Date of Award

2012

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Mohan,Ram Dr.

Abstract

Biomarkers are molecules that indicate changes in a physiological state and are detected by biosensors. Aptamer based biosensors are highly efficient, with high specificity and reusability. An aptamer library for a 25-mer aptamer contains 1015 possible sequences. Experimentally, the procedure known as Systematic Evolution of Ligands by Exponential Enrichment (SELEX) is used. Selecting an aptamer from such a huge library is highly involved and time consuming. A single round of SELEX uses a few hundred aptamers and can take few hours to weeks. Use of computational modeling may simplify this aptamer selection process. Prior to computational modeling of the aptamer selection process, aptamer binding must be simulated and understood as the selection depends on the ability of an aptamer to bind to a target molecule. In the present study, we used Molecular Dynamics modeling to simulate and subsequently visualize the well-established aptamer binding combination of mucin 1(MUC1) peptide and Anti-MUC1 aptamer. During the simulation it was seen that the peptide associated twice with the aptamer. In particular, the peptide associated with the 12th tyrosine residue of the aptamer loop after 25ns before dissociating and binding with the 3’ and 5’ ends of the aptamer. Post simulation analysis of the Radius of Gyration, atomic distance to the wet lab surface plasma resonance imaging (SPRi) results corroborated with the observations of the simulation results. Current foundational study shows that computational molecular dynamics simulations can provide molecular level insight for aptamer-peptide binding process, which is difficult to probe directly in wet lab experiments.

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