Pharmaceutical Sciences

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    Discovery and Structure-Based Optimization of Benzimidazole-Derived Activators of Slack Potassium Channels
    (2024-03-21) Peprah, Paul; Du, Yu; Spitznagel, Brittany; Nguyen, Dalena; Bakonyi, Jayson; Weaver, David; Emmitte, Kyle
    Purpose: Fragile X syndrome (FXS) is a genetic disorder caused by the absence of Fragile X Mental Retardation Protein (FMRP) in neurons resulting in intellectual disability, behavioral, and learning challenges. FMRP is an RNA-binding protein that also interacts with numerous cytoplasmic and nuclear proteins. Preclinical studies have shown that FMRP binds the C-terminus of the sodium-activated potassium channel Slack, to modulate electrical activity in the brain. This finding was validated by biochemical and electrophysiological studies which confirmed that sodium-activated potassium currents in neurons are decreased in Fmr1-knockout versus Slack WT mice. Thus, evidence suggests that the deficiency of FMRP in FXS may affect the physiological role of Slack in regulating neuronal excitability, contributing to cognitive dysfunction associated with FXS. We therefore hypothesize that Slack dysfunction can be restored with small molecules in the treatment of intellectual disability associated with neurodevelopmental disorders. Our research has identified the hit compound VU0519388 (VU388), as a moderately potent Slack activator. Using medicinal chemistry strategies, we seek to generate analogs with enhanced Slack activity, which may serve as valuable tools to characterize the pathophysiological role of Slack in FXS. Method: Our approach involved identifying multiple regions of VU388that could be readily diversified and designing short efficient synthetic routes used to produce small libraries of analogs. Structure and purity of all analogs were confirmed using spectra obtained from a Bruker Fourier 300HD NMR spectrometer and an Agilent 6230 time-of-flight LC/MS. Cellular activity was then evaluated using a Tl+ flux assay in HEK-293 cells that stably express wild-type (WT) Slack channels. Results: Each region of the VU388 scaffold proved tolerant of modification to some degree. Substitution with a variety of electron withdrawing and donating groups at various positions on the western benzimidazole ring and eastern aryl ring produced analogs with superior potency relative to VU388. Monosubstitution on the eastern aryl ring was well tolerated compared to disubstitution. Conclusion: Our systematic optimization plan has identified clear structure-activity relationships and multiple Slack activator analogs with improved activity relative to VU388. Multiple regions of the scaffolds are amenable to SAR development, which greatly enhances the probability of reaching our goal of highly optimized probes. Additional modifications that combine optimal features may provide additional SAR and analogs with optimal potency for use as a molecular probe.
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    Increasing Bioavailability of Simvastatin Using New Drug Formulation
    (2024-03-21) Nguyen, Christine
    Simvastatin (SMV) is a cholesterol lowering drug. It is currently given independently to patients with hypercholesterolemia or in combination with other drugs when hyperlipidemia is a comorbidity. The drug itself is considered a BCS Class II drug because of its high permeability but low solubility properties. Currently, it is created as a prodrug, which means it needs to be converted by liver enzymes to work. This results in a high hepatic extraction with low bioavailability. Because of its low solubility and low bioavailability after high hepatic extraction, the amount of simvastatin being processed into tablets is not enough to effectively treat hypercholesterolemia. Therefore, a Simvastatin granule (SMV combined with other substances) was created to increase the solubility of the drug, which would increase its bioavailability in the body without causing adverse effects that are dose related. To test bioavailability is increased in the granule formulation, a UV spectrophotometer and two-step dissolution method were used to compare the granule to the Simvastatin powder by itself. The two-step dissolution method allows one to compare the concentration of the granule to that of the powder after certain time intervals, and the UV spectrophotometer was used to determine these concentrations throughout this study. From the two-step dissolution study conducted, it was shown that the granule consistently had higher bioavailability compared to the powder counterpart at the same time interval. Therefore, this indicates that the granule formulation has potential to increase Simvastatin’s solubility and bioavailability, which can change the way the drug is packaged into tablets and given as a medication in the future.
