RNA-Puzzles Round V: Models from LCBio group

Nithin, Chandran;Pilla, Smita Priyadarshini;Kurciński, Mateusz;Kmiecik, Sebastian

Description

This dataset comprises the three-dimensional RNA structure models submitted by the LCBio group for the RNA-Puzzles Round V blind prediction challenge. The collection includes computational predictions for seven distinct RNA targets: PZ30, PZ31, PZ32, PZ33, PZ34, PZ35, and PZ36.The models were generated using the LCBio group's pipeline, which combines consensus secondary structure prediction with coarse-grained 3D modeling and refinement. The LCBio approach focuses on: - Secondary Structure Prediction: A consensus secondary structure was derived using multiple methods (ViennaRNA, RNAStructure, ProbKnot, CentroidFold, ContraFold, IPknot) and homologous sequence information from Rfam and RNAcentral. - 3D Modeling: The SimRNA program was used for 3D structure modeling via replica-exchange Monte Carlo simulations, performed both with and without secondary structure restraints. - Refinement: The lowest-energy coarse-grained models were selected and refined using the QRNAs program to reconstruct all-atom details and mitigate modeling errors. - Homology Modeling: For specific targets like PZ30, homology modeling was employed based on identified structural homologs.Each model reflects the group's methodology in predicting tertiary structures from primary sequences, contributing to the community-wide effort to improve RNA structure prediction accuracy. These submissions were part of the RNA-Puzzles Round V assessment, a blind challenge where participants predict structures before the experimental results are released. This dataset provides a valuable resource for researchers interested in benchmarking RNA folding software, analyzing prediction performance, or studying the structural characteristics of the specific targets involved in this round of the challenge.

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Mentions (0)

Metrics

Dataset Index

0.4

FAIR Score

69%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Mendeley Data

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Artificial Intelligence

Field

Computer Science

Domain

Physical Sciences

Confidence Score

49%

Source

Scholar Data Model

Keywords

Structural BiologyBioinformaticsFOS: Computer and information sciencesRNA StructureComputational Biology

Normalization Factors

FT

63.46

CTw

1.00

MTw

1.00