The DOI matches its Crossref record; 215 of the 215 references it cites were found in a registry or an index.
RNA Display Methods for the Discovery of Bioactive Macrocycles
Abstract
The past two decades have witnessed the emergence of macrocycles, including macrocyclic peptides, as a promising yet underexploited class of de novo drug candidates. Both rational/computational design and in vitro display systems have contributed tremendously to the development of cyclic peptide binders of either traditional targets such as cell-surface receptors and enzymes or challenging targets such as protein-protein interaction surfaces. mRNA display, a key platform technology for the discovery of cyclic peptide ligands, has become one of the leading strategies that can generate natural-product-like macrocyclic peptide binders with antibody-like affinities. On the basis of the original cell-free transcription/translation system, mRNA display is highly evolvable to realize its full potential by applying genetic reprogramming and chemical/enzymatic modifications. In addition, mRNA display also allows the follow-up hit-to-lead development using high-throughput focused affinity maturation. Finally, mRNA-displayed peptides can be readily engineered to create chemical conjugates based on known small molecules or biologics. This review covers the birth and growth of mRNA display and discusses the above features of mRNA display with success stories and future perspectives and is up to date as of August 2018.
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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
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066
Smith, G. P. (1985) · Science · doi:10.1126/science.4001944 · Cited by 4,143
Synthesis of Proteins by Native Chemical Ligation
Dawson, P. E., Muir, T. W., Clark-Lewis, I., & Kent, S. B. H. (1994) · Science · doi:10.1126/science.7973629 · Cited by 4,131
Arnison, P. G., Bibb, M. J., Bierbaum, G., Bowers, A. A., Bugni, T. S., Bulaj, G., Camarero, J. A., Campopiano, D. J., Challis, G. L., Clardy, J., et al. (2013) · Nat. Prod. Rep. · doi:10.1039/c2np20085f · Cited by 2,076
Cell-free translation reconstituted with purified components
Shimizu, Y., Inoue, A., Tomari, Y., Suzuki, T., Yokogawa, T., Nishikawa, K., & Ueda, T. (2001) · Nature Biotechnology · doi:10.1038/90802 · Cited by 1,940
Yeast surface display for screening combinatorial polypeptide libraries
Boder, E. T., & Wittrup, K. D. (1997) · Nature Biotechnology · doi:10.1038/nbt0697-553 · Cited by 1,760
The Human Sir2 Ortholog, SIRT2, Is an NAD+-Dependent Tubulin Deacetylase
North, B. J., Marshall, B. L., Borra, M. T., Denu, J. M., & Verdin, E. (2003) · Molecular Cell · doi:10.1016/s1097-2765(03)00038-8 · Cited by 1,536
Expanding the Genetic Code of Escherichia coli
Wang, L., Brock, A., Herberich, B., & Schultz, P. G. (2001) · Science · doi:10.1126/science.1060077 · Cited by 1,499
The exploration of macrocycles for drug discovery — an underexploited structural class
Driggers, E. M., Hale, S. P., Lee, J., & Terrett, N. K. (2008) · Nature Reviews Drug Discovery · doi:10.1038/nrd2590 · Cited by 1,370
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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
Self-citationImpact of non-proteinogenic amino acids in the discovery and development of peptide therapeutics
Ding, Y., Ting, J. P., Liu, J., Al-Azzam, S., Pandya, P., & Afshar, S. (2020) · Amino Acids · doi:10.1007/s00726-020-02890-9 · Cited by 200
Metadata
- Authors
- Huang, Y., Wiedmann, M. M., & Suga, H.
- Venue
- Chemical Reviews
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-11-05
- Volume
- 119
- Issue
- 17
- Pages
- 10360-10391
- ISSN
- 0009-2665 (ISSN-L)
- 1520-6890
- OpenAlex
- W2900111464
- Cited by
- 298
- References
- 215
- FWCI
- 1.66
- Type
- journal article
- Language
- en
- Open access
- closed
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