An RNA Base Discrete State Model toward Tertiary Structure Prediction

Abstract

We report a new ribonucleic acid (RNA) base discrete state model, which was first developed in our lab and designed to provide an efficient and accurate way of representing RNA structures toward RNA three-dimensional structure predictions. Since RNA free energy is largely determined by base pairs and base stackings instead of backbone trajectories, we directly model the RNA base configurations with respect to its previous one along the sequence. This is in sharp contrast with all previous works where the backbone trace was represented. To test how faithfully the discrete model can reproduce the chain trace in continuous space, we randomly select partial chains from the native structure of 23S ribosome RNA and re-grow them. The rms distance of the re-grown structures from the native ones is ∼ 1.7 Å for an optimized 16-state discrete model and gradually increases to ∼ 3.3 Å for long chains of length 50. The efficiency is also good, e.g. the program will finish within several tens of second for long loops of length 50. Our model may facilitate the RNA three-dimensional structure predictions in the near future when combined with appropriate free energy evaluation methods.