Discovery of ligands for a novel target, the human telomerase RNA, based on flexible-target virtual screening and NMR

Biophysical Analysis of Small Molecule Binding to Viral RNA Structures

RNA molecules are essential for carrying genetic information and regulating gene expression in most organisms including human pathogenic RNA and relate retro viruses. Targeting viral RNA (vRNA) structures provide broad opportunities to develop chemical tools to probe molecular virology and to discover novel targets for therapeutic intervention. An increasing number of RNA binding small molecules are being identified, stimulating increased interests in small molecule drug discovery for RNA targets. In this chapter, we describe protocols to characterize and robustly validate vRNA-small molecule (vRNA-sm) interactions starting from vRNA sample preparation, followed by small molecule screening against vRNA targets and finally to validating the vRNA-sm interactions via NMR spectroscopy and calorimetric titrations.

RNA-ligand molecular docking: advances and challenges

With rapid advances in computer algorithms and hardware, fast and accurate virtual screening has led to a drastic acceleration in selecting potent small molecules as drug candidates. Computational modeling of RNA-small molecule interactions has become an indispensable tool for RNA-targeted drug discovery. The current models for RNA-ligand binding have mainly focused on the docking-and-scoring method. Accurate docking and scoring should tackle four crucial problems: (1) conformational flexibility of ligand, (2) conformational flexibility of RNA, (3) efficient sampling of binding sites and binding poses, and (4) accurate scoring of different binding modes. Moreover, compared with the problem of protein-ligand docking, predicting ligand binding to RNA, a negatively charged polymer, is further complicated by additional effects such as metal ion effects. Thermodynamic models based on physics-based and knowledge-based scoring functions have shown highly encouraging success in predicting ligand binding poses and binding affinities. Recently, kinetic models for ligand binding have further suggested that including dissociation kinetics (residence time) in ligand docking would result in improved performance in estimating in vivo drug efficacy. More recently, the rise of deep-learning approaches has led to new tools for predicting RNA-small molecule binding. In this review, we present an overview of the recently developed computational methods for RNA-ligand docking and their advantages and disadvantages.

Small Molecule Screening Discovers Compounds that Reduce FMRpolyG Protein Aggregates and Splicing Defect Toxicity in Fragile X-Associated Tremor/Ataxia Syndrome

Expansion of CGG trinucleotide repeats in 5' untranslated region of the FMR1 gene is the causative mutation of neurological diseases such as fragile X syndrome (FXS), fragile X-associated tremor/ataxia syndrome (FXTAS), and ovarian disorder such as fragile X-associated primary ovarian insufficiency (FXPOI). CGG repeats containing FMR1 transcripts form the toxic ribonuclear aggregates, abrupt pre-mRNA splicing, and cause repeat-associated non-AUG translation, leading to the disease symptoms. Here, we utilized a small molecule library of ~ 250,000 members obtained from the National Cancer Institute (NCI) and implemented a shape-based screening approach to identify the candidate small molecules that mitigate toxic CGG RNA-mediated pathogenesis. The compounds obtained from screening were further assessed for their affinity and selectivity towards toxic CGG repeat RNA by employing fluorescence-binding experiment and isothermal calorimetry titration assay. Three candidate molecules B1, B4, and B11 showed high affinity and selectivity for expanded CGG repeats RNA. Further, NMR spectroscopy, gel mobility shift assay, CD spectroscopy, UV-thermal denaturation assay, and molecular docking affirmed their high affinity and selectivity for toxic CGG RNAs. Next, these lead compounds selectively improved the pre-mRNA alternative splicing defects with no perturbation in global splicing efficacy and simultaneously reduced the FMR1polyG protein aggregate formation without affecting the downstream expression of the gene. Taken together these findings, we addressed compound B1, B4, and B11 as potential lead molecules for developing promising therapeutics against FXTAS. Herein, this study, we have utilized shape similarity approach to screen the NCI library and found out the potential candidate which improves the pre-mRNA splicing defects and reduces FMR1polyG aggregations.

Target-Directed Approaches for Screening Small Molecules against RNA Targets

RNA molecules have a variety of cellular functions that can drive disease pathologies. They are without a doubt one of the most intriguing yet controversial small-molecule drug targets. The ability to widely target RNA with small molecules could be revolutionary, once the right tools, assays, and targets are selected, thereby defining which biomolecules are targetable and what constitutes drug-like small molecules. Indeed, approaches developed over the past 5-10 years have changed the face of small molecule-RNA targeting by addressing historic concerns regarding affinity, selectivity, and structural dynamics. Presently, selective RNA-protein complex stabilizing drugs such as branaplam and risdiplam are in clinical trials for the modulation of SMN2 splicing, compounds identified from phenotypic screens with serendipitous outcomes. Fully developing RNA as a druggable target will require a target engagement-driven approach, and evolving chemical collections will be important for the industrial development of this class of target. In this review we discuss target-directed approaches that can be used to identify RNA-binding compounds and the chemical knowledge we have today of small-molecule RNA binders.

