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A Reloadable Molecular Peptide Synthesizer

Objective

The sequence-specific synthesis of information-rich oligomers and polymers is achieved in nature through the operation of complex molecular machines that transcribe information from the genetic code. The most extraordinary of these ‘molecular factories’ is the ribosome, a molecular machine found in all living cells that assembles amino acids from transfer RNA (tRNA) building blocks into a peptide chain with an order defined by the sequence of the messenger RNA (mRNA) strand that it moves along. The Leigh group recently reported the design, synthesis and operation of a rotaxane-based small-molecule machine in which a functionalized macrocycle operates on a thread containing peptide building blocks in a pre-determined order to achieve sequence-specific peptide synthesis. Limitations of the first generation system include that it erases the sequence information on the strand as it is translated into the product. In this project I aim to protect the information during peptide synthesis in order to mimic multiple translation, the process through which protein is synthesized on the mRNA template by the ribosome. This will be achieved through a reloadable track strategy in which longer peptide chains than has previously been possible will be synthesized and the machine itself will be usable multiple times. Importantly, the peptide loading units are easy to attach and detach from the thread using hydrazone and Pd-metal complex ligand exchange reactions. Achieving a synthetic molecular machine that can do this specific task, i.e. synthesizing a peptide multiple times, will be a major advance in this field.

Call for proposal

FP7-PEOPLE-2013-IEF
See other projects for this call

Coordinator

THE UNIVERSITY OF MANCHESTER
EU contribution
€ 231 283,20
Address
OXFORD ROAD
M13 9PL Manchester
United Kingdom

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Region
North West (England) Greater Manchester Manchester
Activity type
Higher or Secondary Education Establishments
Administrative Contact
Liz Fay (Ms.)
Links
Total cost
No data