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Title: Rationally seeded computational protein design of ɑ-helical barrels
Abstract Computational protein design is advancing rapidly. Here we describe efficient routes starting from validated parallel and antiparallel peptide assemblies to design two families of α-helical barrel proteins with central channels that bind small molecules. Computational designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides, and adjacent helices are connected by loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix–turn–helix–turn–helix motifs that are packed onto the barrels. Throughout these computational pipelines, residues that define open states of the barrels are maintained. This minimizes sequence sampling, accelerating the design process. For each of six targets, just two to six synthetic genes are made for expression inEscherichia coli. On average, 70% of these genes express to give soluble monomeric proteins that are fully characterized, including high-resolution structures for most targets that match the design models with high accuracy.  more » « less
Award ID(s):
2019598
PAR ID:
10621826
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ;
Publisher / Repository:
Nature Chemical Biology
Date Published:
Journal Name:
Nature Chemical Biology
Volume:
20
Issue:
8
ISSN:
1552-4450
Page Range / eLocation ID:
991 to 999
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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