Amino Acids, Peptides, and Proteins Commons^™

Decoding The Allosteric Grammar Of Protein Kinases: A Dual-Stream Framework Integrating Protein Language Models And Energy Landscape Frustration Analysis, Will Gatlin, Max Ludwick, Lucas Turano, Brandon Foley, Kamila Riedlova, Vít Škrhák, Marian Novotný, David Hoksza, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The spatial and energetic encoding of allosteric regulatory sites remains a major challenge in structural biology, frequently representing a “blind spot” for sequence-based artificial intelligence (AI) models. We present a protein language model (PLM)-guided approach complemented by the energy landscape frustration analysis as a dual-stream framework to investigate the relationship between AI prediction of binding sites and biophysical organization of regulatory pockets across the human kinome. By probing a fine-tuned residue-level PLM classifier across 453 kinase structures, a clear performance gap is discovered between highly predictable orthosteric pockets (Types I, I.5, and II) and poorly resolved distal allosteric sites (Type …

Computational Insights Into Nucleosome Dynamics In Epigenetics Using Molecular Dynamics Simulations, Rutika Patel

Dissertations, Theses, and Capstone Projects

Nucleosome core particles (NCP) are the building blocks that form a highly organized and compact chromatin structure. Nucleosomes package DNA in the nucleus of eukaryotic cells. The NCP consists of about 147 base pairs of DNA wrapped around the histone octamer, with 1.65 superhelical turns in a left-handed manner. The histone octamer is composed of two copies of H3, H4, H2A, and H2B. Together with histone H1 and linker DNA, they further assemble into a higher-order chromatin structure. The nucleosome complex is stabilized by electrostatic interactions between positively charged histone residues and the negatively charged DNA backbone. To effectively access …

Predicting And Decoding Allosteric Binding Sites Using Protein Language Models And Structure-Based Machine Learning: An Energy Landscape-Guided Explainable Ai Framework, Kamila Riedlová, Vít Skrhák, William G. Gatlin, Max Ludwick, Lucas Turano, Marian Novotný, David Hoksza, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Computational prediction of allosteric binding sites in protein structures remains a persistent challenge, as these regulatory pockets evade detection by both sequence-based and structure-based algorithms. Both computational and physical origins of this predictive asymmetry remain insufficiently understood. In this study, we systematically examine the determinants of binding site predictability using a dual framework that integrates a fine-tuned protein language model and the structure-based method P2Rank as complementary tools probing a diverse data set of 453 human kinases, together with a physics-based interpretability layer derived from energy landscape frustration analysis. Both predictors exhibit a sharp and reproducible dichotomy on protein kinases, …

Herbularyo (Folk Healer): An Herbal Medicine Card Game, Maryjane T. Magsino, Inah Marie Q. Rivera, Armando M. Guidote, Genejane M. Adarlo

Chemistry Faculty Publications

Herbularyo, a card game teaching about herbal plants (HPs), was created and evaluated as a viable educational card game based on Tuomisto and Aksela’s criteria. A quasi-experiment was performed on 81 Grade 8 students from a private high school and 50 Grade 11 from a public high school. Independent t-test revealed that the control group (CG) and experimental group (EG) (p=0.386), and EG1 (played ≤5) and EG2 (played >5) (p=0.681) are not comparable with each other. Paired t-test showed EG performed better (p=0.001) than CG (p=0.901) whereas ANCOVA showed that playing Herbularyo improved students’ information retention (p=0.006). EG1 and EG2 …

Increased Backbone Rigidity Of Artificial Transcription Factors, Jasmine Glover, Emma Otey, Joanna K. Kwao, Nicholas Truex

Senior Theses

Programming DNA-binding proteins is an effective strategy for developing therapeutics that regulate gene expression. These proteins can directly bind to DNA to activate or repress transcription of specific genes. Zinc finger proteins are a class of DNA-binding proteins commonly found in eukaryotic organisms. Their DNA-binding function is derived from unique amino acid sequences within each domain that recognizes specific nucleotides, allowing each finger to selectively recognize three DNA base pairs. Adjoining of multiple domains in tandem allows recognition of a specific DNA sequence. Artificial transcription factors can be made of multiple zinc finger domains arranged in tandem and engineered to …

From Latent Manifolds To Targeted Molecular Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework For Family-Based Kinase Ligand Design, Gennady M. Verkhivker, Ryan Kassab, Keerthi Krishnan

