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Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

[Image: see text] Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance with...

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Autores principales: Schoeder, Clara T., Schmitz, Samuel, Adolf-Bryfogle, Jared, Sevy, Alexander M., Finn, Jessica A., Sauer, Marion F., Bozhanova, Nina G., Mueller, Benjamin K., Sangha, Amandeep K., Bonet, Jaume, Sheehan, Jonathan H., Kuenze, Georg, Marlow, Brennica, Smith, Shannon T., Woods, Hope, Bender, Brian J., Martina, Cristina E., del Alamo, Diego, Kodali, Pranav, Gulsevin, Alican, Schief, William R., Correia, Bruno E., Crowe, James E., Meiler, Jens, Moretti, Rocco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992133/
https://www.ncbi.nlm.nih.gov/pubmed/33705117
http://dx.doi.org/10.1021/acs.biochem.0c00912
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author Schoeder, Clara T.
Schmitz, Samuel
Adolf-Bryfogle, Jared
Sevy, Alexander M.
Finn, Jessica A.
Sauer, Marion F.
Bozhanova, Nina G.
Mueller, Benjamin K.
Sangha, Amandeep K.
Bonet, Jaume
Sheehan, Jonathan H.
Kuenze, Georg
Marlow, Brennica
Smith, Shannon T.
Woods, Hope
Bender, Brian J.
Martina, Cristina E.
del Alamo, Diego
Kodali, Pranav
Gulsevin, Alican
Schief, William R.
Correia, Bruno E.
Crowe, James E.
Meiler, Jens
Moretti, Rocco
author_facet Schoeder, Clara T.
Schmitz, Samuel
Adolf-Bryfogle, Jared
Sevy, Alexander M.
Finn, Jessica A.
Sauer, Marion F.
Bozhanova, Nina G.
Mueller, Benjamin K.
Sangha, Amandeep K.
Bonet, Jaume
Sheehan, Jonathan H.
Kuenze, Georg
Marlow, Brennica
Smith, Shannon T.
Woods, Hope
Bender, Brian J.
Martina, Cristina E.
del Alamo, Diego
Kodali, Pranav
Gulsevin, Alican
Schief, William R.
Correia, Bruno E.
Crowe, James E.
Meiler, Jens
Moretti, Rocco
author_sort Schoeder, Clara T.
collection PubMed
description [Image: see text] Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.
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spelling pubmed-79921332021-03-25 Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design Schoeder, Clara T. Schmitz, Samuel Adolf-Bryfogle, Jared Sevy, Alexander M. Finn, Jessica A. Sauer, Marion F. Bozhanova, Nina G. Mueller, Benjamin K. Sangha, Amandeep K. Bonet, Jaume Sheehan, Jonathan H. Kuenze, Georg Marlow, Brennica Smith, Shannon T. Woods, Hope Bender, Brian J. Martina, Cristina E. del Alamo, Diego Kodali, Pranav Gulsevin, Alican Schief, William R. Correia, Bruno E. Crowe, James E. Meiler, Jens Moretti, Rocco Biochemistry [Image: see text] Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens. American Chemical Society 2021-03-11 2021-03-23 /pmc/articles/PMC7992133/ /pubmed/33705117 http://dx.doi.org/10.1021/acs.biochem.0c00912 Text en © 2021 The Authors. Published by American Chemical Society Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Schoeder, Clara T.
Schmitz, Samuel
Adolf-Bryfogle, Jared
Sevy, Alexander M.
Finn, Jessica A.
Sauer, Marion F.
Bozhanova, Nina G.
Mueller, Benjamin K.
Sangha, Amandeep K.
Bonet, Jaume
Sheehan, Jonathan H.
Kuenze, Georg
Marlow, Brennica
Smith, Shannon T.
Woods, Hope
Bender, Brian J.
Martina, Cristina E.
del Alamo, Diego
Kodali, Pranav
Gulsevin, Alican
Schief, William R.
Correia, Bruno E.
Crowe, James E.
Meiler, Jens
Moretti, Rocco
Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design
title Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design
title_full Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design
title_fullStr Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design
title_full_unstemmed Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design
title_short Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design
title_sort modeling immunity with rosetta: methods for antibody and antigen design
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992133/
https://www.ncbi.nlm.nih.gov/pubmed/33705117
http://dx.doi.org/10.1021/acs.biochem.0c00912
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