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Expanding the space of protein geometries by computational design of de novo fold families

By Xingjie Pan, Michael Thompson, Yang Zhang, Lin Liu, James S Fraser, Mark J. S. Kelly, Tanja Kortemme

Posted 15 Apr 2020
bioRxiv DOI: 10.1101/2020.04.14.041772 (published DOI: 10.1126/science.abc0881)

Naturally occurring proteins use a limited set of fold topologies, but vary the precise geometries of structural elements to create distinct shapes optimal for function. Here we present a computational design method termed LUCS that mimics nature's ability to create families of proteins with the same overall fold but precisely tunable geometries. Through near-exhaustive sampling of loop-helix-loop elements, LUCS generates highly diverse geometries encompassing those found in nature but also surpassing known structure space. Biophysical characterization shows that 17 (38%) out of 45 tested LUCS designs were well folded, including 16 with designed non-native geometries. Four experimentally solved structures closely match the designs. LUCS greatly expands the designable structure space and provides a new paradigm for designing proteins with tunable geometries customizable for novel functions. ### Competing Interest Statement The authors have declared no competing interest.

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