Literature DB >> 19324053

Energy-based analysis and prediction of the orientation between light- and heavy-chain antibody variable domains.

Arjun Narayanan1, Benjamin D Sellers, Matthew P Jacobson.   

Abstract

Diversity in antibody structure is crucial to the ability of the adaptive immune system to recognize the tremendously diverse set of potential antigens. The diversity in structure is most apparent in the six hypervariable loops of the complementarity-determining regions. However, given that these loops occur at the interface of the heavy- and light-chain variable domains and form the antigen-binding site, the relative orientation of the heavy- and light-chain variable domains can create another source of structural diversity leading to changes in antigen binding. Here, we first reexamine the diversity of V(L):V(H) orientations in existing antibody crystal structures using 153 nonredundant sequences, demonstrating that the variation in V(L):V(H) orientation is greater than that expected from effects of crystal packing, antigen binding, or the presence of antibody constant regions and increases, on average, as sequence similarity decreases for residues in the interface between the domains. We developed a tool for predicting the relative orientations of the heavy- and light-chain variable domains using side-chain rotamer sampling in the interface and molecular-mechanics-based energy calculations. When using variable domain backbones from the crystal structures, the predicted orientation is very close (<1 A RMSD) to the crystallographically observed orientation in most cases, confirming that the V(L):V(H) orientation is determined by the antibody sequence and suggesting an approach to predicting the relative orientation of the variable domains when building homology models of antibodies. When applied to antibody homology models generated from templates with 55-75% sequence identity, we predict the V(L):V(H) orientation of 20 antibodies with an average/median RMSD of 2.1/1.6 A to the crystal structures.

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Year:  2009        PMID: 19324053     DOI: 10.1016/j.jmb.2009.03.043

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  16 in total

1.  Antigen recognition by antibody C836 through adjustment of V(L)/V(H) packing.

Authors:  Alexey Teplyakov; Galina Obmolova; Thomas Malia; Gary Gilliland
Journal:  Acta Crystallogr Sect F Struct Biol Cryst Commun       Date:  2011-09-24

2.  IBC's 22nd Annual Antibody Engineering and 9th Annual Antibody Therapeutics International Conferences and the 2011 Annual Meeting of The Antibody Society, December 5-8, 2011, San Diego, CA.

Authors:  Johan Nilvebrant; D Cameron Dunlop; Aroop Sircar; Thierry Wurch; Emilia Falkowska; Janice M Reichert; Gustavo Helguera; Emily C Piccione; Simon Brack; Sven Berger
Journal:  MAbs       Date:  2012-03-01       Impact factor: 5.857

3.  Immobilized antibody orientation analysis using secondary ion mass spectrometry and fluorescence imaging of affinity-generated patterns.

Authors:  Fang Liu; Manish Dubey; Hironobu Takahashi; David G Castner; David W Grainger
Journal:  Anal Chem       Date:  2010-04-01       Impact factor: 6.986

4.  Antibody humanization by structure-based computational protein design.

Authors:  Yoonjoo Choi; Casey Hua; Charles L Sentman; Margaret E Ackerman; Chris Bailey-Kellogg
Journal:  MAbs       Date:  2015-08-07       Impact factor: 5.857

5.  Affinity maturation in an HIV broadly neutralizing B-cell lineage through reorientation of variable domains.

Authors:  Daniela Fera; Aaron G Schmidt; Barton F Haynes; Feng Gao; Hua-Xin Liao; Thomas B Kepler; Stephen C Harrison
Journal:  Proc Natl Acad Sci U S A       Date:  2014-06-30       Impact factor: 11.205

6.  Shape complementarity and hydrogen bond preferences in protein-protein interfaces: implications for antibody modeling and protein-protein docking.

Authors:  Daisuke Kuroda; Jeffrey J Gray
Journal:  Bioinformatics       Date:  2016-04-19       Impact factor: 6.937

Review 7.  Computer-aided antibody design.

Authors:  Daisuke Kuroda; Hiroki Shirai; Matthew P Jacobson; Haruki Nakamura
Journal:  Protein Eng Des Sel       Date:  2012-06-02       Impact factor: 1.650

8.  The association of heavy and light chain variable domains in antibodies: implications for antigen specificity.

Authors:  Anna Chailyan; Paolo Marcatili; Anna Tramontano
Journal:  FEBS J       Date:  2011-06-28       Impact factor: 5.542

9.  Redistribution of flexibility in stabilizing antibody fragment mutants follows Le Châtelier's principle.

Authors:  Tong Li; Malgorzata B Tracka; Shahid Uddin; Jose Casas-Finet; Donald J Jacobs; Dennis R Livesay
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

10.  SnugDock: paratope structural optimization during antibody-antigen docking compensates for errors in antibody homology models.

Authors:  Aroop Sircar; Jeffrey J Gray
Journal:  PLoS Comput Biol       Date:  2010-01-22       Impact factor: 4.475

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