Estimating RNA secondary structure by maximizing stacking regions

Abstract

Various rudimentary cellular functions that are carried out in an organism are dependent on RNA secondary structure. Thus, accurate prediction of RNA secondary structure is becoming an increasing interest. There are several methods in the literature that predict the secondary structure. In this paper, a maximum independent set (MIS) approach to predict the RNA secondary structure is presented. We find all possible secondary structure which has maximum base pairs using MIS on circle graph. We not only concentrate on maximizing base pairs but maximizing stacking regions, as it reinforces the stability of secondary structure. We also compare the suboptimal structures using stacking energy and then Tinocos stability number. The output of our algorithm could be more than one secondary structure, as in real-life scenario, the secondary structures may have different sets of base pairs with similar energy level. We also have provided a Web portal named TU Web server available at http://14.139.219.242:8003/rna_struct to visualize predicted RNA secondary structure.