Mathematics, Physics, and Computer Science Faculty Articles and Research

Scaffold-aware artificial intelligence (AI) models enable systematic exploration of chemical space conditioned on protein-interacting ligands, yet the representational principles governing their behavior remain poorly understood. The computational representation of structurally complex kinase small molecules remains a formidable challenge due to the high conservation of ATP active site architecture across the kinome and the topological complexity of structural scaffolds in current generative AI frameworks. In this study, we present a diagnostic, modular and chemistry-first generative framework for design of targeted SRC kinase ligands by integrating ChemVAE-based latent space modeling, a chemically interpretable structural similarity metric (Kinase Likelihood Score), Bayesian optimization, and …

Short-Term Preeclampsia Prediction: Cutoff Variations For Sflt-1/Plgf In U.S. Patients With Or Without Hypertensive Disorders, Yaxin Li, Kristen Cagino, Jim Yee, Caroline Andy, Dajana Borova, Ayush Shah, Isla Racine, Tracy Grossman, Zhen Zhao

Student Papers, Posters & Projects

BACKGROUND: Preeclampsia (PE) is a complex disorder with significant maternal and fetal risks. The soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF) ratio shows promise as a diagnostic tool, but its adoption in the U.S. remains limited due to the lack of accessible testing platforms, U.S.-based studies, and evidence-based implementation guidelines.

PATIENTS/MATERIALS AND METHODS: We conducted a cohort study to evaluate the sFlt-1/PlGF ratio for predicting PE within two weeks among pregnant individuals ≥18 years, ≥20 weeks gestation. Serum samples were obtained from routine prenatal visits or triage evaluations. sFlt-1/PlGF ratios were measured using Roche Elecsys assays, and …

Non-Invasive Detection Of Choroidal Melanoma Via Tear-Derived Protein Corona On Gold Nanoparticles: A Machine Learning Approach, Hakimeh Rakhshandeh, Ahmad Nasiraei, Hamid Riazi-Esfahani, Babak Masoomian, Fariba Ghassemi, Mojtaba Arjmand, Saeed Heidari Keshel, Fatemeh Atyabi, Rassoul Dinarvand

Wills Eye Hospital Papers

This study investigates the feasibility of using tear sample analysis, based on protein corona formation on gold nanoparticles combined with electrospray ionization mass spectrometry (ESI-MS) and machine learning techniques, as a non-invasive approach for the detection of choroidal melanoma. The aim is to assess whether protein-nanoparticle interactions can support early and reliable identification of this ocular condition. Tear samples were collected using Schirmer strips from six healthy individuals and six patients diagnosed with choroidal melanoma, with subsequent augmentation to 18 samples per group. Gold nanoparticles (AuNPs, ~ 20 nm) were synthesized via citrate reduction and incubated with tear samples to …

Allosteric Control Overcomes Steric Limitations For Neutralizing Antibodies Targeting Conserved Binding Epitopes Of The Sars-Cov-2 Spike Protein: Exploring The Intersection Of Binding, Allostery, And Immune Escape With A Multimodal Computational Approach, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Understanding the atomistic basis of multi-layer mechanisms employed by broadly reactive neutralizing antibodies of the SARS-CoV-2 spike protein without directly blocking receptor engagement remains an important challenge in coronavirus immunology. Class 4 antibodies represent an intriguing case: they target a deeply conserved, cryptic epitope on the receptor-binding domain yet exhibit variable neutralization potency across subgroups F1 (CR3022, EY6A, COVA1-16), F2 (DH1047), and F3 (S2X259). The molecular basis for this variability is not fully understood. Here, we employed a multi-modal computational approach integrating atomistic and coarse-grained molecular dynamics simulations, binding free energy calculations, mutational scanning, and dynamic network analysis to elucidate …

Air Pollution And Diseases: Signaling, G Protein-Coupled And Toll Like Receptors, Isabella Cattani-Cavalieri, Katrina F. Ostrom, Jordyn Margolis, Rennolds S. Ostrom, Martina Schmidt

