Literature DB >> 17624471

Complex SELEX against target mixture: stochastic computer model, simulation, and analysis.

Chi-Kan Chen1.   

Abstract

Systematic evolution of ligands by exponential enrichment (SELEX) is an important technology in combinatorial chemistry and molecular biology of developing high affinity target-binding molecules (aptamers) from highly complex nucleic acid ligand libraries. Schematically, the SELEX is a series of iterative rounds of operations where in each operational round ligands are incubated with the target (e.g., a purified protein), and target-binding ligands are extracted and amplified. In the recent development of biological study and drug discovery, by incubating ligand libraries with complex target mixtures (e.g., cell fragments), the SELEX experiments have been explored to simultaneously develop aptamers for targets embedded in target mixtures: the complex SELEX. While holding the considerable advantages of saving experimental resources, practicing the complex SELEX has often accompanied with unstable experimental performances. It is therefore important to understand the behaviors of the new application. In this paper, we develop stochastic computer model, and customized computational algorithm to numerically mimic the complex SELEX. We model the ligand selection through the probability of ligand binding to complex targets at the binding equilibrium, and efficiency of separating target-binders for amplification. The customized computational algorithm allows us to simulate real experiments that operate on huge ligand libraries. We evaluate the ligand evolution, and aptamer enrichment of complex SELEX under various experimental conditions by stochastic simulations, and theorize the simulated results. We argue that the stochastic effects, which were not previously captured in the studies of complex SELEX, may significantly affect the results of experiments.

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Year:  2007        PMID: 17624471     DOI: 10.1016/j.cmpb.2007.05.008

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  5 in total

1.  Controlling uncertainty in aptamer selection.

Authors:  Fabian Spill; Zohar B Weinstein; Atena Irani Shemirani; Nga Ho; Darash Desai; Muhammad H Zaman
Journal:  Proc Natl Acad Sci U S A       Date:  2016-10-07       Impact factor: 11.205

2.  Heuristic algorithms in evolutionary computation and modular organization of biological macromolecules: Applications to in vitro evolution.

Authors:  Alexander V Spirov; Ekaterina M Myasnikova
Journal:  PLoS One       Date:  2022-01-27       Impact factor: 3.240

Review 3.  Aptamer Bioinformatics.

Authors:  Andrew B Kinghorn; Lewis A Fraser; Shaolin Lang; Simon Chi-Chin Shiu; Julian A Tanner
Journal:  Int J Mol Sci       Date:  2017-11-24       Impact factor: 5.923

Review 4.  Inside the Black Box: What Makes SELEX Better?

Authors:  Natalia Komarova; Alexander Kuznetsov
Journal:  Molecules       Date:  2019-10-07       Impact factor: 4.411

Review 5.  DNA nanomedicine: Engineering DNA as a polymer for therapeutic and diagnostic applications.

Authors:  Michael J Campolongo; Shawn J Tan; Jianfeng Xu; Dan Luo
Journal:  Adv Drug Deliv Rev       Date:  2010-03-23       Impact factor: 15.470

  5 in total

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