SequenceCraft: machine learning-based resource for exploratory analysis of RNA-cleaving deoxyribozymes.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Deoxyribozymes or DNAzymes represent artificial short DNA sequences bearing many catalytic properties. In particular, DNAzymes able to cleave RNA sequences have a huge potential in gene therapy and sequence-specific analytic detection of disease markers. This activity is provided by catalytic cores able to perform site-specific hydrolysis of the phosphodiester bond of an RNA substrate. However, the vast majority of existing DNAzyme catalytic cores have low efficacy in in vivo experiments, whereas SELEX based on in vitro screening offers long and expensive selection cycle with the average success rate of ~ 30%, moreover not allowing the direct selection of chemically modified DNAzymes, which were previously shown to demonstrate higher activity in vivo. Therefore, there is a huge need in in silico approach for exploratory analysis of RNA-cleaving DNAzyme cores to drastically ease the discovery of novel catalytic cores with superior activities.

Authors

  • M Eremeyeva
    International Institute "Solution Chemistry of Advanced Materials and Technologies", ITMO University, Saint-Petersburg, Russian Federation, 191002.
  • Y Din
    International Institute "Solution Chemistry of Advanced Materials and Technologies", ITMO University, Saint-Petersburg, Russian Federation, 191002.
  • N Shirokii
    International Institute "Solution Chemistry of Advanced Materials and Technologies", ITMO University, Saint-Petersburg, Russian Federation, 191002.
  • N Serov
    International Institute "Solution Chemistry of Advanced Materials and Technologies", ITMO University, Saint-Petersburg, Russian Federation, 191002. serov@scamt-itmo.ru.