Login / Signup

Evaluation of the stereochemical quality of predicted RNA 3D models in the RNA-Puzzles submissions.

Francisco CarrascozaMaciej AntczakZhichiao MiaoEric WesthofMarta Szachniuk
Published in: RNA (New York, N.Y.) (2021)
In silico prediction is a well-established approach to derive a general shape of an RNA molecule based on its sequence or secondary structure. This paper reports an analysis of the stereochemical quality of the RNA three-dimensional models predicted using dedicated computer programs. The stereochemistry of 1,052 RNA 3D structures, including 1,030 models predicted by fully automated and human-guided approaches within 22 RNA-Puzzles challenges and reference structures, is analysed. The evaluation is based on standards of RNA stereochemistry that the Protein Data Bank requires from deposited experimental structures. Deviations from standard bond lengths and angles, planarity or chirality are quantified. A reduction in the number of such deviations should help in the improvement of RNA 3D structure modelling approaches.
Keyphrases
  • nucleic acid
  • high resolution
  • public health
  • endothelial cells
  • deep learning
  • machine learning
  • high throughput
  • small molecule