Medicinal-Pharmaceutical Chemistry Commons^™

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, …

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 …

Selenium Nanoparticles As Versatile Delivery Tools, Amir Nasrolahi Shirazi, Rajesh Vadlapatla, Ajoy Koomer, Kyle Yep, Keykavous Parang

Pharmacy Faculty Articles and Research

Selenium nanoparticles (SeNPs) have emerged as promising metal-based nanoparticles for drug delivery due to their unique physicochemical properties, intrinsic bioactivity, and biocompatibility. SeNPs offer a lower toxicity, higher bioavailability, and flexibility to be customized for surface chemistry compared to traditional selenium compounds. Advances in synthetic strategies, including chemical reduction, green biosynthesis, and surface functionalization with polymers, peptides, or ligands, have improved their stability, targeting capability, and circulation time. SeNP-based systems have demonstrated unique anticancer, antimicrobial, and anti-inflammatory activities, as they can function as drug carriers and active therapeutic agents. The surface of SeNPs has been functionalized with ligands such as …

Computational Molecular Docking Of Fluorinated Morphine Derivatives For Improved Pain Management, Mirabella Romano, 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 its tertiary amino group 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 could provide pain relief without …

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 …

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 …

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). …

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, …

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 …

Mutational Scanning And Binding Free Energy Computations Of The Sars-Cov-2 Spike Complexes With Distinct Groups Of Neutralizing Antibodies: Energetic Drivers Of Convergent Evolution Of Binding Affinity And Immune Escape Hotspots, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Nishank Raisinghani, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has led to the emergence of variants with increased immune evasion capabilities, posing significant challenges to antibody-based therapeutics and vaccines. In this study, we conducted a comprehensive structural and energetic analysis of SARS-CoV-2 spike receptor-binding domain (RBD) complexes with neutralizing antibodies from four distinct groups (A–D), including group A LY-CoV016, group B AZD8895 and REGN10933, group C LY-CoV555, and group D antibodies AZD1061, REGN10987, and LY-CoV1404. Using coarse-grained simplified simulation models, rapid energy-based mutational scanning, and rigorous MM-GBSA binding free energy calculations, we elucidated the molecular mechanisms of antibody binding and escape mechanisms, identified key …

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 …

Computational Logp Calculations And Determination Of Lipophilicity Values Of Fluorinated Morphine Derivatives, Mirabella Romano, Allison Vu, Emily Chen

Student Scholar Symposium Abstracts and Posters

The addictive effect of opioids impacted 60 million people globally in 2023. This opioid crisis necessitates the development of opioid derivatives that maintain analgesic efficacy while minimizing addictive effects from opioid use. The present work focuses on morphine, a commonly prescribed opioid with high affinity to the mu-opioid receptor (MOR). Morphine binds non-selectively within both healthy and inflamed tissue. By modifying morphine’s structure through fluorination to counteract its non-selective binding, the drug’s pharmacological ability to provide effective pain relief comes with a lower risk of addiction. Specifically, the addition of fluorine to differing beta positions of the main binding site …

Rings Of Power: Controlling Sod Mimic Activity By The Addition Of Pyridine Rings Within The Pyridinophane Scaffold, Katherine J. Smith, Timothy M. Schwartz, David M. Freire, Cameron Bowers, Sarah K. Dunn, Jackson F. Bonnell, Magy A. Mekhail, Giridhar Akkaraju, Kayla N. Green

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Superoxide dismutase enzymes are a major defense against superoxide, which is a potent reactive oxygen species. Misregulation of reactive oxygen species and subsequent neuronal damage are etiological hallmarks of neurodegenerative disease. Macrocyclic small molecules have offered inroads toward functional SOD1 mimics. Herein, we report a series of five tetra-aza macrocyclic ^RPy₂N₂ ligands, varied by 4-position substitution of the pyridine ring with both electron-donating (R = OMe) and withdrawing groups (R = Cl, I, and CF₃) to offer the first comparison to well-studied ^RPyN₃ congeners and other mimics in the literature. New ligands …

