Modeling Antibody-Antigen Complexes by Information-Driven Docking

Francesco Ambrosetti; Brian Jiménez-García; Jorge Roel-Touris; Alexandre M J J Bonvin

doi:10.1016/j.str.2019.10.011

Modeling Antibody-Antigen Complexes by Information-Driven Docking

Francesco Ambrosetti, Brian Jiménez-García, Jorge Roel-Touris, Alexandre M J J Bonvin

extern

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Antibodies are Y-shaped proteins essential for immune response. Their capability to recognize antigens with high specificity makes them excellent therapeutic targets. Understanding the structural basis of antibody-antigen interactions is therefore crucial for improving our ability to design efficient biological drugs. Computational approaches such as molecular docking are providing a valuable and fast alternative to experimental structural characterization for these complexes. We investigate here how information about complementarity-determining regions and binding epitopes can be used to drive the modeling process, and present a comparative study of four different docking software suites (ClusPro, LightDock, ZDOCK, and HADDOCK) providing specific options for antibody-antigen modeling. Their performance on a dataset of 16 complexes is reported. HADDOCK, which includes information to drive the docking, is shown to perform best in terms of both success rate and quality of the generated models in both the presence and absence of information about the epitope on the antigen.

Original language	English
Pages (from-to)	119-129.e2
Journal	Structure with Folding & design
Volume	28
Issue number	1
DOIs	https://doi.org/10.1016/j.str.2019.10.011
Publication status	Published - 7 Jan 2020

Keywords

ClusPro
H3 modeling
HADDOCK
LightDock
ZDOCK
antibody
binding sites
conformational changes
docking

Access to Document

10.1016/j.str.2019.10.011

1-s2.0-S0969212619303521-mainFinal published version, 3.24 MBLicence: Taverne

Cite this

@article{bc423aceab6649e79a3bc063f1c1ea45,

title = "Modeling Antibody-Antigen Complexes by Information-Driven Docking",

abstract = "Antibodies are Y-shaped proteins essential for immune response. Their capability to recognize antigens with high specificity makes them excellent therapeutic targets. Understanding the structural basis of antibody-antigen interactions is therefore crucial for improving our ability to design efficient biological drugs. Computational approaches such as molecular docking are providing a valuable and fast alternative to experimental structural characterization for these complexes. We investigate here how information about complementarity-determining regions and binding epitopes can be used to drive the modeling process, and present a comparative study of four different docking software suites (ClusPro, LightDock, ZDOCK, and HADDOCK) providing specific options for antibody-antigen modeling. Their performance on a dataset of 16 complexes is reported. HADDOCK, which includes information to drive the docking, is shown to perform best in terms of both success rate and quality of the generated models in both the presence and absence of information about the epitope on the antigen.",

keywords = "ClusPro, H3 modeling, HADDOCK, LightDock, ZDOCK, antibody, binding sites, conformational changes, docking",

author = "Francesco Ambrosetti and Brian Jim{\'e}nez-Garc{\'i}a and Jorge Roel-Touris and Bonvin, {Alexandre M J J}",

year = "2020",

month = jan,

day = "7",

doi = "10.1016/j.str.2019.10.011",

language = "English",

volume = "28",

pages = "119--129.e2",

journal = "Structure with Folding & design",

issn = "0969-2126",

publisher = "Cell Press",

number = "1",

}

TY - JOUR

T1 - Modeling Antibody-Antigen Complexes by Information-Driven Docking

AU - Ambrosetti, Francesco

AU - Jiménez-García, Brian

AU - Roel-Touris, Jorge

AU - Bonvin, Alexandre M J J

PY - 2020/1/7

Y1 - 2020/1/7

N2 - Antibodies are Y-shaped proteins essential for immune response. Their capability to recognize antigens with high specificity makes them excellent therapeutic targets. Understanding the structural basis of antibody-antigen interactions is therefore crucial for improving our ability to design efficient biological drugs. Computational approaches such as molecular docking are providing a valuable and fast alternative to experimental structural characterization for these complexes. We investigate here how information about complementarity-determining regions and binding epitopes can be used to drive the modeling process, and present a comparative study of four different docking software suites (ClusPro, LightDock, ZDOCK, and HADDOCK) providing specific options for antibody-antigen modeling. Their performance on a dataset of 16 complexes is reported. HADDOCK, which includes information to drive the docking, is shown to perform best in terms of both success rate and quality of the generated models in both the presence and absence of information about the epitope on the antigen.

AB - Antibodies are Y-shaped proteins essential for immune response. Their capability to recognize antigens with high specificity makes them excellent therapeutic targets. Understanding the structural basis of antibody-antigen interactions is therefore crucial for improving our ability to design efficient biological drugs. Computational approaches such as molecular docking are providing a valuable and fast alternative to experimental structural characterization for these complexes. We investigate here how information about complementarity-determining regions and binding epitopes can be used to drive the modeling process, and present a comparative study of four different docking software suites (ClusPro, LightDock, ZDOCK, and HADDOCK) providing specific options for antibody-antigen modeling. Their performance on a dataset of 16 complexes is reported. HADDOCK, which includes information to drive the docking, is shown to perform best in terms of both success rate and quality of the generated models in both the presence and absence of information about the epitope on the antigen.

KW - ClusPro

KW - H3 modeling

KW - HADDOCK

KW - LightDock

KW - ZDOCK

KW - antibody

KW - binding sites

KW - conformational changes

KW - docking

U2 - 10.1016/j.str.2019.10.011

DO - 10.1016/j.str.2019.10.011

M3 - Article

C2 - 31727476

SN - 0969-2126

VL - 28

SP - 119-129.e2

JO - Structure with Folding & design

JF - Structure with Folding & design

IS - 1

ER -

Modeling Antibody-Antigen Complexes by Information-Driven Docking

Abstract

Keywords

Access to Document

Fingerprint

Cite this