Computational Chemistry Commons^™

Molecular Insights Into The Role Of Estrogen Receptor Beta In Ecdysterone Mediated Anabolic Activity, Syeda Sumayya Tariq, Madiha Sardar, Muhammad Shafiq, Hendrick Heinz, Mohammad Nur-E-Alam, Aftab Ahmad, Zaheer Ul-Haq

Pharmacy Faculty Articles and Research

Ecdysterone, often dubbed a “natural steroid,” has garnered significant attention among athletes for its reputed growth-promoting and anabolic properties. Unlike synthetic anabolic steroids, which are classified as controlled substances, ecdysteroids remain largely unregulated in many countries and are widely marketed as dietary supplements. Notably, ecdysterone has been included in the World Anti-Doping Agency (WADA) monitoring program, highlighting its potential impact on athletic performance and raising questions about its regulation. Emerging evidence indicates that, unlike traditional anabolic steroids that act primarily via the Androgen Receptor (AR), ecdysterone’s anabolic effects may be mediated through Estrogen Receptors (ERs), particularly Estrogen Receptor beta (ERβ). …

Myceli-Yum: Elucidating Structure-Property Relationships For Polymer Degradation By Mycelial Digestion, Jordan Scott Ford

Master's Theses

Since the industrial entrance of polymer plastic materials, plastic has become ubiquitous in both everyday use and waste. Due to inefficiencies and knowledge gaps, current recycling methods are not able to account for the high scale of plastic waste, resulting in the bulk of this waste being landfilled, mishandled, and deposited in the environment. Mycelium, the microorganism responsible for fruiting mushroom bodies and mold growth, holds potential to reduce plastic waste and can potentially be utilized as a method of industrial recycling. Following a drug-design approach, the active site of mycelial enzymes responsible for natural biopolymer degradation have been assessed …

Comparing Machine Learning Paired Optimization Strategies For Single-Component Waterborne Direct-To-Metal Coatings, Harvir S. Kalkat

Master's Theses

As R&D attempts to fine tune properties before production, the redesign and testing process can become highly iterative. The repetitive nature of formulating can be difficult to escape when relying on chemical intuition alone. To provide some guidance in this process, machine learning (ML) can leverage data from previous trials¹ to design suggestions for subsequent trials. Although ML capabilities have vastly expanded in the last few years, integration of ML into chemistry R&D and education has been slow. Unraveling the mystique of ML can help change what has been a slow embrace in the coatings industry. It is important …

Characterizing Electrospray Performance Of Hydroxylammonium Nitrate (Han) And 2-Hydroxyethylhydrazinium Nitrate (Hehn) Ionic Liquids By Mass Spectrometry And Dynamics Simulations, Wenjing Zhou

Dissertations, Theses, and Capstone Projects

Dual-mode propulsion combines chemical and electric propulsion methods into a single compact system by sharing hardware and propellant for both modes, offering complementary advantages tailored to specific mission needs. A promising propellant candidate for dual-mode propulsion is a binary mixture of hydroxylammonium nitrate (HAN) and 2-hydroxyethylhydrazinium nitrate (HEHN) ionic liquids (ILs). Each of the two ILs was developed as a greener alternative to the traditional, yet toxic, hydrazine monopropellant used in chemical propulsion. Recently, their potentials in electrospray propulsion have garnered attention. This thesis focused on the investigation of reaction dynamics and kinetics of HAN, HEHN and their binary mixture …

Understanding The Morphology And Mass Transport Resistance Of Mesoporous Carbon-Supported Pemfc Based On Modeling Analysis, Hao Deng, Jia Liu, Zhong-Jun Hou

Journal of Electrochemistry

Mesoporous carbon supports mitigate Pt sulfonic poisoning through nanopore-confined Pt deposition, yet their morphological impacts on oxygen transport remain unclear. This study integrates carbon support morphology simulation with an enhanced agglomerate model to establish a mathematical framework elucidating pore evolution, Pt utilization, and oxygen transport in catalyst layers. Results demonstrate dominant local mass transport resistance governed by three factors: (1) active site density dictating oxygen flux; (2) ionomer film thickness defining shortest transport path; (3) ionomer-to-Pt surface area ratio modulating practical pathway length. At low ionomer-to-carbon (I/C) ratios, limited active sites elevate resistance (Factor 1 dominant). Higher I/C ratios improve …