Pharmacy Faculty Articles and Research

Air pollution is a significant public health issue that impacts lung health, particularly in vulnerable populations such as children, the elderly, and individuals with pre-existing respiratory conditions. Both natural and anthropogenic sources of air pollution give rise to a variety of toxic compounds, including particulate matter (PM), ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and polycyclic aromatic hydrocarbons (PAHs). Exposure to these pollutants is strongly associated with the development and exacerbation of respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), lung cancer, and idiopathic pulmonary fibrosis (IPF). Notably, early life exposure to pollutants such as …

Dynamic Mutational Profiling Of Binding Interactions And Allosteric Networks In Conformational Ensembles Of The Sars-Cov-2 Spike Protein Complexes With Classes Of Antibodies Targeting Cryptic Binding Sites: Confluence Of Binding And Allostery Determines Molecular Mechanisms And Hotspots Of Immune Escape, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The ongoing evolution of SARS-CoV-2 variants has underscored the need to understand not only the structural basis of antibody recognition but also the dynamic and allosteric mechanisms that could underlie complexity of broad and escape-resistant neutralization. In this study, we employed a multi-scale approach integrating structural analysis, hierarchical molecular simulations, mutational scanning and network-based allosteric modeling to dissect how Class 4 antibodies (represented by S2X35, 25F9, and SA55) and Class 5 antibodies (represented by S2H97, WRAIR-2063 and WRAIR-2134) can modulate conformational behavior, binding energetics, allosteric interactions and immune escape patterns of the SARS-CoV-2 spike protein. Using hierarchical simulations of the …

A Mutational Analysis Of Thatisin: How Single Point Mutations Impact The Biosynthetic Process Of A Group 16 Graspetide, John F. Boynton Jr

Chemistry and Chemical Biology ETDs

Abstract:

Graspetides are a family of Ribosomally synthesized and Post-translationally modified Peptide (RiPP) natural products named for their ATP Grasp Macrocyclases. We identified several Graspetide Biosynthetic Gene Clusters containing common double glycine cleavage motifs and attempted characterization of the mature Graspetides. One of the resulting peptides, Thatisin, has a topology with two interlocking macrolactones installed by a single ATP Grasp Ligase named ThtC. Here we use single and double point mutations to observe the impact or variation on the installation of these macrocycles. Alanine scan mutagenesis is used to assess leader peptide residues in the precursor peptide ThtA to determine …

Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope …

Ensemble-Based Binding Free Energy Profiling And Network Analysis Of The Kras Interactions With Darpin Proteins Targeting Distinct Binding Sites: Revealing Molecular Determinants And Universal Architecture Of Regulatory Hotspots And Allosteric Binding, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

KRAS is a pivotal oncoprotein that regulates cell proliferation and survival through interactions with downstream effectors such as RAF1. Despite significant advances in understanding KRAS biology, the structural and dynamic mechanisms of KRAS allostery remain poorly understood. In this study, we employ microsecond molecular dynamics simulations, mutational scanning, and binding free energy calculations together with dynamic network modeling to dissect how engineered DARPin proteins K27, K55, K13, and K19 engage KRAS through diverse molecular mechanisms ranging from effector mimicry to conformational restriction and allosteric modulation. Mutational scanning across all four DARPin systems identifies a core set of evolutionarily constrained residues …

Integrative Computational Modeling Of Distinct Binding Mechanisms For Broadly Neutralizing Antibodies Targeting Sars-Cov-2 Spike Omicron Variants: Balance Of Evolutionary And Dynamic Adaptability In Shaping Molecular Determinants Of Immune Escape, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this study, we conducted a comprehensive analysis of the interactions between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and four neutralizing antibodies—S309, S304, CYFN1006, and VIR-7229. Using integrative computational modeling that combined all-atom molecular dynamics (MD) simulations, mutational scanning, and MM-GBSA binding free energy calculations, we elucidated the structural, energetic, and dynamic determinants of antibody binding. Our findings reveal distinct dynamic binding mechanisms and evolutionary adaptation driving the broad neutralization effect of these antibodies. We show that S309 targets conserved residues near the ACE2 interface, leveraging synergistic van der Waals and electrostatic interactions, while S304 focuses on …

Probing Binding And Allosteric Mechanisms Of The Kras Interactions With Monobodies And Affimer Proteins : Ensemble-Based Mutational Profiling And Thermodynamic Analysis Of Binding Energetics And Allostery Reveal Diversity Of Functional Hotspots And Cryptic Pockets Linked By Conserved Communication Network, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Guang Hu, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

