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DESCRIPTION:This webinar is by the ELIXIR 3D-BioInfo\, chaired by Dr. Anas
 tassia Andreevna Vorobieva with two presentations:\n\n\n	\n		\n			\n			\n	
 	\n		\n			\n				    Dr. Charlotte Miton\n\n				    Michael Smith Lab
 oratories\,  \n					    University of British Columbia\,\n					   
  Canada\n\n				Title: Causes and Consequences of Epistasis in Protein Evol
 ution and Design\n			\n			\n				    Dr. Possu Huang\n\n				    Stanf
 ord University\n					\n					 \n\n				Title: Protein Design for Epitope-sp
 ecific Molecular Recognition\n			\n		\n	\n\n\nAbstract: Causes and Consequ
 ences of Epistasis in Protein Evolution and Design\n\nProteins are complex
  molecular machines\, composed of highly interconnected amino acid network
 s. Protein evolution may require the alteration of these intramolecular ne
 tworks\, to foster novel functions. While there have been considerable adv
 ances\, our ability to optimize protein functions in the laboratory remain
 s limited. One reason for these shortcomings may be the cryptic role playe
 d by epistasis\, i.e.\, the dependency of mutational effects on the genet
 ic context\, during the rewiring of intramolecular networks. By permitting
  or restricting access to certain mutations over the course of evolution\,
  epistasis shapes evolutionary pathways\, influencing outcomes. Decipherin
 g its biophysical basis is essential if we wish to understand\, predict an
 d design proteins.\n	In this talk\, I will discuss various molecular and b
 iophysical origins of mutational epistasis\, and illustrate how this pheno
 menon can lead to the bifurcation of evolutionary pathways\, in which two 
 trajectories segregate and become incompatible over time. Our results illu
 minate how rapidly\, but gradually\, distinct molecular outcomes can arise
  in nature and the laboratory.\n\nAbstract: Protein Design for Epitope-spe
 cific Molecular Recognition\n\nThe growing need for antibodies with custom
 ized specificity provides a rich environment for engineering efforts. In r
 ecent years\, despite having streamlined experimental pipelines\, the fund
 amental math requiring extensive libraries and screen campaigns to get an 
 initial binding signal remains unchanged. A major advancement would be to 
 directly design in silico an epitope-specific binder from scratch\, prov
 iding a signal for potential optimization by artificial evolution. We have
  observed several key advantages in neural network approaches over existin
 g methods. By leveraging the unique properties of generative neural networ
 ks\, we developed a model for immunoglobulin 3D structures\, with which di
 verse structures can be modeled with unprecedented speed. We extended it t
 o a purely deep learning-based protein-protein interface design pipeline t
 hat optimize not only spatial orientations but fully-flexible protein stru
 ctures on the fly to desired epitopes. This novel strategy explores neural
  network’s capabilities in modeling dynamic structures\, and preliminary
  experimental results on multiple targets support the plausibility of in s
 ilico design of epitope-specific antibodies.\n\nPrevious webinars from the
  ELIXIR 3D-BioInfo Community:\n\n\n	Computer Aided Drug Design (CADD) \n	P
 rotein Engineering \n	Nucleic Acid Tools\n\n\nFor more information on the
  ELIXIR 3D-BioInfo Community: link \n\n 
SUMMARY:3D-BioInfo Webinar on Protein Design and Evolution
URL;VALUE=URI:https://www.elixir-europe.org/events/3d-bioinfo-webinar-prote
 in-design-and-evolution
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