Methanogens are a diverse group of archaea with ancient evolutionary origins. They are found in a wide range of anoxic environments where they carry out a form of anaerobic respiration known as methanogenesis. This process reduces simple oxidized carbon compounds to generate methane as an end product. Another group of archaea related to methanogens carry out the anaerobic oxidation of methane (AOM) and are known as anaerobic methanotrophs (ANME).  Methanogens and ANME are both key components in the global carbon cycle and play a central role in controlling atmospheric methane concentrations. Consistent with their anaerobic lifestyles and ancient evolutionary origins, methanogens and ANME contain an abundance of Fe-S cluster proteins. Radical S-adenosylmethionine (SAM) enzymes are [4Fe-4S]-cluster containing enzymes that catalyze a wide variety of difficult biochemical reactions through the generation of a highly reactive 5’-deoxyadenosyl radical. Here, we discuss our recent progress towards uncovering the functions of novel radical SAM enzymes in methanogens and ANME. We identified the missing glutamate 2,3-aminomutase important for salt tolerance in marine organisms as well as characterized the first archaeal methylthiotransferase involved in tRNA modification. 

The structure of plant cell wall carbohydrates creates the strength and flexibility of the plant cell wall, which shapes plants’ overall agronomic fitness in the field. Differences in cell wall carbohydrates and associated compounds are also influential post-harvest, since carbohydrate structural characteristics can influence a material’s food processing characteristics, feed value for livestock, and biofuel production potential.

The core areas of Dr. Schendel’s research program at the University of Kentucky are plant cell wall characterization (especially detailed structural analysis of cell wall carbohydrates) and analysis and application of phenolics and other secondary plant metabolites. Strategic collaborations have allowed us to explore applied questions such as ruminant microbe fermentation of cell wall carbohydrates. This seminar will share results from several projects, including our in-depth characterizations of the cell walls of cool-season forages and hempseeds and exploration of their seasonal and species/cultivar variation. 

Abstract: Our research group focuses on building tools that enable inverse materials design and give new insights into the fundamental chemical physics of liquids, interfaces, and materials. For this talk, we will discuss our progress in two of our primary research thrusts.

The first part of the talk will focus on our work in developing methods that are used to accelerate the design of functional materials, including radical-based polymers and organic optoelectronic materials. The radical-based polymers have the potential to serve as energy storage materials. Successful materials design requires careful molecular engineering of the polymer and electrolyte. To solve the molecular-scale part of the problem, we develop physically motivated machine learning models that predict molecular properties (e.g., hole reorganization energies) from low-cost representations, and pair these with reinforcement learning methods for inverse design applications. In our first demonstration of the reinforcement learning scheme, we show that this framework is capable of integrating with quantum chemistry calculations in real-time, and through a careful design of the curriculum, we are able to find a diverse set of molecules with desired singlet and triplet energy levels.

The second part will focus on our efforts on developing representations for predicting the polymer physics of intrinsically disordered proteins at a much lower computational cost that current coarse-grained methods. One advantage of our new representation is that it avoids specifying the longest length of the chain in advance. In addition, this representation works well with a set of highly charged amino acid sequences, uncovering new insights to the fundamental interactions and scaling behavior of these systems.

Bio: Daniel Tabor received his B.S. in Chemistry from the University of Texas at Austin in 2011, where he was advised by John F. Stanton. He then attended the University of Wisconsin—Madison for his Ph.D. (2016), where he was a member of Ned Sibert’s group. From 2016-2019, he was a postdoc with Alán Aspuru-Guzik at Harvard University. Daniel began his independent career on the faculty at Texas A&M in the Fall of 2019, where he is currently an Assistant Professor in the Department of Chemistry. He was named a Texas A&M Institute of Data Science Career Initiation Fellow in 2021 and a Cottrell Scholar in 2023.

Conjugated polymers have been the cornerstone of organic electronics, with applications in such diverse areas as photovoltaics, field effect transistors, batteries, and bioelectronics. However, a number of challenges are still apparent, including, scalability, sustainability, and applicability under a broad range of real-world conditions. Our efforts have focused on novel, simplified polymer architectures, scalable synthetic methods and applications in solar cells and batteries. In this talk, a primary focus will be on the design of novel semiconducting polymers for intrinsically stretchable solar cells (IS-PSCs). We have designed novel side-chain functionalized conjugated polymers bearing hydrogen-bonding groups, such as thymine. Such units capable of inducing strong intermolecular hydrogen-bonding leading to polymer assembly and highly efficient and mechanically robust PSCs. Importantly, such polymers have enabled IS-PSCs showing an unprecedented combination of PCE (13.7%) and ultrahigh mechanical durability (maintaining 80% of initial PCE after 43% strain). Additionally, efforts toward the development of novel non-conjugated electroactive polymers will be introduced where we focus on elucidating structure-function relationships and synthetic pathways for this promising materials class.