Drugging the RNA World

Although we live in the remnants of an RNA world, the world of drug discovery and chemical probes is firmly protein-centric. Developing highly selective small molecules targeting RNA is often considered to be an insurmountable challenge. Our goal is to demystify the design of such compounds. In this review, we describe various approaches to design small molecules that target RNA from sequence and the application of these compounds in RNA biology, with a focus on inhibition of human RNA-protein complexes. We have developed a library-versus-library screening approach to define selective RNA-small-molecule binding partners and applied them to disease-causing RNAs, in particular noncoding oncogenic RNAs and expanded RNA repeats, to modulate their biology in cells and animals. We also describe the design of new types of small-molecule probes that could broadly decipher the mysteries of RNA in cells.

Shortening the HIV-1 TAR RNA Bulge by a Single Nucleotide Preserves Motional Modes over a Broad Range of Time Scales

Helix-junction-helix (HJH) motifs are flexible building blocks of RNA architecture that help define the orientation and dynamics of helical domains. They are also frequently involved in adaptive recognition of proteins and small molecules and in the formation of tertiary contacts. Here, we use a battery of nuclear magnetic resonance techniques to examine how deleting a single bulge residue (C24) from the human immunodeficiency virus type 1 (HIV-1) transactivation response element (TAR) trinucleotide bulge (U23-C24-U25) affects dynamics over a broad range of time scales. Shortening the bulge has an effect on picosecond-to-nanosecond interhelical and local bulge dynamics similar to that casued by increasing the Mg(2+) and Na(+) concentration, whereby a preexisting two-state equilibrium in TAR is shifted away from a bent flexible conformation toward a coaxial conformation, in which all three bulge residues are flipped out and flexible. Surprisingly, the point deletion minimally affects microsecond-to-millisecond conformational exchange directed toward two low-populated and short-lived excited conformational states that form through reshuffling of bases pairs throughout TAR. The mutant does, however, adopt a slightly different excited conformational state on the millisecond time scale, in which U23 is intrahelical, mimicking the expected conformation of residue C24 in the excited conformational state of wild-type TAR. Thus, minor changes in HJH topology preserve motional modes in RNA occurring over the picosecond-to-millisecond time scales but alter the relative populations of the sampled states or cause subtle changes in their conformational features.

New prospects for targeting telomerase beyond the telomere

Telomerase activity is responsible for the maintenance of chromosome end structures (telomeres) and cancer cell immortality in most human malignancies, making telomerase an attractive therapeutic target. The rationale for targeting components of the telomerase holoenzyme has been strengthened by accumulating evidence indicating that these molecules have extra-telomeric functions in tumour cell survival and proliferation. This Review discusses current knowledge of the biogenesis, structure and multiple functions of telomerase-associated molecules intertwined with recent advances in drug discovery approaches. We also describe the fertile ground available for the pursuit of next-generation small-molecule inhibitors of telomerase.

Methods to enable the design of bioactive small molecules targeting RNA

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including structure-activity relationships through sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome.

Sequence-based design of bioactive small molecules that target precursor microRNAs

Oligonucleotides are designed to target RNA using base pairing rules, but they can be hampered by poor cellular delivery and nonspecific stimulation of the immune system. Small molecules are preferred as lead drugs or probes but cannot be designed from sequence. Herein, we describe an approach termed Inforna that designs lead small molecules for RNA from solely sequence. Inforna was applied to all human microRNA hairpin precursors, and it identified bioactive small molecules that inhibit biogenesis by binding nuclease-processing sites (44% hit rate). Among 27 lead interactions, the most avid interaction is between a benzimidazole (1) and precursor microRNA-96. Compound 1 selectively inhibits biogenesis of microRNA-96, upregulating a protein target (FOXO1) and inducing apoptosis in cancer cells. Apoptosis is ablated when FOXO1 mRNA expression is knocked down by an siRNA, validating compound selectivity. Markedly, microRNA profiling shows that 1 only affects microRNA-96 biogenesis and is at least as selective as an oligonucleotide.

Structure-based virtual screening for the identification of RNA-binding ligands

Structure-based virtual screening exploits the 3D structure of the target as a template for the discovery of new ligands. It is a key method for hit discovery and was originally developed for protein targets. Recently, this method has also been applied to RNA targets. This chapter gives an overview of this method and its application in the context of ligand discovery for RNA. In addition, it describes in detail how to conduct virtual screening for RNA targets, making use of software that is free for noncommercial use. Some advice on how to avoid common pitfalls in virtual screening is also given.