Optimization Of Renewable Energy Systems: Comparative Analysis Of Advanced Algorithms And Photovoltaic-Electrolyzer Performance For Cost Reduction And Efficiency Enhancement, Mohamed-Amine Babay, Mustapha Adar, Ahmed Chebak, Mustapha Mabroukia

Journal of Electrochemistry

The increasing demand for cost-effective and efficient renewable energy solutions presents significant optimization challenges in hybrid energy systems. This paper addresses these challenges by conducting a comparative analysis of three advanced optimization algorithms—Lévy Flight Optimization (LFO), Archimedean Optimization (AO), and Quantum Gorilla Optimization (QGO)—to minimize the Total Net Present Cost (TNPC) and Levelized Cost of Energy (LCOE) in hybrid renewable energy systems. The study integrates critical cost parameters such as Capital Expenditure (CAPEX), Operational Expenditure (OPEX), replacement costs, and salvage values into an advanced optimization framework. Three system configurations are evaluated: Wind Turbines and Fuel Cells (WT/FC), Photovoltaic Systems and …

Characterization Of Sars-Cov-2 Replication And Transcription Complexes Via Structural And Evolutionary Approaches, Amelie Ghirardo, Ben Shabatian, Avishai Aghelian, Kyle Tau, Eleonora Gianti

Undergraduate Research

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused around 700M cases and over 7M COVID-19-related deaths recorded worldwide (World Health Organization, March 2025). Aiming to effectively combat this and other disease-causing Coronaviruses (CoV), unprecedented research efforts led to the development of new vaccines and antiviral therapies. Due to emergence of variants of concern (VOCs) with increased transmissibility, immune evasion from vaccination, and potential to resist the available treatments, SARS-CoV-2 continues to represent a major threat to global health. Hence, there is a pressing need to discover new antivirals with broad-spectrum efficacy against multiple SARS-CoV-2 variants and related CoVs. This project …

Quantum Chemical Methods And Multiscale Modeling In Computer-Aided Drug Design, Hunter W. La Force

Chemistry Theses and Dissertations

Computer-Aided Drug Design (CADD) leverages a diverse toolkit of computational methods to accelerate the discovery and development of novel therapeutics. Among these, quantum chemical calculations provide unparalleled accuracy in understanding molecular interactions, albeit at a higher computational cost. This accuracy is crucial for identifying and quantifying fundamental interactions that dictate drug efficacy and selectivity, as exemplified by our investigation of ruthenium polypyridyl complexes. These metal-based compounds are model systems for studying covalent coordination bonds between ruthenium and its ligands and noncovalent interactions with DNA and protein targets. Local Mode Vibrational Theory emerges as a powerful lens within this framework, enabling …

A Computational Method For Detecting Compound Promiscuity In Early-Stage Pharmaceutical Discovery, John Allen Ringer

Computer Science ETDs

Modern drug discovery and chemical biology research relies heavily on analyzing bioassay data. One of the many challenges in bioassay data analysis is identifying false trails, i.e., chemical compounds which initially appear to have desirable activity but are found to be problematic upon further investigation. Badapple (the BioAssay-Data Associative Promiscuity Pattern Learning Engine) was created over ten years ago to help researchers identify promiscuous compounds and thus avoid a common source of these false trails. Through an effort involving software engineering, cheminformatics, and biomedical data science we have developed Badapple 2.0, which incorporates updated assay records and expanded data semantics. …

Trade-Off Between Limonene & Geraniol-Based Reprocessable And Non-Reprocessable Epoxy Thermosets: Role Of Aliphatic Diamines In Polymer Networks Design, Priyankkumar Kanubhai Patel

