3RFN

Epitope backbone grafting by computational design for improved presentation of linear epitopes on scaffold proteins


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.80 Å
  • R-Value Free: 0.237 
  • R-Value Work: 0.219 
  • R-Value Observed: 0.219 

wwPDB Validation   3D Report Full Report


This is version 1.4 of the entry. See complete history


Literature

Computational design of high-affinity epitope scaffolds by backbone grafting of a linear epitope.

Azoitei, M.L.Ban, Y.E.Julien, J.P.Bryson, S.Schroeter, A.Kalyuzhniy, O.Porter, J.R.Adachi, Y.Baker, D.Pai, E.F.Schief, W.R.

(2012) J Mol Biol 415: 175-192

  • DOI: https://doi.org/10.1016/j.jmb.2011.10.003
  • Primary Citation of Related Structures:  
    3RFN, 3RHU, 3RI0, 3RIJ

  • PubMed Abstract: 

    Computational grafting of functional motifs onto scaffold proteins is a promising way to engineer novel proteins with pre-specified functionalities. Typically, protein grafting involves the transplantation of protein side chains from a functional motif onto structurally homologous regions of scaffold proteins. Using this approach, we previously transplanted the human immunodeficiency virus 2F5 and 4E10 epitopes onto heterologous proteins to design novel "epitope-scaffold" antigens. However, side-chain grafting is limited by the availability of scaffolds with compatible backbone for a given epitope structure and offers no route to modify backbone structure to improve mimicry or binding affinity. To address this, we report here a new and more aggressive computational method-backbone grafting of linear motifs-that transplants the backbone and side chains of linear functional motifs onto scaffold proteins. To test this method, we first used side-chain grafting to design new 2F5 epitope scaffolds with improved biophysical characteristics. We then independently transplanted the 2F5 epitope onto three of the same parent scaffolds using the newly developed backbone grafting procedure. Crystal structures of side-chain and backbone grafting designs showed close agreement with both the computational models and the desired epitope structure. In two cases, backbone grafting scaffolds bound antibody 2F5 with 30- and 9-fold higher affinity than corresponding side-chain grafting designs. These results demonstrate that flexible backbone methods for epitope grafting can significantly improve binding affinities over those achieved by fixed backbone methods alone. Backbone grafting of linear motifs is a general method to transplant functional motifs when backbone remodeling of the target scaffold is necessary.


  • Organizational Affiliation

    Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.


Macromolecules
Find similar proteins by:  (by identity cutoff)  |  3D Structure
Entity ID: 1
MoleculeChains Sequence LengthOrganismDetailsImage
BB_1wnu_001159Pyrococcus horikoshii OT3Mutation(s): 4 
Gene Names: alaXSPH0574
UniProt
Find proteins for O58307 (Pyrococcus horikoshii (strain ATCC 700860 / DSM 12428 / JCM 9974 / NBRC 100139 / OT-3))
Explore O58307 
Go to UniProtKB:  O58307
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
UniProt GroupO58307
Sequence Annotations
Expand
  • Reference Sequence
Small Molecules
Ligands 1 Unique
IDChains Name / Formula / InChI Key2D Diagram3D Interactions
ZN
Query on ZN

Download Ideal Coordinates CCD File 
B [auth A]ZINC ION
Zn
PTFCDOFLOPIGGS-UHFFFAOYSA-N
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.80 Å
  • R-Value Free: 0.237 
  • R-Value Work: 0.219 
  • R-Value Observed: 0.219 
  • Space Group: C 1 2 1
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 93.8α = 90
b = 36.1β = 99.4
c = 46.3γ = 90
Software Package:
Software NamePurpose
MAR345dtbdata collection
MOLREPphasing
CNSrefinement
HKL-2000data reduction
HKL-2000data scaling

Structure Validation

View Full Validation Report



Entry History 

Deposition Data

Revision History  (Full details and data files)

  • Version 1.0: 2011-11-09
    Type: Initial release
  • Version 1.1: 2011-11-23
    Changes: Database references
  • Version 1.2: 2012-01-18
    Changes: Database references
  • Version 1.3: 2017-07-26
    Changes: Refinement description, Source and taxonomy
  • Version 1.4: 2023-09-13
    Changes: Data collection, Database references, Derived calculations, Refinement description