Sequence-structure relations of biopolymers

TL;DR

This paper explores the correlation between sequence and structure in biopolymers like RNA, introducing a novel approach to identify embedded patterns beyond traditional sequence alignment by analyzing mutual information and energy spectra.

Contribution

It presents a new framework connecting sequence-structure mutual information with partition functions and introduces methods to detect embedded patterns in RNA sequences.

Findings

Identifies multiple sequences with similar mutual information but poor alignment.

Connects partition function computation to mutual information in RNA structures.

Provides a criterion to distinguish native structures based on sequence patterns.

Abstract

Motivation: DNA data is transcribed into single-stranded RNA, which folds into specific molecular structures. In this paper we pose the question to what extent sequence- and structure-information correlate. We view this correlation as structural semantics of sequence data that allows for a different interpretation than conventional sequence alignment. Structural semantics could enable us to identify more general embedded "patterns" in DNA and RNA sequences. Results: We compute the partition function of sequences with respect to a fixed structure and connect this computation to the mutual information of a sequence-structure pair for RNA secondary structures. We present a Boltzmann sampler and obtain the a priori probability of specific sequence patterns. We present a detailed analysis for the three PDB-structures, 2JXV (hairpin), 2N3R (3-branch multi-loop) and 1EHZ (tRNA). We localize specific sequence patterns, contrast the energy spectrum of the Boltzmann sampled sequences versus those sequences that refold into the same structure and derive a criterion to identify native structures. We illustrate that there are multiple sequences in the partition function of a fixed structure, each having nearly the same mutual information, that are nevertheless poorly aligned. This indicates the possibility of the existence of relevant patterns embedded in the sequences that are not discoverable using alignments.