Unknotting RNA: A Method to Resolve Computational Artifacts
Simón Poblete, Mikolaj Mlynarczyk, Marta Szachniuk.
Abstract
To summarize the existing evidence from double-blind randomized controlled trials (RCTs) and cohort studies regarding the effects of biologic agents for the treatment of large vessel vasculitis.
Introduction
RNA 3D structure prediction often encounters entanglements, computational artifacts that complicate structural models, resulting in their exclusion from further studies despite the potentially accurate prediction of regions outside the entanglement. This study presents a protocol aimed at resolving such issues in RNA models while preserving the overall 3D fold and structural integrity. By employing the SPQR coarse-grained model and short Molecular Dynamics simulations, the protocol imposes energy terms that enable selective modifications to disentangle structures without causing significant distortions.
Materials and Methods:
To test the disentanglement protocol, we downloaded RNA 3D models predicted in the CASP15 and RNA-Puzzles competitions, available in their online repositories as of January 2024.
The RNA-Puzzles dataset (https://github.com/RNA-Puzzles) contained 1,028 models targeting 22 RNA sequences in rounds I-IV of RNA-Puzzles. From this collection, we discarded redundant structures and blobs, focusing our analysis on the remaining models for the entanglements. Specifically, among the 122 entangled predictions from CASP15, 21 were redundant, 8 were counted as blobs, and 4 were discarded due to clear artifacts in their coordinates
Discussion
We applied the disentanglement protocol to each of the 195 entangled structures from the benchmark set (the resulting structures are available at doi: 10.5281/zenodo.13840004). Table 1 presents the aggregate results of this experiment. The protocol successfully resolved approximately half (49%) of the entanglements in eligible RNA structures, with 72% of successful cases coming from CASP15 predictions and 28% from RNA-Puzzles.
Citation: Poblete S, Mlynarczyk M, Szachniuk M (2025) Unknotting RNA: A method to resolve computational artifacts. PLoS Comput Biol 21(3): e1012843. https://doi.org/10.1371/journal.pcbi.1012843
Editor: Dina Schneidman, Hebrew University of Jerusalem, ISRAEL
Received: October 5, 2024; Accepted: February 2, 2025; Published: March 20, 2025.
Copyright: © 2025 Poblete et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: RNA models predicted in CASP15 are available at https://predictioncenter.org/download_area/CASP15/predictions/RNA/, while those of RNA-Puzzles at http://www.rnapuzzles.org/results/. RNA 3D models with entanglements resolved using the SPQR-based protocol are available at doi: 10.5281/zenodo.13840004. RNAspider is accessible at https://rnaspider.cs.put.poznan.pl/ and SPQR at doi: 10.5281/zenodo.14658435 and https://github.com/srnas/spqr.
Funding: SP was supported by the Fondecyt Regular project No. 1231071 and Centro Ciencia & Vida, FB210008, Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia de ANID (https://anid.cl). MM and MS were supported by the statutory funds of Poznan University of Technology (https://www.put.poznan.pl/en) and the Institute of Bioorganic Chemistry, Polish Academy of Sciences (https://www.ibch.poznan.pl/en.html). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
