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Unlocking the full potential of proteins for medical and industrial applications relies on optimization of properties like thermostability, catalytic activity, and stereoselectivity through protein engineering. Recent work has emphasized the value of a semi-rational approach to protein engineering that combines existing knowledge of protein structure and function with the power of library screening and selection to evaluate large numbers of protein variants. The advent of sophisticated new computational tools and the ever-increasing availability of structural and sequence information have made this strategy increasingly powerful over recent years.
The aim of this symposium is to equip PhD students and postdoctoral researchers in the field of protein engineering with a broad knowledge of computational tools and experimental techniques available for library design and creation. The symposium will focus on cutting-edge techniques for library design, such as machine learning and computational design, as well as new applications of phylogenetic methods (e.g., ancestral protein reconstruction) and computational chemistry.