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    • Keywords


      Energy landscape; Monte Carlo; optimization; RNA; tertiary structure

    • Abstract


      The energy landscape of RNA is known to be extremely rugged, and hence finding low-energy structures starting from a random structure is a challenging task for any optimization algorithm. In the current work, we have investigated the ability of one Monte Carlo–based optimization algorithm, Temperature Basin Paving, to explore the energy landscape of a small RNA T-loop hairpin. In this method, the history of the simulation is used to increase the probability of states less visited in the simulation. It has been found that using both energy and end-to-end distance as the biasing parameters in the simulation, the partially folded structure of the hairpin starting from random structures could be obtained.

    • Author Affiliations


      Sudhanshu Shanker1 Pradipta Bandyopadhyay1

      1. School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110 067, India
    • Dates

  • Journal of Biosciences | News

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      Posted on July 25, 2019

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