Literature DB >> 15017055

Maxizyme technology.

Mayu Iyo1, Hiroaki Kawasaki, Kazunari Taira.   

Abstract

Ribozymes are small and versatile nucleic acids that can cleave RNAs at specific sites. These molecules have great potential to be used as effective gene-therapeutic agents. However, because of the limitation for cleavable sequences within the target mRNA, in some cases conventional ribozymes have failed to exhibit precise cleavage specificity. A maxizyme is the dimer of minimized ribozymes (minizymes), which can specifically cleave two distinct target sites. The maxizyme also has an allosteric function in that it can form an active conformation and cleave the two target sites only when it recognizes two distinct target sites. We demonstrated previously that an allosterically controllable maxizyme was a powerful tool in the disruption of an abnormal chimeric RNA (bcr-abl) in cells and in mice. Furthermore, more than five custom-designed maxizymes have clearly demonstrated these allosteric functions in vitro and in vivo. Thus, maxizyme technology is not limited to one specific case, but may have broad general applicability in molecular biology and in molecular gene therapy.

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Year:  2004        PMID: 15017055     DOI: 10.1385/1-59259-746-7:257

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

1.  A binary deoxyribozyme for nucleic acid analysis.

Authors:  Dmitry M Kolpashchikov
Journal:  Chembiochem       Date:  2007-11-23       Impact factor: 3.164

2.  Design and analysis of hammerhead ribozyme activity against an artificial gene target.

Authors:  James R Carter; Pruksa Nawtaisong; Velmurugan Balaraman; Malcolm J Fraser
Journal:  Methods Mol Biol       Date:  2014

3.  Controlling the rate of organic reactions: rational design of allosteric Diels-Alderase ribozymes.

Authors:  Sergey Amontov; Andres Jäschke
Journal:  Nucleic Acids Res       Date:  2006-09-20       Impact factor: 16.971

Review 4.  Programmable Genome Editing Tools and their Regulation for Efficient Genome Engineering.

Authors:  Tuhin Kumar Guha; Alvan Wai; Georg Hausner
Journal:  Comput Struct Biotechnol J       Date:  2017-01-12       Impact factor: 7.271

  4 in total

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