Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition
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- 作者：Christian Reichen1 ; Simon Hansen1 ; Cristina Forzani1 ; Annemarie Honegger1 ; Sarel J. Fleishman2 ; 4 ; Ting Zhou1 ; Fabio Parmeggiani1 ; Patrick Ernst1 ; Chaithanya Madhurantakam1 ; Christina Ewald3 ; Peer R.E. Mittl1 ; Oliver Zerbe3 ; David Baker2 ; Amedeo Caflisch1 ; Andreas Plü ; ckthun1 ; plueckthun@bioc.uzh.ch" class="auth_mail" title="E-mail the corresponding author
- 关键词：ArmRP ; armadillo repeat protein ; ANS ; 1-anilino-8-naphthalene-sulfonate ; dArmRP ; computationally designed armadillo repeat protein ; cArmRP ; consensus armadillo repeat protein ; CAR0 ; computationally designed ArmRP version 0 ; nArmRP ; natural armadillo repeat protein ; MALS ; multi-angle light scattering ; MD ; molecular dynamics ; MRE ; mean residue ellipticity ; NLS ; nuclear localization sequence ; PDB ; Protein Data Bank ; PEG ; polyethylene glycol ; RMSF ; root mean square fluctuation ; SEC ; size-exclusion c
- 刊名：Journal of Molecular Biology
- 出版年：2016
- 出版时间：6 November 2016
- 年：2016
- 卷：428
- 期：22
- 页码：4467-4489
- 全文大小：2896 K
文摘
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Today, binding proteins must be generated for every target individually.
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A modular binder for peptides would allow sequence recognition from premade units.
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ArmRPs were computationally designed, and binding pockets were added.
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Crystal structures showed successful modular binding of the expected peptide.
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Low nanomolar affinities to the expected peptides were measured