title: Controlling uncertainty in aptamer selection.
abstract: 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 stochastic hybrid model that describes the evolutionary selection of aptamers 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 strategies to control these uncertainties to ultimately improve the outcome and speed of this time- and resource-intensive process.
authors: Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Biomedical Engineering, Boston University, Boston MA 02215.
authors: Fabian
authors: F
authors: Spill
authors: Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine, Boston, MA 02118.
authors: Zohar B
authors: ZB
authors: Weinstein
authors: Department of Biomedical Engineering, Boston University, Boston MA 02215.
authors: Atena
authors: A
authors: Irani Shemirani
authors: Department of Biomedical Engineering, Boston University, Boston MA 02215.
authors: Nga
authors: N
authors: Ho
authors: Department of Biomedical Engineering, Boston University, Boston MA 02215; ddesai@bu.edu zaman@bu.edu.
authors: Darash
authors: D
authors: Desai
authors: Department of Biomedical Engineering, Boston University, Boston MA 02215; Howard Hughes Medical Institute, Boston University, Boston, MA 02215 ddesai@bu.edu zaman@bu.edu.
authors: Muhammad H
authors: MH
authors: Zaman
mesh_terms: D052157:Aptamers, Nucleotide / Q000737:chemistry*; D001665:Binding Sites; D001667:Binding, Competitive; D006801:Humans; D007700:Kinetics; D008024:Ligands; D009010:Monte Carlo Method; D009696:Nucleic Acids / Q000737:chemistry*; D011506:Proteins / Q000737:chemistry*; D052156:SELEX Aptamer Technique / Q000706:statistics & numerical data*; D054852:Small Molecule Libraries / Q000737:chemistry*; D013269:Stochastic Processes; D035501:Uncertainty
chemical_list: D052157:Aptamers, Nucleotide; D008024:Ligands; D009696:Nucleic Acids; D011506:Proteins; D054852:Small Molecule Libraries
keywords: SELEX; aptamer; evolutionary dynamics; hybrid model; stochastic process