A-P.34: Reference-Free Ranking Method for RNA 3D Models
Authors
Tomasz Żok
Poznan University of Technology
Maciej Antczak
Poznan University of Technology,Institute of Bioorganic Chemistry, Polish Academy of Sciences
Marta Szachniuk
Poznań University of Technology,Institute of Bioorganic Chemistry, Polish Academy of Sciences
Keywords
RNA modeling, RNA structure prediction, reference-free RNA modelling
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In current times, researchers have started to notice the importance of understanding the structure and function of RNA. This prompts the growth of the number of attempts in RNA 3D structure prediction. As the knowledge of RNA molecules grows, we can use the advancements made in protein structure prediction to improve our prognoses in the RNA field; however, it faces a challenge – produced models need to have their quality assessed. Multiple or sometimes even thousands of models can be generated from a single input. The traditional method for determining the quality of the model is based on energy terms calculation with force fields or coarse-grained statistical potentials. The main issue with such an approach is that the energy landscape usually contains many local minima, which leads to inconclusive results.
Therefore, we propose a different approach for ranking multiple 3D models of the same RNA sequence. The basis for this algorithm is the analysis of the base pairs and stacking interactions within them. A consensus secondary structure is built from the extracted data, and each model has its interaction network ranked against the aforementioned consensus to provide a final ranking.
Our method has been benchmarked on datasets used in RNA 3D modeling to verify its quality in comparison to the state-of-the-art energy-based evaluations. The entire system has been made publicly available at https://rnative.cs.put.poznan.pl/, and published in Bioinformatics (https://doi.org/10.1093/bioinformatics/btaf601)
Co-authors: Maciej Antczak, Marta Szachniuk, Tomasz Zok
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