Peer-Reviewed Publication
Elife2022;11May 5, 2022Journal Article
Heterogeneity of the GFP fitness landscape and data-driven protein design.
Louisa Gonzalez Somermeyer1, Aubin Fleiss2,3, Alexander S Mishin4, Nina G Bozhanova5, Anna A Igolkina6, Jens Meiler5,7, Maria-Elisenda Alaball Pujol2,3, Ekaterina V Putintseva8, Karen S Sarkisyan2,3,4, Fyodor A Kondrashov1,9
1Institute of Science and Technology Austria, Klosterneuburg, Austria.
2Synthetic Biology Group, MRC London Institute of Medical Sciences, London, United Kingdom.
3Institute of Clinical Sciences, Faculty of Medicine and Imperial College Centre for Synthetic Biology, Imperial College London, London, United Kingdom.
4Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russian Federation.
5Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, United States.
6Gregor Mendel Institute, Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria.
7Institute for Drug Discovery, Medical School, Leipzig University, Leipzig, Germany.
8LabGenius, London, United Kingdom.
9Evolutionary and Synthetic Biology Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan.
Abstract
Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad ran…
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