Markov state models reveal a two-step mechanism of miRNA loading into the human argonaute protein: selective binding followed by structural re-arrangement

H Jiang, FK Sheong, L Zhu, X Gao… - PLoS computational …, 2015 - journals.plos.org
PLoS computational biology, 2015journals.plos.org
Argonaute (Ago) proteins and microRNAs (miRNAs) are central components in RNA
interference, which is a key cellular mechanism for sequence-specific gene silencing.
Despite intensive studies, molecular mechanisms of how Ago recognizes miRNA remain
largely elusive. In this study, we propose a two-step mechanism for this molecular
recognition: selective binding followed by structural re-arrangement. Our model is based on
the results of a combination of Markov State Models (MSMs), large-scale protein-RNA …
Argonaute (Ago) proteins and microRNAs (miRNAs) are central components in RNA interference, which is a key cellular mechanism for sequence-specific gene silencing. Despite intensive studies, molecular mechanisms of how Ago recognizes miRNA remain largely elusive. In this study, we propose a two-step mechanism for this molecular recognition: selective binding followed by structural re-arrangement. Our model is based on the results of a combination of Markov State Models (MSMs), large-scale protein-RNA docking, and molecular dynamics (MD) simulations. Using MSMs, we identify an open state of apo human Ago-2 in fast equilibrium with partially open and closed states. Conformations in this open state are distinguished by their largely exposed binding grooves that can geometrically accommodate miRNA as indicated in our protein-RNA docking studies. miRNA may then selectively bind to these open conformations. Upon the initial binding, the complex may perform further structural re-arrangement as shown in our MD simulations and eventually reach the stable binary complex structure. Our results provide novel insights in Ago-miRNA recognition mechanisms and our methodology holds great potential to be widely applied in the studies of other important molecular recognition systems.
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