DrTransformer: Heuristic cotranscriptional RNA folding using the nearest neighbor energy model

Bioinformatics(2022)

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摘要
AbstractBackgroundFolding during transcription can have an important influence on the structure and function of ℝNA molecules, as regions closer to the 5’ end can fold into metastable structures before potentially stronger interactions with the 3’ end become available. Thermodynamic ℝNA folding models are not suitable to analyze this problem, as they can only calculate properties of the equilibrium distribution. Other software packages that simulate the kinetic process of ℝNA folding during transcription exist, but they are mostly applicable for short sequences.ResultsWe present a new algorithm that tracks changes to the ℝNA secondary structure ensemble during transcription. At every transcription step, new representative local minima are identified, a neighborhood relation is defined and transition rates are estimated for kinetic simulations. After every simulation, a part of the ensemble is removed and the remainder is used to search for new potentially relevant structures. The presented algorithm is deterministic (up to numeric instabilities of simulations), fast (in comparison with existing methods), and it is capable of folding ℝNAs much longer than 200 nucleotides.AvailabilityThis software is open-source and available at https://github.com/ViennaRNA/drtransformer.
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heuristic cotranscriptional rna
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