High-quality, customizable heuristics for RNA 3D structure alignment

Abstract

Motivation Tertiary structure alignment is one of the main challenges in the computer-aided comparative study of molecular structures. Its aim is to optimally overlay the three-dimensional shapes of two or more molecules in space to find the correspondence between their nucleotides. Alignment is the starting point for most algorithms that assess structural similarity or find common substructures. Thus, it has applications in solving a variety of bioinformatics problems, e.g., in the search for structural patterns, structure clustering, identifying structural redundancy, and evaluating the prediction accuracy of 3D models. To date, several tools have been developed to align 3D structures of RNA. However, most of them are not applicable to arbitrarily large structures and do not allow users to parameterize the optimization algorithm. Results We present two customizable heuristics for flexible alignment of 3D RNA structures, geometric search (GEOS), and genetic algorithm (GENS). They work in sequence-dependent/independent mode and find the suboptimal alignment of expected quality (below a predefined RMSD threshold). We compare their performance with those of state-of-the-art methods for aligning RNA structures. We show the results of quantitative and qualitative tests run for all of these algorithms on benchmark sets of RNA structures. Availability Source codes for both heuristics are hosted at https://github.com/RNApolis/rnahugs Supplementary information Supplementary data are available at Bioinformatics online

ARTEMIS - a method for topology-independent superposition of RNA 3D structures and structure-based sequence alignment

“…While several methods, such as Rclick [7] and a more recent development RNAhugs [19], demonstrate capability in topology-independent superposition, comprehensive benchmarking of their performance in this regard has not been undertaken, to the best of our knowledge. Moreover, US-align, standing as the state-of-the-art tool for sequentially-ordered superposition, also exhibits proficiency in topology-independent superposition, although this aspect was not addressed in the original paper [2].…”

“…The greatest challenge of the RNA 3D structure alignment problem, both sequentially-ordered and topology-independent, is the exponential time complexity of the computational problem [2]. Currently, this is being handled either by employing fast but simple heuristics [2] or by relying on intricate but slow ones [19]. Furthermore, the problem of detecting backbone-permuted RNA 3D structure similarities has not been previously explored.…”