Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches

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.

Citation

Jiang H, Zhu L, Héliou A, Gao X, Bernauer J, et al. (2016) Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches. Drug Target miRNA: 251–275. Available: http://dx.doi.org/10.1007/978-1-4939-6563-2_18.

Sponsors

This work is supported by the Hong Kong Research Grant Council [grant numbers 16302214, 609813, HKUST C6009-15G, AoE/ M-09/12, M-HKUST601/13, and T13-607/12R to X.H.] and the National Science Foundation of China [grant number 21273188 to X.H.]. The work is also supported by a grant from the PROCOREFrance/ Hong Kong Joint Research Scheme sponsored by the Research Grants Council and the Consulate General of France in Hong Kong (F-HK29/11T) (X.H. and J.B.). X.G. was supported by funding from King Abdullah University of Science and Technology. This research made use of the resources of the Supercomputing Laboratory at King Abdullah University of Science and Technology.