Röder Konstantin, Stirnemann Guillaume, Faccioli Pietro, Pasquali Samuela
Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
CNRS Laboratoire de Biochimie Théorique, Institut de Biologie Physico-Chimique, PSL University, Université de Paris, 13 rue Pierre et Marie Curie, Paris 75005, France.
QRB Discov. 2022 Oct 17;3:e21. doi: 10.1017/qrd.2022.19. eCollection 2022.
While RNA folding was originally seen as a simple problem to solve, it has been shown that the promiscuous interactions of the nucleobases result in structural polymorphism, with several competing structures generally observed for non-coding RNA. This inherent complexity limits our understanding of these molecules from experiments alone, and computational methods are commonly used to study RNA. Here, we discuss three advanced sampling schemes, namely Hamiltonian-replica exchange molecular dynamics (MD), ratchet-and-pawl MD and discrete path sampling, as well as the HiRE-RNA coarse-graining scheme, and highlight how these approaches are complementary with reference to recent case studies. While all computational methods have their shortcomings, the plurality of simulation methods leads to a better understanding of experimental findings and can inform and guide experimental work on RNA polymorphism.
虽然RNA折叠最初被视为一个易于解决的简单问题，但研究表明，核碱基的混杂相互作用会导致结构多态性，对于非编码RNA通常会观察到几种相互竞争的结构。这种固有的复杂性仅通过实验限制了我们对这些分子的理解，因此计算方法通常用于研究RNA。在这里，我们讨论三种先进的采样方案，即哈密顿复制交换分子动力学（MD）、棘齿MD和离散路径采样，以及HiRE-RNA粗粒化方案，并参照最近的案例研究强调这些方法如何相互补充。虽然所有计算方法都有其缺点，但多种模拟方法有助于更好地理解实验结果，并可为RNA多态性的实验工作提供信息和指导。
