Sequence matching algorithms and pairing of noncoding RNAs

TL;DR

This paper introduces a novel statistical alignment method for noncoding RNAs that accounts for secondary structures, enabling accurate prediction of RNA interactions and structures from primary sequences using a hierarchical cloverleaf model.

Contribution

It presents a new constructive algorithm for RNA-RNA binding energy estimation that incorporates secondary structures through a hierarchical statistical model.

Findings

The algorithm effectively predicts secondary structures of ncRNAs from primary sequences.

It models the binding of heteropolymer chains considering secondary structure entropy.

The method enables structure recovery in the zero-temperature limit.

Abstract

A new statistical method of alignment of two heteropolymers which can form hierarchical cloverleaf-like secondary structures is proposed. This offers a new constructive algorithm for quantitative determination of binding free energy of two noncoding RNAs with arbitrary primary sequences. The alignment of ncRNAs differs from the complete alignment of two RNA sequences: in ncRNA case we align only the sequences of nucleotides which constitute pairs between two different RNAs, while the secondary structure of each RNA comes into play only by the combinatorial factors affecting the entropc contribution of each molecule to the total cost function. The proposed algorithm is based on two observations: i) the standard alignment problem is considered as a zero-temperature limit of a more general statistical problem of binding of two associating heteropolymer chains; ii) this last problem is generalized onto the sequences with hierarchical cloverleaf-like structures (i.e. of RNA-type). Taking zero-temperature limit at the very end we arrive at the desired "cost function" of the system with account for entropy of side cactus-like loops. Moreover, we have demonstrated in detail how our algorithm enables to solve the "structure recovery" problem. Namely, we can predict in zero-temperature limit the cloverleaf-like (i.e. secondary) structure of interacting ncRNAs by knowing only their primary sequences.