Deciphering the Details of RNA Aminoglycoside Interactions: From Atomistic Models to Biotechnological Applications

Aminoglycosides are a class of antibiotics functioning through binding to 16S rRNA A-site and inhibiting the bacterial translation. However, the continuous emergence of drug-resistant strains makes the development of new and more potent antibiotics necessary. Aminoglycosides are also known to interact with various biologically crucial RNA molecules other than 16S rRNA A-site and inhibit their functions. As a result, they are considered as the single most important model to understand the principles of RNA small molecule recognition. The detailed understanding of these interactions is necessary for the development of novel antibacterial, antiviral or even anti-oncogenic agents. In our studies, we have studied both the natural aminoglycoside targets like Rev responsive element (RRE), trans-activating region (TAR) of HIV-1 and thymidylate synthase mRNA 5\u27 untranslated (UTR) region as well as the in vitro selected neomycin, tobramycin and kanamycin RNA aptamers. By this way, we think we have covered a variety of binding pockets to figure out the critical nucleic acid residues playing essential role in aminoglycoside recognition. Along with all these RNAs, we studied more than 10 aminoglycoside ligands to pinpoint the chemical groups in close contact with RNAs. To determine thermodynamic parameters for these interactions, we utilized isothermal titration calorimetry (ITC) assay by which we found that the majority of these interactions are enthalpy driven. More specifically, RNA aminoglycoside interactions are mainly derived by electrostatic and hydrogen binding interactions. Our studies indicated that the amino groups on the first ring of the aminoglycosides are essential for high affinity binding whereas having bulky groups on ring II sterically eliminate their interactions with RNAs. RNA binding trend of aminoglycosides are as follows: neomycin-B \u3e ribostamycin \u3e kanamycin-B \u3e tobramycin \u3e paromomycin \u3e sisomicin \u3e gentamicin \u3e kanamycin-A \u3e geneticin \u3e amikacin \u3e netilmicin. Aminoglycoside binding to the aptamer was shown highly buffer dependent. This phenomenon was analyzed in five different buffers and found that cacodylate-based buffer changes the specificity of the aptamer. In addition to ITC, we have used molecular docking to specifically find out the chemical groups in these interactions. We have specified the nucleic acid residues interacting with aminoglycosides. In parallel, molecular dynamics (MD) simulations of neomycin RNA aptamer with neomycin-B in an all-atom platform in GROMACS were carried out. The results showed a mobile structure consistent with the ability of this aptamer to interact with a wide range of ligands. From molecular docking and MD simulations, we identified the neomycin-B aptamer residues that might contribute to its ligand selectivity and designed a series of new aptamers accordingly. Also, A16 was found to be flexible, which was confirmed by 2AP fluorescence studies. In this analysis, the buffer dependence was also confirmed against neomycin-B, ribostamycin and paromomycin. One of the challenges in therapeutics is the emergence of resistant cells. They become reistant to the drugs via changing the target site, or enzymatically modifying the drug, or producing drug pumps to export the drugs. To overcome the very last challenge, we are utilizing RNA-aminoglycoside partners to keep high intracellular drug concentration and increase the efficacy of aminoglycosides against bacteria. We called the system as DRAGINs (Drug binding aptamers for growing intracellular numbers). We express these RNAs in bacteria and detect their growth rate in order to evaluate their response to different concentration of aminoglycosides. In this study, we found that we could successfully decrease the IC50 values by 2 to 5 fold with the help of aminoglycoside-binding RNA aptamers. Finally, we are mathematically modeling the effect of aptamers on IC50 values of drugs with the use of four-compartment model. In our research group, we are utilizing these RNA-aminoglycoside partners to develop tags for detecting RNA in vivo and in real time. We called this system as intracellular multiaptamer genetic tags (IMAGEtags)

Aptamers Targeting Membrane Proteins for Sensor and Diagnostic Applications.

Many biological processes (physiological or pathological) are relevant to membrane proteins (MPs), which account for almost 30% of the total of human proteins. As such, MPs can serve as predictive molecular biomarkers for disease diagnosis and prognosis. Indeed, cell surface MPs are an important class of attractive targets of the currently prescribed therapeutic drugs and diagnostic molecules used in disease detection. The oligonucleotides known as aptamers can be selected against a particular target with high affinity and selectivity by iterative rounds of in vitro library evolution, known as Systematic Evolution of Ligands by EXponential Enrichment (SELEX). As an alternative to antibodies, aptamers offer unique features like thermal stability, low-cost, reuse, ease of chemical modification, and compatibility with various detection techniques. Particularly, immobilized-aptamer sensing platforms have been under investigation for diagnostics and have demonstrated significant value compared to other analytical techniques. These "aptasensors" can be classified into several types based on their working principle, which are commonly electrochemical, optical, or mass-sensitive. In this review, we review the studies on aptamer-based MP-sensing technologies for diagnostic applications and have included new methodological variations undertaken in recent years

Specificity and ligand affinities of the cocaine aptamer: impact of structural features and physiological NaCl

