5N7W

Computationally designed functional antibody


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.96 Å
  • R-Value Free: 0.250 
  • R-Value Work: 0.199 
  • R-Value Observed: 0.202 

wwPDB Validation 3D Report Full Report


This is version 1.2 of the entry. See complete history


Literature

Computational Design of Epitope-Specific Functional Antibodies.

Nimrod, G.Fischman, S.Austin, M.Herman, A.Keyes, F.Leiderman, O.Hargreaves, D.Strajbl, M.Breed, J.Klompus, S.Minton, K.Spooner, J.Buchanan, A.Vaughan, T.J.Ofran, Y.

(2018) Cell Rep 25: 2121-2131.e5

  • DOI: 10.1016/j.celrep.2018.10.081
  • Structures With Same Primary Citation

  • PubMed Abstract: 
  • The ultimate goal of protein design is to introduce new biological activity. We propose a computational approach for designing functional antibodies by focusing on functional epitopes, integrating large-scale statistical analysis with multiple struct ...

    The ultimate goal of protein design is to introduce new biological activity. We propose a computational approach for designing functional antibodies by focusing on functional epitopes, integrating large-scale statistical analysis with multiple structural models. Machine learning is used to analyze these models and predict specific residue-residue contacts. We use this approach to design a functional antibody to counter the proinflammatory effect of the cytokine interleukin-17A (IL-17A). X-ray crystallography confirms that the designed antibody binds the targeted epitope and the interaction is mediated by the designed contacts. Cell-based assays confirm that the antibody is functional. Importantly, this approach does not rely on a high-quality 3D model of the designed complex or even a solved structure of the target. As demonstrated here, this approach can be used to design biologically active antibodies, removing some of the main hurdles in antibody design and in drug discovery.


    Organizational Affiliation

    Biolojic Design, Ltd., 12 Hamada Street, Rehovot 7670314, Israel; The Goodman Faculty of Life Sciences, Nanotechnology Building, Bar Ilan University, Ramat Gan 52900, Israel. Electronic address: yanay@ofranlab.org.



Macromolecules

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Entity ID: 1
MoleculeChainsSequence LengthOrganismDetails
Antibody Fragment Heavy ChainA, H224Homo sapiensMutation(s): 0 
Protein Feature View
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  • Reference Sequence

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Entity ID: 2
MoleculeChainsSequence LengthOrganismDetails
Antibody Fragment Light ChainB, L214Homo sapiensMutation(s): 0 
Protein Feature View
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  • Reference Sequence

Find similar proteins by: Sequence  |  Structure

Entity ID: 3
MoleculeChainsSequence LengthOrganismDetails
Interleukin-17AX, Y155Homo sapiensMutation(s): 0 
Gene Names: IL17ACTLA8IL17
Find proteins for Q16552 (Homo sapiens)
Explore Q16552 
Go to UniProtKB:  Q16552
NIH Common Fund Data Resources
PHAROS  Q16552
Protein Feature View
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  • Reference Sequence
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.96 Å
  • R-Value Free: 0.250 
  • R-Value Work: 0.199 
  • R-Value Observed: 0.202 
  • Space Group: P 1 21 1
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 42.24α = 90
b = 199.98β = 96.42
c = 76.35γ = 90
Software Package:
Software NamePurpose
REFMACrefinement
xia2data reduction
Aimlessdata scaling
PHASERphasing

Structure Validation

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Entry History 

Deposition Data

Revision History 

  • Version 1.0: 2018-11-14
    Type: Initial release
  • Version 1.1: 2018-11-21
    Changes: Data collection, Database references
  • Version 1.2: 2018-12-05
    Changes: Data collection, Database references