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, …

Alphafold2 Modeling And Molecular Dynamics Simulations Of The Conformational Ensembles For The Sars-Cov-2 Spike Omicron Jn.1, Kp.2 And Kp.3 Variants: Mutational Profiling Of Binding Energetics Reveals Epistatic Drivers Of The Ace2 Affinity And Escape Hotspots Of Antibody Resistance, Nishank Raisinghani, Mohammed Alshahrani, Grace Gupta, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

AlphaFold2-based atomistic predictions of structures and conformational ensembles of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the most dominant Omicron variants JN.1, KP.1, KP.2 and KP.3 to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and computations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that protect and restore …

Synthesis Of Thermoresponsive Poly(N-Isopropyl Acrylamide) Based Core-Shell And Hollow Shell Nanogel With Tunable Core And Shell Thickness, Mohamad Hijazi, Molla R. Islam

Student Scholar Symposium Abstracts and Posters

Nanogels have emerged as a notably safer and more effective means for drug delivery, primarily due to their adjustable drug-loading capabilities. Hollow-core nanoparticles offer some unique properties that are desirable for drug delivery applications. Initially, silica core nanoparticles were synthesized using the Stöber process at different temperatures where Tetraethoxysilane (TEOS) undergoes hydrolysis in the presence of ethanol and then a condensation reaction to form silica nanoparticles. Scanning Electron Microscopy (SEM) and Optical Microscopy (OM) analysis revealed that the size of silica core particles varied with the synthesis temperature (300 nm at 30°C to 150 at 60°C). The core silica particles …

Ultrasoft Platelet-Like Particles Stop Bleeding In Rodent And Porcine Models Of Trauma, Kimberly Nellenbach, Emily Mihalko, Seema Nandi, Drew W. Koch, Jagathpala Shetty, Leandra Moretti, Jennifer Sollinger, Nina Moiseiwitsch, Ana Sheridan, Sanika Pandit, Maureane Hoffman, Lauren V. Schnabel, L. Andrew Lyon, Thomas H. Barker, Ashley C. Brown

Engineering Faculty Articles and Research

Uncontrolled bleeding after trauma represents a substantial clinical problem. The current standard of care to treat bleeding after trauma is transfusion of blood products including platelets; however, donated platelets have a short shelf life, are in limited supply, and carry immunogenicity and contamination risks. Consequently, there is a critical need to develop hemostatic platelet alternatives. To this end, we developed synthetic platelet-like particles (PLPs), formulated by functionalizing highly deformable microgel particles composed of ultralow cross-linked poly (N-isopropylacrylamide) with fibrin-binding ligands. The fibrin-binding ligand was designed to target to wound sites, and the cross-linking of fibrin polymers was designed …

Accurate Characterization Of Binding Kinetics And Allosteric Mechanisms For The Hsp90 Chaperone Inhibitors Using Ai-Augmented Integrative Biophysical Studies, Chao Xu, Xianglei Zhang, Lianghao Zhao, Gennady M. Verkhivker, Fang Bai

Mathematics, Physics, and Computer Science Faculty Articles and Research

The binding kinetics of drugs to their targets are gradually being recognized as a crucial indicator of the efficacy of drugs in vivo, leading to the development of various computational methods for predicting the binding kinetics in recent years. However, compared with the prediction of binding affinity, the underlying structure and dynamic determinants of binding kinetics are more complicated. Efficient and accurate methods for predicting binding kinetics are still lacking. In this study, quantitative structure–kinetics relationship (QSKR) models were developed using 132 inhibitors targeting the ATP binding domain of heat shock protein 90α (HSP90α) to predict the dissociation rate …

Methionyl-Trna Synthetase Synthetic And Proofreading Activities Are Determinants Of Antibiotic Persistence, Whitney N. Wood, Miguel Angel Rubio, Lorenzo Eugenio Leiva, Gregory J. Phillips, Michael Ibba

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Bacterial antibiotic persistence is a phenomenon where bacteria are exposed to an antibiotic and the majority of the population dies while a small subset enters a low metabolic, persistent, state and are able to survive. Once the antibiotic is removed the persistent population can resuscitate and continue growing. Several different molecular mechanisms and pathways have been implicated in this phenomenon. A common mechanism that may underly bacterial antibiotic persistence is perturbations in protein synthesis. To investigate this mechanism, we characterized four distinct metG mutants for their ability to increase antibiotic persistence. Two metG mutants encode changes near the catalytic site …

