Critical role of backbone coordination in the mRNA recognition by RNA induced silencing complex

Lizhe Zhu, Hanlun Jiang, Siqin Cao, Ilona Christy Unarta, Xin Gao, Xuhui Huang

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

AbstractDespite its functional importance, the molecular mechanism underlying target mRNA recognition by Argonaute (Ago) remains largely elusive. Based on extensive all-atom molecular dynamics simulations, we constructed quasi-Markov State Model (qMSM) to reveal the dynamics during recognition at position 6-7 in the seed region of human Argonaute 2 (hAgo2). Interestingly, we found that the slowest mode of motion therein is not the gRNA-target base-pairing, but the coordination of the target phosphate groups with a set of positively charged residues of hAgo2. Moreover, the ability of Helix-7 to approach the PIWI and MID domains was found to reduce the effective volume accessible to the target mRNA and therefore facilitate both the backbone coordination and base-pair formation. Further mutant simulations revealed that alanine mutation of the D358 residue on Helix-7 enhanced a trap state to slow down the loading of target mRNA. Similar trap state was also observed when wobble pairs were introduced in g6 and g7, indicating the role of Helix-7 in suppressing non-canonical base-paring. Our study pointed to a general mechanism for mRNA recognition by eukaryotic Agos and demonstrated the promise of qMSM in investigating complex conformational changes of biomolecular systems.
Original languageEnglish (US)
JournalCommunications Biology
Volume4
Issue number1
DOIs
StatePublished - Nov 30 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-12-14
Acknowledged KAUST grant number(s): FCC/1/1976-04, URF/1/4098-01-01, URF/1/4352-01-01, URF/1/4379-01-0
Acknowledgements: We thank Dr. Fu Kit Sheong for fruitful discussions about the Argonaute proteins. This work was supported by the Hong Kong Research Grant Council [16303919, 16307718, and 16318816] to X.H., Shenzhen Science and Technology Innovation Committee [JCYJ20200109150003938] to L.Z., the National Science Foundation of China General Fund [31971179] to L.Z., research fund from Warshel Institute for Computational Biology and Longgang District Shenzhen to L.Z., and King Abdullah University of Science and Technology (KAUST) under award number FCC/1/1976-04-01, URF/1/4098-01-01, URF/1/4352-01-01, and URF/1/4379-01-01 to X.G.. This research made use of the resources of the Supercomputing Laboratory at KAUST.

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