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SUMMARY:From confusion to construction: data-rich protein engineering - Fl
 orian Hollfelder - University of Cambridge
DTSTART:20251009T140000Z
DTEND:20251009T150000Z
UID:TALK238066@talks.cam.ac.uk
CONTACT:90994
DESCRIPTION:Functional proteins for a variety of useful applications\, as 
 binders and catalysts\, are required\, but currently not known. Functional
  metagenomics and directed evolution promise access to such new proteins\,
  but the chances of finding them are low. Therefore high-throughput techno
 logies are crucial to beat the odds:  screening in picoliter water-in–oi
 l emulsion droplets produced at kHz rates in microfluidic devices allow sc
 reening of >10e7 clones and permit successful selections. While much faste
 r than traditional screening approaches\, the vastness of sequence space (
 and the scarcity of ‘solutions’ in it) require strategies for the iden
 tification and interconversion of enzymes. \nDecoding the selected clones 
 by short or long-read sequencing methods leads to large sequence-function 
 datasets that may allow extrapolation from experimental directed evolution
  to further improved mutants beyond the observed hits. We will introduce e
 xperimental approaches for drawing up ‘fitness landscapes’ that illust
 rate trajectories in sequence space. Starting with large datasets harveste
 d from droplet microfluidics\, this information is used for AI/ML-assisted
  enzyme engineering\, allowing meaningful predictions that accelerate bioc
 atalyst engineering and leveraging the synergy of experimental and in sili
 co approaches. 
LOCATION:Jean Thomas Lecture theatre\, Sanger Building\, Tennis Court Road
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