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

• Published in: Science (American Association for the Advancement of Science) Vol. 369; no. 6507; pp. 1132 - 1136
• Main Authors: Pan, Xingjie, Thompson, Michael C, Zhang, Yang, Liu, Lin, Fraser, James S, Kelly, Mark J S, Kortemme, Tanja
• Format: Journal Article
• Language: English
• Published: United States The American Association for the Advancement of Science 28-08-2020
• Subjects: Combinatorial analysis; Computer applications; Computer-Aided Design; Custom design; Landscape design; Protein Engineering - methods; Protein Folding; Protein Structure, Secondary; Proteins; Sampling; Structural analysis; Structural Elements (Construction); Structural members; Topology
• ISSN: 0036-8075; 1095-9203
• DOI: 10.1126/science.abc0881

Naturally occurring proteins vary the precise geometries of structural elements to create distinct shapes optimal for function. We present a computational design method, loop-helix-loop unit combinatorial sampling (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 showed that 17 (38%) of 45 tested LUCS designs encompassing two different structural topologies were well folded, including 16 with designed non-native geometries. Four experimentally solved structures closely matched the designs. LUCS greatly expands the designable structure space and offers a new paradigm for designing proteins with tunable geometries that may be customizable for novel functions.