Optimizing synthetic nucleic acid and protein nanocarriers: The chemical evolution approach

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. (c) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

Optimizing synthetic nanocarriers is a challenging process that involves strategies similar to chemical evolution. Libraries of nanocarriers are generated through combinatorial chemistry or variation and combination of known functional elements, with screening in appropriate test systems providing delivery candidates and a refined understanding of cellular delivery mechanisms. Rational design and computational algorithms are also used to further optimize candidates into nanocarriers with improved safety and efficacy.