Furan Oxidation Based Cross-Linking: A New Approach for the Study and Targeting of Nucleic Acid and Protein Interactions

2016 
Furan mediated nucleic acid cross-linking, initially developed for DNA interstrand duplex cross-linking, has matured into a versatile tool for the study of protein and nucleic acid interactions, ready to face its applications. The methodology was initially developed for easy and clean chemical generation of DNA interstrand cross-linked duplexes, but has been further expanded for use with other probes, targets and triggers, now allowing mild biologically significant cross-linking with potential therapeutic benefit. It was shown that the methodology could be repurposed for RNA interstrand cross-linking, which is very relevant in today’s antisense approaches or miRNA target identification endeavors. This further illustrates the furan oxidation method’s generality and mildness, especially when using red light for oxidation. A complementary antigene approach has been explored through duplex targeting with furan modified triplex forming oligonucleotides (TFOs) and DNA binding proteins. Also targeting of peptides and proteins by furan-modified DNA and peptides has been explored. Thorough methodology examination exploring variable reaction conditions in combination with a series of different furan-modified building blocks and application of different activation signals resulted in a detailed understanding of the mechanisms involved and factors influencing the yield and selectivity of the reaction. In order to draw the bigger picture of the scope and limitations of furan-oxidation cross-linking, we here provide a unique side by side comparison and discussion of our published data, supplemented with unpublished results, providing a clear performance report of the currently established furan toolbox and its application potential in various biomacromolecular complexes.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    1
    References
    0
    Citations
    NaN
    KQI
    []