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Development of synthetic methodologies for N- to C-terminal cyclization of peptidomimetic small molecules and in silico and in vitro studies of the role of cyclization on antibacterial and antiviral activities
Get PDFAmong the different mechanisms of resistance in Gram-negative bacteria, the permeability barrier of the outer membrane and efflux pumps represent a significant challenge to address as they synergize to reduce accumulation of most antibiotics. As no predictive model of the structural and physicochemical properties governing efflux susceptibility and outer membrane permeability has been developed, there is a pressing need for strategies to enhance the accumulation of small molecules in Gram-negative bacteria. The Small-molecule Penetration & Efflux in Antibiotic-Resistant Gram-Negatives (SPEAR-GN) project takes a multidisciplinary approach to develop a class- and activity-independent model for antibiotic permeability by building small-molecule libraries. For my contribution to this project, I conducted the synthesis of a library centered around a piperazinone scaffold which is derived from the natural product acyldepsipeptide (ADEP), a potent activator of bacterial caseinolytic protease P (ClpP). The N- to C-terminal cyclization of the ADEP pharmacophore, N-heptenoyl 3,5-difluorophenylalanine, was hypothesized to constraint the conformation of the scaffold and improve its metabolic stability. From an optimized three-step synthetic route to produce the piperazinone core, I generated a library of 48 chemically diverse piperazinone analogs, for which I investigated and optimized different methodologies such as N-alkylation of secondary amides with inactivated alkyl halides using phase-transfer catalysis, photoinduced copper catalysis and synthetic handles. In parallel to the piperazinone library, Quentin Gibault and Katelyn Stevens generated a set of uncyclized or seco analogs to examine the role of the cyclization on antibacterial activity and accumulation in Gram-negatives. The Zgurskaya lab evaluated the antibacterial activity of the library by the measuring the minimum inhibitory concentration (MIC) in isogenic strain sets of wild-type, hyperporinated, efflux-deficient, and doubly compromised (i.e., hyperporinated and efflux-deficient) E. coli, P. aeruginosa, and A. baumannii. The promising biological results set the stage for future LC/MS accumulation studies and will lead to the identification of physicochemical properties or motifs governing efflux susceptibility and outer membrane permeability in the seco and piperazinone libraries.
The persistent emergence of antimicrobial-resistant bacteria, paired with a dwindling pipeline of therapeutic treatments amplifies the urgency for novel antibacterials. However, antibiotics that exploit new mechanisms of action provide modern challenges to bacteria; and thus, require the development of a completely new resistance regime, potentially lengthening the duration of action. One promising target departing from traditional antibacterial discovery paradigm is caseinolytic protease P (ClpP). Essential in bacterial homeostasis and virulence, this protease can be chemo-activated by natural products such as acyldepsipeptide (ADEP), resulting in uncontrolled protein degradation and subsequent bacterial cell death. Although ADEP exhibit impressive potency against Gram-positive pathogens, its overall low stability and the synthetic challenge that represents the peptidolactone prevent further development as an antibacterial. To structurally simplify ADEP and maintain its potency associated with the peptidolactone, I investigated the introduction of structural constraint to the ADEP bioactive fragment, N-heptenoyl-3,5-difluorophenylalanine, via N- to C-terminal cyclization. To understand the conformational behavior of the cyclized ClpP activators ranging from six- to eight-membered ring, I conducted computational studies on the conformational space of each analog. The synthetic work I performed provided methodologies to access the six-membered rings (piperazinones and pyrazinones), the seven-membered ring (1,4-diazepan-2-one), and the eight-membered ring (1,4-diazecan-2-one), and the generation of the corresponding small-molecule ADEP analogs. To evaluate the capacity of this series to activate ClpP, I employed a fluorescence-based peptide degradation assay. Although all the cyclized analogs were inactive against Bacillus subtilis ClpP, the biological results demonstrated that, in conjunction with docking studies, a hydrogen bonding with ADEP and Tyr62 is essential for the chemo-activation of ClpP and conformational alteration of the scaffold cannot overcome the loss of this interaction.
