Prediction of RNA 3D Structure using Parallel Algorithm

Abstract

RNA structures are generally organized hierarchically organized. Prediction of RNA structure is a big challenge for the researchers. Many prediction algorithms have been develop for RNA secondary structure prediction. But prediction of tertiary structure is still a big area of research. Approaches for RNA tertiary structure prediction are broadly categorized into two methods viz. de novo methods and template-based prediction method. The De novo are useful only for the small sequences of the nucleotides. For the sequences with large number of nucleotides template based modelling technique is more useful. These template based method are very common in protein structure prediction but it is not explored in RNA tertiary structure prediction. This paper presents a novel methodology for prediction of RNA tertiary structure using the bank ok known structure (template). First, the RNA secondary structure is analysed on the basis of free nucleotides available region wise which may contribute in the prediction of tertiary structure. Next similar region structure templates are searched in PDB metadata. These templates are then used to for the tertiary structure. As all the templates stored in PDB are predicted structures with minimum negative energy, the resultant tertiary structure is also consequently has minimum negative energy. The proposed method is able to predict even large ribosomal RNA structures. The experimental results have shown for the predicted structures on the basis of percentage similarity as well as time required for prediction.