Antibody-SGM, a Score-Based Generative Model for Antibody Heavy-Chain Design-Reference-Cited by-同舟云学术

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Antibody-SGM, a Score-Based Generative Model for Antibody Heavy-Chain Design

Published:2024-08-27 Issue:17 Volume:64 Page:6745-6757
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Xie Xuezhi¹²,Valiente Pedro A.¹^ORCID,Lee Jin Sub¹³,Kim Jisun¹,Kim Philip M.¹²³^ORCID

Affiliation:

1. Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada

2. Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3E1, Canada

3. Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada

Funder

Canadian Institutes of Health Research

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00711

Reference36 articles.

1. Ig-VAE: Generative modeling of protein structure by direct 3D coordinate generation

2. Deep generative modeling for protein design

3. Antibody H3 Structure Prediction

4. Geometric potentials from deep learning improve prediction of CDR H3 loop structures

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