The cocaine aptamer has been seen as a good candidate for development as a probe for cocaine in many contexts. Here, we demonstrate that the aptamer binds cocaine, norcocaine, and cocaethylene with similar affinities and aminoglycosides with similar or higher affinities in a mutually exclusive manner with cocaine. Analysis of its affinities for a series of cocaine derivatives shows that the aptamer specificity is the consequence of its interaction with all faces of the cocaine molecule. Circular dichroism spectroscopy and 2-aminopurine (2AP) fluorescence studies show no evidence of large structural rearrangement of the cocaine aptamer upon ligand binding, which is contrary to the general view of this aptamer. The aptamer’s affinity for cocaine and neomycin-B decreases with the inclusion of physiological NaCl. The substitution of 2AP for A in position 6 (2AP6) of the aptamer sequence eliminated the effect of NaCl on its affinities for cocaine and analogues, but not for neomycin-B, showing a selective effect of 2AP substitution on cocaine binding. The affinity for cocaine also decreased with increasing concentrations of serum or urine, with the 2AP6 substitution blunting the effect of urine. Its low affinities for cocaine and metabolites and its ability to bind irrelevant compounds limit the opportunities for application of this aptamer in its current form as a selective and reliable sensor for cocaine. However, these studies also show that a small structural adjustment to the aptamer (2AP exchanged for adenine) can increase its specificity for cocaine in physiological NaCl relative to an off-target ligand

Common Secondary and Tertiary Structural Features of Aptamer–Ligand Interaction Shared by RNA Aptamers with Different Primary Sequences

Aptamer selection can yield many oligonucleotides with different sequences and affinities for the target molecule. Here, we have combined computational and experimental approaches to understand if aptamers with different sequences but the same molecular target share structural and dynamical features. NEO1A, with a known NMR-solved structure, displays a flexible loop that interacts differently with individual aminoglycosides, its ligand affinities and specificities are responsive to ionic strength, and it possesses an adenosine in the loop that is critical for high-affinity ligand binding. NEO2A was obtained from the same selection and, although they are only 43% identical in overall sequence, NEO1A and NEO2A share similar loop sequences. Experimental analysis by 1D NMR and 2-aminopurine reporters combined with molecular dynamics modeling revealed similar structural and dynamical characteristics in both aptamers. These results are consistent with the hypothesis that the target ligand drives aptamer structure and also selects relevant dynamical characteristics for high-affinity aptamer-ligand interaction. Furthermore, they suggest that it might be possible to “migrate” structural and dynamical features between aptamer group members with different primary sequences but with the same target ligand

Aptamers for Diagnostics with Applications for Infectious Diseases

Aptamers are in vitro selected oligonucleotides (DNA, RNA, oligos with modified nucleotides) that can have high affinity and specificity for a broad range of potential targets with high affinity and specificity. Here we focus on their applications as biosensors in the diagnostic field, although they can also be used as therapeutic agents. A small number of peptide aptamers have also been identified. In analytical settings, aptamers have the potential to extend the limit of current techniques as they offer many advantages over antibodies and can be used for real-time biomarker detection, cancer clinical testing, and detection of infectious microorganisms and viruses. Once optimized and validated, aptasensor technologies are expected to be highly beneficial to clinicians by providing a larger range and more rapid output of diagnostic readings than current technologies and support personalized medicine and faster implementation of optimal treatments

Sampling Performance of Multiple Independent Molecular Dynamics Simulations of an RNA Aptamer

Using multiple independent simulations instead of one long simulation has been shown to improve the sampling performance attained with the molecular dynamics (MD) simulation method. However, it is generally not known how long each independent simulation should be, how many independent simulations should be used, or to what extent either of these factors affects the overall sampling performance achieved for a given system. The goal of the present study was to assess the sampling performance of multiple independent MD simulations, where each independent simulation begins from a different initial molecular conformation. For this purpose, we used an RNA aptamer that is 25 nucleotides long as a case study. The initial conformations of the aptamer are derived from six de novo predicted 3D structures. Each of the six de novo predicted structures is energy minimized in solution and equilibrated with MD simulations at high temperature. Ten conformations from these six high-temperature equilibration runs are selected as initial conformations for further simulations at ambient temperature. In total, we conducted 60 independent MD simulations, each with a duration of 100 ns, to study the conformation and dynamics of the aptamer. For each group of 10 independent simulations that originated from a particular de novo predicted structure, we evaluated the potential energy distribution of the RNA and used recurrence quantification analysis to examine the sampling of RNA conformational transitions. To assess the impact of starting from different de novo predicted structures, we computed the density of structure projection on principal components to compare the regions sampled by the different groups of ten independent simulations. The recurrence rate and dependence of initial conformation among the groups were also compared. We stress the necessity of using different initial configurations as simulation starting points by showing long simulations from different initial structures suffer from being trapped in different states. Finally, we summarized the sampling efficiency for the complete set of 60 independent simulations and determined regions of under-sampling on the potential energy landscape. The results suggest that conducting multiple independent simulations using a diverse set of de novo predicted structures is a promising approach to achieve sufficient sampling. This approach avoids undesirable outcomes, such as the problem of the RNA aptamer being trapped in a local minimum. For others wishing to conduct multiple independent simulations, the analysis protocol presented in this study is a guide for examining overall sampling and determining if more simulations are necessary for sufficient sampling

