School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC 29634, United States.
School of Mathematics, Georgia Institute of Technology, Atlanta, GA 30332-0160, United States.
J Struct Biol. 2020 Apr 1;210(1):107475. doi: 10.1016/j.jsb.2020.107475. Epub 2020 Feb 4.
Prediction of RNA base pairings yields insight into molecular structure, and therefore function. The most common methods predict an optimal structure under the standard thermodynamic model. One component of this model is the equation which governs the cost of branching, where three or more helical "arms" radiate out from a multiloop (also known as a junction). The multiloop initiation equation has three parameters; changing those values can significantly alter the predicted structure. We give a complete analysis of the prediction accuracy, stability, and robustness for all possible parameter combinations for a diverse set of tRNA sequences, and also for 5S rRNA. We find that the accuracy can often be substantially improved on a per sequence basis. However, simultaneous improvement within families, and most especially between families, remains a challenge.
预测 RNA 碱基配对可以深入了解分子结构，从而了解其功能。最常用的方法是根据标准热力学模型预测最优结构。该模型的一个组成部分是控制分支成本的方程，其中三个或更多的螺旋“臂”从多环（也称为连接点）辐射出来。多环起始方程有三个参数；改变这些值可以显著改变预测的结构。我们对一组不同的 tRNA 序列和 5S rRNA 的所有可能参数组合的预测准确性、稳定性和稳健性进行了全面分析。我们发现，在每个序列的基础上，准确性通常可以得到显著提高。然而，在家族内部以及最重要的是在家族之间同时提高，仍然是一个挑战。
