Downloads provided by UsageCounts
pmid: 32246984
Optimizing synthetic nanocarriers is like searching for a needle in a haystack. How to find the most suitable carrier for intracellular delivery of a specified macromolecular nanoagent for a given disease target location? Here, we review different synthetic 'chemical evolution' strategies that have been pursued. Libraries of nanocarriers have been generated either by unbiased combinatorial chemistry or by variation and novel combination of known functional delivery elements. As in natural evolution, definition of nanocarriers as sequences, as barcode or design principle, may fuel chemical evolution. Screening in appropriate test system may not only provide delivery candidates, but also a refined understanding of cellular delivery including novel, unpredictable mechanisms. Combined with rational design and computational algorithms, candidates can be further optimized in subsequent evolution cycles into nanocarriers with improved safety and efficacy. Optimization of nanocarriers differs for various cargos, as illustrated for plasmid DNA, siRNA, mRNA, proteins, or genome-editing nucleases.
Drug Carriers, Computational Chemistry, Evolution, Chemical, Macromolecular Substances, Polymers, Chemistry, Pharmaceutical, Nucleic Acids, Nanoparticles, Proteins, Algorithms
Drug Carriers, Computational Chemistry, Evolution, Chemical, Macromolecular Substances, Polymers, Chemistry, Pharmaceutical, Nucleic Acids, Nanoparticles, Proteins, Algorithms
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 74 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
| views | 28 | |
| downloads | 5 |

Views provided by UsageCounts
Downloads provided by UsageCounts