Matching Items (3)
Description
Over the past two decades, a significant amount of research has been conducted investigating cyanovirin-N (CVN), which has been shown to be an effective antiviral agent by inhibiting entry of HIV into the cell. The virucidal activity of CVN is attributed to the tight binding interactions with the glycosylated surfaces of the envelope protein gp120. In this study we investigated how the incorporation of various single point mutations in the glycan binding site would ultimately affect the overall binding affinity of the protein with the glycan. These mutations were predicted through computational methods. Using a BP-docking program and molecular dynamics (MD) simulation, the free energy change upon the ligand binding to the each protein was determined. Experimental work and Isothermal Titration Calorimetry (ITC) was used to determine the Kd values for each protein mutant. A total of three different CVN mutants, T57S, S52T, and a double mutant T57S-S52T, or simply TS, were investigated on the background of P51G-m4-CVN. After conducting the experimental work, it was concluded that the overall fold and stability of the protein was conserved for each mutant. ITC data showed that T57S displayed the lowest dissociation constant valued in the micromolar range. In fact, T57S had a much lower Kd value in comparison to P51G-m4. In contrast, the double mutant TS, showed poor binding affinity for the glycan. When comparing experimental data with the data provided by MD simulation and BP-docking, the results were fairly correlated for all mutants, except for that of the double mutant, TS. According to information provided by MD simulation and BP docking, the binding of the sugar to TS is a very exergonic reaction, which is indicative of very negative free energy change (ΔG). However, the experimental Kd, which was very high, contradicts this data and is thus indicative of lower binding affinity for the glycan. This contradiction is currently being investigated.
ContributorsAllen, Denysia Monique (Author) / Ghirlanda, Giovanna (Thesis director) / Ozkan, S. Banu (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2015-05
Description
Contrary to the traditional structure-function paradigm for proteins, intrinsically disorderedproteins (IDPs) and regions (IDRs) are highly disordered sequences that lack a fixed
crystal structure yet perform various biological activities such as cell signaling, regulation,
and recognition. The interactions of these disordered regions with water molecules are essential
in the conformational distribution. Hence, exploring their solvation thermodynamics
is crucial for understanding their functions, which are challenging to study experimentally.
In this thesis, classical Molecular Dynamics (MD), 3D-Two Phase Thermodynamics (3D-
2PT), and umbrella sampling have been employed to gain insights into the behaviors of
intrinsically disordered proteins (IDPs) and water.
In the first project, local and total solvation thermodynamics around the K-18 domain
of the intrinsically disordered protein Tau were compared, and simulated with four pairs
of modified and standard force fields. In empirical force fields, an imbalance between
intramolecular protein interactions and protein-water interactions often leads to collapsed
IDP structures in simulations. To counter this, various methods have been devised to refine
protein-water interaction models. This research applied both standard and adapted force
fields in simulations, scrutinizing the effects of each adjustment on solvation free energy.
In the second project, the MD-based 3D-2PT analysis was utilized to examine variations
in local entropy and number density of bulk water in response to an electric field, focusing
on the vicinity of reference water molecules.
In the third project, various peptide sequences were examined to quantify the free energy
involved when specific sequences, known as alpha-MoRFs (alpha-Molecular Recognition
Features), transition from intrinsically disordered states to structured secondary motifs
like the alpha-helix. The low folding free energy penalty of these sequences can be exploited
to design peptide-based or small-molecule drugs. Upon binding to alpha-MoRFs,
these drugs can stabilize the helix structure through a binding-induced folding mechanism.
Alpha-MoRFs were juxtaposed with entirely disordered sequences from known proteins,
with findings benchmarked against leading structure prediction models. Additionally, the
binding free energies of various alpha-MoRFs in their folded conformation were assessed
to discern if experimental binding free energies reflect the separate contributions of folding
and binding, as obtained from umbrella sampling simulations.
ContributorsMaiti, Sthitadhi (Author) / Heyden, Matthias (Thesis advisor) / Ozkan, S. Banu (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2024
Description
Proteins are essential for most biological processes that constitute life. The function of a protein is encoded within its 3D folded structure, which is determined by its sequence of amino acids. A variation of a single nucleotide in the DNA during transcription (nSNV) can alter the amino acid sequence (i.e., a mutation in the protein sequence), which can adversely impact protein function and sometimes cause disease. These mutations are the most prevalent form of variations in humans, and each individual genome harbors tens of thousands of nSNVs that can be benign (neutral) or lead to disease. The primary way to assess the impact of nSNVs on function is through evolutionary approaches based on positional amino acid conservation. These approaches are largely inadequate in the regime where positions evolve at a fast rate. We developed a method called dynamic flexibility index (DFI) that measures site-specific conformational dynamics of a protein, which is paramount in exploring mechanisms of the impact of nSNVs on function. In this thesis, we demonstrate that DFI can distinguish the disease-associated and neutral nSNVs, particularly for fast evolving positions where evolutionary approaches lack predictive power. We also describe an additional dynamics-based metric, dynamic coupling index (DCI), which measures the dynamic allosteric residue coupling of distal sites on the protein with the functionally critical (i.e., active) sites. Through DCI, we analyzed 200 disease mutations of a specific enzyme called GCase, and a proteome-wide analysis of 75 human enzymes containing 323 neutral and 362 disease mutations. In both cases we observed that sites with high dynamic allosteric residue coupling with the functional sites (i.e., DARC spots) have an increased susceptibility to harboring disease nSNVs. Overall, our comprehensive proteome-wide analysis suggests that incorporating these novel position-specific conformational dynamics based metrics into genomics can complement current approaches to increase the accuracy of diagnosing disease nSNVs. Furthermore, they provide mechanistic insights about disease development. Lastly, we introduce a new, purely sequence-based model that can estimate the dynamics profile of a protein by only utilizing coevolution information, eliminating the requirement of the 3D structure for determining dynamics.
ContributorsButler, Brandon Mac (Author) / Ozkan, S. Banu (Thesis advisor) / Vaiana, Sara (Committee member) / Ghirlanda, Giovanna (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2016