UWEC CERCA 2026

Triplet excited states are reactive molecular species containing two unpaired electrons. Computational chemistry helps us understand how triplet states mediate photochemical reactions, such as those occurring in the atmosphere. In this project, we have used a high-level computational technique known as CC/DFT to investigate the lowest-energy triplet state of the gamma-pyrone molecule. The CC/DFT method allows us to predict the bond vibrational frequencies of the excited-state species. In turn, this information gives information about the stiffness of the bonds and the likelihood that a bond would be broken in a collision with another molecule. The computed triplet-state frequencies obtained using CC/DFT are within a few percent of experimentally observed values for gamma-pyrone. With CC/DFT computed frequency predictions, the deviations from experiment are approximately four times smaller than those obtained via conventional computational methods. This work represents the first time CC/DFT has been used successfully to predict vibrational frequencies of an excited-state species.

Proteins are dynamic units with conformations that are constantly changing. This can make it difficult to accurately select a drug molecule that selectively binds to an enzyme of one species rather than another, a trait very helpful in antibiotic/drug design. Prolyl tRNA Synthetase (ProRS) is an enzyme responsible for attaching proline to corresponding tRNA molecules in protein synthesis, along with regulating protein synthesis. Inhibition of a ProRS molecule in a targeted species can very effectively cure disease by stopping replication processes of that species. However, computationally finding the sites of selective recognition is quite challenging, especially for enzymes, where species-specific differences are very small. Thus, we are using an artificial intelligence–based tool combining neural networks and computational chemistry, to screen potential inhibitors of these enzymes. A deep-learning fingerprinting tool with a published protein–ligand interaction fingerprinting technique is being used along with traditional molecular dynamics simulations to identify enzyme-specific recognition features. The results of the simulations and the analysis of fingerprinting are expected to reveal distinct molecular characteristics of ligands and active-site elements that significantly influence enzyme inhibition.

RIG-I-like receptors (RLRs) are important cytosolic sensors that detect and respond to viral dsRNA during an infection. This family is characterized by the conserved RIG-I-like helicase domain that binds dsRNA and hydrolyzes ATP. Many viruses have evolved mechanisms to evade or suppress this mechanism, including the expression of Viral Suppressors of RNA Sensing (VSR) proteins. Although the role of RLR signaling is well-studied, specific VSR-RLR protein interactions are not fully characterized. In this project, we utilized the Yeast Two-Hybrid method to identify whether candidate VSRs interact with the RLRs RIG-I, MDA5, LGP2, and Dicer. Yeast are transformed with a pair of plasmids containing the split halves of the yeast GAL4 transcription factor. The activation domain (AD) is fused with one of the RLRs (‘bait’) while the DNA-binding domain (DNA-BD) is fused with a VSR (‘prey’). After co-transformation and culturing on selective media, yeast can only grow if the bait and prey interact. This method allows us to screen many VSR-RLR combinations to determine if VSRs are specific inhibitors of one RLR or general inhibitors of the family. Future work will determine if any detected interactions are dependent on the RIG-I-like helicase domain. Overall, this project provides insight into virus-host interactions during infection and the important of RLRs to innate immunity.

Enoate reductases are a promising class of biocatalysts which have been shown to reduce the carbon-carbon double bonds of cis,cis-muconic acid in vivo, generating adipic acid, an important precursor used in the synthesis of nylon-6,6. Bacillus coagulans (ERBC) is a well researched enoate reductase proven to work with several catechol ring cleavage products. Our research has shown that ERBC is capable of reducing carbon-carbon double bonds in a variety of molecules produced using the extradiol dioxygenase BphC. Since the native substrate of ERBC is unknown, studying its activity with a variety of similar substrates will be beneficial for evaluating the scope of its reactivity. Our research aims to catalogue viable substrates using UV-visible light spectroscopy and to characterize enzymatic products through high performance liquid chromatography (HPLC) analysis. Furthermore, optimizing these reaction conditions will permit high throughput product formation and isolation. Identifying substrates and subsequent enhancement of the catalytic activity of ERBC can enable the development of environmentally benign synthetic methods for the production of a variety of commodity chemicals. In the future, other enoate reductases will be studied to evaluate their potential as viable candidates for the adipic acid production pathway.

Our research is focused on the synthesis of a bridged biphenyl molecule with an amino donor, cyano acceptor, and tetraethylene glycol solubilizing groups (TEG). This three-state biphenyl molecule could find applications like nanoscale fluorescent sensors and molecular mechanical devices. Biphenyl molecules have known dihedral angles, leading to differing optical and conducting properties when manipulated. Utilizing a lactone-bridge, we can force the molecule into and out of planarity by changing pH: at low pH, the molecule takes a planar conformation (“ON”) due to the lactone bridge being intact, while at high pH it adopts a non-planar (“OFF”) geometry resulting from lactone cleavage. Planar biphenyl-containing systems often suffer from poor solubility and thus limited application. However, addition of TEG solubilizing groups will aid in their synthesis, study, and application due to enhanced solubility. Previous research in our group has shown analogous two-state biaryl lactone systems to readily switch conformations when exposed to different pH environments. This pH sensitivity will be even more precise with the addition of a third “OFF” state. At low pH, the amino donor group should become protonated, leading to the second “OFF” state and giving a narrow “ON” state. The “ON” state results in visible color and fluorescence differences from the “OFF” states of the molecule. We will be reporting on the synthetic progress of these molecules as well as evidence supporting their use as three-state molecular switches.

