Russian Supercomputer and Three Chinese Universities Join the Good Hope Net Project to Combat Coronavirus

May 28, 2020

MOSCOW, Russia and HUNAN, Shanghai, Xiamen (China), May 28, 2020 — The China’s Hunan University, Shanghai Jiao Tong University and Xiamen University have joined an international science group named The Good Hope Net. The scientists from Russia, Finland, Italy, Canada and China have a high priority access to RSC Tornado supercomputer deployed at Joint Supercomputing Center of Russian Academy of Sciences (JSCC RAS) for studying methods to fight against the COVID-19 coronavirus infection. This project aims to develop medicine for diagnostics and therapy against the coronavirus contagious disease that became the cause of the global pandemic.

Image courtesy of RSC Group.

The Good Hope Net team uses a recently upgraded cluster system based on 2nd Generation Intel Xeon Scalable processors, which has been deployed by RSC Group, the leading Russian and worldwide well known solution provider for high-performance computing and data storage-on-demand.

The coronavirus pandemic in 2020 threatens lives of many people and hinders economic and social activity in multiple countries all over the world. As a result, it attracted significant attention of many research groups. Finding treatments to prevent and mitigate the negative impact of COVID-19 is the highest priority in the worldwide scientific community now. The international and multidisciplinary The Good Hope Net project takes advantages of the latest advances in experimental physics, chemistry, and biology to investigate the life cycle of the virus and to target specifically its specific proteins.

Sophisticated simulation methods require supercomputing power to study all details of the interaction between the Spike-protein on coronavirus surface and the human protein ACE2 which is known to be the entry point for SARS and SARS-2 coronaviruses. It will help to complete all research stages within a limited amount of time.

International project to fight the global pandemic

“Rapid global spread of COVID-19 coronavirus infection pandemic has shown that there are no clear global emergency response plans against threats to humankind caused by new viruses. One of the obvious shortcomings is the lack of technologies for quick development of medicines for diagnostics and therapy. To help solving this problem, an international team of scientists – from Russia, Finland, Italy and Canada – was formed. We all have different competences, knowledge, skills and resources. Our geographically distributed team includes virologists, biologists, chemists, mathematicians and physical scientists. The international cooperation is extremely important to achieve quick progress and rapidly react to the ever-changing situation with global COVID-19 pandemic. We hope that our research will actually help to fight spread of such infections,” explains Anna Kichkailo, Head of Laboratory For Digital Controlled Drugs and Theranostics at the Krasnoyarsk Federal Science Center of RAS, Head of the Laboratory for Biomolecular and Medical Technology of the V.F. Voyno-Yasenetsky Krasnoyarsk State Medical University.

The Good Hope Net project team consists of:

  • Laboratory for Digital Controlled Drugs and Theranostics and Laboratory of Physics of Magnetic Phenomena, Kirensky Institute of Physics at the Federal Science Center, Siberian Branch of Russian Academy of Sciences (KIP FSC SB RAS, Krasnoyarsk, Russia),
  • Laboratory for Biomolecular and Medical Technology, V.F. Voyno-Yasenetsky Krasnoyarsk State Medical University (KSMU, Krasnoyarsk, Russia) – project coordinator,
  • Laboratory of Chemical Cybernetics, Department of Chemistry at Lomonosov Moscow State University (MSU, Moscow, Russia),
  • Laboratory for Computer Simulation of Biomolecular Systems and Nanomaterials at N. M. Emanuel Institute of Biochemical Physics, Russian Academy of Sciences (IBCP RAS, Moscow, Russia),
  • Organic Synthesis Laboratory, Institute of Chemical Biology and Fundamental Medical Science, Siberian Branch of the Russian Academy of Sciences (ICBFM SB RAS, Novosibirsk, Russia),
  • Nanoscience Center and Department of Chemistry, University of Jyväskylä, Jyväskylä (Finland),
  • Institute for Experimental Endocrinology and Oncology (IEOS), part of National Research Council (CNR), Naples (Italy),
  • Department of Molecular Medicine and Medical Biotechnologies, Department of Pharmacy, Federico II University of Naples (Italy),
  • The Bioanalytical and Molecular Interaction Laboratory, Department of Chemistry and Biomolecular Sciences, University of Ottawa (Canada),
  • The Molecular Science and Biomedicine Laboratory, Hunan University (China),
  • School of Medicine, Institute of Molecular Medicine, Shanghai Jiao Tong University (China),
  • Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian (China).

