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Inside Back Cover: Co‐Evolutionary Fitness Landscapes for Sequence Design (Angew. Chem. Int. Ed. 20/2018)
Author(s) -
Tian Pengfei,
Louis John M.,
Baber James L.,
Aniana Annie,
Best Robert B.
Publication year - 2018
Publication title -
angewandte chemie international edition
Language(s) - English
Resource type - Reports
SCImago Journal Rank - 5.831
H-Index - 550
eISSN - 1521-3773
pISSN - 1433-7851
DOI - 10.1002/anie.201803004
Subject(s) - cover (algebra) , fitness landscape , sequence (biology) , series (stratigraphy) , evolutionary algorithm , computational biology , computer science , evolutionary biology , biology , genetics , artificial intelligence , engineering , sociology , paleontology , mechanical engineering , population , demography
Evolutionary information about structural and functional constraints on proteins can be mined from genome sequences. In their Communication on page 5674 ff., R. B. Best and co‐workers report a series of stable and functional sequences for three different protein folds that is created by applying a protein co‐evolutionary fitness landscape. Co‐evolutionary information extracted by direct coupling analysis can be an effective guide for rational protein engineering. Graphic credit: Catherine Hefferan.