An adaptive defect weighted sampling algorithm to design pseudoknotted RNA secondary structures

Abstract

Computational design of RNA sequences that fold into targeted secondary structures hasmany applications in biomedicine, nanotechnology and synthetic biology. An RNA molecule ismade of different types of secondary structure elements and an important RNA element namedpseudoknot plays a key role in stabilizing the functional form of the molecule. However, due tothe computational complexities associated with characterizing pseudoknotted RNA structures,most of the existing RNA sequence designer algorithms generally ignore this important structuralelement and therefore limit their applications. In this paper we present a new algorithm todesign RNA sequences for pseudoknotted secondary structures. We use NUPACK as thefolding algorithm to compute the equilibrium characteristics of the pseudoknotted RNAs, anddescribe a new adaptive defect weighted sampling algorithm named Enzymer to design lowensemble defect RNA sequences for targeted secondary structures including pseudoknots. Weused a biological data set of 201 pseudoknotted structures from the Pseudobase library tobenchmark the performance of our algorithm. We compared the quality characteristics of theRNA sequences we designed by Enzymer with the results obtained from the state of the artMODENA and antaRNA. Our results show our method succeeds more frequently than MODENAand antaRNA do, and generates sequences that have lower ensemble defect, lower probabilitydefect and higher thermostability. Finally by using Enzymer and by constraining the designto a naturally occurring and highly conserved Hammerhead motif, we designed 8 sequencesfor a pseudoknotted cis-acting Hammerhead ribozyme. Enzymer is available for download athttps://bitbucket.org/casraz/enzymer