Electronic Theses & Dissertations

The growing demand for sustainable materials, driven by environmental concerns and the rapid depletion of fossil fuels, has garnered significant attention in the fabrication of bio-based epoxy thermosets as renewable alternatives to petroleum-derived thermosetting polymers. The present study focuses on the synthesis and characterization of epoxy prepolymer resins derived from limonene and geraniol via a two-step process, followed by the fabrication of thermally cross-linked flexible epoxy thermoset films using various traditional aliphatic diamine curing agents, namely 1,2-ethylenediamine (EDA), 1,4-butylenediamine (BDA), and 1,6-hexamethylenediamine (HDA). Additionally, the incorporation of cystamine, a disulfide-containing diamine, enabled the formation of a covalent adaptable network through …

Modeling Molten Lithium Carbonate As Pollutant Absorbing Agent, Lucian G. Forestieri

Student Summer Scholars Manuscripts

Coal burning generates gaseous pollutants that are toxic to local environments and human health, namely hydrochloric acid and sulfur dioxide ( HCl and SO₂). Current methods for capturing these pollutants are flue gas desulfurization, which utilize solid or water- dissolved carbonates. This method, however, is inefficient mainly due to the product salts blocking further reactions. Molten carbonates may be a more efficient alternative. Experimental work cannot observe these reaction mechanisms, and the small number of current computational models do not match experimental properties. This work aims to develop a computational model of gaseous HCl scattering off the surface …

Computational Lipophilicity Calculations Of Fluorinated Morphine Derivatives For Improved Pain Management, Mirabella Romano, Allison Vu, Emily Chen

Student Scholar Symposium Abstracts and Posters

The opioid epidemic impacts 60 million people worldwide every year. Morphine, a commonly prescribed opioid, binds to the μ opioid receptor (MOR) in the body via protonation of the tertiary amino group of morphine and the MOR. An unfortunate side effect of this binding process is its non-selectivity in both peripheral and central tissues. While activation within inflamed peripheral tissues results in pain relief, activation within central tissues results in the unwanted and addictive side effects of opioids. Because there is a discrepancy in pH between healthy (central) and inflamed (peripheral) tissue, selective binding within the inflamed tissues results in …

From Molecular Crystals To Catalytic Surfaces: Computational Approaches To Complex Systems, Thiago Henrique Da Silva

Boise State University Theses and Dissertations

Understanding and modeling complex systems is one of the core challenges in modern science. Whether it be the intricate interactions within molecular crystals, the evolving mechanisms of bacterial resistance, or the dynamics of catalytic surfaces, accurately representing these systems is essential for scientific progress. This dissertation addresses these challenges by focusing on advances in computational modeling, demonstrating how various methods such as Density Functional Theory (DFT), machine learning, and custom-developed methods can simplify and help predict complex behaviors across multiple domains. By applying and understanding the scope of these methods to each field, this work underscores how computational modeling bridges …

Using Gaussian Process Regression To Learn Thermodynamic Equations Of State With Uncertainty Quantification, Austen T. Lee

Chemical Engineering Undergraduate Honors Theses

This study investigates the use of derivative-informed Gaussian Process (GP) models to estimate thermodynamic behavior across temperature and density by building a Helmholtz-based equation of state. Argon, a stable monatomic gas, was chosen as a case study within the vapor region. The GP model was trained using values of experimentally measurable properties found by taking first and second derivatives of the original potential function. Results show that while the GP model offered uncertainty quantification and informed thermodynamic behavior, it predicted values that deviated from the ground truth depending on the property. The model exhibited high confidence in regions with substantial …

Synthesis, Characterization, And Redox Properties Of Select 1,4-Diazocine-6,11-Diones Towards An Electrochromic Dye-Set, Jeffrey Scott Richards

Open Access Theses & Dissertations

The daily consumption of personalized digital visual information depends on the current purview of electronic-based displays. Present manufacturers utilize modern technologies, such as LCD, OLED, QLED, and electronic ink, or "E Ink," in their devices to display text, pictures, and other forms of media to individual users. However, as modern society continues to rely on the use of digital displays, the demand for low-power alternatives will continue to rise as their application in varying scenarios is realized. Currently, "E Ink" technology continues to grow as the dominant solution in the e-readers and digital signage marketplace, and can even be seen …