De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder–Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards …

Additive Effects Of Cyclic Peptide [R4w4] When Added Alongside Azithromycin And Rifampicin Against Mycobacterium Avium Infection, Melissa Kelley, Kayvan Sasaninia, Arbi Abnousian, Ali Badaoui, James Owens, Abrianna Beever, Nala Kachour, Rakesh Kumar Tiwari, Vishwanath Venketaraman

Pharmacy Faculty Articles and Research

Mycobacterium avium (M. avium), a type of nontuberculous mycobacteria (NTM), poses a risk for pulmonary infections and disseminated infections in immunocompromised individuals. Conventional treatment consists of a 12-month regimen of the first-line antibiotics rifampicin and azithromycin. However, the treatment duration and low antibiotic tolerability present challenges in the treatment of M. avium infection. Furthermore, the emergence of multidrug-resistant mycobacterium strains prompts a need for novel treatments against M. avium infection. This study aims to test the efficacy of a novel antimicrobial peptide, cyclic [R4W4], alongside the first-line antibiotics azithromycin and rifampicin in reducing M. avium survival. Colony-forming unit (CFU) …

Probing Conformational Landscapes Of Binding And Allostery In The Sars-Cov-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations And Perturbation-Based Profiling Approaches: Hidden Role Of Omicron Mutations As Modulators Of Allosteric Signaling And Epistatic Relationships, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta, Sian Xiao, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this study, we systematically examine the conformational dynamics, binding and allosteric communications in the Omicron BA.1, BA.2, BA.3 and BA.4/BA.5 spike protein complexes with the ACE2 host receptor using molecular dynamics simulations and perturbation-based network profiling approaches. Microsecond atomistic simulations provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the BA.2 variant which can be contrasted with the BA.4/BA.5 variants inducing a significant mobility of the complexes. Using the dynamics-based mutational scanning of spike residues, we identified structural stability and binding affinity hotspots in the Omicron complexes. Perturbation response scanning and network-based mutational …

Development And Validation Of A Uplc-Ms/Ms Method To Investigate The Plasma Pharmacokinetics Of A KCa2.2/KCa2.3 Positive Allosteric Modulator In Mice, Mohammad Asikur Rahman, Devaraj Venkatapura Chandrashekar, Young-Woo Nam, Basir Syed, David Salehi, Hamidreza Montazeri Aliabadi, Miao Zhang, Reza Mehvar

Pharmacy Faculty Articles and Research

Rationale

There is currently no treatment for spinocerebellar ataxias (SCAs), which are a group of genetic disorders that often cause a lack of coordination, difficulty walking, slurred speech, tremors, and eventually death. Activation of K_Ca2.2/K_Ca2.3 channels reportedly exerts beneficial effects in SCAs. Here, we report the development and validation of an analytical method for quantitating a recently-developed positive allosteric modulator of K_Ca2.2/K_Ca2.3 channels (compound 2q) in mouse plasma.

Methods

Mouse plasma samples (10 μL) containing various concentrations of 2q were subjected to protein precipitation in the presence of a structurally similar internal …

Balancing Functional Tradeoffs Between Protein Stability And Ace2 Binding In The Sars-Cov-2 Omicron Ba.2, Ba.2.75 And Xbb Lineages: Dynamics-Based Network Models Reveal Epistatic Effects Modulating Compensatory Dynamic And Energetic Changes, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta

Mathematics, Physics, and Computer Science Faculty Articles and Research

Evolutionary and functional studies suggested that the emergence of the Omicron variants can be determined by multiple fitness trade-offs including the immune escape, binding affinity for ACE2, conformational plasticity, protein stability and allosteric modulation. In this study, we systematically characterize conformational dynamics, structural stability and binding affinities of the SARS-CoV-2 Spike Omicron complexes with the host receptor ACE2 for BA.2, BA.2.75, XBB.1 and XBB.1.5 variants. We combined multiscale molecular simulations and dynamic analysis of allosteric interactions together with the ensemble-based mutational scanning of the protein residues and network modeling of epistatic interactions. This multifaceted computational study characterized molecular mechanisms and …