KRAS, a historically "undruggable" oncogenic driver, has eluded targeted therapies due to its lack of accessible binding pockets in its active state. This study investigates the conformational dynamics, binding mechanisms, and allosteric communication networks of KRAS in complexes with monobodies (12D1, 12D5) and affimer proteins (K6, K3, K69) to characterize the binding and allosteric mechanisms and hotspots of KRAS binding. Through molecular dynamics simulations, mutational scanning, binding free energy analysis and network-based analyses, we identified conserved allosteric hotspots that serve as critical nodes for long-range communication in KRAS. Key residues in β-strand 4 (F78, L80, F82), α-helix 3 (I93, H95, …

Quantitative Characterization And Prediction Of The Binding Determinants And Immune Escape Hotspots For Groups Of Broadly Neutralizing Antibodies Against Omicron Variants: Atomistic Modeling Of The Sars-Cov-2 Spike Complexes With Antibodies, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Nishank Raisinghani, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

A growing body of experimental and computational studies suggests that the cross-neutralization antibody activity against Omicron variants may be driven by the balance and tradeoff between multiple energetic factors and interaction contributions of the evolving escape hotspots involved in antigenic drift and convergent evolution. However, the dynamic and energetic details quantifying the balance and contribution of these factors, particularly the balancing nature of specific interactions formed by antibodies with epitope residues, remain largely uncharacterized. In this study, we performed molecular dynamics simulations, an ensemble-based deep mutational scanning of SARS-CoV-2 spike residues, and binding free energy computations for two distinct groups …

Asymmetric Synthesis Of The Hiv Protease Inhibitor Tmc-126 And An Anti-Malarial Agent Via A Titanium Tetrachloride Mediated Asymmetric Glycolate Aldol Addition Reaction. Redefining The Curtius Rearrangement Reaction Via Dehomologation Of Carboxylic Acids Bearing Alpha-Leaving Groups, Kweku Amaning Affram

Theses and Dissertations

Acquired Immune Deficiency Syndrome (AIDS) and malaria are two devastating infectious diseases caused by HIV and Plasmodium parasites. AIDS is caused by HIV-1 and HIV-2, transmitted through sexual contact, blood transfusions, needle sharing, and perinatal routes. Malaria, caused by plasmodium parasites through mosquito bites. Today, millions of people around the world have been infected with HIV and malaria and much research has been done to treat it. However, despite advancements in therapeutic options, these diseases remain a significant global health threat, particularly in developing countries due to the emergence of drug-resistant strains for both HIV and malaria complicating eradication efforts. …

Alpha-Synuclein Interaction With Gedunin, Tony Matundura Nyabayo

Graduate Theses/Dissertations

Parkinson’s disease (PD) and other Proteinopathies develop when α-synuclein misfolds and aggregates into toxic amyloids. While existing treatments for PD are primarily focused on managing its symptoms, a viable solution for slowing down the progress of Parkinson’s disease involves targeting the toxic α-synuclein amyloids. Gedunin, a natural inhibitor of heat shock protein 90, has been extensively used to treat malaria. Also, recent research investigations have shed light on its potential beyond malaria therapy, indicating that Gedunin may offer a possible solution for treating a variety of neurodegenerative diseases. Using plate-based assays, we examined how Gedunin influences α-synuclein fibrillation and its …

Deciphering The Chemistry Of Condensed Aromatic "Black" Carbon And Nitrogen In Amazonian Anthrosols, João Vitor Dos Santos, Aleksandar I. Goranov, Laís G. Fregolente, Marcia C. Bisinoti, Zhenhuan Sun, Klaus Schmidt-Rohr, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

Amazonian anthrosols are renowned for their high fertility and dark color, properties primarily attributed to the abundance of condensed aromatic carbon (ConAC) in the soil organic matter. ConAC, commonly referred to as black carbon, play a key role in the stability and nutrient retention of these soils. However, the processes governing the formation of ConAC and its transformation into oxygenated derivatives remain poorly understood. In this study, we used multiple analytical platforms to investigate the chemistry of ConAC-rich humic acids (HA) extracted from Terra Mulata de Indio, a type of Amazonian anthrosol. The results reveal that ConAC are predominantly …

