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How Open Science Can Help Researchers Prepare for the Next Pandemic
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When COVID-19 emerged, scientists had a crucial advantage: Decades of prior research on coronaviruses meant they understood the virus’ key proteins well enough to design vaccines in record time.
Key facts
- The collaboration spans the Coalition for Epidemic Preparedness Innovations, EMBL-EBI, Google DeepMind, NVIDIA, Seoul National University, Sungkyunkwan University, the Swiss Institute
- Understanding the 3D structure of the COVID-19 virus’ spike protein, for example, proved foundational to vaccine design
- About 30% of the protein interactions being added to the database are completely new to science, showing interaction shapes that have never been documented in the Protein Data Bank, the main
- When COVID-19 emerged, scientists had a crucial advantage: Decades of prior research on coronaviruses meant they understood the virus’ key proteins well enough to design vaccines in record time
Summary
To help improve the odds, NVIDIA has joined a coalition of global research organizations, including Google DeepMind and the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI), to release predicted 3D structures for the protein complexes of more than 2,800 viruses, openly available to any scientist, anywhere, through the AlphaFold Database. The structures in the newly released dataset were inferred using AlphaFold2, Google DeepMind’s AI model for predicting how proteins fold into 3D shapes, with optimization from NVIDIA BioNeMo Inference Runtime. “Our ambition with the AlphaFold Database has always been to democratize access to foundational biology at scale,” said Risha Patel, life sciences partnerships manager at Google DeepMind.