Analyses of interactions between small molecules and Tyr-Am aptamer
PF–NEACE was performed to evaluate the interactions of the Tyr-Am aptamer (Apt49-T) with the Tyr-Am analogs. As shown in Fig. 3a, only Tyr-Am and Phe-Am showed a remarkable decrease in the peak heights with large tailing, whereas the other five analogs, Tyr, Phe, Trp, AAP, and t-BP, did not change their peak heights and shapes significantly. The normalized values of the peak ratio are summarized in Fig. 3b, which clearly indicate the specific interaction between Apt49-T and Tyr-Am/Phe-Am. The Kd values between Apt49-T with Tyr-Am, Phe-Am, and Tyr were reported to be 45, 80, and 520 µM, respectively, by equilibrium dialysis , whereas the Kd values of the other analogs were not due to their weak or non-interaction. From the reported Kd values, the amount of Tyr-Am, Phe-Am, and Tyr bound to Apt49-T were calculated to be ca. 6.8, 5.4, and 1.6 µM, respectively. However, the obtained results did not show an interaction between Tyr and Apt49-T (Fig. 2A(c)) under nonequilibrium conditions. These results suggest that the presence or absence of an amide group has a significant effect on the association reaction rate under nonequilibrium conditions. Consequently, it is demonstrated that the proposed PF–NEACE can easily distinguish molecules that rapidly interact with the ligand from those that do not interact by the variation in the height and shape of the 2nd peak.
Evaluation of the association rate constant, k
on, by PF–NEACE
As explained in Fig. 1 and the Experimental section, a higher concentration of the sample solution (100 µM) was introduced into the capillary than the injected DNA (10 µM). Therefore, the free sample molecules in the DNA zone without binding should be rapidly separated from the bound one, thereby decreasing the height of the 2nd peak. From Eq. (10), the association rate constant kon can be evaluated by varying the reaction time. Under experimental conditions, the reaction time can be estimated as the time required for the 2nd sample zone to overtake the DNA zone, and can be easily controlled by changing the injected length of the DNA zone. In the case of Tyr-Am, the values of injected length and reaction time were calculated to be ca. 1.45–11.6 cm, and ca. 6.9–56.9 s, respectively when the injection time of the DNA zone changed from 10 to 80 s. In the case of Phe-Am, the values of injected length and reaction time were calculated to be ca. 1.23–6.15 cm, and ca. 5.8–30.5 s when the injection time of the DNA zone changed from 10 to 50 s. The height of the 2nd peak decreased with increasing injection time/length of the DNA zone owing to the increase in complex formation. These results are summarized in Fig. 3, and the kon values were determined from the slopes of the approximate lines (Eq. 8), and the kon values of Tyr-Am and Phe-Am against Apt49-T were estimated to be 2300 ± 0.99 and 4300 ± 0.92 M−1 s−1, respectively.
Evaluation of the dissociation constant, K
d, by PF–NEACE
In PF–NEACE, the first complex formed during the penetration of the sample solution into the ligand zone is rapidly separated from the remaining free sample molecules without interactions (Fig. 1b). After separation, the complex reaches a new association/dissociation equilibrium in the ligand zone. As a result of the successive formation of the complex and its separation from the free sample molecules, the 2nd sample zone shows a significant tailing shape (Fig. 1d). As described above, the apparent migration time of S interacting with L is measured by the tailed part of the observed peak, whose height (h′) is half the height of the initial complex X1 estimated by Eq. (3) using the estimated values of kon. When the baseline drift was observed in the electropherogram, the baseline was adjusted by referring to the baselines before and after detecting the 1st and 2nd sample peaks, respectively. When the tailing of the 2nd peak was observed without the ligand, the difference in the detection time of tail parts whose heights were h′ with/without the ligand were measured after adjusting the baselines. Typical results of the calculated average values of kon, Kd, and koff (n = 3) are summarized in Table 1.
As described above, a smaller Kd value (stronger binding) was estimated for Tyr-Am, despite the larger kon value of Phe-Am. This could be explained by differences in the reaction rates and stabilities of the complexes. The only difference between Tyr-Am and Phe-Am is the presence or absence of a hydroxy group on the aromatic ring. Thus, the faster binding of Phe-Am to Apt49-T can be attributed to the hydrophobic interactions related to the aromatic ring without hydroxy groups. However, the formation of the more stable complex of Tyr-Am with Apt49-T is expected to be due to the hydrogen bonding of the hydroxy group. Consequently, it was confirmed that the proposed PF–NEACE can assess the interaction between the analytes and ligands with a short analysis time and minimal consumption of the sample and ligands, which will contribute to drug screening of rare biological samples as a high-throughput method.
