6GC2 | pdb_00006gc2

AbLIFT: Antibody stability and affinity optimization by computational design of the variable light-heavy chain interface


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.55 Å
  • R-Value Free: 
    0.261 (Depositor), 0.259 (DCC) 
  • R-Value Work: 
    0.193 (Depositor), 0.197 (DCC) 
  • R-Value Observed: 
    0.196 (Depositor) 

Starting Model: experimental
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wwPDB Validation 3D Report Full Report

Validation slider image for 6GC2

This is version 1.4 of the entry. See complete history

Literature

Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces.

Warszawski, S.Katz, A.B.Lipsh, R.Khmelnitsky, L.Ben Nissan, G.Javitt, G.Dym, O.Unger, T.Knop, O.Albeck, S.Diskin, R.Fass, D.Sharon, M.Fleishman, S.J.

(2019) PLoS Comput Biol 15: e1007207-e1007207

  • DOI: https://doi.org/10.1371/journal.pcbi.1007207
  • Primary Citation Related Structures: 
    6GC2

  • PubMed Abstract: 

    Antibodies developed for research and clinical applications may exhibit suboptimal stability, expressibility, or affinity. Existing optimization strategies focus on surface mutations, whereas natural affinity maturation also introduces mutations in the antibody core, simultaneously improving stability and affinity. To systematically map the mutational tolerance of an antibody variable fragment (Fv), we performed yeast display and applied deep mutational scanning to an anti-lysozyme antibody and found that many of the affinity-enhancing mutations clustered at the variable light-heavy chain interface, within the antibody core. Rosetta design combined enhancing mutations, yielding a variant with tenfold higher affinity and substantially improved stability. To make this approach broadly accessible, we developed AbLIFT, an automated web server that designs multipoint core mutations to improve contacts between specific Fv light and heavy chains (http://AbLIFT.weizmann.ac.il). We applied AbLIFT to two unrelated antibodies targeting the human antigens VEGF and QSOX1. Strikingly, the designs improved stability, affinity, and expression yields. The results provide proof-of-principle for bypassing laborious cycles of antibody engineering through automated computational affinity and stability design.


  • Organizational Affiliation
    • Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.

Macromolecule Content 

  • Total Structure Weight: 51.74 kDa 
  • Atom Count: 3,392 
  • Modeled Residue Count: 427 
  • Deposited Residue Count: 479 
  • Unique protein chains: 2

Macromolecules

Find similar proteins by:|  3D Structure
Entity ID: 1
MoleculeChains  Sequence LengthOrganismDetailsImage
Light ChainA [auth L]252Homo sapiensMutation(s): 0 
Find similar proteins by:|  3D Structure
Entity ID: 2
MoleculeChains  Sequence LengthOrganismDetailsImage
Heavy chainB [auth H]227Homo sapiensMutation(s): 0 

Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 2.55 Å
  • R-Value Free:  0.261 (Depositor), 0.259 (DCC) 
  • R-Value Work:  0.193 (Depositor), 0.197 (DCC) 
  • R-Value Observed: 0.196 (Depositor) 
Space Group: P 2 21 21
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 46.51α = 90
b = 75.81β = 90
c = 135.29γ = 90
Software Package:
Software NamePurpose
PHENIXrefinement
MOSFLMdata reduction
SCALAdata scaling
PHASERphasing

Structure Validation

View Full Validation Report



Entry History 

Revision History  (Full details and data files)

  • Version 1.0: 2019-05-01
    Type: Initial release
  • Version 1.1: 2019-06-19
    Changes: Data collection, Database references, Source and taxonomy
  • Version 1.2: 2019-09-04
    Changes: Data collection, Database references
  • Version 1.3: 2024-01-17
    Changes: Data collection, Database references, Refinement description
  • Version 1.4: 2024-10-09
    Changes: Structure summary