Computational Study Of The Proton Transfer In The H7o3+ Cluster, Anna James, Martina Kaledin

Symposium of Student Scholars

Proton transfer (PT) from one molecule to another is among the most studied phenomena in chemistry. PT requires the bond cleavage and the formation of a new one, AH⁺ + B -> A+ BH⁺. In protonated water clusters, such a process consists of the interconversion of hydrogen bonds. Experimentally, such a process can be observed as a significant increase of a dipole moment. However, other vibrational transitions often occur with small changes in the dipole moment while large changes in polarizability. In this work, we study the PT process in a protonated water cluster, H₇O …

Computational Analysis Of Proton Conductivity Factors In Grotthuss-Style Mechanisms, Brock Dyer

Physics and Astronomy Honors Papers

The mechanism and fundamental molecular properties involved in proton conduction are discussed. Four calculable properties are presented: the proton affinity, binding energy (between protonated and neutral forms), intramolecular tautomerization barrier, and proton hopping barrier. An overview of the computational methods used in this thesis, including an introduction to the many-body Schrödinger equation and Density Functional Theory, as well as a look at Plane-Wave Density Functional Theory and Gaussian-Type Orbital Density Functional Theory are presented. 4,5-dimethyl-[1,2,3]-triazole is used as a model system, with 10 variations being generated with varying amounts and positions of fluorine substitution on the methyl groups. Preliminary calculations …

Ancestral Sequence Reconstruction On Antibiotic-Resistance Bacteria, Jeyun Park

SACAD: Scholarly Activities

The spread of antibiotic-resistant bacteria poses a global health threat, and it is predominantly driven by enzymes that neutralize antibiotics or alter their drug targets. This study uses Ancestral Sequence Reconstruction (ASR) to explore the evolutionary history of a key bacterial enzyme that plays a role in antibiotic resistance. Protein sequences were aligned, and a phylogenetic tree constructed utilizing MEGA 11. Ancestral sequences are predicted to identify the conserved regions that are essential for enzyme function. Understanding these conserved locations provides insights into potential drug targets for developing new drugs against resistant strains of bacteria.

Drug Targets Illumination: An Evidence-Based Data Analytics & Informatics Approach To Hypothesis Generation Through Clinical Trials And Genomic Variants, Jeremiah I. Abok

Chemistry and Chemical Biology ETDs

DRUG TARGETS ILLUMINATION: AN EVIDENCE-BASED DATA ANALYTICS & INFORMATICS APPROACH TO HYPOTHESIS GENERATION THROUGH CLINICAL TRIALS AND GENOMIC VARIANTS

Target Illumination Clinical Trial Analytics with Cheminformatics (TICTAC) introduces a scalable data integration pipeline that aggregates multivariate clinical trial evidence to systematically rank disease–target associations. By harmonizing metadata from AACT and employing confidence-scoring techniques, TICTAC facilitates hypothesis-driven target selection for drug discovery, enabling a data-driven approach to therapeutic development. In parallel, a bioinformatics-driven analysis of gnomAD exome mutations in the ZPR1 gene highlights the broader role of genetic variants in disease association. By employing variant effect predictors, protein stability modeling, and …

Solvation Thermodynamic Mapping Approaches For Computer-Aided Drug Discovery, Vjay Molino

Dissertations, Theses, and Capstone Projects

The drug discovery process is inherently long and costly, prompting the development and integration of computational tools to mitigate these challenges. One of area explored in computer-aided drug discovery is to understand the role of solvation in protein-drug binding and to develop computational tools and methods that can be integrated in the drug discovery process. Grid Inhomogeneous Solvation Theory (GIST) is a tool that provides a framework for mapping solvation thermodynamiproperties of water molecules on the protein surface.This thesis explores the use of GIST in generating pharmacophore models and elucidates the role of solvation in protein structural fluctuations.

One of …