  The search for high-affinity aptamers for targets such as proteins, small
molecules, or cancer cells remains a formidable endeavor. Systematic Evolution
of Ligands by EXponential Enrichment (SELEX) offers an iterative process to
discover these aptamers through evolutionary selection of high-affinity
candidates from a highly diverse random pool. This randomness dictates an
unknown population distribution of fitness parameters, encoded by the binding
affinities, toward SELEX targets. Adding to this uncertainty, repeating SELEX
under identical conditions may lead to variable outcomes. These uncertainties
pose a challenge when tuning selection pressures to isolate high-affinity
ligands. Here, we present a novel stochastic hybrid model that describes the
evolutionary selection of aptamers in order to explore the impact of these
unknowns. To our surprise, we find that even single copies of high-affinity
ligands in a pool of billions can strongly influence population dynamics, yet
their survival is highly dependent on chance. We perform Monte Carlo
simulations to explore the impact of environmental parameters, such as the
target concentration, on selection efficiency in SELEX and identify new
strategies to control these uncertainties to ultimately improve the outcome and
speed of this time- and resource-intensive process.