Rational design of chemical genetic probes of RNA function and lead therapeutics targeting repeating transcripts

RNA is an important yet vastly underexploited target for small molecule chemical probes or lead therapeutics. Small molecules have been used successfully to modulate the function of the bacterial ribosome, viral RNAs and riboswitches. These RNAs are either highly expressed or can be targeted using substrate mimicry, a mainstay in the design of enzyme inhibitors. However, most cellular RNAs are neither highly expressed nor have a lead small molecule inhibitor, a significant challenge for drug discovery efforts. Herein, I describe the design of small molecules targeting expanded repeating transcripts that cause myotonic muscular dystrophy (DM). These test cases illustrate the challenges of designing small molecules that target RNA and the advantages of targeting repeating transcripts. Lastly, I discuss how small molecules might be more advantageous than oligonucleotides for targeting RNA.

Novel insights of structure-based modeling for RNA-targeted drug discovery

Substantial progress in RNA biology highlights the importance of RNAs (e.g., microRNAs) in diseases and the potential of targeting RNAs for drug discovery. However, the lack of RNA-specific modeling techniques demands the development of new tools for RNA-targeted rational drug design. Herein, we implemented integrated approaches of accurate RNA modeling and virtual screening for RNA inhibitor discovery with the most comprehensive evaluation to date of five docking and 11 scoring methods. For the first time, statistical analysis was heavily employed to assess the significance of our predictions. We found that GOLD:GOLD Fitness and rDock:rDock_solv could accurately predict the RNA ligand poses, and ASP rescoring further improved the ranking of ligand binding poses. Due to the weak correlations (R(2) < 0.3) of existing scoring with experimental binding affinities, we implemented two new RNA-specific scoring functions, iMDLScore1 and iMDLScore2, and obtained better correlations with R(2) = 0.70 and 0.79, respectively. We also proposed a multistep virtual screening approach and demonstrated that rDock:rDock_solv together with iMDLScore2 rescoring obtained the best enrichment on the flexible RNA targets, whereas GOLD:GOLD Fitness combined with rDock_solv rescoring outperformed other methods for rigid RNAs. This study provided practical strategies for RNA modeling and offered new insights into RNA-small molecule interactions for drug discovery.

Virtual Screening for RNA-Interacting Small Molecules

Computational virtual screening is useful and powerful strategy for rapid discovery of small biologically active molecules in the early stage of drug discovery. The discovery of a broad range of important biological processes involved by RNA has increased the importance of RNA as a new drug target. To apply structure-based virtual screening methods to the discovery of RNA-binding ligands, many RNA 3D structure prediction programs and optimized docking algorithms have been developed. In this chapter, a number of successful cases of virtual screening targeting RNA will be introduced.

Binding-interaction prediction of RNA-binding ligands

RNA molecules are involved in a wide range of biological processes and have been recognized as very important therapeutic targets. Mainly owing to the scarcity of information and experimental studies, the application of computational approaches and, in particular, of docking methodologies in the RNA field has developed slowly. However, in recent years the docking of RNA-binding ligands has experienced significant expansion. This article focuses attention on the docking of RNA-binding ligands, analyzing the development of RNA-docking approaches, the reliability of the docking methods and, finally, evaluating the results of docking-based virtual screening studies reported in the literature.

Binding characteristics of small molecules that mimic nucleocapsid protein-induced maturation of stem-loop 1 of HIV-1 RNA

As a retrovirus, the human immunodeficiency virus (HIV-1) packages two copies of the RNA genome as a dimer in the infectious virion. Dimerization is initiated at the dimer initiation site (DIS) which encompasses stem-loop 1 (SL1) in the 5'-UTR of the genome. Study of genomic dimerization has been facilitated by the discovery that short RNA fragments containing SL1 can dimerize spontaneously without any protein factors. On the basis of the palindromic nature of SL1, a kissing loop model has been proposed. First, a metastable kissing dimer is formed via standard Watson-Crick base pairs and then converted into a more stable extended dimer by the viral nucleocapsid protein (NCp7). This dimer maturation in vitro is believed to mimic initial steps in the RNA maturation in vivo, which is correlated with viral infectivity. We previously discovered a small molecule activator, Lys-Ala-7-amido-4-methylcoumarin (KA-AMC), which facilitates dimer maturation in vitro, and determined aspects of its structure-activity relationship. In this report, we present measurements of the binding affinity of the activators and characterization of their interactions with the SL1 RNA. Guanidinium groups and increasing positive charge on the side chain enhance affinity and activity, but features in the aromatic ring at least partially decouple affinity from activity. Although KA-AMC can bind to multiple structural motifs, the NMR study showed KA-AMC preferentially binds to unique structural motifs, such as the palindromic loop and the G-rich internal loop in the SL1 RNA. NCp7 binds to SL1 only 1 order of magnitude more tightly than the best small molecule ligand tested. This study provides guidelines for the design of superior small molecules that bind to the SL1 RNA that have the potential of being developed as an antiviral by interfering with SL1-NCp7 interaction at the packaging and/or maturation stages.