The COVID-19 pandemic culminated in more than 470 million cases and six million deaths worldwide since the outbreak of SARS-CoV-2 in December 2020. These numbers along with our individual experience during the last two years make the need for antiviral treatments for coronaviruses indisputable. As the pandemic was taking hold, Jessi Gardner, Katelyn Stevens and I investigated four structurally diverse scaffolds for potential non-covalent SARS-CoV-2 Main protease (Mpro) inhibitors. Among these four scaffolds I designed by leveraging existing literature on Mpro inhibitors and hits from a large-scale crystallographic fragment screen by Diamond Light Source, I conducted docking studies to validate a piperazine scaffold. Although the piperazine scaffold was not pursued because of its poor binding to Mpro, it informed the design of a substituted piperazinone scaffold. Docking studies indicated that this scaffold engaged in multiple protein-ligand interactions with Mpro resulting in good docking scores. Since the piperazinone ring is the result of a N- to C-terminal cyclization of a “peptidic” scaffold, I also conducted docking studies of an “uncyclized” peptidic series of analogs to compare the impact of the cyclization on the binding. Although the docking score of these analogs was weaker, I synthesized a preliminary library of piperazinone and peptidic potential Mpro inhibitors setting the stage for biochemical evaluation against SARS-CoV-2 Mpro
Modeling the outcomes of a longitudinal tie-breaker regression discontinuity design to assess an in-home training program for families at risk of child abuse and neglect
Get PDFThe current study examined the treatment effects of a newly adapted in-home training program for families at risk of child abuse and neglect. In-home interventions for child abuse and neglect have proven effective for reducing risk in low to mid-risk families, but high-risk families are underserved and have a pattern of high recidivism post-treatment. This study compared the standard training (Services as usual; SAU) to the new program, SafeCare+ (SC+), for impact on three different predictors of risk: depression, social support, and access to resources. Subjects were assigned using a tie breaker regression discontinuity design (LTBRDD) which allowed for experimental and ethical outcomes. Multilevel piecewise growth modeling was employed to capture pre-treatment, post-treatment, and follow-up data nested within subjects so that differences in treatment, assignment method, and change in time could all be modeled. Significant moderator effects of treatment on slope in two of the three outcomes, depression and social support, supported the hypothesis that SC+ recipients experience greater positive change in risk factors than SAU recipients. This significant treatment effect on slope also indicated a continued growth from post-treatment to follow-up, supporting the efficacy of SC+ to not lead to high recidivism. Due to the complexity of the design, there is not much in the literature to guide analytic procedures for LTBRDD, so future research should test, compare, and validate different analytic methods to make this design more approachable
Effects of pH on the Raman Spectra of Brines
No full textThe use of Raman spectroscopy on Mars can help us understand the geochemistry of past or present brines on Mars which could help us assess the overall habitability of Mars. Raman can detect biosignatures from organic matter, look for signs of transient flowing water, analyze fluid inclusions and measure ion concentrations in solution. While Raman can be used to determine the bulk composition of a brine it is essential to understand what other factors may also affect the Raman spectra. We conducted experiments assessing the effects of pH on the Raman spectra of Mars analog brines. Our results show Raman spectra of carbonate, sulfate, and phosphate-bearing solutions vary considerably with pH, while chloride and perchlorate brines recorded only minor or no changes with pH. We found that changes in pH correspond to changes in concentration for various species which in turn affects peak intensity. By plotting peak heights against pH for certain brine types we should be able to determine the relative pH of an unknown brine of similar composition. We also found that shifts in peak position occur as pH changes, likely due to the presence of different species at different pH conditions. Changes in the spectra represent changes in the overall aqueous chemistry of the solution which can affect habitability and biogeochemical processes
Does Faculty Student Mentoring Improve Program Performance and Mediate Stress for First-Year Dental Hygiene Students?
Get PDFDental hygiene education requires students to connect classroom learning with patient care very early in the scholastic process. This challenge can be a considerable source of stress for first-year students who are disproportionately, compared to second year students, at-risk for dropping out. In student surveys, first-year dental hygiene students routinely highlight a need for an improved support system when navigating through their degree programs. Although scholars have theorized that faculty-student mentoring may provide critical support for students in health care programs, little empirical research has tested these relationships. A quantitative method was utilized, surveying 472 first-year dental hygiene students during their first year of the program to gain a better understanding of the faculty-student mentoring programs and the role they play in supporting student stress, clinical competence and academic improvement. A pilot tested survey was administered to students after the completion of the first semester of their dental hygiene education but before the termination of the second semester. Results from this study provide evidence regarding factors associated with the effects of the mentoring on program success for the first-year dental hygiene students. This study will add to the body of knowledge that dental hygiene academic programs may reference when investigating the possible benefits of faculty-student mentoring
Synthesis and Redox Behavior of Ruthenium Nitrosyl Porphyrin Complexes
Get PDFThis dissertation details the synthesis, characterization, and redox behavior of various six-coordinate ruthenium nitrosyl porphyrin complexes. The primary focus of this work is centered on factors that impact the redox behavior and the reactivity of these previously unreported compounds.
Chapter 1 introduces, in a broader sense, the interactions of nitric oxide with heme proteins and the utilization of synthesized metalloporphyrins as models. Specifically, this dissertation focuses on employing ruthenium as the metal center, and I place my work in context of related adducts from previous research by former group members and others.
