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Synthesis of skeletally diverse alkaloid-like molecules: exploitation of metathesis substrates assembled from triplets of building blocks.

ABSTRACT: A range of metathesis substrates was assembled from triplets of unsaturated building blocks. The approach involved the iterative attachment of a propagating and a terminating building block to a fluorous-tagged initiating building block. Metathesis cascade chemistry was used to "reprogram" the molecular scaffolds. Remarkably, in one case, a cyclopropanation reaction competed with the expected metathesis cascade process. Finally, it was demonstrated that the metathesis products could be derivatised to yield the final products. At each stage, purification was facilitated by the presence of a fluorous-tagged protecting group.

SUBMITTER: Maurya SK

PROVIDER: S-EPMC3678641 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Synthesis of skeletally diverse alkaloid-like molecules: exploitation of metathesis substrates assembled from triplets of building blocks.

Maurya Sushil K SK Dow Mark M Warriner Stuart S Nelson Adam A

Beilstein journal of organic chemistry 20130422

A range of metathesis substrates was assembled from triplets of unsaturated building blocks. The approach involved the iterative attachment of a propagating and a terminating building block to a fluorous-tagged initiating building block. Metathesis cascade chemistry was used to "reprogram" the molecular scaffolds. Remarkably, in one case, a cyclopropanation reaction competed with the expected metathesis cascade process. Finally, it was demonstrated that the metathesis products could be derivatis ...[more]

PMID: 23766790

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Project description:Wet spinning is an established fibre manufacturing route to realise collagen fibres with preserved triple helix architecture and cell acceptability for applications in biomedical membranes. However, resulting fibres still need to be chemically modified post-spinning to ensure material integrity in physiological media, with inherent risks of alteration of fibre morphology and with limited opportunities to induce fibrillogenesis following collagen fixation in the crosslinked state. To overcome this challenge, we hypothesised that a photoactive type I collagen precursor bearing either single or multiple monomers could be employed to accomplish hierarchically assembled fibres with improved processability, macroscopic properties and nanoscale organisation via sequential wet spinning and UV-curing. In-house-extracted type I rat tail collagen functionalised with both 4-vinylbenzyl chloride (4VBC) and methacrylate residues generated a full hydrogel network following solubilisation in a photoactive aqueous solution and UV exposure, whereby ~85 wt.% of material was retained following 75-day hydrolytic incubation. Wide-angle X-ray diffraction confirmed the presence of typical collagen patterns, whilst an averaged compression modulus and swelling ratio of more than 290 kPa and 1500 wt.% was recorded in the UV-cured hydrogel networks. Photoactive type I collagen precursors were subsequently wet spun into fibres, displaying the typical dichroic features of collagen and regular fibre morphology. Varying tensile modulus (E = 5 ± 1 - 11 ± 4 MPa) and swelling ratio (SR = 1880 ± 200 - 3350 ± 500 wt.%) were measured following post-spinning UV curing and equilibration with phosphate-buffered saline (PBS). Most importantly, 72-h incubation of the wet spun fibres in PBS successfully induced renaturation of collagen-like fibrils, which were fixed following UV-induced network formation. The whole process proved to be well tolerated by cells, as indicated by a spread-like cell morphology following a 48-h culture of L929 mouse fibroblasts on the extracts of UV-cured fibres.

Dataset Information

Synthesis of skeletally diverse alkaloid-like molecules: exploitation of metathesis substrates assembled from triplets of building blocks.

Publications

Synthesis of skeletally diverse alkaloid-like molecules: exploitation of metathesis substrates assembled from triplets of building blocks.

Similar Datasets

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