The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.
Sequence-Controlled Polymers
Abstract
Background: During the last few decades, progress has been made in manipulating the architecture of synthetic polymer materials. However, the primary structure—that is, the sequential arrangement of monomer units in a polymer chain—is generally poorly controlled in synthetic macromolecules. Common synthetic polymers are usually homopolymers, made of the same monomer unit, or copolymers with simple chain microstructures, such as random or block copolymers. These polymers are used in many areas but do not have the structural and functional complexity of sequence-defined biopolymers, such as nucleic acids or proteins. Indeed, monomer sequence regulation plays a key role in biology and is a prerequisite for crucial features of life, such as heredity, self-replication, complex self-assembly, and molecular recognition. In this context, developing synthetic polymers containing controlled monomer sequences is an important area for research. Advances: Various synthetic methods for controlling monomer sequences in polymers have been identified, and two major trends in the field of sequence-controlled polymers have emerged. Some approaches use biological concepts that have been optimized by nature for sequence regulation. For instance, DNA templates, enzymes, or even living organisms can be used to prepare sequence-defined polymers. These natural mechanisms can be adapted to tolerate nonnatural monomers. The other trend is the preparation of sequence-controlled polymers by synthetic chemistry. In the most popular approach, monomer units are attached one by one to a support, which is an efficient method but demanding in practice. Recently, some strategies have been proposed for controlling sequences in chain-growth and step-growth polymerizations. These mechanisms usually allow fast and large-scale synthesis of polymers. Specific kinetics and particular catalytic or template conditions allow sequence regulation in these processes. Outlook: The possibility of controlling monomer sequences in synthetic macromolecules has many scientific and technological implications. Information can be controlled at the molecular level in synthetic polymer chains. This opens up interesting perspectives for the field of data storage. In addition, having power over monomer sequences could mean structural control of the resulting polymer, as it strongly influences macromolecular folding and self-assembly. For instance, functional synthetic assemblies that mimic the properties of globular proteins, such as enzymes and transporters, can be foreseen. Moreover, monomer sequence control influences some macroscopic properties. For example, bulk properties such as conductivity, rigidity, elasticity, or biodegradability can be finely tuned in sequence-controlled polymers. The behavior of polymers in solution, particularly in water, is also strongly dependent on monomer sequences. Thus, sequence regulation may enable a more effective control of structure-property relations in tomorrow’s polymer materials.
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Cites
Primer-Directed Enzymatic Amplification of DNA with a Thermostable DNA Polymerase
Saiki, R. K., Gelfand, D. H., Stoffel, S., Scharf, S. J., Higuchi, R., Horn, G. T., Mullis, K. B., & Erlich, H. A. (1988) · Science · doi:10.1126/science.2448875 · Cited by 17,719
Solid Phase Peptide Synthesis. I. The Synthesis of a Tetrapeptide
Merrifield, R. B. (1963) · Journal of the American Chemical Society · doi:10.1021/ja00897a025 · Cited by 7,647
Self-Assembly and Mineralization of Peptide-Amphiphile Nanofibers
Hartgerink, J. D., Beniash, E., & Stupp, S. I. (2001) · Science · doi:10.1126/science.1063187 · Cited by 3,601
Hill, D. J., Mio, M. J., Prince, R. B., Hughes, T. S., & Moore, J. S. (2001) · Chemical Reviews · doi:10.1021/cr990120t · Cited by 2,239
Living ring-opening metathesis polymerization
Bielawski, C. W., & Grubbs, R. H. (2007) · Progress in Polymer Science · doi:10.1016/j.progpolymsci.2006.08.006 · Cited by 1,518
Next-Generation Digital Information Storage in DNA
Church, G. M., Gao, Y., & Kosuri, S. (2012) · Science · doi:10.1126/science.1226355 · Cited by 1,441
SZWARC, M. (1956) · Nature · doi:10.1038/1781168a0 · Cited by 1,360
Zuckermann, R. N., Kerr, J. M., Kent, S. B. H., & Moos, W. H. (1992) · Journal of the American Chemical Society · doi:10.1021/ja00052a076 · Cited by 1,277
Ouchi, M., Terashima, T., & Sawamoto, M. (2009) · Chemical Reviews · doi:10.1021/cr900234b · Cited by 1,257
Self-citationMultiblock Polymers: Panacea or Pandora’s Box?
Bates, F. S., Hillmyer, M. A., Lodge, T. P., Bates, C. M., Delaney, K. T., & Fredrickson, G. H. (2012) · Science · doi:10.1126/science.1215368 · Cited by 1,147
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Adjacent cationic–aromatic sequences yield strong electrostatic adhesion of hydrogels in seawater
Fan, H., Wang, J., Tao, Z., Huang, J., Rao, P., Kurokawa, T., & Gong, J. P. (2019) · Nature Communications · doi:10.1038/s41467-019-13171-9 · Cited by 379
Iterative exponential growth of stereo- and sequence-controlled polymers
Barnes, J. C., Ehrlich, D. J. C., Gao, A. X., Leibfarth, F. A., Jiang, Y., Zhou, E., Jamison, T. F., & Johnson, J. A. (2015) · Nature Chemistry · doi:10.1038/nchem.2346 · Cited by 361
Synthesis of proteins by automated flow chemistry
Hartrampf, N., Saebi, A., Poskus, M., Gates, Z. P., Callahan, A. J., Cowfer, A. E., Hanna, S., Antilla, S., Schissel, C. K., Quartararo, A. J., et al. (2020) · Science · doi:10.1126/science.abb2491 · Cited by 367
Random heteropolymers preserve protein function in foreign environments
Panganiban, B., Qiao, B., Jiang, T., DelRe, C., Obadia, M. M., Nguyen, T. D., Smith, A. A. A., Hall, A., Sit, I., Crosby, M. G., et al. (2018) · Science · doi:10.1126/science.aao0335 · Cited by 294
Design and synthesis of digitally encoded polymers that can be decoded and erased
Roy, R. K., Meszynska, A., Laure, C., Charles, L., Verchin, C., & Lutz, J.-F. (2015) · Nature Communications · doi:10.1038/ncomms8237 · Cited by 308
Self-citation
Metadata
- Authors
- Lutz, J.-F., Ouchi, M., Liu, D. R., & Sawamoto, M.
- Venue
- Science
- Published
- 2013-08-09
- Volume
- 341
- Issue
- 6146
- Pages
- 1238149-1238149
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W1995024825
- Cited by
- 1,381
- References
- 85
- FWCI
- 43.83
- Type
- journal article
- Language
- en
- Open access
- closed
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