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Publication Abstract from PubMed

Armadillo repeat proteins (ArmRP) recognize their target peptide in extended conformation and bind, in a first approximation, two residues per repeat. They may thus form the basis for building a modular system, in which each repeat is complementary to a piece of the target peptide. Accordingly, preselected repeats could be assembled into specific binding proteins on demand and thereby avoid the traditional generation of every new binding molecule by an independent selection from a library. Stacked armadillo repeats, each consisting of 42 amino acids arranged in three alpha-helices, build an elongated superhelical structure. Here, we analyzed curvature variations in natural ArmRPs, and identified a repeat pair from yeast importin-alpha as having the optimal curvature geometry to be complementary to a peptide over its whole length. We employed a symmetric in silico design to obtain a uniform sequence for a stackable repeat while maintaining the desired curvature geometry. Computationally designed armadillo repeat proteins (dArmRPs) had to be stabilized by mutations to remove regions of higher flexibility, which were identified by molecular dynamics (MD) simulations in explicit solvent. Using an N-capping repeat from the consensus-design approach, two different crystal structures of dArmRP were determined. Although the experimental structures of dArmRP deviated from the designed curvature, the insertion of the most conserved binding pockets of natural ArmRPs onto the surface of dArmRPs resulted in binders against the expected peptide with low nanomolar affinities, similar to the binders from the consensus-design series.

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition.,Reichen C, Hansen S, Forzani C, Honegger A, Fleishman SJ, Zhou T, Parmeggiani F, Ernst P, Madhurantakam C, Ewald C, Mittl PR, Zerbe O, Baker D, Caflisch A, Pluckthun A J Mol Biol. 2016 Sep 21. pii: S0022-2836(16)30376-X. doi:, 10.1016/j.jmb.2016.09.012. PMID:27664438^[1]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.