Common Secondary and Tertiary Structural Features of Aptamer–Ligand Interaction Shared by RNA Aptamers with Different Primary Sequences

Aptamer selection can yield many oligonucleotides with different sequences and affinities for the target molecule. Here, we have combined computational and experimental approaches to understand if aptamers with different sequences but the same molecular target share structural and dynamical features. NEO1A, with a known NMR-solved structure, displays a flexible loop that interacts differently with individual aminoglycosides, its ligand affinities and specificities are responsive to ionic strength, and it possesses an adenosine in the loop that is critical for high-affinity ligand binding. NEO2A was obtained from the same selection and, although they are only 43% identical in overall sequence, NEO1A and NEO2A share similar loop sequences. Experimental analysis by 1D NMR and 2-aminopurine reporters combined with molecular dynamics modeling revealed similar structural and dynamical characteristics in both aptamers. These results are consistent with the hypothesis that the target ligand drives aptamer structure and also selects relevant dynamical characteristics for high-affinity aptamer-ligand interaction. Furthermore, they suggest that it might be possible to “migrate” structural and dynamical features between aptamer group members with different primary sequences but with the same target ligand

Deciphering the Details of RNA Aminoglycoside Interactions: From Atomistic Models to Biotechnological Applications

Aminoglycosides are a class of antibiotics functioning through binding to 16S rRNA A-site and inhibiting the bacterial translation. However, the continuous emergence of drug-resistant strains makes the development of new and more potent antibiotics necessary. Aminoglycosides are also known to interact with various biologically crucial RNA molecules other than 16S rRNA A-site and inhibit their functions. As a result, they are considered as the single most important model to understand the principles of RNA small molecule recognition. The detailed understanding of these interactions is necessary for the development of novel antibacterial, antiviral or even anti-oncogenic agents. In our studies, we have studied both the natural aminoglycoside targets like Rev responsive element (RRE), trans-activating region (TAR) of HIV-1 and thymidylate synthase mRNA 5' untranslated (UTR) region as well as the in vitro selected neomycin, tobramycin and kanamycin RNA aptamers. By this way, we think we have covered a variety of binding pockets to figure out the critical nucleic acid residues playing essential role in aminoglycoside recognition. Along with all these RNAs, we studied more than 10 aminoglycoside ligands to pinpoint the chemical groups in close contact with RNAs. To determine thermodynamic parameters for these interactions, we utilized isothermal titration calorimetry (ITC) assay by which we found that the majority of these interactions are enthalpy driven. More specifically, RNA aminoglycoside interactions are mainly derived by electrostatic and hydrogen binding interactions. Our studies indicated that the amino groups on the first ring of the aminoglycosides are essential for high affinity binding whereas having bulky groups on ring II sterically eliminate their interactions with RNAs. RNA binding trend of aminoglycosides are as follows: neomycin-B > ribostamycin > kanamycin-B > tobramycin > paromomycin > sisomicin > gentamicin > kanamycin-A > geneticin > amikacin > netilmicin. Aminoglycoside binding to the aptamer was shown highly buffer dependent. This phenomenon was analyzed in five different buffers and found that cacodylate-based buffer changes the specificity of the aptamer. In addition to ITC, we have used molecular docking to specifically find out the chemical groups in these interactions. We have specified the nucleic acid residues interacting with aminoglycosides. In parallel, molecular dynamics (MD) simulations of neomycin RNA aptamer with neomycin-B in an all-atom platform in GROMACS were carried out. The results showed a mobile structure consistent with the ability of this aptamer to interact with a wide range of ligands. From molecular docking and MD simulations, we identified the neomycin-B aptamer residues that might contribute to its ligand selectivity and designed a series of new aptamers accordingly. Also, A16 was found to be flexible, which was confirmed by 2AP fluorescence studies. In this analysis, the buffer dependence was also confirmed against neomycin-B, ribostamycin and paromomycin. One of the challenges in therapeutics is the emergence of resistant cells. They become reistant to the drugs via changing the target site, or enzymatically modifying the drug, or producing drug pumps to export the drugs. To overcome the very last challenge, we are utilizing RNA-aminoglycoside partners to keep high intracellular drug concentration and increase the efficacy of aminoglycosides against bacteria. We called the system as DRAGINs (Drug binding aptamers for growing intracellular numbers). We express these RNAs in bacteria and detect their growth rate in order to evaluate their response to different concentration of aminoglycosides. In this study, we found that we could successfully decrease the IC50 values by 2 to 5 fold with the help of aminoglycoside-binding RNA aptamers. Finally, we are mathematically modeling the effect of aptamers on IC50 values of drugs with the use of four-compartment model. In our research group, we are utilizing these RNA-aminoglycoside partners to develop tags for detecting RNA in vivo and in real time. We called this system as intracellular multiaptamer genetic tags (IMAGEtags).</p