DeepMind: against COVID-19 Company
Entity: DeepMind
Category: AI for Drug Discovery
Description: DeepMind is a world leader in artificial intelligence for positive impact.
Project: AlphaFold Algorithm against COVID-19.
Summary: In the wake of a growing number of cases of COVID-19, DeepMind has utilized their AlphaFold algorithm to predict a variety of protein structures associated with COVID-19. Given a sequence of amino acids, the building blocks for proteins, AlphaFold is able to predict a three-dimensional protein structure. Typically, going from a sequence of amino acids to a three-dimensional structure is a long and intensive process, requiring a wide variety of protein visualization techniques and structural analysis such as cryo-electron microscopy, nuclear magnetic resonance, and X-ray crystallography. However, AlphaFold, which recently won the CASP13 competition (Critical Assessment of Techniques for Protein Structure Prediction), bypasses these techniques with a deep neural network that predicts distances and angles between amino acids, scored with gradient descent. It uses free-modeling, which means that it ignores similar structures when making predictions, which is particularly helpful for COVID-19, as few similar protein structures are readily available. After cross-validating their results on the COVID-19 spike protein with the structures determined experimentally by the Francis Crick Institute, DeepMind submitted their predictions for the proteins whose structures are not readily determined. These proteins include the membrane protein, protein 3a, nsp2, nsp4, nsp6, and papain-like C-terminal domain. These protein structures can potentially contain docking sites for new drugs or therapeutics, and were intended to help with future drug development in the efforts to contain COVID-19.
Category: AI for Drug Discovery
Description: DeepMind is a world leader in artificial intelligence for positive impact.
Project: AlphaFold Algorithm against COVID-19.
Summary: In the wake of a growing number of cases of COVID-19, DeepMind has utilized their AlphaFold algorithm to predict a variety of protein structures associated with COVID-19. Given a sequence of amino acids, the building blocks for proteins, AlphaFold is able to predict a three-dimensional protein structure. Typically, going from a sequence of amino acids to a three-dimensional structure is a long and intensive process, requiring a wide variety of protein visualization techniques and structural analysis such as cryo-electron microscopy, nuclear magnetic resonance, and X-ray crystallography. However, AlphaFold, which recently won the CASP13 competition (Critical Assessment of Techniques for Protein Structure Prediction), bypasses these techniques with a deep neural network that predicts distances and angles between amino acids, scored with gradient descent. It uses free-modeling, which means that it ignores similar structures when making predictions, which is particularly helpful for COVID-19, as few similar protein structures are readily available. After cross-validating their results on the COVID-19 spike protein with the structures determined experimentally by the Francis Crick Institute, DeepMind submitted their predictions for the proteins whose structures are not readily determined. These proteins include the membrane protein, protein 3a, nsp2, nsp4, nsp6, and papain-like C-terminal domain. These protein structures can potentially contain docking sites for new drugs or therapeutics, and were intended to help with future drug development in the efforts to contain COVID-19.
Technology:
AI for Drug Discovery
Headquarters:
United Kingdom
Founded Date:
2010
Employees Number:
501-1000
Funding Status:
M&A
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