Keywords
Nucleic acid analysis, nucleic acid detection, single nucleotide polymorphisms, covalent inhibitors, irreversible inhibitors
Abstract
The design of probes for the selective recognition of biopolymers (nucleic acids and proteins) is a fundamental task for studying, diagnosing, and treating diseases. Traditional methods utilize a single component (small molecule or oligonucleotide) that binds directly to the target biopolymer. However, many biopolymers are unable to be targeted with this approach. The overarching goal of this dissertation is to explore a new, binary approach for designing probes. The binary approach requires two components that cooperatively bind to the target, triggering a recognition event. The requisite binding of two-components allows the probes to have excellent selectivity and modularity. The binary approach was applied to design a new sensor, called operating cooperatively (OC) sensor, for recognition of nucleic acids, including selectively differentiating between single nucleotide polymorphisms (SNPs). An OC sensor contains two oligonucleotide probe strands, called O and C, each with two domains. The first domain contains a target recognition sequence, whereas the second domain is complementary to a molecular beacon (MB) probe. Binding of both probe strands to the fully matched analyte generates a full MB probe recognition site, allowing a MB to bind and report the presence of the target analyte. Importantly, we show that the OC sensor selectively discriminates between single nucleotide polymorphisms (SNPs) in DNA and RNA targets at room temperature, including those with stable secondary structures. Furthermore, the combinatorial use of OC sensors to create a DNA logic gate capable of analyzing DNA sequences of Mycobacterium tuberculosis is described. The binary approach was also applied to design covalent inhibitors for HIV-1 reverse transcriptase (RT). In this application, two separate pre-reactive groups were attached to a natural RT ligand, deoxythymidine triphosphate (dTTP). Upon binding of both dTTP analogs in the RT active site, the pre-reactive groups are brought into the proper proximity and react with each other forming an intermediate that subsequently reacts with an amino acid side chain from the RT. This leads to covalent modification of RT, and inhibition of its DNA polymerase activity. This concept was tested in vitro using dTTP analogs containing pre-reactive groups derived from ?-lactamase inhibitors clavulanic acid (CA) and sulbactam (SB). Importantly, our in vitro assays show that CA based inhibitors are more potent than zidovudine (AZT), a representative of the dominant class of RT inhibitors currently used in anti-HIV therapy. Furthermore, molecular dynamics simulations predict that complexes of RT with these analogs are stable, and point to possible reaction mechanisms. The inhibitors described in this work may serve as the basis for the development of the first covalent inhibitors for RT. Moreover, the pre-reactive groups used in this study can be used to design covalent inhibitors for other targets by attaching them to different ligands. Overall, the work presented herein establishes the binary approach as a straightforward way to develop new probes to selectively recognize nucleic acids and proteins.
Notes
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
Graduation Date
2015
Semester
Spring
Advisor
Kolpashchikov, Dmitry
Degree
Doctor of Philosophy (Ph.D.)
College
College of Sciences
Department
Biology
Degree Program
Biomedical Sciences
Format
application/pdf
Identifier
CFE0006031
URL
http://purl.fcla.edu/fcla/etd/CFE0006031
Language
English
Release Date
November 2020
Length of Campus-only Access
5 years
Access Status
Doctoral Dissertation (Open Access)
Subjects
Dissertations, Academic -- Sciences; Sciences -- Dissertations, Academic
STARS Citation
Cornett, Evan, "A Binary Approach for Selective Recognition of Nucleic Acids and Proteins" (2015). Electronic Theses and Dissertations. 1483.
https://stars.library.ucf.edu/etd/1483