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PD-1 Targeted Antibody Discovery Using AI Protein Diffusion
Open accessPreprint — published as 10.1177/15330338241275947 · Paper page
Abstract
The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncological diseases. This checkpoint protein inhibits T lymphocytes from attacking other cells in the body and thus blocking it improves the clearance of tumor cells by the immune system. While there are already multiple FDA-approved anti-PD-1 antibodies, including nivolumab ( Opdivo ® from Bristol-Myers Squibb) and pembrolizumab ( Keytruda ® from Merck), there are ongoing efforts to discover new and improved checkpoint inhibitor therapeutics. In this study, we present multiple anti-PD-1 antibody fragments that were derived computationally using protein diffusion and evaluated through our scalable, in silico pipeline. Here we present nine synthetic Fv structures that are suitable for further empirical testing of their anti-PD-1 activity due to desirable predicted binding performance.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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- David S. Wilkes and William J. Burlingham . Immunobiology of Organ Transplantation. Springer, 2012. ISBN 9781441989994.
- 10.1016/j.critrevonc.2016.02.001 · DOI
- 10.2147/ott.s105862 · DOI · Paper page
- 10.3389/fphar.2017.00561 · DOI
- 10.1517/13543784.2015.991819 · DOI
- 10.1177/1758834014567470 · DOI
- 10.1177/1758834014567469 · DOI
- 10.1056/NEJMoa1510665 · DOI · Paper page
- 10.1080/14737140.2018.1480942 · DOI
- 10.1126/science.aaa1348 · DOI · Paper page
- 10.1080/21645515.2016.1199310 · DOI
- 10.1016/S1470-2045(17)30607-1 · DOI
- 10.1016/j.critrevonc.2017.06.001 · DOI
- 10.1038/s41416-022-01743-4 · DOI
- 10.3389/fimmu.2020.00339 · DOI
- 10.1093/nar/gkz827 · DOI · Paper page
- 10.1186/1471-2105-5-113 · DOI
- 10.1101/2023.09.11.556673 · DOI · Paper page
- 10.1016/j.jmb.2016.08.019 · DOI · Paper page
- 10.1038/s41592-022-01488-1 · DOI · Paper page
- 10.1101/2021.10.04.463034 · DOI · Paper page
- 10.1038/nbt.3988 · DOI · Paper page
- 10.1371/journal.pcbi.1005659 · DOI · Paper page
- 10.1016/j.jmb.2015.09.014 · DOI · Paper page
- 10.1093/bioinformatics/btv552 · DOI
- 10.3389/fbinf.2024.1397968 · DOI · Paper page
- 10.1016/J.STR.2019.10.011 · DOI
- 10.1007/978-1-0716-2609-2_14 · DOI
- 10.7554/eLife.07454 · DOI
- 10.1021/acs.jctc.5b00935 · DOI
- 10.1063/1.464397 · DOI
- 10.1038/cr.2016.77 · DOI
- 10.1038/ncomms14369 · DOI
- 10.1016/j.semcancer.2023.06.005 · DOI
- 10.1093/bioinformatics/btz895 · DOI · Paper page
- 10.1038/s41586-023-06415-8 · DOI · Paper page
- 10.1038/s41586-023-06728-8 · DOI · Paper page
- 10.3389/fviro.2022.830202 · DOI · Paper page
- 10.3389/fviro.2023.1172027 · DOI · Paper page
- 10.1016/j.meegid.2023.105418 · DOI
- 10.1101/2023.11.17.567543 · DOI · Paper page
- 10.1038/s41598-023-42090-5 · DOI
- Copyright - Copyright NeuroQuantology 2023; Last updated - 2023-12-19, 2023, Antibody engineering to increase the affinity of edrecolomab monoclonal antibody against vegf-a protein in the treatment of colorectal cancer, NeuroQuantology, 21, 263
Metadata
- Authors
- Ford, C. T.
- Affiliations
- University of North Carolina at Charlotte (US)
- Corresponding author
- Ford, Colby T.
- ORCID
- Ford, Colby T.
- Venue
- Technology in Cancer Research & Treatment
- Publisher
- openRxiv
- Published
- 2024-01-23
- Volume
- 23
- Pages
- 15330338241275947-15330338241275947
- ISSN
- 1533-0338 (ISSN-L)
- PMC
- PMC11375674
- OpenAlex
- W4402239168
- Cited by
- 7
- References
- 1
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 1
- FWCI
- 1.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- Technology in Cancer Research & Treatment (publishedVersion, cc-by-nc)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Keywords
- PD-1, anti-PD-1, protein diffusion, Fv fragment, immune checkpoint inhibitors, cancer immunotherapy, nivolumab, pembrolizumab, computational antibody design
- MeSH terms
- Immune Checkpoint Inhibitors, Antibodies, Artificial Intelligence, Humans, Immunoglobulin Variable Region, Neoplasms, Protein Binding, Drug Design, Drug Discovery, Molecular Targeted Therapy, Programmed Cell Death 1 Receptor
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