Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition.
Armadillo repeat proteins (ArmRPs) recognize their target peptide in extended conformation and bind, in a first approximation, two residues per repeat. Thus, they may 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 aa arranged in three α-helices, build an elongated superhelical structure. Here, we analyzed the curvature variations in natural ArmRPs and identified a repeat pair from yeast importin-α as having the optimal curvature geometry that is 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 ArmRPs (dArmRPs) had to be stabilized by mutations to remove regions of higher flexibility, which were identified by molecular dynamics 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.
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Christian
C
Reichen
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Simon
S
Hansen
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Cristina
C
Forzani
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Annemarie
A
Honegger
Department of Biochemistry, University of Washington, Seattle 98195, WA, USA.
Sarel J
SJ
Fleishman
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Ting
T
Zhou
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Fabio
F
Parmeggiani
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Patrick
P
Ernst
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Chaithanya
C
Madhurantakam
Department of Chemistry, University of Zurich, 8057 Zurich, Switzerland.
Christina
C
Ewald
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Peer R E
PRE
Mittl
Department of Chemistry, University of Zurich, 8057 Zurich, Switzerland.
Oliver
O
Zerbe
Department of Biochemistry, University of Washington, Seattle 98195, WA, USA.
David
D
Baker
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland.
Amedeo
A
Caflisch
Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland. Electronic address: plueckthun@bioc.uzh.ch.
Andreas
A
Plückthun
D051186:Armadillo Domain Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism*; D018360:Crystallography, X-Ray; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D011487:Protein Conformation; D011994:Recombinant Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism*
D051186:Armadillo Domain Proteins; D011994:Recombinant Proteins
Rosetta; armadillo repeat protein; computational protein design; molecular dynamics; peptide binding