Aptamers are short single-stranded DNA or RNA molecules that fold into 3D structures capable of binding targets (proteins, small molecules, cells, or even complex particles) with high specificity and affinity. “Aptamer methods” usually refers to the full pipeline: library design → selection (SELEX) → enrichment monitoring → sequencing & bioinformatics → candidate optimization → biophysical/functional validation → stability engineering. Modern platforms improve speed and hit quality by combining smarter selection pressures with microfluidics and next-generation sequencing. 1) Core Aptamer Selection Method: SELEX (Systematic Evolution of Ligands by EXponential Enrichment) 1.1 Classical SELEX workflow (baseline method) Start with a random oligonucleotide library (often 10^13–10^15 unique sequences) Incubate library with the target Partition bound vs unbound sequences Elute binders Amplify (PCR for DNA; RT-PCR + transcription for RNA) Repeat iterative rounds with increasing stringency until enrichment is achieved Why it works: each round increases the fraction of sequences that can bind under the imposed conditions (buffer, temperature, competitor molecules, etc.). Why it’s hard: classical SELEX can be slow, labor intensive, and prone to amplification bias—hence the rise of “advanced SELEX” platforms. 1.2 “Stringency engineering” (how you make aptamers useful) Selection success often depends less on the target itself…
What “Affinity Determination” Means Affinity determination is the process of quantifying how strongly two molecules bind to each other—commonly protein–protein, antibody–antigen, receptor–ligand, or protein–small molecule interactions. In most bioscience and drug discovery contexts, affinity is summarized by the equilibrium dissociation constant (KD): Lower KD = higher affinity (tighter binding). KD is an equilibrium quantity, meaning it reflects the balance between binding and unbinding at steady state. A related way to express the same concept is the association constant (KA), where KA = 1 / KD. The Core Parameters: KD, KA, kon, koff Affinity can be described in two complementary ways: 1) Equilibrium view (how much binds at steady state) KD (M): concentration at which half of binding sites are occupied in a simple 1:1 interaction model. KA (M⁻¹): binding strength as an association constant (inverse of KD). 2) Kinetic view (how fast binding happens) Many instruments determine affinity by measuring rates: kon (M⁻¹·s⁻¹): association/on-rate (how quickly complex forms) koff (s⁻¹): dissociation/off-rate (how quickly complex falls apart) For a 1:1 interaction: KD = koff / kon (at equilibrium). Surface-based biosensors often estimate affinity by extracting these rates from real-time binding curves. Why Affinity Determination…
