Sequence-Informed Geometric Evaluation of RNA 3D Structures
Computational RNA structure pipelines generate many candidate conformations for the same sequence. Reliable evaluation therefore requires more than recognising plausible geometry, it requires determining whether that geometry is compatible with the sequence. We introduce SIRGE, a sequence-informed geometric evaluator that conditions structural representations on nucleotide embeddings from a pretrained RNA language model. Early results show that SIRGE outperforms established evaluators in Kendall--$τ$ alignment, Top-1 selection, and Top-3 ranking. Controlled comparisons further show that sequence conditioning corrects errors made by an otherwise matched geometric model and improves target-...
| Authors | Andrea Zerio, Yighua Yao, Alessandro Micheli et al. |
|---|---|
| Primary category | q-bio.BM |
| Published | 9 September 2026 |
| Last updated at source | 9 September 2026 |
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