Controlling uncertainty in aptamer selection

Oligonucleotide aptamers have increasing applications as a class of molecules that bind with high affinity and specificity to a target. Aptamers are typically selected from a large pool of random candidate nucleic acid libraries through competition for the target. Using a stochastic hybrid model, we are able to study the combined impact of important evolutionary success factors such as competition, randomness, and changes in the environment. Whereas the environment may be tuned with experimental parameters such as target concentration, competition varies with differences in the initial distribution of aptamer-target binding affinities, and random events can eliminate even the ligands with the highest affinity.