Taking the RNA aptamer Ta, which targets the RBD (receptor-binding domain), as an example, researchers conducted a systematic single-point mutation screening and quantified the effect of each mutation on the binding free energy using free energy perturbation (FEP) calculations.

In the apical loop region of aptamer Ta, almost all mutations resulted in a decrease in binding affinity. For example, the change in binding free energy (ΔΔG) for the G25C mutation was +1.94 ± 0.43 kcal/mol, for U27G it was +0.66 ± 0.16 kcal/mol, and for C29G it was as high as +4.66 ± 0.76 kcal/mol. This suggests that the bases at these sites are already the optimal choice for RBD binding, and any alteration would weaken the binding.

Interestingly, in the aptamer’s end stem region—which also binds tightly to the RBD—base mutations had only a minor effect on binding affinity: the ΔΔG for A42G was only +0.22 ± 0.56 kcal/mol, and for G43U, +0.37 ± 0.30 kcal/mol. This is because binding in this region relies primarily on electrostatic interactions between phosphate groups and positively charged residues on the RBD, rather than base-specific hydrogen bonds or steric interactions.

This example clearly illustrates that, for different regions of the same aptamer, the effect of mutations on binding free energy can differ by more than an order of magnitude, depending on whether the region plays a role in “base-specific recognition” or “electrostatic backbone contacts” during binding.

The selection of RNA and DNA essentially involves a trade-off between structural flexibility/binding potential and chemical stability/cost.

Scenarios for selecting RNA aptamers:
(i) When the target is a small molecule or requires a complex tertiary structure for recognition (e.g., topological structures such as pseudoknots or kissing loops)
(ii) The 2′-hydroxyl group provides a richer network of hydrogen bonds and metal ion coordination capabilities, allowing for a more compact fold
(iii) Willingness to accept chemical modifications (e.g., 2′-F, 2′-O-Me) to enhance stability

Scenarios for selecting DNA aptamers:
(i) Applications in biological fluids (serum, plasma, etc.) that require inherent stability
(ii) Desire to reduce screening and synthesis costs
(iii) Need for more consistent conformation and activity—studies show that under normal conditions, only about 25–58% of theophylline RNA aptamers adopt the correct binding conformation, whereas DNA aptamers primarily exist in a single active fold
(iv) Targets are larger molecules such as proteins, where shape complementarity is sufficient to drive high-affinity binding

Thermal reversibility refers to the ability of an aptamer to refold into its original active three-dimensional structure—without losing function—through slow cooling following heat denaturation (which breaks hydrogen bonds and base-pairing, causing single-stranded nucleic acids to unfold into a random coil).

Typical Procedure:
(i) Denaturation:
Heat the aptamer solution to 90–95°C and maintain this temperature for 3–5 minutes to completely unfold all secondary and tertiary structures
(ii) Renaturation:
Immediately place on ice for 5–10 minutes (rapid cooling), or slowly cool to room temperature (slow cooling)
(iii) Equilibration:
Incubate at room temperature for 10–30 minutes in a binding buffer containing appropriate metal ions (e.g., Mg²⁺) to allow the aptamer to refold into its active conformation

Sequences vary greatly, primarily in the following aspects:
(i) G-rich sequences (forming G-quadruplexes):
Rapid renaturation; the G-tetramer itself exhibits high thermal stability
(ii) RNA rich in complex pseudoknot structures:
Slow renaturation; may require a more precise cooling protocol and higher Mg²⁺ concentrations
(iii) Simple stem-loop structures:
Rapid and highly efficient renaturation

The core principle is that renaturation conditions (temperature gradient, ion concentration, and time) must be optimized for specific sequences; a one-size-fits-all approach is not applicable.

Not necessarily. When two aptamers bind to the same target but via different mechanisms, this typically implies that they bind to different epitopes—because different binding forces (hydrogen-bond-dominated vs. shape-matching-dominated vs. electrostatic-dominated) require the target surface to provide different chemical groups and geometric features.

However, there are exceptions: two aptamers may bind to the same epitope but via different mechanisms. For example, aptamer A binds to a specific groove on the target via shape complementarity (primarily relying on van der Waals forces and shape matching), while aptamer B binds to different residues within the same groove via a network of hydrogen bonds. The epitopes of the two aptamers overlap but are not identical, and their binding mechanisms are distinctly different.

Conversely, it is entirely possible for two aptamers to share the same binding mechanism but bind to different epitopes. For example, two aptamers may both bind to a target via shape complementarity, but one binds to the “front” of the target while the other binds to the “side.” Although their mechanisms are identical (both driven by shape complementarity), their epitopes are completely different.

An interesting case: studies of multiple aptamers targeting the Ebola virus soluble glycoprotein (sGP) have shown that they bind to the same site on sGP, but this site is different from the binding site of antibodies. This demonstrates that even when the binding site is the same, nucleic acid aptamers and protein antibodies may recognize the same epitope in completely different ways.

The systematic experimental workflow is as follows:

Step 1: Structure Prediction and Modeling
(i) Predict secondary structure using mFold, RNAfold, or NUPACK
(ii) Predict tertiary structure using molecular dynamics (MD) simulations or homology modeling

Step 2: Identification of Candidate Regions
(i) Contact residues: Nucleotides within 4–5 Å of the target in the 3D structure
(ii) Scaffold residues: Nucleotides involved in stem base pairing and maintaining overall folding but not directly contacting the target
(iii) Flexible linker regions: Nucleotides connecting different structural domains that may be neither contact nor scaffold residues

Step 3: Systematic Truncation Experiments
(i) Gradually truncate from both ends (removing 2–5 nucleotides at a time)
(ii) Design internal truncations (removing non-essential residues from the loop region or bulge)
(iii) Assess binding activity for each truncation round using EMSA, SPR, or fluorescence polarization

Step 4: Validation of Key Regions
(i) Perform single-point mutations on suspected contact residues (e.g., A→G or C→U); if activity decreases significantly, the residue is confirmed as a contact residue
(ii) Perform stability modifications on suspected scaffold residues in the stem region (e.g., AT→GC); if activity increases, the region is confirmed as a scaffold region

Typical Case:
In the study of the aptamer Ta, researchers selected 16 key nucleotides through contact frequency analysis. Through single-point mutation screening and FEP calculations, they precisely distinguished between “apical ring contact residues” (where mutations significantly reduced affinity), “terminal stem electrostatic residues” (where mutations had minimal impact), and “bulge linking regions” (where mutations affected the overall shape).

Key Principle:
Truncation must preserve all contact residues and the scaffold elements that maintain the spatial positioning of these contact residues. It is impossible to determine which elements are scaffolds based solely on sequence observations—structural information is essential.