Strategies for the design of RNA-binding small molecules

Bacterial ribosomal RNA is the target of clinically important antibiotics, while biologically important RNAs in viral and eukaryotic genomes present a range of potential drug targets. The physicochemical properties of RNA present difficulties for medicinal chemistry, particularly when oral availability is needed. Peptidic ligands and analysis of their RNA-binding properties are providing insight into RNA recognition. RNA-binding ligands include far more chemical classes than just aminoglycosides. Chemical functionalities from known RNA-binding small molecules are being exploited in fragment- and ligand-based projects. While targeting of RNA for drug design is very challenging, continuing advances in our understanding of the principles of RNA–ligand interaction will be necessary to realize the full potential of this class of targets.

Discovery of new inhibitors of resistant Streptococcus pneumoniae penicillin binding protein (PBP) 2x by structure-based virtual screening

Penicillin binding proteins (PBPs) are involved in the biosynthesis of the peptidoglycan layer constitutive of the bacterial envelope. They have been targeted for more than half a century by extensively derived molecular scaffolds of penicillins and cephalosporins. Streptococcus pneumoniae resists the antibiotic pressure by inducing highly mutated PBPs that can no longer bind the beta-lactam containing agents. To find inhibitors of PBP2x from Streptococcus pneumoniae (spPBP2x) with novel chemical scaffold so as to circumvent the resistance problems, a hierarchical virtual screening procedure was performed on the NCI database containing approximately 260000 compounds. The calculations involved ligand-based pharmacophore mapping studies and molecular docking simulations in a homology model of spPBP2x from the highly resistant strain 5204. A total of 160 hits were found, and 55 were available for experimental tests. Three compounds harboring two novel chemical scaffolds were identified as inhibitors of the resistant strain 5204-spPBP2x at the micromolar range.

Adaptive ligand binding by the purine riboswitch in the recognition of guanine and adenine analogs

Purine riboswitches discriminate between guanine and adenine by at least 10,000-fold based on the identity of a single pyrimidine (Y74) that forms a Watson-Crick base pair with the ligand. To understand how this high degree of specificity for closely related compounds is achieved through simple pairing, we investigated their interaction with purine analogs with varying functional groups at the 2- and 6-positions that have the potential to alter interactions with Y74. Using a combination of crystallographic and calorimetric approaches, we find that binding these purines is often facilitated by either small structural changes in the RNA or tautomeric changes in the ligand. This work also reveals that, along with base pairing, conformational restriction of Y74 significantly contributes to nucleobase selectivity. These results reveal that compounds that exploit the inherent local flexibility within riboswitch binding pockets can alter their ligand specificity.

DOCK 6: combining techniques to model RNA-small molecule complexes

With an increasing interest in RNA therapeutics and for targeting RNA to treat disease, there is a need for the tools used in protein-based drug design, particularly DOCKing algorithms, to be extended or adapted for nucleic acids. Here, we have compiled a test set of RNA-ligand complexes to validate the ability of the DOCK suite of programs to successfully recreate experimentally determined binding poses. With the optimized parameters and a minimal scoring function, 70% of the test set with less than seven rotatable ligand bonds and 26% of the test set with less than 13 rotatable bonds can be successfully recreated within 2 A heavy-atom RMSD. When DOCKed conformations are rescored with the implicit solvent models AMBER generalized Born with solvent-accessible surface area (GB/SA) and Poisson-Boltzmann with solvent-accessible surface area (PB/SA) in combination with explicit water molecules and sodium counterions, the success rate increases to 80% with PB/SA for less than seven rotatable bonds and 58% with AMBER GB/SA and 47% with PB/SA for less than 13 rotatable bonds. These results indicate that DOCK can indeed be useful for structure-based drug design aimed at RNA. Our studies also suggest that RNA-directed ligands often differ from typical protein-ligand complexes in their electrostatic properties, but these differences can be accommodated through the choice of potential function. In addition, in the course of the study, we explore a variety of newly added DOCK functions, demonstrating the ease with which new functions can be added to address new scientific questions.