The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Trends in peptide drug discovery
Open accessAbstract
Since the introduction of insulin almost a century ago, more than 80 peptide drugs have reached the market for a wide range of diseases, including diabetes, cancer, osteoporosis, multiple sclerosis, HIV infection and chronic pain. In this Perspective, we summarize key trends in peptide drug discovery and development, covering the early efforts focused on human hormones, elegant medicinal chemistry and rational design strategies, peptide drugs derived from nature, and major breakthroughs in molecular biology and peptide chemistry that continue to advance the field. We emphasize lessons from earlier approaches that are still relevant today as well as emerging strategies such as integrated venomics and peptide-display libraries that create new avenues for peptide drug discovery. We also discuss the pharmaceutical landscape in which peptide drugs could be particularly valuable and analyse the challenges that need to be addressed for them to reach their full potential. Since the introduction of insulin almost a century ago, more than 80 peptide drugs have been approved for a wide range of diseases. This Perspective summarizes trends in peptide drug discovery, emphasizing lessons from earlier approaches as well as emerging strategies such as integrated venomics and peptide-display libraries. It also analyses the remaining challenges and the pharmaceutical landscape in which peptide drugs are particularly valuable.
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Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(00)00129-0 · Cited by 18,139
Oxytocin increases trust in humans
Kosfeld, M., Heinrichs, M., Zak, P. J., Fischbacher, U., & Fehr, E. (2005) · Nature · doi:10.1038/nature03701 · Cited by 3,690
Therapeutic peptides: Historical perspectives, current development trends, and future directions
Lau, J. L., & Dunn, M. K. (2018) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2017.06.052 · Cited by 1,879
Overcoming the challenges in administering biopharmaceuticals: Formulation and delivery strategies
Mitragotri, S., Burke, P. A., & Langer, R. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4363 · Cited by 1,702
Polyethylene glycol (PEG): A versatile polymer for pharmaceutical applications
D’souza, A. A., & Shegokar, R. (2016) · Expert Opinion on Drug Delivery · doi:10.1080/17425247.2016.1182485 · Cited by 1,282
Intranasal delivery of biologics to the central nervous system
Lochhead, J. J., & Thorne, R. G. (2012) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2011.11.002 · Cited by 1,214
Hirsch, I. B. (2005) · New England Journal of Medicine · doi:10.1056/nejmra040832 · Cited by 667
Solid-phase peptide synthesis: from standard procedures to the synthesis of difficult sequences
Coin, I., Beyermann, M., & Bienert, M. (2007) · Nature Protocols · doi:10.1038/nprot.2007.454 · Cited by 638
Intranasal Oxytocin: Myths and Delusions
Leng, G., & Ludwig, M. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.05.003 · Cited by 616
Peptide-Based Vaccines: Current Progress and Future Challenges
Malonis, R. J., Lai, J. R., & Vergnolle, O. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00472 · Cited by 602
Cited by
Therapeutic Peptides: Current Applications and Future Directions
Wang, L., Wang, N., Zhang, W., Cheng, X., Yan, Z., Shao, G., Wang, X., Wang, R., & Fu, C. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00904-4 · Cited by 2,131
Therapeutic strategies for COVID-19: progress and lessons learned
Li, G., Hilgenfeld, R., Whitley, R., & De Clercq, E. (2023) · Nature Reviews Drug Discovery · doi:10.1038/s41573-023-00672-y · Cited by 676
Advance in peptide-based drug development: delivery platforms, therapeutics and vaccines
Xiao, W., Jiang, W., Chen, Z., Huang, Y., Mao, J., Zheng, W., Hu, Y., & Shi, J. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-02107-5 · Cited by 449
Chen, S., Lin, T., Basu, R., Ritchey, J., Wang, S., Luo, Y., Li, X., Pei, D., Kara, L. B., & Cheng, X. (2024) · Nature Communications · doi:10.1038/s41467-024-45766-2 · Cited by 324
Huang, J., Xu, Y., Xue, Y., Huang, Y., Li, X., Chen, X., Xu, Y., Zhang, D., Zhang, P., Zhao, J., et al. (2023) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00991-2 · Cited by 270
Metadata
- Authors
- Muttenthaler, M., King, G. F., Adams, D. J., & Alewood, P. F.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2021-02-03
- Volume
- 20
- Issue
- 4
- Pages
- 309-325
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W3127297964
- Cited by
- 1,964
- References
- 25
- FWCI
- 26.33
- Type
- journal article
- Language
- en
- Open access
- green
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