InfoMols | Recognition-encoded synthetic information molecules

Summary
Linear oligomers encoded with a sequence of side-chains that have specific recognition properties are the basis for a range of properties that are the hallmarks of Nature’s nanotechnology: folding, substrate recognition, catalysis, self-assembly, and molecular replication. Nucleic acids are currently unrivalled as the only molecular architecture that embodies all of these properties, and this ability to encode, express and replicate sequence information is the molecular basis for the evolution of life on Earth. The aim of this proposal is to develop synthetic oligomeric molecules that encode and express chemical information in the same way as nucleic acids, via a sequence of recognition sites attached as side-chains to a linear backbone. We have already reported a range of synthetic oligomers that bear no relation to the structures of their biological counterparts, yet show efficient sequence-selective duplex formation via H-bonding interactions and can be used for replication of sequence information via covalent base-pairing interactions. Here hybrid systems are proposed that combine the most successful elements of backbone architecture and oligomerisation chemistry with a mixture of dynamic and kinetically inert base-pairing side-chains to obtain new synthetic systems that show all of the functional properties found in biomolecules. The ability to replicate sequence in recognition-encoded synthetic information molecules will enable exploration of new chemical spaces using directed evolution. These new chemical systems will allow us to evolve synthetic oligomers that fold into stable well-defined 3D structures, bind substrates with high affinity, and catalyse reactions. Programmable abiotic molecular nanotechnology will open a new area of chemistry with huge unexplored potential.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101018984
Start date: 01-10-2021
End date: 30-09-2026
Total budget - Public funding: 2 499 850,00 Euro - 2 499 850,00 Euro
Cordis data

Original description

Linear oligomers encoded with a sequence of side-chains that have specific recognition properties are the basis for a range of properties that are the hallmarks of Nature’s nanotechnology: folding, substrate recognition, catalysis, self-assembly, and molecular replication. Nucleic acids are currently unrivalled as the only molecular architecture that embodies all of these properties, and this ability to encode, express and replicate sequence information is the molecular basis for the evolution of life on Earth. The aim of this proposal is to develop synthetic oligomeric molecules that encode and express chemical information in the same way as nucleic acids, via a sequence of recognition sites attached as side-chains to a linear backbone. We have already reported a range of synthetic oligomers that bear no relation to the structures of their biological counterparts, yet show efficient sequence-selective duplex formation via H-bonding interactions and can be used for replication of sequence information via covalent base-pairing interactions. Here hybrid systems are proposed that combine the most successful elements of backbone architecture and oligomerisation chemistry with a mixture of dynamic and kinetically inert base-pairing side-chains to obtain new synthetic systems that show all of the functional properties found in biomolecules. The ability to replicate sequence in recognition-encoded synthetic information molecules will enable exploration of new chemical spaces using directed evolution. These new chemical systems will allow us to evolve synthetic oligomers that fold into stable well-defined 3D structures, bind substrates with high affinity, and catalyse reactions. Programmable abiotic molecular nanotechnology will open a new area of chemistry with huge unexplored potential.

Status

SIGNED

Call topic

ERC-2020-ADG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2020
ERC-2020-ADG ERC ADVANCED GRANT