Jiang Hanlun, Zhu Lizhe, Héliou Amélie, Gao Xin, Bernauer Julie, Huang Xuhui
Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, Washington, 98195, USA.
Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.
Methods Mol Biol. 2017;1517:251-275. doi: 10.1007/978-1-4939-6563-2_18.
MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.
微小RNA（miRNA）与AGO蛋白共同形成RNA诱导沉默复合体（RISC），该复合体在基因表达调控中发挥着至关重要的作用。因此，阐明AGO-miRNA识别的潜在机制不仅对于深入理解miRNA功能具有重要意义，而且对于开发针对miRNA的新药也具有启发作用。在本章中，我们介绍一种结合分子动力学（MD）模拟、马尔可夫状态模型（MSM）和蛋白质-RNA对接的计算方法，以研究AGO-miRNA识别。由MD模拟构建的MSM可以在生物学相关的时间尺度上阐明AGO的构象动力学。然后，蛋白质-RNA对接可以有效地识别miRNA在几何上可接近的AGO构象。以我们最近关于人类AGO2的研究工作为例，我们详细解释了我们方法的原理和工作流程。这种结合方法在揭示大型、灵活且复杂的生物分子之间的分子识别机制方面，有望对实验起到补充作用。