Structure-Guided Mutagenesis Reveals The Catalytic Residue That Controls The Regiospecificity Of C6-Indole Prenyltransferases, Ahmed R. Aoun, Nagaraju Mupparapu, Diem N. Nguyen, Tae Ho Kim, Christopher M. Nguyen, Zhengfeiyue Pan, Sherif I. Elshahawi

Pharmacy Faculty Articles and Research

Indole is a significant structural moiety and functionalization of the C−H bond in indole-containing molecules expands their chemical space, and modifies their properties and/or activities. Indole prenyltransferases (IPTs) catalyze the direct regiospecific installation of prenyl moieties on indole-derived compounds. IPTs have shown relaxed substrate flexibility enabling them to be used as tools for indole functionalization. However, the mechanism by which certain IPTs target a specific carbon position is not fully understood. Herein, we use structure-guided site-directed mutagenesis, in vitro enzymatic reactions, kinetics and structural-elucidation of analogs to verify the key catalytic residues that control the regiospecificity of all characterized regiospecific …

Computational Design And Molecular Modeling Of Morphine Derivatives For Preferential Binding In Inflamed Tissue, Makena Augenstein, Nayiri Alexander, Matthew Gartner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The opioid epidemic has impacted over 10 million Americans in 2019. Opioids, like morphine, bind non-selectively in both peripheral tissue, leading to effective pain relief, and central tissue, resulting in dangerous side effects and addiction. The inflamed conditions of injured tissues have a lower pH (pH = 6–6.5) environment than healthy tissue (pH = 7.4). We aim to design a morphine derivative that binds selectively within inflamed tissue using molecular extension and dissection techniques. Morphine binds to the μ-opioid receptor (MOR) when the biochemically active amine group is protonated. Fluorination of a β-carbon from the tertiary amine group led to …

Coarse-Grained Molecular Simulations And Ensemble-Based Mutational Profiling Of Protein Stability In The Different Functional Forms Of The Sars-Cov-2 Spike Trimers: Balancing Stability And Adaptability In Ba.1, Ba.2 And Ba.2.75 Variants, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta

Mathematics, Physics, and Computer Science Faculty Articles and Research

Evolutionary and functional studies have suggested that the emergence of Omicron variants can be determined by multiple fitness tradeoffs including immune escape, binding affinity, conformational plasticity, protein stability, and allosteric modulation. In this study, we embarked on a systematic comparative analysis of the conformational dynamics, electrostatics, protein stability, and allostery in the different functional states of spike trimers for BA.1, BA.2, and BA.2.75 variants. Using efficient and accurate coarse-grained simulations and atomistic reconstruction of the ensembles, we examined the conformational dynamics of the spike trimers that agree with the recent functional studies, suggesting that BA.2.75 trimers are the most stable …

Virtual And In Vitro Screening Of Natural Products Identifies Indole And Benzene Derivatives As Inhibitors Of Sars-Cov-2 Main Protease (MPro), Dony Ang, Riley Kendall, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The rapid spread of the coronavirus disease 2019 (COVID-19) resulted in serious health, social, and economic consequences. While the development of effective vaccines substantially reduced the severity of symptoms and the associated deaths, we still urgently need effective drugs to further reduce the number of casualties associated with SARS-CoV-2 infections. Machine learning methods both improved and sped up all the different stages of the drug discovery processes by performing complex analyses with enormous datasets. Natural products (NPs) have been used for treating diseases and infections for thousands of years and represent a valuable resource for drug discovery when combined with …

Probing Conformational Landscapes And Mechanisms Of Allosteric Communication In The Functional States Of The Abl Kinase Domain Using Multiscale Simulations And Network-Based Mutational Profiling Of Allosteric Residue Potentials, Keerthi Krishnan, Hao Tian, Peng Tao, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

In the current study, multiscale simulation approaches and dynamic network methods are employed to examine the dynamic and energetic details of conformational landscapes and allosteric interactions in the ABL kinase domain that determine the kinase functions. Using a plethora of synergistic computational approaches, we elucidate how conformational transitions between the active and inactive ABL states can employ allosteric regulatory switches to modulate intramolecular communication networks between the ATP site, the substrate binding region, and the allosteric binding pocket. A perturbation-based network approach that implements mutational profiling of allosteric residue propensities and communications in the ABL states is proposed. Consistent with …