PARSEbp: Pairwise Agreement-based RNA Scoring with Emphasis on Base Pairings

Tarafder, S.; Bhattacharya, D.

doi:10.1101/2025.10.13.682106

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bioRxiv · 10.1101/2025.10.13.682106

PARSEbp: Pairwise Agreement-based RNA Scoring with Emphasis on Base Pairings

Tarafder, S.·Bhattacharya, D.

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Abstract

MotivationHigh-fidelity scoring of RNA 3D structures remains a major challenge in RNA structure prediction and conformational sampling. While single-model methods for scoring RNA structures can capture individual structural features, they fail to capture the broader structural consensus within a conformational ensemble, limiting their effectiveness in ranking and model selection. ResultsWe present PARSEbp, a fast and effective multi-model RNA scoring method that integrates pairwise structural agreement across the conformational ensemble with base pairing consistency. By leveraging both alignment-based global structural agreement at the 3D level and base pairing consistency at the 2D level, PARSEbp efficiently constructs a consensus similarity matrix from which per-structure accuracy scores are computed. Tested on 16th Critical Assessment of Structure Prediction (CASP16) RNA targets, PARSEbp significantly outperforms existing single- and multi-model RNA scoring functions, including traditional statistical potentials, state-of-the-art deep learning methods, and consensus-based approaches, as well as a baseline variant of PARSEbp without the emphasis on base pairings, across a wide range of complementary assessment metrics. AvailabilityPARSEbp is freely available at https://github.com/Bhattacharya-Lab/PARSEbp.

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Tarafder, S., Bhattacharya, D.. 2025-10-14. PARSEbp: Pairwise Agreement-based RNA Scoring with Emphasis on Base Pairings. https://doi.org/10.1101/2025.10.13.682106

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