Interaction Of Cardiac Leiomodin With The Native Cardiac Thin Filament, Madison Little, Cristina M. Risi, Tania M. Larrinaga, Mason D. Summers, Tyler Nguyen, Garry E. Smith Jr., Jennifer Atherton, Carol C. Gregorio, Alla S. Kostyukova, Vitold E. Galkin

Department of Biomedical and Translational Sciences Faculty Publications

Every heartbeat depends on cyclical contraction-relaxation produced by the interactions between myosin-containing thick and actin-based thin filaments (TFs) arranged into a crystalline-like lattice in the cardiac sarcomere. Therefore, the maintenance of thin filament length is crucial for myocardium function. The thin filament is comprised of an actin backbone, the regulatory troponin complex and tropomyosin that controls interactions between thick and thin filaments. Thin filament length is controlled by the tropomodulin family of proteins; tropomodulin caps pointed ends of thin filaments, and leiomodin (Lmod) promotes elongation of thin filaments by a “leaky-cap” mechanism. The broader distribution of Lmod on the thin …

Structural Optimization And Stability Enhancement Of Uba(2) And Ntl9 Using The Computational Tool: Emcast, Bahar Ghazi Esfahani

Graduate Student Theses, Dissertations, & Professional Papers

This study enhances protein stability prediction by refining EmCAST (Empirical C-Alpha Stability Tool), a computational tool used to identify stabilizing mutations in protein domains. We applied EmCAST to two model proteins: the α-helical ubiquitin-associated domain 2 (UBA(2)) and the α/β N-terminal domain of ribosomal protein L9 (NTL9). Protein stability is critical for proper function, and mutations can lead to misfolding and disease. To validate EmCAST’s predictions, guanidine hydrochloride-induced denaturation was monitored using circular dichroism (CD) spectroscopy for both wild-type and mutant variants. Results guided refinements to EmCAST’s algorithm, incorporating new experimental datasets to improve accuracy. Additionally, we examined the assumption …

Redox Control In A Fused Electron Transfer Flavoprotein From A Thermophilic Archaeon And Expanded Significance Of A Hydrogen Bond From A Conserved Histidine Residue That Contributes To Flavin Redox Tuning And Activation For Covalent Modification, Debarati Das

Theses and Dissertations--Chemistry

In absence of O₂ as terminal electron acceptors in anaerobic bacteria and archaea, carbohydrate metabolism is 15 times less efficient compared to aerobic energy metabolism resulting in energy deficit conditions. Despite their meager resources these anaerobes were able to generate H₂ and a chemiosmotic potential able to drive energy demanding reactions such as CO₂ or N₂ fixation. These observations raised concerns as production of high energy reductants (H₂) from mediocre fuels (NADH) defied the laws of thermodynamics.

In 2008, a known mechanism “electron bifurcation” but with flavins as redox mediators instead of quinones was …

Determination Of Structural Factors Contributing To Protection Of Zinc Fingers In Estrogen Receptor Α Through Molecular Dynamic Simulations, Patricia B. Lutz, Wesley R. Coombs, Craig A. Bayse

Chemistry & Biochemistry Faculty Publications

The ERα transcription factor that induces tumor growth is a potential target for breast cancer treatment. Each monomer of the ERα DNA-binding domain (ERαDBD) homodimer has two conserved (Cys)₄-type zinc fingers, ZF1 (N-terminal) and ZF2 (C-terminal). Electrophilic agents release Zn²⁺ by oxidizing the coordinating Cys of the more labile ZF2 to inhibit dimerization and DNA binding. Microsecond-length molecular dynamics (MD) simulations show that greater flexibility of ZF2 in the ERαDBD monomer leaves its Cys more solvent accessible and less shielded from electrophilic attack by sulfur-centered hydrogen bonds than ZF1 which is buried in the protein. In the …

Automating The Amino Acid Identification In Elliptical Dichroism Spectrometer With Machine Learning, Ridhanya Sree Balamurugan, Yusuf Asad, Tommy Gao, Dharmakeerthi Nawarathna, Umamaheswara Rao Tida, Dali Sun

Electrical & Computer Engineering Faculty Publications

Amino acid identification is crucial across various scientific disciplines, including biochemistry, pharmaceutical research, and medical diagnostics. However, traditional methods such as mass spectrometry require extensive sample preparation and are time-consuming, complex and costly. Therefore, this study presents a pioneering Machine Learning (ML) approach for automatic amino acid identification by utilizing the unique absorption profiles from an Elliptical Dichroism (ED) spectrometer. Advanced data preprocessing techniques and ML algorithms to learn patterns from the absorption profiles that distinguish different amino acids were investigated to prove the feasibility of this approach. The results show that ML can potentially revolutionize the amino acid analysis …

