The methylase METTL3 is the writer enzyme of the N 6 -methyladenosine (m 6 A) modification of RNA. Using a structure-based drug discovery approach, we identified a METTL3 inhibitor with potency in a biochemical assay of 280 nM, while its enantiomer is 100 times less active. We observed a dose-dependent reduction in the m 6 A methylation level of mRNA in several cell lines treated with the inhibitor already after 16 h of treatment, which lasted for at least 6 days. Importantly, the prolonged incubation (up to 6 days) with the METTL3 inhibitor did not alter levels of other RNA modifications (i. e., m 1 A, m 6 A m , m 7 G), suggesting selectivity of the developed compound towards other RNA methyltransferases.

Three YTH-domain family proteins (YTHDF1, YTHDF2, and YTHDF3) recognize the N6-methyladenosine (m6A) modification of mRNA in cells. However, the redundancy of their cellular functions has been disputed. We investigate their interactions with m6A-containing RNA using X-ray crystallography and molecular dynamics (MD). The new X-ray structures and MD simulations show that the three proteins share identical interactions with the m6A-containing RNA and have similar intrinsic plasticity, thus evidencing the redundant roles of the three proteins in cellular functions.

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Ribonucleic acid (RNA) molecules play central roles in a variety of biological processes and, hence, are attractive targets for therapeutic intervention. In recent years, molecular docking techniques have become one of the most popular and successful approaches in drug discovery; however, almost all docking programs are protein based. The adaptability of popular docking programs in RNA world has not been systematically evaluated. This paper describes the comprehensive evaluation of two widely used protein-based docking programs--GOLD and Glide--for their docking and virtual screening accuracies against RNA targets. Using multiple docking strategies, both GOLD 4.0 and Glide 5.0 successfully reproduced most binding modes of the 60 tested RNA complexes. Applying different docking/scoring combinations, significant enrichments from the simulated virtual and fragment screening experiments were achieved against tRNA decoding A site of 16S rRNA (rRNA A-site). Our study demonstrated that current protein-based docking programs can fulfill general docking tasks against RNA, and these programs are very helpful in RNA-based drug discovery and design.