Computer design of medicine against COVID-19

“We aim to use molecular simulation to create a computer model of a medical drug with selective interaction with receptor-binding domain of Spike protein of SARS-CoV-2 coronavirus strain. The most promising specific binding agents to be used for diagnostics (identification of virus particles in saliva) and development of virus treatment drugs preventing ingress of infection. The results of theoretical calculations and computer simulation will be experimentally tested on proteins, viruses and cells,” summarizes Anna Kichkailo.

Image courtesy of RSC Group.

Supercomputer simulations are used to study details of interaction between Spikeprotein on coronavirus surface and the human protein ACE2 (angiotensin converting enzyme 2). ACE2 is known to be the entry point for SARS and SARS-2 coronaviruses. By blocking its interaction with the spike protein, it is possible to reduce virus activity in human body. Massive molecular dynamics and quantum chemistry calculations of virus and human proteins are using to estimate protein binding energies. The results of simulations will be used to design aptamers that will bind with virus proteins better than ACE2. Molecular docking and molecular dynamics methods will be used to create a library of promising aptamers and to estimate the strength of their interaction with virus proteins. Binding energies for the most promising aptamers will be refined with quantumchemistry methods. A lot of supercomputing resources is required to complete all these research stages within limited amount of time.

The need for supercomputers

Developing drugs to mitigate the disease and reduce the risk of the severe complications is one of the most important tasks before coronavirus vaccine will be widely adopted. Computer simulations deliver valuable information on the viral activity on atomic level and they can be used to predict the efficiency of potential drugs. Such calculations are extremely demanding and can be done only with the most powerful supercomputers.

HPC systems are widely used in simulations of biochemical processes. The simulations help to reduce the number of experiments that would otherwise be needed to get same results. Leading global pharmaceutical and research centers use molecular modeling at the initial steps of drug development, when a massive number of chemical substances have to be investigated for specific activity.

Experimental data about the coronavirus activity on molecular level is very limited and have been produced in vitro. For example, the viral protein structure corresponds tothe crystallized protein and not to a virus in solution. Moreover, there is not enough experimental data on complexes between virus and human proteins or virus proteins and potential drugs. On the other hand, supercomputer calculations can give all the structural data and the details of binding process. Therefore, the computing part is critically important, as well as subsequent experimental verification.

Upgraded MVS-10P OP supercomputer at JSCC RAS

The Joint Supercomputer Center of the Russian Academy of Sciences is one of the most powerful Russian supercomputing centers in the fields of science and education. JSCC RAS staff includes qualified scientists, programmers and engineers. Over 150 groups of researches use JSCC resources for fundamental and applied research tasks. Total peak performance of JSCC RAS computing facilities exceeds 1.3 Petaflops (petaflops – quadrillion of floating-point operations per second, or 1000 teraflops). Five JSCC RAS cluster systems are included in the Top50 list of the most powerful Russian supercomputers.

After the recent upgrade of MVS-10P OP at the end of 2019 completed by the Ministry of Science and Highest Education of the Russian Federation, its peak performance reached 771 Teraflops (teraflops – trillion of floating-point operations per second). Adding a new segment based on the modern high-performance 2nd Generation Intel Xeon Scalable processors allowed to achieve the significant performance increase of y 209 Teraflops. MVS-10P OP is based on RSC Tornado, an universal ultrahigh-dense and energy efficient platform developed by RSC Group (Russia).

“By regularly upgrading JSCC RAS computing resources we get new R&D opportunities, provide RAS and academic researches with powerful resources for various complex fundamental and applied tasks and improve overall efficiency of Russian scientists,” said Gennady Savin, Academician of RAS and Science Head of the Joint Supercomputer Center of the Russian Academy of Sciences.

Researchers access resources of JSCC RAS using the National Research Network (NICS) of the Ministry of Science and Highest Education of the Russian Federation.


Source: RSC Group 

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