Folding of proteins into their active 3D-structure occurs spontaneously or is assisted with the help of chaperones within a biologically reasonable time, from micro- to milliseconds. It occurs within different compartments of the cell, controlled by the chemical environment. When folding goes wrong in cells, misfolded and/or aggregated proteins may arise, unable to perform their specific biological function. The correlation between structural motifs and their 3D-structure has been established to influence biology. However, less is known about the biological implications of protein topology, i.e., motifs that can act as a structural switch in response to environmental changes. Leptin is the founding member of the Pierced Lasso Topology (PLT), a newly discovered protein family sharing the unique features of a “knot-like” topology.  A PLT is formed when the protein backbone pierces through a covalent loop formed by a single disulfide bond. PLTs are found in all kingdoms of life, with 14-different biological functions, found in different cell compartments. Despite the large number found in nature, where more than 600 proteins have been found with a PLT, a connection between topology and biological function has not yet been determined. We investigate three biological systems, the hormone leptin, chemokines, and the oxidoreductase superoxide dismutase (SOD1) and the association between the threaded topology and the biological function. Our results show that a PLT may control conformational dynamics switching biological activity on/off depending on the chemical environment. Thus, we propose that PLTs may act as a molecular switch to control biological activity in vivo.

Abstract: There is a pressing need to develop novel therapeutic agents against new targets for chronic pain. The Tidgewell Lab uses cyanobacterial-derived natural products as the starting point for chronic neuropathic pain drug development by targeting receptors and other targets involved in pain. The Tidgewell lab works in the areas of natural products chemistry conducting isolation and structure elucidation work and combines that with medicinal and organic chemistry for the understanding and enhancement of these leads for physicochemical and biological effect. In this talk, you will hear about the background of natural products for developing our understanding of the brain as well as current work and projects using marine cyanobacterial natural products to understand and treat chronic pain.

Bio: Tidgewell grew up in southern California before heading east to earn his BS in Chemistry with a minor in Mathematics from Mercyhurst College (now University). He then joined the Prisinzano lab at the University of Iowa, where he earned his Ph.D. in 2007, working to develop non-addictive analgesics based on the plant hallucinogen Salvinorin A.

Tidgewell returned to southern California for a Post-Doc in the Gerwick Lab at Scripps Institution of Oceanography and the University of California, San Diego. He spent two years working at SIO on cancer drug discovery from marine cyanobacteria before moving to Panama to work on Dr. Gerwick’s ICBG project at the Smithsonian Tropical Research Institute. Tidgewell spent just over two years working in Panama on neglected tropical diseases drug discovery from marine cyanobacteria before starting a faculty position at Duquesne University in 2012.

The Tidgewell lab moved to Kentucky in July of 2023, and the work focuses on combining marine natural products with synthetic, medicinal chemistry to discover and better understand novel compounds from marine cyanobacteria for CNS disorders.

The ability to systematically alter the electronic properties of organic materials is vital for their incorporation into next-generation electronic devices. Polycyclic aromatic hydrocarbons (PAHs) are of significant interest for organic electronics, as relevant properties are highly dependent on their size, structure, and functionalities, and thus can be tuned to fit a wide variety of applications. Due to the enormous number of structural isomers available in larger PAHs, the development of design protocols is necessary to efficiently develop high-performing materials. Linear extension of the aromatic core, such as that seen in the acene series, is an efficient yet underexplored method for tuning the electronic properties of 2-D PAHs. The development of synthetic procedures is necessary to systematically explore the properties of the larger aromatic compounds. This work will explore novel synthetic routes that allow for the systematic exploration of acene-fused PAHs of similar size but vastly different electronic properties. Such work demonstrates that by strategically altering the mode of ring fusion, PAHs can be tuned for applications such as organic field-effect transistors (OFETs) and quantum information science (QIS). The impact of linear ring extension in 2-D PAHs is also explored, demonstrating that the electronic structure of larger PAHs can be systematically tuned with significant implications for their applications and stability. The functionalization of a series of organic dyes, with the goal of tuning their optical properties for implementation into wearable radiation sensors, will also be discussed.

