Cargando…

RosettaAntibodyDesign (RAbD): A general framework for computational antibody design

A structural-bioinformatics-based computational methodology and framework have been developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) samples the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for...

Descripción completa

Detalles Bibliográficos
Autores principales: Adolf-Bryfogle, Jared, Kalyuzhniy, Oleks, Kubitz, Michael, Weitzner, Brian D., Hu, Xiaozhen, Adachi, Yumiko, Schief, William R., Dunbrack, Roland L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5942852/
https://www.ncbi.nlm.nih.gov/pubmed/29702641
http://dx.doi.org/10.1371/journal.pcbi.1006112
_version_ 1783321531695235072
author Adolf-Bryfogle, Jared
Kalyuzhniy, Oleks
Kubitz, Michael
Weitzner, Brian D.
Hu, Xiaozhen
Adachi, Yumiko
Schief, William R.
Dunbrack, Roland L.
author_facet Adolf-Bryfogle, Jared
Kalyuzhniy, Oleks
Kubitz, Michael
Weitzner, Brian D.
Hu, Xiaozhen
Adachi, Yumiko
Schief, William R.
Dunbrack, Roland L.
author_sort Adolf-Bryfogle, Jared
collection PubMed
description A structural-bioinformatics-based computational methodology and framework have been developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) samples the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for the design of antibodies in a broad range of applications. The program samples antibody sequences and structures by grafting structures from a widely accepted set of the canonical clusters of CDRs (North et al., J. Mol. Biol., 406:228–256, 2011). It then performs sequence design according to amino acid sequence profiles of each cluster, and samples CDR backbones using a flexible-backbone design protocol incorporating cluster-based CDR constraints. Starting from an existing experimental or computationally modeled antigen-antibody structure, RAbD can be used to redesign a single CDR or multiple CDRs with loops of different length, conformation, and sequence. We rigorously benchmarked RAbD on a set of 60 diverse antibody–antigen complexes, using two design strategies—optimizing total Rosetta energy and optimizing interface energy alone. We utilized two novel metrics for measuring success in computational protein design. The design risk ratio (DRR) is equal to the frequency of recovery of native CDR lengths and clusters divided by the frequency of sampling of those features during the Monte Carlo design procedure. Ratios greater than 1.0 indicate that the design process is picking out the native more frequently than expected from their sampled rate. We achieved DRRs for the non-H3 CDRs of between 2.4 and 4.0. The antigen risk ratio (ARR) is the ratio of frequencies of the native amino acid types, CDR lengths, and clusters in the output decoys for simulations performed in the presence and absence of the antigen. For CDRs, we achieved cluster ARRs as high as 2.5 for L1 and 1.5 for H2. For sequence design simulations without CDR grafting, the overall recovery for the native amino acid types for residues that contact the antigen in the native structures was 72% in simulations performed in the presence of the antigen and 48% in simulations performed without the antigen, for an ARR of 1.5. For the non-contacting residues, the ARR was 1.08. This shows that the sequence profiles are able to maintain the amino acid types of these conserved, buried sites, while recovery of the exposed, contacting residues requires the presence of the antigen-antibody interface. We tested RAbD experimentally on both a lambda and kappa antibody–antigen complex, successfully improving their affinities 10 to 50 fold by replacing individual CDRs of the native antibody with new CDR lengths and clusters.
format Online
Article
Text
id pubmed-5942852
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-59428522018-05-18 RosettaAntibodyDesign (RAbD): A general framework for computational antibody design Adolf-Bryfogle, Jared Kalyuzhniy, Oleks Kubitz, Michael Weitzner, Brian D. Hu, Xiaozhen Adachi, Yumiko Schief, William R. Dunbrack, Roland L. PLoS Comput Biol Research Article A structural-bioinformatics-based computational methodology and framework have been developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) samples the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for the design of antibodies in a broad range of applications. The program samples antibody sequences and structures by grafting structures from a widely accepted set of the canonical clusters of CDRs (North et al., J. Mol. Biol., 406:228–256, 2011). It then performs sequence design according to amino acid sequence profiles of each cluster, and samples CDR backbones using a flexible-backbone design protocol incorporating cluster-based CDR constraints. Starting from an existing experimental or computationally modeled antigen-antibody structure, RAbD can be used to redesign a single CDR or multiple CDRs with loops of different length, conformation, and sequence. We rigorously benchmarked RAbD on a set of 60 diverse antibody–antigen complexes, using two design strategies—optimizing total Rosetta energy and optimizing interface energy alone. We utilized two novel metrics for measuring success in computational protein design. The design risk ratio (DRR) is equal to the frequency of recovery of native CDR lengths and clusters divided by the frequency of sampling of those features during the Monte Carlo design procedure. Ratios greater than 1.0 indicate that the design process is picking out the native more frequently than expected from their sampled rate. We achieved DRRs for the non-H3 CDRs of between 2.4 and 4.0. The antigen risk ratio (ARR) is the ratio of frequencies of the native amino acid types, CDR lengths, and clusters in the output decoys for simulations performed in the presence and absence of the antigen. For CDRs, we achieved cluster ARRs as high as 2.5 for L1 and 1.5 for H2. For sequence design simulations without CDR grafting, the overall recovery for the native amino acid types for residues that contact the antigen in the native structures was 72% in simulations performed in the presence of the antigen and 48% in simulations performed without the antigen, for an ARR of 1.5. For the non-contacting residues, the ARR was 1.08. This shows that the sequence profiles are able to maintain the amino acid types of these conserved, buried sites, while recovery of the exposed, contacting residues requires the presence of the antigen-antibody interface. We tested RAbD experimentally on both a lambda and kappa antibody–antigen complex, successfully improving their affinities 10 to 50 fold by replacing individual CDRs of the native antibody with new CDR lengths and clusters. Public Library of Science 2018-04-27 /pmc/articles/PMC5942852/ /pubmed/29702641 http://dx.doi.org/10.1371/journal.pcbi.1006112 Text en © 2018 Adolf-Bryfogle et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Adolf-Bryfogle, Jared
Kalyuzhniy, Oleks
Kubitz, Michael
Weitzner, Brian D.
Hu, Xiaozhen
Adachi, Yumiko
Schief, William R.
Dunbrack, Roland L.
RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
title RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
title_full RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
title_fullStr RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
title_full_unstemmed RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
title_short RosettaAntibodyDesign (RAbD): A general framework for computational antibody design
title_sort rosettaantibodydesign (rabd): a general framework for computational antibody design
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5942852/
https://www.ncbi.nlm.nih.gov/pubmed/29702641
http://dx.doi.org/10.1371/journal.pcbi.1006112
work_keys_str_mv AT adolfbryfoglejared rosettaantibodydesignrabdageneralframeworkforcomputationalantibodydesign
AT kalyuzhniyoleks rosettaantibodydesignrabdageneralframeworkforcomputationalantibodydesign
AT kubitzmichael rosettaantibodydesignrabdageneralframeworkforcomputationalantibodydesign
AT weitznerbriand rosettaantibodydesignrabdageneralframeworkforcomputationalantibodydesign
AT huxiaozhen rosettaantibodydesignrabdageneralframeworkforcomputationalantibodydesign
AT adachiyumiko rosettaantibodydesignrabdageneralframeworkforcomputationalantibodydesign
AT schiefwilliamr rosettaantibodydesignrabdageneralframeworkforcomputationalantibodydesign
AT dunbrackrolandl rosettaantibodydesignrabdageneralframeworkforcomputationalantibodydesign