A Survey On Deep Learning For Drug-Target Binding Prediction: Models, Benchmarks, Evaluation, And Case Studies, Kusal Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Conventional drug discovery is expensive, time-consuming, and prone to failure. Artificial intelligence has become a potent substitute over the last decade, providing strong answers to challenging biological issues in this field. Among these difficulties, drug-target binding (DTB) is a key component of drug discovery techniques. In this context, drug-target affinity and drug–target interaction are complementary and essential frameworks that work together to improve our comprehension of DTB dynamics. In this work, we thoroughly analyze the most recent deep learning models, popular benchmark datasets, and assessment metrics for DTB prediction. We look at the paradigm shift in the development of drug …

Deepssetracer 2.0: Improved Deep Learning Model Performance For Protein Secondary Structure Segmentation From Cryo-Em Maps, Bryan Hawickhorst, Thu Nguyen, Willy Wriggers, Jiangwen Sun, Jing He

Computer Science Faculty Publications

DeepSSETracer is a method for segmenting protein secondary structure from medium-resolution (5-10Å) cryogenic electron microscopy (cryo-EM) density maps. We conducted experiments and ablation studies to examine the effects of normalization methods, max-pooling, activation functions, and loss calculation region on DeepSSETracer. By combining multiple technical improvements, the performance of the new version, DeepSSETracer 2.0, was significantly enhanced compared to DeepSSETracer 1.1. On a set of 77 test cases, the weighted average per-voxel F1 score increased from 62.1% to 70.3% for helix detection, and from 47.8% to 62.5% for β-sheet detection. While each of the five modifications in the network enhanced the …

Assembly Of Ppsu-Oligomers, Mariam Nesterov

Student Theses and Dissertations

The development of nanostructures for delivering multiple proteins to targeted antibodies has become a promising avenue in biotechnology, driven by advancements in synthetic polymers like poly(propylene sulfone), PPSU. However, the PPSU polymer faces a major limitation - its high insolubility. To address this challenge, this study investigates whether PPSU oligomers can enhance both the solubility and stability of lysozyme, a model protein that is cost-effective and widely accessible. Using dimer, trimer, tetramer, and hexamer configurations, we analyzed the interactions between PPSU oligomer and lysozyme under varying conditions. Our results show that the dimer and trimer are water soluble (no aggregate …

Design, Synthesis, And Nmr-Guided Characterization Of A Targeted Covalent Inhibitor-Like Molecule Against Ivyp1 From P. Aeruginosa, Samuel Taylor Moore

Master's Theses

Multi-drug resistance poses a serious threat to future generations and historical antibiotic pipelines; consequently, the medical and economic burdens associated with treating multidrug-resistant bacteria are substantiated. In this context, P. aeruginosa (PA) emerges as one of the most significant healthcare challenges, being a leading cause of resistance-associated mortality worldwide. Despite modern efforts to combat these poor outcomes, drug-resistant cases continue to rise, and the need for novel antibiotic treatment is apparent. To this end, we investigated relevant resistance mechanisms and past antibiotic targets within PA, and in doing so, we identified relationships between peptidoglycan biology and a periplasmic protein, Inhibitor …

Alphafold2-Based Characterization Of Apo And Holo Protein Structures And Conformational Ensembles Using Randomized Alanine Sequence Scanning Adaptation: Capturing Shared Signature Dynamics And Ligand-Induced Conformational Changes, Nishank Raisinghani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Proteins often exist in multiple conformational states, influenced by the binding of ligands or substrates. The study of these states, particularly the apo (unbound) and holo (ligand-bound) forms, is crucial for understanding protein function, dynamics, and interactions. In the current study, we use AlphaFold2, which combines randomized alanine sequence masking with shallow multiple sequence alignment subsampling to expand the conformational diversity of the predicted structural ensembles and capture conformational changes between apo and holo protein forms. Using several well-established datasets of structurally diverse apo-holo protein pairs, the proposed approach enables robust predictions of apo and holo structures and conformational ensembles, …