Air pollution is a major national and global health concern that is responsible for more than 1 in 8 deaths globally and is the second leading risk factor for early death. A large portion of this pollution is from atmospheric smog whose main component is ground level ozone that is generated when other pollutants, often nitrogen oxides, are emitted into the air and undergo photochemical reactions. Ozone pollution is particularly dangerous because it is very stable, so it is often carried by the wind from urban areas to rural areas hundreds of miles away. Due to this severity, accurately and precisely quantifying ozone in the lower atmosphere is vital in making informed responses and policies. This is done by flying a Personal Ozone Monitor (POM) on an unmanned aerial vehicle to measure the nearby ozone concentrations (ppb). To ensure the readings are accurate and precise an automated calibration curve procedure was created to more easily compare the recorded measurements to predetermined and accurate measurements, POM batteries were tested for effective operational time, and temperature tests were conducted to verify calibration.

NO2 is emitted into the atmosphere as a byproduct of combustion from vehicles, power plants, and industrial processes. Once in the atmosphere, the photochemical reaction of NO2 and volatile organic compounds (VOCs) results in the formation of ozone within the atmosphere. Ground-level ozone is a dangerous respiratory irritant. Because NO2 is the direct emission that leads to the presence of ground-level ozone, it is pertinent to monitor the concentration of NO2 at low altitudes. To better understand the concentration of NO2 at different altitudes around the Lake Michigan waterfront, we are constructing a lightweight cavity enhanced spectrometer capable of measuring NO2 while flown on a drone. The light source is a blue LED emitting in the 300-550 nanometer wavelength range. The light is reflected between two mirrors with 99.998% reflectivity to achieve a sufficiently long path length for measurement. Absorption spectra are measured using an Ocean Optics SR6 spectrometer. Collected spectral data are converted into concentrations using a spectral fitting algorithm that incorporates known Rayleigh scattering values and literature cross sections for five main chemical species. This poster describes our instrument’s integral components, the initial construction of the optical cavity, and the development of a data analysis program in MATLAB.

Linear alpha olefins (LAOs) are an important commodity used in high-performance plastics, motor oils, and synthetic lubricants. LAOs are short to long carbon chain molecules produced via selective polymerization of ethylene using transition metal catalysts. This project aims to develop a viable synthetic route to produce a ligand that can direct a metal complex to selectively catalyze the formation of LAOs. The ligand is referred to as the PCN-type ligand, which coordinates through phosphorus, carbon, and nitrogen to the metal. The PCN ligand features a benzimidazole central carbene with asymmetrical opposing pendant arms featuring an imine and phosphine. The pre-ligand has been verified through a multi-step synthesis process using air-sensitive techniques. Investigation into the isolation of metal complexes is underway. The synthetic steps to obtain the ligand precursor molecules have been described. The precursor molecule structures have been verified with 1H-NMR and FT-IR. Future work will validate the synthesis of the pre-ligand as well as new metal-coordinated ligand molecules.

Understanding the cow rumen microbiome is an ongoing project with significant implications for agriculture, as the health, weight, and methane emissions of the animal are tied to the microbiome. However, knowledge of rumen microbiomes is biased towards dairy cows and geographically influenced by European breeds. Therefore, to more comprehensively understand the contributions of the microbiome to sustainable animal agriculture, there is a need to study American and beef cattle rumen microbial communities. Using metagenomic techniques, we identified 1,329 microbial genomes from beef cattle rumen fluid. Using the Blugold HPC, we compared these genomes to a database of 12,906 microbial genomes compiled from different ruminants to determine which were newly-sampled. This identified 505 rumen microbial genomes that were uniquely-recovered in our American beef cattle metagenomes. We selected a genome classified as a Prevotella, a ubiquitous rumen genus, and characterized its phylogeny, revealing it likely represents a novel species. We will characterize its metabolic potential to understand the role of this genome in rumen microbiome carbon and nitrogen cycling. This work will lead to a more thorough understanding of the rumen microbiome, informing any efforts to improve animal health, reduce methane emissions, and otherwise improve farming practices.

Oxidative stress is caused by an imbalance between antioxidants and reactive oxygen and nitrogen species. It can lead to DNA damage and plays a critical role in the development and progression of cancer. Because of this, oxidative stress serves as an important biomarker for cancer detection and prognosis. It is also implicated in a variety of other pathologies, including increased viral severity, such as that observed in COVID‑19 infections. In this study, we aim to detect and quantify oxidative stress in cancer patients by measuring 8‑oxo‑2′‑deoxyguanosine (8‑oxo‑dG), a key biomarker of oxidative DNA damage. We are developing a DNA‑aptamer–based, gold‑nanoparticle colorimetric assay to quantify 8‑oxo‑dG in saliva samples. The outcomes of this work will advance the assessment of oxidative stress levels and strengthen investigations into potential correlations between oxidative stress, cancer development, and patient prognosis.

Fluorinated drugs are pharmaceutical compounds that contain one or more fluorine atoms, which enhance their metabolic stability, bioavailability, and binding affinity to biological targets. Every year, more fluorinated pharmaceuticals are being approved for use by the FDA, with 52 approved from 2018-2022. These compounds span various therapeutic areas such as antidepressants, antibiotics, cholesterol-lowering agents, and corticosteroids. Emerging research suggests that fluorinated compounds may influence health outcomes or contribute to neurological concerns. The goal of this project is to investigate key physicochemical properties of fluorinated pharmaceuticals using computational methods and to evaluate whether these compounds could affect the human body, particularly the brain, in ways not originally intended. The computational chemistry platform WebMO, along with Q Chem and the ADMET AI program are being used to calculate parameters, such as chemical hardness, blood–brain barrier (BBB) penetration, intestinal absorption, and toxicity. Thus far, our results indicate that most fluorinated drugs have at least some probability of crossing the BBB, with predicted penetration ranging from 10% to 70%. Additionally, the majority of these molecules appear to be chemically soft, suggesting that if they cross the BBB, they may be more likely to interact with regions such as the prefrontal cortex, corpus callosum, and brainstem.