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SUMMARY:Enzyme function discovery: tactics\, lessons\, and prospects. - Lu
 iz Carvalho
DTSTART:20250909T100000Z
DTEND:20250909T110000Z
UID:TALK235606@talks.cam.ac.uk
CONTACT:90994
DESCRIPTION:In the post-genomic era\, genome sequencing has rapidly advanc
 ed\, but our ability to assign functions to genes—especially enzymes—l
 ags behind. Many enzymes remain uncharacterized or misannotated\, limiting
  our understanding of metabolism and biology. Enzymes drive essential chem
 ical reactions in cells\, but identifying their specific roles\, including
  substrates\, products\, and biological context\, remains a major challeng
 e. While bioinformatics tools can predict functions based on sequence simi
 larity\, they often fail for enzymes without known homologs. Structural an
 d machine learning approaches also struggle with the complexity of enzyme 
 chemistry. Experimental techniques\, particularly high-resolution mass spe
 ctrometry\, have become vital for discovering new enzymatic activities by 
 directly detecting substrates\, intermediates\, and products. Accurate enz
 yme annotation is crucial not only for advancing basic science but also fo
 r enabling progress in drug development\, biotechnology\, and synthetic bi
 ology.
LOCATION:Department of Biochemistry\, Hopkins Building\, Colman Library
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