Discovery of selective bioactive small molecules by targeting an RNA dynamic ensemble

Department of Chemistry and Biophysics, University of Michigan, Ann Arbor, Michigan, USA.
Nature Chemical Biology (Impact Factor: 13). 06/2011; 7(8):553-9. DOI: 10.1038/nchembio.596
Source: PubMed


Current approaches used to identify protein-binding small molecules are not suited for identifying small molecules that can bind emerging RNA drug targets. By docking small molecules onto an RNA dynamic ensemble constructed by combining NMR spectroscopy and computational molecular dynamics, we virtually screened small molecules that target the entire structure landscape of the transactivation response element (TAR) from HIV type 1 (HIV-1). We quantitatively predict binding energies for small molecules that bind different RNA conformations and report the de novo discovery of six compounds that bind TAR with high affinity and inhibit its interaction with a Tat peptide in vitro (K(i) values of 710 nM-169 μM). One compound binds HIV-1 TAR with marked selectivity and inhibits Tat-mediated activation of the HIV-1 long terminal repeat by 81% in T-cell lines and HIV replication in an HIV-1 indicator cell line (IC(50) ∼23.1 μM).

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Available from: Aaron T Frank, Mar 19, 2015
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    ABSTRACT: Antiretroviral therapy (ART) potently suppresses HIV-1 replication, but the virus persists in quiescent infected CD4(+)T cells as a latent integrated provirus, and patients must indefinitely remain on therapy. If ART is terminated, these integrated proviruses can reactivate, driving new rounds of infection. A functional cure for HIV requires eliminating low-level ongoing viral replication that persists in certain tissue sanctuaries and preventing viral reactivation. The HIV Tat protein plays an essential role in HIV transcription by recruiting the kinase activity of the P-TEFb complex to the viral mRNA's stem-bulge-loop structure, TAR, activating transcriptional elongation. Because the Tat-mediated transactivation cascade is critical for robust HIV replication, the Tat/TAR/P-TEFb complex is one of the most attractive targets for drug development. Importantly, compounds that interfere with transcription could impair viral reactivation, low-level ongoing replication, and replenishment of the latent reservoir, thereby reducing the size of the latent reservoir pool. Here, we discuss the potential importance of transcriptional inhibitors in the treatment of latent HIV-1 disease and review recent findings on targeting Tat, TAR, and P-TEFb individually or as part of a complex. Finally, we discuss the impact of extracellular Tat in HIV-associated neurocognitive disorders and cancers.
    Current topics in microbiology and immunology 03/2015; 389. DOI:10.1007/82_2015_435
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    • "Complications relate to dynamics, the time scales of the dynamics, and whether these motions are even accessible on the timescale sampled during the molecular dynamics refinement. Moreover, RNA may populate multiple conformations under the given set of experimental conditions (Al-Hashimi and Walter 2008; Hall 2008; Baird and Ferre-D'Amare 2010; Solomatin et al. 2010; Stelzer et al. 2011). With traditional refinement , high restraint weights may lead to structural representations that are too tight, that hide dynamics, and that limit potential transformations between multiple conformations (James 2001). "
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    ABSTRACT: Restrained molecular dynamics simulations are a robust, though perhaps underused, tool for the end-stage refinement of biomolecular structures. We demonstrate their utility—using modern simulation protocols, optimized force fields, and inclusion of explicit solvent and mobile counterions—by re-investigating the solution structures of two RNA hairpins that had previously been refined using conventional techniques. The structures, both domain 5 group II intron ribozymes from yeast ai5γ and Pylaiella littoralis, share a nearly identical primary sequence yet the published 3D structures appear quite different. Relatively long restrained MD simulations using the original NMR restraint data identified the presence of a small set of violated distance restraints in one structure and a possibly incorrect trapped bulge nucleotide conformation in the other structure. The removal of problematic distance restraints and the addition of a heating step yielded representative ensembles with very similar 3D structures and much lower pairwise RMSD values. Analysis of ion density during the restrained simulations helped to explain chemical shift perturbation data published previously. These results suggest that restrained MD simulations, with proper caution, can be used to “update” older structures or aid in the refinement of new structures that lack sufficient experimental data to produce a high quality result. Notable cautions include the need for sufficient sampling, awareness of potential force field bias (such as small angle deviations with the current AMBER force fields), and a proper balance between the various restraint weights. Electronic supplementary material The online version of this article (doi:10.1007/s10858-012-9642-5) contains supplementary material, which is available to authorized users.
    Journal of Biomolecular NMR 06/2012; 53(4):321-39. DOI:10.1007/s10858-012-9642-5
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    • "In addition to being important for fundamental reasons, theoretical or hybrid theoretical–experimental methods for characterisation of structural heterogeneity can be very important in structure-based drug discovery. In the near future, as recently demonstrated by the Al-Hashimi laboratory (Stelzer et al. 2011), it will indeed be possible to improve in-silico drug screening by use of conformational ensembles, because these contain the inherent functional motion of the therapeutic target. Here we review the advances that have been made in the understanding of the motion, molecular recognition, and allostery of biomolecules by use of conformational ensembles and discuss how these powerful techniques will continue to guide our understanding of these and related important biological phenomena. "
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    ABSTRACT: We review the role conformational ensembles can play in the analysis of biomolecular dynamics, molecular recognition, and allostery. We introduce currently available methods for generating ensembles of biomolecules and illustrate their application with relevant examples from the literature. We show how, for binding, conformational ensembles provide a way of distinguishing the competing models of induced fit and conformational selection. For allostery we review the classic models and show how conformational ensembles can play a role in unravelling the intricate pathways of communication that enable allostery to occur. Finally, we discuss the limitations of conformational ensembles and highlight some potential applications for the future.
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