Fujitsu to Detect and Analyze New COVID-19 Drugs by Leveraging World’s Fastest Supercomputer
By HospiMedica International staff writers Posted on 24 Jun 2021 |
Illustration
Fujitsu Japan Limited (Tokyo, Japan), along with the Research Center for Advanced Science and Technology (RCAST) at the University of Tokyo (Tokyo, Japan), has initiated a new research project utilizing the world's fastest supercomputer for identifying new COVID-19 therapies.
The research will leverage Fugaku, the world's fastest supercomputer jointly developed by RIKEN and Fujitsu, to identify small molecule inhibitory compounds that can be used as potential drugs in treatments for COVID-19, as well as clarifying the molecular mechanism by which COVID-19 infections are inhibited, leading to the eventual development of small molecule therapeutic drugs. Since 2011, Fujitsu has been engaged in joint research with RCAST on IT drug discovery technologies to create candidate small molecule compounds for anticancer drugs and other therapies. While a number of highly effective vaccines have been successfully developed in response to the spread of the COVID-19 pandemic, the development of effective therapeutic drugs remains an important priority. Based on the fruits of their joint research to date in the field of IT drug discovery technology, Fujitsu and RCAST have decided to embark on a new intensive research project to identify inhibitory compounds that will lead to the development of new coronavirus drugs, leveraging the unparalleled computing power of Fugaku to contribute to this goal.
Since 2011, Fujitsu and RCAST have been conducting joint research on small molecule drugs that are highly likely to be taken orally, are chemically synthesizable, and have low production costs compared to drugs in forms of peptide drugs, antibody drugs, nucleic acid drugs, and cell drugs. With the goal of identifying inhibitory compounds that lead to develop new coronavirus drugs that are effective in small doses and reduce the risk of side effects, molecular simulation technology that is the result of the joint research will be utilized. As it is vital to create a molecular structure that can bind strongly to the viral protein and control its activity, molecular simulation technology and Fugaku will be widely used for tasks including the creation of three-dimensional structural models, clarifying the molecular mechanisms of infection inhibition, and predicting the properties of mutant strains. Going forward, Fujitsu will continue harnessing the power of supercomputers and molecular simulation technologies as it strives to quickly deliver on the promise of potential therapies for COVID-19.
Related Links:
Fujitsu Japan Limited
University of Tokyo
The research will leverage Fugaku, the world's fastest supercomputer jointly developed by RIKEN and Fujitsu, to identify small molecule inhibitory compounds that can be used as potential drugs in treatments for COVID-19, as well as clarifying the molecular mechanism by which COVID-19 infections are inhibited, leading to the eventual development of small molecule therapeutic drugs. Since 2011, Fujitsu has been engaged in joint research with RCAST on IT drug discovery technologies to create candidate small molecule compounds for anticancer drugs and other therapies. While a number of highly effective vaccines have been successfully developed in response to the spread of the COVID-19 pandemic, the development of effective therapeutic drugs remains an important priority. Based on the fruits of their joint research to date in the field of IT drug discovery technology, Fujitsu and RCAST have decided to embark on a new intensive research project to identify inhibitory compounds that will lead to the development of new coronavirus drugs, leveraging the unparalleled computing power of Fugaku to contribute to this goal.
Since 2011, Fujitsu and RCAST have been conducting joint research on small molecule drugs that are highly likely to be taken orally, are chemically synthesizable, and have low production costs compared to drugs in forms of peptide drugs, antibody drugs, nucleic acid drugs, and cell drugs. With the goal of identifying inhibitory compounds that lead to develop new coronavirus drugs that are effective in small doses and reduce the risk of side effects, molecular simulation technology that is the result of the joint research will be utilized. As it is vital to create a molecular structure that can bind strongly to the viral protein and control its activity, molecular simulation technology and Fugaku will be widely used for tasks including the creation of three-dimensional structural models, clarifying the molecular mechanisms of infection inhibition, and predicting the properties of mutant strains. Going forward, Fujitsu will continue harnessing the power of supercomputers and molecular simulation technologies as it strives to quickly deliver on the promise of potential therapies for COVID-19.
Related Links:
Fujitsu Japan Limited
University of Tokyo
Latest COVID-19 News
- Low-Cost System Detects SARS-CoV-2 Virus in Hospital Air Using High-Tech Bubbles
- World's First Inhalable COVID-19 Vaccine Approved in China
- COVID-19 Vaccine Patch Fights SARS-CoV-2 Variants Better than Needles
- Blood Viscosity Testing Can Predict Risk of Death in Hospitalized COVID-19 Patients
- ‘Covid Computer’ Uses AI to Detect COVID-19 from Chest CT Scans
- MRI Lung-Imaging Technique Shows Cause of Long-COVID Symptoms
- Chest CT Scans of COVID-19 Patients Could Help Distinguish Between SARS-CoV-2 Variants
- Specialized MRI Detects Lung Abnormalities in Non-Hospitalized Long COVID Patients
- AI Algorithm Identifies Hospitalized Patients at Highest Risk of Dying From COVID-19
- Sweat Sensor Detects Key Biomarkers That Provide Early Warning of COVID-19 and Flu
- Study Assesses Impact of COVID-19 on Ventilation/Perfusion Scintigraphy
- CT Imaging Study Finds Vaccination Reduces Risk of COVID-19 Associated Pulmonary Embolism
- Third Day in Hospital a ‘Tipping Point’ in Severity of COVID-19 Pneumonia
- Longer Interval Between COVID-19 Vaccines Generates Up to Nine Times as Many Antibodies
- AI Model for Monitoring COVID-19 Predicts Mortality Within First 30 Days of Admission
- AI Predicts COVID Prognosis at Near-Expert Level Based Off CT Scans