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A Biologically Meaningful Extension of the Efficient Method for Deleterious Mutations Prediction in RNAs: Insertions and Deletions in Addition to Substitution Mutations

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10847))

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Abstract

The RNAmute and MultiRNAmute interactive java programs were developed to predict deleterious point mutations in RNA sequences, which intently cause a global conformational rearrangement of the secondary structure of the functional RNA molecules and thereby disrupt their function. RNAmute was designed to deal with only single point mutations in a brute force manner, while the MultiRNAmute tool uses an efficient approach to deal with multiple point mutations. The approach used in MultiRNAmute is based on the stabilization of the suboptimal RNA folding solutions and/or destabilization of the optimal MFE structure of the wild type RNA molecule. Both programs utilize the Vienna RNA package to find the optimal and suboptimal (in case of MultiRNAmute) RNA secondary structures. The main limitation of both programs is their ability to predict only substitution mutations and these programs were not designed to work with deletion or insertion mutations. Herein we develop an efficient approach, based on suboptimal folding solutions, to predict multiple point mutations consisting of deletions, insertions and substitution mutations. All RNAmute algorithms were validated on the TPP-riboswitch and some other functional RNAs.

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Correspondence to Alexander Churkin .

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Churkin, A., Barash, D. (2018). A Biologically Meaningful Extension of the Efficient Method for Deleterious Mutations Prediction in RNAs: Insertions and Deletions in Addition to Substitution Mutations. In: Zhang, F., Cai, Z., Skums, P., Zhang, S. (eds) Bioinformatics Research and Applications. ISBRA 2018. Lecture Notes in Computer Science(), vol 10847. Springer, Cham. https://doi.org/10.1007/978-3-319-94968-0_15

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  • DOI: https://doi.org/10.1007/978-3-319-94968-0_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94967-3

  • Online ISBN: 978-3-319-94968-0

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