Chapter 2 describes the preparation of aryloxide complexes (por)Ru(NO)(OArxH) (por = OEP and T(p-OMe)PP; x = 0, 1, 2) from the alcohol exchange reaction of the corresponding (por)Ru(NO)(OR) precursors with the appropriate phenol reagent containing an increasing number of internal hydrogen bonds. These nitrosyl aryloxide complexes were characterized by X-ray crystallography, and IR and 1H NMR spectroscopy. The IR spectra exhibit higher νNO frequencies in compounds possessing more internal hydrogen bonds, a result of diminished π-backdonation to the Ru-NO fragment. Similarly, crystal structures of the OEP and T(p-OMe)PP complexes display a trend of increasing Ru-O bond lengths with increasing intramolecular hydrogen bonds. This is also reflected in the redox behavior of these (por)Ru(NO)(OArxH) complexes, which have been examined by cyclic voltammetry and IR-spectroelectrochemistry, showing the first oxidation occurs at an increasingly positive potential with more intramolecular hydrogen bonds present. The subsequent chemical process for the 0- and 1-H compounds become more reversible at scan rates above 200 mV/s while the 2-H complexes displayed chemically irreversible oxidations. An aryloxide ligand-centered oxidation and dissociation was confirmed via chemical oxidation of (OEP)Ru(NO)(OAr2H) with AgPF6 and supported by DFT calculations for the frontier molecular orbitals of these (porphine)Ru(NO)(OArxH) complexes.
Chapter 3 details the synthesis and reactivity of several ruthenium nitroxyl (HNO) porphyrin complexes. The preparation of these (por)Ru(HNO)(LIm) (por = TPP, T(p-OMe)PP, T(p-Cl)PP; LIm = 1-MeIm, -EtIm and –PhIm) compounds were achieved following hydride attack on the corresponding [(por)Ru(NO)(LIm)]BF4 precursors with NaBH4. Unlike the Fe-HNO analogues, the decomposition of the Ru-HNO complexes appear to undergo hydride loss. The IR spectra of the solid samples displayed νNO bands at significantly lower frequencies (1372-1381 cm-1) than the reported value for free HNO (1500 cm-1) and the experimentally obtained nitrosonium compounds (1862-1869 cm-1). 1H NMR spectral data of the target nitroxyl complexes demonstrated δHNO peaks in a similar range to previously reported heme-HNO models but are significantly different from non-heme group 7-9 transition metal complexes. Reactions with the known HNO trap PPh3 resulted in the generation of the corresponding O=PPh3 and HN=PPh3 adducts, confirming the presence of coordinated HNO. Reactions utilizing carbon monoxide and nitric oxide gas both yielded N2O, although through slightly different mechanisms. A similar approach was performed with PhNO but did not produce N2O and is believed to be the result of an alternative reaction mechanism involving an as yet unidentified intermediate. The separate reactivity studies employing 1,3-cyclohexadiene and HS-C(CH3)3 showed no evidence for direct interaction with the Ru-HNO fragment, but instead displayed the presence of the decomposition product.
Chapter 4 highlights the preparation and redox behavior of monometallic and dimetallic complexes of ruthenium nitrosyl porphyrins containing carboxylate and bridging dicarboxylate axial ligands. IR data of the monometallic acid and ester compounds revealed a shift of the νNO to lower frequencies with increasing alkyl chain length of the axial ligand due to increased electron density being donated to the Ru-NO fragment. The dimetallic derivatives display an opposing trend as a result of weak electronic communication between the porphyrin macrocycles in close proximity. The redox behavior of these monometallic ester and dimetallic complexes were investigated by cyclic voltammetry and IR-spectroelectrochemistry, which revealed the more electron donating components (e.g., T(p-OMe)PP > TPP and C6 > C2) yielded slightly lower oxidation and higher reduction potentials. A porphyrin-centered first oxidation and first reduction that led to slow dissociation of the carboxylate ligand was confirmed via chemical redox reagents (e.g., AgPF6 and Cp*2Co) with TRuC2RuT and was supported by frontier molecular orbitals analyses of the model (porphine)Ru(NO)(OC(=O)(CH2)2C(=O)OMe) complex. The dimetallic derivatives undergo a similar mechanism exhibiting two sequential 1-electron transfers that form a mixed valence state enroute to its final dicationic product, as demonstrated by the large peak potential differences and increased current
Automatic Machine Learning in Optimization and Data Augmentation
Get PDFThis dissertation introduces Automatic Machine Learning (AutoML) as a potential approach to overcome current deep learning challenges on efficiency and cost. It also proposes two novel AutoML workflows to areas in deep learning where AutoML is less recognized by the AI community: optimization and data augmentation.
The proposed AutoML workflow in optimization can automatically adjust the learning rate for deep learning tasks. It monitors the signals generated during optimization and dynamically changes the learning rate based on the signal observed. The workflow is successfully deployed in image classification, instance detection and language modeling tasks. The method delivers better performance and faster convergence speed than widely-used static and learning-based schedulers under various different settings.
The new AutoML workflow in data augmentation can help deep neural networks achieve better generalization performance through automated optimization of data augmentation policies. Comparing with the prior best method, the workflow halves the computation required while achieving equivalent or better results on the same benchmarks. In addition, it also removes the need of human intervention in the workflow, making the workflow truly automated for deep learning applications.
Finally, the dissertation concludes that AutoML can play a significant role on various aspects of deep learning through further efficiency improvement and cost reduction. The hope of the dissertation is to inspire more AutoML research on all areas of deep learning, so that AutoML can eventually facilitate the development of fully automated learning, an important milestone in our long pursuit of Artificial Intelligence that can lead us to a brighter future
