The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Computer-aided antibody design
Open accessAbstract
Recent clinical trials using antibodies with low toxicity and high efficiency have raised expectations for the development of next-generation protein therapeutics. However, the process of obtaining therapeutic antibodies remains time consuming and empirical. This review summarizes recent progresses in the field of computer-aided antibody development mainly focusing on antibody modeling, which is divided essentially into two parts: (i) modeling the antigen-binding site, also called the complementarity determining regions (CDRs), and (ii) predicting the relative orientations of the variable heavy (V(H)) and light (V(L)) chains. Among the six CDR loops, the greatest challenge is predicting the conformation of CDR-H3, which is the most important in antigen recognition. Further computational methods could be used in drug development based on crystal structures or homology models, including antibody-antigen dockings and energy calculations with approximate potential functions. These methods should guide experimental studies to improve the affinities and physicochemical properties of antibodies. Finally, several successful examples of in silico structure-based antibody designs are reviewed. We also briefly review structure-based antigen or immunogen design, with application to rational vaccine development.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Somatic generation of antibody diversity
Tonegawa, S. (1983) · Nature · doi:10.1038/302575a0 · Cited by 4,005
Effects of protein aggregates: An immunologic perspective
Rosenberg, A. S. (2006) · The AAPS Journal · doi:10.1208/aapsj080359 · Cited by 1,355
Rationalization of the effects of mutations on peptide andprotein aggregation rates
Chiti, F., Stefani, M., Taddei, N., Ramponi, G., & Dobson, C. M. (2003) · Nature · doi:10.1038/nature01891 · Cited by 1,072
A new clustering of antibody CDR loop conformations
North, B., Lehmann, A., & Dunbrack, R. L. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.10.030 · Cited by 380
Computational design of antibody-affinity improvement beyond in vivo maturation
Lippow, S. M., Wittrup, K. D., & Tidor, B. (2007) · Nature Biotechnology · doi:10.1038/nbt1336 · Cited by 342
Prediction of aggregation prone regions of therapeutic proteins
Chennamsetty, N., Voynov, V., Kayser, V., Helk, B., & Trout, B. L. (2010) · The Journal of Physical Chemistry B · doi:10.1021/jp911706q · Cited by 200
RosettaAntibody: antibody variable region homology modeling server
Sircar, A., Kim, E. T., & Gray, J. J. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp387 · Cited by 161
Almagro, J. C., Beavers, M. P., Hernandez‐Guzman, F., Maier, J., Shaulsky, J., Butenhof, K., Labute, P., Thorsteinson, N., Kelly, K., Teplyakov, A., et al. (2011) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.23130 · Cited by 131
Antibody evolution constrains conformational heterogeneity by tailoring protein dynamics
Zimmermann, J., Oakman, E. L., Thorpe, I. F., Shi, X., Abbyad, P., Brooks, C. L., Boxer, S. G., & Romesberg, F. E. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0603282103 · Cited by 116
Analyzing the ‘Degree of Humanness’ of antibody sequences
Abhinandan, K. R., & Martin, A. C. R. (2007) · Journal of Molecular Biology · doi:10.1016/j.jmb.2007.02.100 · Cited by 99
Cited by
SAbDab: the structural antibody database
Dunbar, J., Krawczyk, K., Leem, J., Baker, T., Fuchs, A., Georges, G., Shi, J., & Deane, C. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1043 · Cited by 674
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
Salo-Ahen, O. M. H., Alanko, I., Bhadane, R., Bonvin, A. M. J. J., Honorato, R. V., Hossain, S., Juffer, A. H., Kabedev, A., Lahtela-Kakkonen, M., Larsen, A. S., et al. (2020) · Processes · doi:10.3390/pr9010071 · Cited by 659
Bioengineering virus‐like particles as vaccines
Lua, L. H. L., Connors, N. K., Sainsbury, F., Chuan, Y. P., Wibowo, N., & Middelberg, A. P. J. (2014) · Biotechnology and Bioengineering · doi:10.1002/bit.25159 · Cited by 355
Moal, I. H., & Fernández-Recio, J. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts489 · Cited by 281
ABodyBuilder: automated antibody structure prediction with data-driven accuracy estimation
Leem, J., Dunbar, J., Georges, G., Shi, J., & Deane, C. M. (2016) · mAbs · doi:10.1080/19420862.2016.1205773 · Cited by 238
Metadata
- Authors
- Kuroda, D., Shirai, H., Jacobson, M. P., & Nakamura, H.
- Venue
- Protein Engineering Design and Selection
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-06-02
- Volume
- 25
- Issue
- 10
- Pages
- 507-522
- ISSN
- 0269-2139 (ISSN-L)
- 1741-0126
- 1741-0134
- OpenAlex
- W2167833742
- Cited by
- 222
- References
- 13
- FWCI
- 14.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Computer-aided antibody design. https://app.cochat.ai/papers/10.1093/protein/gzs024
- The paper
- Kuroda, D., Shirai, H., Jacobson, M. P., & Nakamura, H. (2012). Computer-aided antibody design. Protein Engineering Design and Selection. https://doi.org/10.1093/protein/gzs024
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
