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. 2016 Feb 22:6:21285.
doi: 10.1038/srep21285.

In silico selection of an aptamer to estrogen receptor alpha using computational docking employing estrogen response elements as aptamer-alike molecules

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In silico selection of an aptamer to estrogen receptor alpha using computational docking employing estrogen response elements as aptamer-alike molecules

Rajesh Ahirwar et al. Sci Rep. .

Abstract

Aptamers, the chemical-antibody substitute to conventional antibodies, are primarily discovered through SELEX technology involving multi-round selections and enrichment. Circumventing conventional methodology, here we report an in silico selection of aptamers to estrogen receptor alpha (ERα) using RNA analogs of human estrogen response elements (EREs). The inverted repeat nature of ERE and the ability to form stable hairpins were used as criteria to obtain aptamer-alike sequences. Near-native RNA analogs of selected single stranded EREs were modelled and their likelihood to emerge as ERα aptamer was examined using AutoDock Vina, HADDOCK and PatchDock docking. These in silico predictions were validated by measuring the thermodynamic parameters of ERα -RNA interactions using isothermal titration calorimetry. Based on the in silico and in vitro results, we selected a candidate RNA (ERaptR4; 5'-GGGGUCAAGGUGACCCC-3') having a binding constant (Ka) of 1.02 ± 0.1 × 10(8) M(-1) as an ERα-aptamer. Target-specificity of the selected ERaptR4 aptamer was confirmed through cytochemistry and solid-phase immunoassays. Furthermore, stability analyses identified ERaptR4 resistant to serum and RNase A degradation in presence of ERα. Taken together, an efficient ERα-RNA aptamer is identified using a non-SELEX procedure of aptamer selection. The high-affinity and specificity can be utilized in detection of ERα in breast cancer and related diseases.

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Figures

Figure 1
Figure 1. Flow chart showing the designed in silico approach of non-SELEX selection of an ERα binding aptamer.
Figure 2
Figure 2. Analysis of the predicted intermolecular interactions in the selected ERα-RNA complex.
(A,B) Numbers of the predicted hydrophobic interactions and H-bonds in complex of ERα with ERaptR1-ERaptR5. These interactions are predicted using Ligplot and Nucplot. (C) Ribbon view of the HADDOCK predicted ERα (1SJ0)-ERaptR4 complex, depicting the interacting residues and the spatial arrangement of protein chains in the vicinity of aptamer molecule. (D) H-bonding residues in the AutoDock Vina generated complex of ERα-ERaptR4. The blue colour represents the aptamer bases while the green colour indicates the amino acids. (E) Surface view of the PatchDock generated ERα-ERaptR4 complex showing the relative orientations of interacting bases and amino acid chain. (F) Structural representation of H-bond and hydrophobic interactions in the ERα-ERaptR4 complex as predicted using Ligplot. H-bonds are represented by dashed lines between H-bonding atoms, whereas the hydrophobic interactions are shown by an arc with spokes radiating towards the interacting ligand atoms.
Figure 3
Figure 3. Measuring the in vitro affinities of the in silico selected ERα-aptamers.
(A) ITC isotherms of ERα interactions with aptamer ERaptR4. For each titration, the ERα concentration in 1.4 ml sample cell was taken as 1 μM and aptamer concentration in syringe was 10 μM. The top panel represents the raw heats of binding obtained upon titration of aptamer to ERα protein. The lower panel is the binding isotherm fitted to the raw data using one site model. (B) ELISA-based measurement of the relative binding of selected sequences with ERα. Binding of aptamer candidates is presented after normalizing against the ERα-antibody control. A random 17-mer RNA sequence (5′-aucgugugcugcuacga-3′) is taken as a random RNA control.
Figure 4
Figure 4. Validating the target specificity of ERaptR4 aptamer.
(A) The specificity of ERaptR4 binding to ERα, as estimated by an ELISA-based detection of purified ERα, nuclear and cytoplasmic extracts of MCF-7 and MDA MB-231 cells and human serum proteins, using biotinylated ERaptR4 as detection molecule. A 17-mer random RNA sequence (5′-aucgugugcugcuacga-3′) was used as random RNA control. Data is plotted after subtracting the background binding. (B) Western blot analysis of SDS PAGE separated ERα, MCF-7 and MDA MB-231 nuclear extract using biotinylated ERaptR4. (C) ELISA-detection of ER (lbd) and PR (lbd and dbd) using biotinylated ERaptR4. Random RNA and ER-antibody were taken as negative and positive controls, respectively. (D) Cytochemical detection of ERα in the fixed monolayer culture of MCF-7 and MDA MB-231 breast cancer cells as carried out using biotinylated-ERaptR4.
Figure 5
Figure 5. Stability analysis of ERaptR4.
(A) Nuclease stability of ERaptR4, as measured using the RNA protection assay. ERaptR4 (2.0 μg) was incubated with RNase A in the presence of 0.5, 1.5 and 3.0 μg of ERα. The samples were separated on 2.0%. The un-degraded ERaptR4 was detected using EtBr staining. (B) Serum stability of ERaptR4 was examined in 10% foetal calf serum and human serum for time intervals of 0–1200 minutes. The un-degraded ERaptR4 was determined by separating it on 2% agarose and EtBr staining. The graph was normalized by taking the fluorescence intensity of initial sample (0 min) as 100%.

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