Beyond AlphaFold: achieving new levels of protein performance through direct function prediction

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Find out how deep learning is allowing us to design optimized protein sequences to perform beyond those found in nature.

This achievement offers the promise of developing medicines, materials, and catalysts that deliver new levels of performance to solve some of humanity's biggest challenges.

Proteins are nature’s catalytic and functional materials. Their application in medicines, and as industrial catalysts and novel materials, often requires functional properties beyond those designed by nature.

There has been much research in this area recently, and some amazing breakthroughs by DeepMind's AlphaFold2 in predicting protein structure. However, protein structure is not the end goal of this research, but rather the ability to predict and also to optimize how well a protein will perform at a given task.

We'll present our work to combine deep learning, public data sources, and unique bio-engineering laboratory work to develop high-performance proteins.

Date | 12-16 April 2021
Time | on-demand
Track | Healthcare

  • Tim Ensor, Director of AI, Cambridge Consultants
  • Ian Taylor, Principal Scientist Bioinnovation, Cambridge Consultants
  • Russell Maguire, AI Engineer, Cambridge Consultants


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