Application of PF–NEACE on screening for drug candidates with disease-related oligonucleotides
To confirm the applicability of PF–NEACE in the screening of drug candidates against disease-related oligonucleotides, the RNA of the expanded repeat ((GGGGCC)n), which possibly causes frontotemporal dementia and amyotrophic lateral sclerosis, was selected as a model RNA sample. As model ligands, artificially synthesized RNAs, (GGGGCC)6 and (GGGGCC)8, and biosynthesized RNA, (GGGGCC)20, were prepared in 0.25–10 µM solutions containing 10 mM Tris–HCl buffer (pH 7.5) and 10% (v/v) DMSO. As model target samples, compounds A and B were prepared at 100 µM by diluting stock solutions with BGS without DMSO. "Upon checking, it was noticed that there are panels in the caption and citation of Figure ; however, they were not found in the corresponding image. Please provide us with an updated figure with corresponding panels matching their description in the figure caption."?> "Thanks for careful check. Please revise the Figure caption from "Evaluation of association rate constants of (a) Tyr-Am and (b) Phe-Am" to "Evaluation of association rate constants of Tyr-Am and Phe-Am against Apt49-T"."?>
Figure 4 shows the electropherograms obtained by PF–NEACE analyses of compounds A and B. Negative peaks were often observed because there was a slight difference in their components between the solutions due to the addition of 10% (v/v) DMSO. Compound A showed a significant decrease in the peak height (Fig. 4A), whereas compound B showed a small decrease (Fig. 4B). The calculated values of the peak ratio of compounds A and B against RNA are summarized in Fig. 4C. These results indicate that there were multiple compounds bonded to a single RNA molecule, and the number of molecules bound to the RNA was higher in compound A than in compound B. In the case of one-to-many interactions, it is very difficult to calculate accurate binding constants, whereas it is possible to roughly estimate the difference in interactions, as shown in Fig. 4. Compound A is known to interact with the (GGGGCC)8 structure with a Kd of 16 µM , and compound B has been reported to interact with the G–G mismatch structure . Thus, the observed results related to compound A indicated that both RNAs, (GGGGCC)6 and (GGGGCC)20, have a similar structure to the reported RNA, (GGGGCC)8, with a G-quadruplex providing a remarkably strong interaction between compound A and (GGGGCC)6/(GGGGCC)20, which may have G-quadruplex structures. On the other hand, the lower binding of compound B suggests that these RNAs do not have many G–G mismatch structures. Consequently, these results indicate the applicability of PF–NEACE to not only the screening but also the evaluation of the structure of DNAs/RNAs in solution.
It is also well known that potassium ions can stabilize G-quadruplex structures. To evaluate the effect of potassium ions on the interaction between compounds A and RNAs, the concentration of RNAs was varied with and without adding KCl in the BGS. The results are summarized in Fig. 5. This clearly showed a decrease in the peak ratio wiht increasing concentrations of each disease-related RNA. For each RNA, the molar binding ratios were also calculated from the decrease in the peak intensities and the initial molar ratio of [S] and [RNA]. Without adding KCl, it was clarified that (GGGGCC)6 and (GGGGCC)8 could bind 17–26 molecules of compound A, while (GGGGCC)20 could only bind up to 17, despite the longer sequence.
On the other hand, when KCl was added in the BGS, the peak heights became larger as compared to those without KCl. The estimated numbers of binding molecules were reduced by 9–11 for (GGGGCC)6, 12–17 for (GGGGCC)8, and 3–5 for (GGGGCC)20. These results indicate that the binding of RNAs stabilized by potassium ions reduced the binding sites for compounds A as compared to that without stabilization. Thus, it was suggested that compound A bound to the RNAs at the binding sites related not only to the stabilized planar G-quartet structures but also to the various gaps of the G-quadruplex structures without stabilization by potassium ions. Further and more detailed investigations are required to clarify their binding structure; however, the proposed PF–NEACE analyses provide important insights related to the interactions between compounds A/B and RNAs with simple operation, short analysis time, and minimal consumption of the reagents.
Comparison of PF–NEACE to conventional methods
As discussed above, PF–NEACE has great potential as a useful analysis tool in the interaction screening of small molecules and oligonucleotides. On the other hand, there are various conventional methods to assess the interactions between biological samples as described in the Introduction. Table 2 shows the reported analysis time and reagent consumption using conventional methods and the proposed PF–NEACE. With respect to the analysis time, the proposed method and NECEEM were shorter than those of the other methods. These methods also have a great advantage in that they do not require the immobilization of a sample/ligand, whereas SPR and QCM do. ITC also measures the interactions without any immobilization process, but it requires a large amount of samples/reagents and complicated procedures. Estimations of the interactions between DNA and a target molecule using magnetic nanoparticles (MNP) have been also reported . The MNP method is very easy to use but requires a long analysis time and a large consumption of reagents. In NECEEM, mixed solutions of samples and ligands reaching equilibrium were analyzed in CE within a short analysis time. However, NECEEM needs to wait until the mixed solutions reach equilibrium and prepare tens of microliters of each sample solution for use in the CE apparatus. PF–NEACE also requires at least several tens of microliters of sample and ligand solutions in the vials, but only a small portion of them (several tens of nanoliters) is introduced into the capillary to measure the interaction. Thus, PF–NEACE saves both the mixing time and volume of the sample and ligands. Conventional PF–ACE also provides interaction assays with minimal consumption of samples/reagents. However, PF–ACE often requires a higher concentration of the ligand than that of the target to maintain the stable complexation of the whole target molecules, which sometimes interferes with the measurement of rare, dilute, and difficult to obtain ligands such as biomolecules from patients. On the other hand, PF–NEACE is applicable to the condition that the concentration of ligands is lower than that of targets as described above. Therefore, high-throughput screening of disease-related oligonucleotide-target drugs is expected to be realized by PF–NEACE.