Abstract: Traumatic brain injury (TBI) continues to be a significant cause of morbidity and mortality worldwide. Despite significant progress in understanding the complex pathophysiology of TBI, the underlying mechanisms remain poorly understood. The primary brain damage is acute and irreversible. However, secondary brain injuries often develop gradually over months to years, creating an opportunity for critical therapeutic interventions. In the past decade, research on TBI biomarkers has seen significant progress. This progress has been driven by the diverse nature of TBI pathologies and the challenges they present for evaluation, management, and prognosis. TBI biomarker proteins resulting from axonal, neuronal, or glial cell injuries have been extensively studied and widely used. However, their detection in peripheral blood specimens may be limited due to difficulties in crossing the blood-brain barrier in sufficient quantities. Even with the advances made in TBI research, there remains a clinical need to develop and identify novel TBI biomarkers that can address these limitations and provide more accurate and accessible diagnostic tools.

As part of the ongoing effort to substitute finite fuel and chemical resources with renewable ones, biomass is emerging as one of the most promising sources. Biomass consists of three main components of cellulose, hemicellulose, and lignin. Traditionally, cellulose has been used extensively in pulping industry, while lignin has been considered waste and is burned to generate heat. Lignin, a complex aromatic polymer component of biomass, has the potential to be used as a source of aromatic chemicals and pharmaceutical synthons. The recalcitrant nature of lignin, the lack of effective lignin breakdown methods and analytical techniques to analyze it are the main obstacles to obtaining high-yield chemicals from lignin. Mass spectrometry has proven to be one of the most promising analytical techniques and it is widely used in the pharmaceutical and chemical industries.  The goal of this work is to develop analytical methods using mass spectrometry and lignin model compounds. Additionally, this work focused on the development and application of quantitative Derivatization Followed by Reductive Cleavage(q-DFRC) for the evaluation of various biomass pretreatment methods. 

Since most commercially available lignin model compounds fail to mimic the structure of native lignin, it is necessary to develop compounds that more closely reflect the functionality of native lignin. The first project of this dissertation is focused on developing precursors for synthesizing b-O-4 model compounds and modifying their functional groups. The precursors have been synthesized and analyzed using gas chromatography-mass spectrometry. These precursors were used to synthesize b-O-4 model compounds that exhibit all characteristics of the native lignin. 

The second project involved the synthesis and mass spectral analysis of a mixed linkage trimer containing both b-O-4 and b-5 bond types. A detailed analysis of the mass spectral fragmentation of lignin trimer with lithium adduct ionization is presented. The developed analysis of the lignin trimer facilitates the structural elucidation of lignin breakdown products. 

The third project involved the application of q-DFRC as one of the lignin breakdown techniques to evaluate different biomass pretreatment methods. Ethanosolv, dioxosolv, co-solvent enhanced lignocellulosic fractionation (CELF), hydrotropic, and acetic acid/formic acid pretreatments were evaluated by q-DFRC with deuterium-labeled acylated monolignols internal standard. An evaluation and comparison of the quality of lignin obtained from each of these pretreatments was conducted. This dissertation provides valuable information for the advancement of mass spectrometric analysis of lignin, and it can be applied to lignin oligomer analysis. Furthermore, the q-DFRC results provide insight into how various pretreatments are related to the extent of condensation in extracted lignin. 

Organic semiconductors have gained attention recently due to their potential applications in flexible, low-cost, lightweight electronics and solar cells. However, developing new organic semiconductors with improved performance remains a significant challenge due to the vast space of possible molecular structures. Furthermore, the high cost and time-consuming nature of experimental synthesis and characterization hinder the rapid discovery of new materials. To overcome these challenges, this dissertation presents a novel data-driven approach. The primary focus of this work is the development of data-driven tools, namely machine learning models, to predict critical electronic and structural properties of molecular organic semiconductors. These models are trained on a large dataset of quantum chemical calculations, enabling the efficient screening of thousands of candidate molecules. In addition to developing the predictive models, this work includes creating a user-friendly web platform. The platform enables scientists and engineers to access the models and rapidly explore the chemical space to design new materials. The platform also includes visualization and analysis tools to guide the design process and facilitate collaboration between researchers. The data-driven tools developed in this research have the potential to significantly accelerate the discovery and development of new molecular organic semiconductors, paving the way for the next generation of flexible electronics and renewable energy technologies. Overall, this dissertation offers a practical and innovative framework for designing organic semiconductors, leveraging data-driven approaches to overcome the challenges of the traditional experimental trial-and-error process.