Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/68580
標題: Simulations of SELEX against complex receptors with a condensed statistical model
作者: Chen, C.K.
Kuo, T.C.
關鍵字: SELEX;aptamers;computer model;computer simulation;in-vitro selection;nucleic-acid aptamers;exponential enrichment;systematic evolution;molecular computation;rna;dna;ligands;repertoires;recognition
Project: Computers & Chemical Engineering
期刊/報告no:: Computers & Chemical Engineering, Volume 31, Issue 9, Page(s) 1007-1019.
摘要: 
Systematic evolution of ligands by exponential enrichment (SELEX) is an in vitro combinatorial engineering approach to enrich aptamers from a library of nucleic acids ligands by iterative extraction and amplification of receptor-bound ligands. Aptamers are the selected nucleic acid ligands with high receptor-binding affinity. Typically, they are obtained in single-receptor SELEX experiments where the ligand library is incubated with receptor molecules of a single identity, e.g., a purified protein. For years, aptamers have been shown to be valuable for biomedical applications and research. To further explore the power of SELEX technology, the idea of complex SELEX was proposed to obtain multiple aptamers by incubating the ligand library with multiple species of receptors. However, the reports on complex SELEX have been few, possible due to the ignorance of the effects of experimental variables. To address this problem, computer simulations should be useful. A major task of simulating complex SELEX is to solve interdependent binding equilibrium equations for binding events among heterogeneous ligands and receptors. Although a detailed subpooling model was developed, that model could be useful to simulate complex SELEX against at most four species of receptors, because the demand of computer memory grew exponentially with the number of receptor species. Here we develop a novel, condensed subpooling model where ligands of similar characteristic affinity are first pooled together regardless of receptor- specificity, and then divided into partial subpools receptor-specific ally. With this model, the need of computer memory grows only linearly with receptor number. In the simulation of SELEX against four receptors, our results are the same or very similar to earlier work. We have further simulated SELEX against 100 heterogeneous receptors. We suggest that our computation method can be applied to other research fields where binding events between heterogeneous ligands and receptors are involved. (c) 2006 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/11455/68580
ISSN: 0098-1354
DOI: 10.1016/j.compchemeng.2006.08.015
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