Heredia Negron, Frances L.

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    Biophysical studies: Interaction of the Aptamer-protein complexes
    (2022-05-16) Heredia Negron, Frances L.; Parés Matos, Elsie I.; College of Arts and Sciences - Sciences; Bauer, William; Ríos Steiner, Jorge L.; Ríos Guillet, Robert; Resto Irizarry, Pedro J.; Department of Chemistry; Rúa de la Asunción, Armando
    Aptamers are synthetic nucleotides used as probes for a plethora of molecules. Their applications include therapeutics, biosensors, drug delivery, among others. Aptamers bind strongly and selectively to a target because of their ability to adopt different three-dimensional structures that form complementary shapes that fit very well into the recognition site. To understand the binding mechanism of Aptamers and to optimize the design of Aptamer-based technologies, it is necessary to understand the details of the Aptamer folding and target interactions from a structural perspective. Unfortunately, while the number of publications of Aptamer applications keeps growing, there is scant research on Aptamers from a structural perspective. This dissertation addresses that knowledge gap by employing two different approaches. The structural characterization of a DNA Aptamer-protein complex using X-ray Crystallography, and the analysis and identification of common patterns within Aptamer sequences using Machine Learning (ML). Two DNA Aptamer-protein pairs were chosen for characterization by X-ray Crystallography: IBA-Insulin and LyApt-Lysozyme. The analysis of the interaction between the DNA Aptamer IBA and Insulin suggests that this Aptamer binds to its target trough the induced-fit model, stabilized by hydrophobic, electrostatic, and non-covalent interactions. Meanwhile in the crystal structure of the DNA Aptamer LyApt and Lysozyme, the Aptamer shows a lack of a folding motif, and the stability of the complex is mainly driven by non-covalent interactions, thus forcing the Aptamer to bind the Lysozyme's heparin binding sites. In both cases, these DNA Aptamers are binding to “hot-spots” within the target proteins. In machine learning analyses, DNA sequences were broken into six nucleotide motifs called 6-mers. From their modeling, it was found that Aptamers have a high “GT” content and the 6-mers with the highest relevance across all ML models were TGG TGG, TGG GGG, GGG GTG, GGT TGG, GCA CAG and GGG GGG. These six 6-mers are found to be involved in protein binding or are structurally significant within the Aptamers. These results expand the understanding of where within a protein, does an Aptamer bind and it can be helpful in the future design of SELEX experiments by developing new screening libraries, overexpressing the promising 6-mers or by pre-selecting sequences as potential Aptamers.