High-performance virtual screening by targeting a high-resolution RNA dynamic ensemble

Abstract

Dynamic ensembles hold great promise in advancing RNA-targeted drug discovery. Here, we subjected the transactivation response element (TAR) RNA from human immunodeficiency virus type-1 to experimental high-throughput screening against ~100,000 drug-like small molecules. Results were augmented with 170 known TAR-binding molecules and used to generate sub-libraries optimized for evaluating enrichment when virtually screening (VS) a dynamic ensemble of TAR determined by combining NMR spectroscopy data and molecular dynamics (MD) simulations. Ensemble-based VS scores molecules with an area under the receiver operator characteristic curve of ~0.85-0.94 and with ~40-75% of all hits falling within the top 2% of scored molecules. The enrichment decreased significantly for ensembles generated from the same MD simulations without input NMR data and for other control ensembles. The results demonstrate that experimentally determined RNA ensembles can significantly enrich libraries with true hits, and that the degree of enrichment is dependent on the accuracy of the ensemble.

Dynamic ensemble of HIV-1 RRE stem IIB reveals non-native conformations that disrupt the Rev binding site

“…A similar approach was used to prepare site labeled RREII ( 15 N3-U72-RREII, 13 C6-U72-RREII and 13 C8-G71-RREII) using 13 (Table S3) using seven delay times between 0 and 60 ms (73). Peak intensities for each delay time point were obtained using NMRPipe and fit to a monoexponential decay function using in-house python script to calculate R 1ρ values (74).…”

“…Recognizing that the ES1 population in RREIIB is quite high (p B ~18%), we reasoned that it may be possible to directly observe ES1 in RREII provided that specific sites were 13 C/ 15 N labeled to aid observation of resonances belonging to the minor ES populations from the overwhelming excess of resonances belonging to the dominant GS. If exchange in RREII was slow on the NMR timescale, it should be feasible to directly observe the chemical shifts of ES1 and thereby also estimate its population (Fig.…”

“…The biological activities of nearly all non-coding RNAs depend on these dynamics. For example, binding of ligands, proteins, other RNAs, or changes in physiological conditions such as temperature can favor specific conformations in the ensemble and cause a structure specific change in activity (13)(14)(15). Thus, a deep understanding of how RNAs function within cells requires an understanding of their dynamic behavior.…”

“…This in turn may enable the targeting of RNA in drug discovery efforts (12,13) as well as the rational design of RNA-based devices (7).…”

“…The new non-native ESs, which remodel key structural features required for Rev binding could constitute novel states for targeting with small molecules. Determining the structures of the RRE ESs would make it possible to apply ensemble-based virtual screening approaches(12,13) to identify small molecule that selectively bind the ESs. The ES-stabilizing mutants could also be subjected to high throughput screening to help identify compounds that selectively bind these non-native states.…”