GVSS) were developed with the docking engine of the Autodock 3.0.5. A JAVA-based graphical user interface and the GAP allow end-users to specify target and compound library, set up docking parameters, monitor docking jobs and computing resources, visualize and refine docking results, and finally download the final results. To provide a more user-friendly Grid service, GVSS was designed for conducting large-scale molecular docking more easily.
Large scale grids for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale virtual docking within the framework of the WISDOM initiative against malaria and avian influenza requiring about 100 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large scale grids for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large scale deployment.
Large scale grids for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale virtual docking within the framework of the WISDOM initiative against malaria and avian influenza requiring about 100 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large scale grids for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large scale deployment.
Large-scale grid infrastructures for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale in silico docking within the framework of the WISDOM initiative against Malaria and Avian Flu requiring about 105 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large-scale grid infrastructures for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large-scale deployment.
Encouraged by the success of the first EGEE biomedical data challenge against malaria (WISDOM) , the second data challenge battling avian flu was kicked off in April 2006 to identify new drugs for the potential variants of the influenza A virus. Mobilizing thousands of CPUs on the Grid, the six-week-long high-throughput screening activity has fulfilled over 100 CPU years of computing power and produced around 600 gigabytes of results on the Grid for further biological analysis and testing. In the paper, we demonstrate the impact of a worldwide Grid infrastructure to efficiently deploy large-scale virtual screening to speed up the drug design process. Lessons learned through the data challenge activity are also discussed