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SUMMARY:Protein structure\, dynamics\, and assembly through the lens of th
 e computational microscope
DTSTART:20230525T150000
DTSTAMP:20260501T160523Z
UID:870cb7f800c5e606b0b414c83a56f92086b57233adae0cae8f88663e
CATEGORIES:Conferences - Seminars
DESCRIPTION:Matteo Degiacomi - Durham University\nAny organism\, from a si
 mple bacterium up to a human body\, contains millions of proteins with rol
 es as diverse as sensing\, transport\, defense\, motility or structural su
 pport. Proteins have characteristic three-dimensional shapes enabling them
  to interact with designated binding partners (e.g. DNA\, drugs or other p
 roteins). These interactions are key for life\, making their atomic-level 
 characterization crucial to understand illnesses and inform the design of 
 new therapies. No biomolecule should be considered as a single atomic arra
 ngement though\, as biological function often emerges from specific confor
 mational dynamics. Ideally\, a full understanding of any protein (mal)func
 tion would require accurate knowledge of its whole conformational space in
  both the absence and presence of its binding partners. Existing experimen
 tal techniques cannot typically fully meet this need though. I will discus
 s molecular modelling and simulations techniques developed by my lab to he
 lp address this knowledge gap. I will focus on the common problem of predi
 cting how flexible proteins assemble into complexes\, and how machine lear
 ning can be used to predict how proteins move.\n 
LOCATION:SV 1717 https://plan.epfl.ch/?room==SV%201717
STATUS:CONFIRMED
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