Year: 2017
Type: article
Abstract: BACKGROUND: The sequence of nucleotides in an RNA determines the possible base pairs for an RNA fold and thus also determines the overall shape and function of an RNA. The Swellix program presented here combines a helix abstraction with a combinatorial approach to the RNA folding problem in order to compute all possible non-pseudoknotted RNA structures for RNA sequences. The Swellix program builds on the Crumple program and can include experimental constraints on global RNA structures such as the minimum number and lengths of helices from crystallography, cryoelectron microscopy, or in vivo crosslinking and chemical probing methods. RESULTS: The conceptual advance in Swellix is to count helices and generate all possible combinations of helices rather than counting and combining base pairs. Swellix bundles similar helices and includes improvements in memory use and efficient parallelization. Biological applications of Swellix are demonstrated by computing the reduction in conformational space and entropy due to naturally modified nucleotides in tRNA sequences and by motif searches in Human Endogenous Retroviral (HERV) RNA sequences. The Swellix motif search reveals occurrences of protein and drug binding motifs in the HERV RNA ensemble that do not occur in minimum free energy or centroid predicted structures. CONCLUSIONS: Swellix presents significant improvements over Crumple in terms of efficiency and memory use. The efficient parallelization of Swellix enables the computation of sequences as long as 418 nucleotides with sufficient experimental constraints. Thus, Swellix provides a practical alternative to free energy minimization tools when multiple structures, kinetically determined structures, or complex RNA-RNA and RNA-protein interactions are present in an RNA folding problem.
Source: BMC Bioinformatics
Authors: Nathan Sloat, Jui-Wen Liu, Susan J. Schroeder
Institution: University of Oklahoma
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,990
Funders: National Science Foundation, Houston Advanced Research Center, Oklahoma Center for the Advancement of Science and Technology, National Institutes of Health, University of Illinois at Urbana-Champaign, Supercomputing Center for Education and Research, University of Oklahoma, National Institute of General Medical Sciences
Awards: Leadership Class Scientific and Engineering Computing: Breaking Through the Limits, HARC Center: HIV Accessory and Regulatory Complexes, G2952167421, CAREER: Advancing Viral RNA Structure Prediction, Sustained-Petascale In Action: Blue Waters Enabling Transformative Science And Engineering, G5367696895, G8324313409, Predicting viral RNA structure, function and drug targets
OpenAlex ID: W2768535008