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    Leveraging Graph Attention Mechanisms to Create an Explainable Multi-Function Machine Learning Model
    (2024-03-21) Mathew, Ezek; Madugula, Sita Sirisha; Emmitte, Kyle; Liu, Jin
    Purpose: Identifying target-specific ligands is a difficult task, especially in cases where receptors display high structural similarity. Such is the case for metabotropic glutamate receptor subtype 2 (mGlu2) and metabotropic glutamate receptor subtype 3 (mGlu3), which are prime targets for various neurological treatments. However, signal transduction through these two receptors often yields opposing physiological function and differentially affect pathologies. Methods: Understanding the need to differentiate ligands based on their binding to mGlu2 and mGlu3, we employed a machine learning (ML) approach. The ML model performed three distinct tasks and leveraged transfer learning to inform each subsequent task. Task 1: Simple Classification was performed, as the ML model predicted if the ligands displayed selectivity for the mGlu2 or mGlu3 class. Task 2: Regression was performed, as the ML model estimated the IC50 values of individual input ligands. The classification weights from Task 1 were broadcasted into the attention layers of the ML model for Task 2, serving as a starting point. Task 3: Classification was performed, as the ML model sought to determine if a ligand displayed low or high potency for the target class. Classification weights and regression weights from previous tasks were broadcasted into the model. Results: The model yielded greater than 99% accuracy in the selectivity classification task, while also delivering satisfactory performance when predicting potency (72.80% error). The model yielded 83% accuracy in correctly identifying high potency mGlu2 ligands, as high potency mGlu2 compounds. Meanwhile, the algorithm displayed 75% accuracy in correctly identifying high potency mGlu3 ligands, as high potency mGlu3 compounds. Conclusions: This approach allows for prediction of multiple target properties using a single model. With access to other high-quality datasets, this model has the potential to apply to other ligand classes of interest, posing great potential for drug repurposing studies.
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    Efficacy of Using Zoledronate for Prevention of Craniofacial Fractures in Mice with Osteogenesis Imperfecta
    (2024-03-21) Pattillo, Bryce; Miller, Courtney A.; Emmanuel, Tanusha; Crowe, Nicole M.; Menegaz, Rachel A.
    Osteogenesis imperfecta (OI) is a genetic disorder of type I collagen that results in increased bone fragility, increased fracture rates, and abnormalities of the limbs, vertebral column, and craniofacial skeleton. Long-lasting bisphosphonate drugs, like zoledronate, are used in children with OI to increase bone mineral density and prevent skeletal fractures. Zoledronate increases osteoclast apoptosis, thus reducing relative rates of bone resorption and increasing formation rates. Previous experimental research on the efficacy of zoledronate has focused largely on the postcranial skeleton (e.g. limbs). The goal of this study is to investigate if zoledronate reduces the rate of craniofacial fractures in mice with osteogenesis imperfecta. We hypothesize that mice treated with zoledronate will have fewer skeletal fractures of the skull compared to untreated mice. Mice with OI (OIM, B6C3Fe a/a-Col1a2oim/oim) and unaffected littermates (wild-type, WT) were randomly assigned into either control (C) or zoledronate (ZOL) treatment groups (n=5/genotype/group). Mice treated with zoledronate received subcutaneous injections of the drug (80 µg/kg) at 4, 8, and 12 weeks of age. The craniofacial skeleton of all mice was imaged with a micro-CT scanner (20 µm3 voxels) every 4 weeks from 4-16 weeks. 3D models of the craniofacial skeleton were generated in 3D Slicer software, and analyzed for incidence and location of fractures. At 8 weeks, no fractures were observed in WT-C or WT-ZOL mice. However, fractures were observed in both groups of OIM mice. 80% (4/5 per group) of OIM-C and OIM-ZOL mice had skeletal fractures, and the remaining 20% (1/5 per group) had fractured incisors. All skeletal fractures were observed along the zygomatic arch, proximal to the attachment site of the masseter muscle. Both unilateral and bilateral zygomatic fractures were observed. Preliminary data indicates that a single treatment with zoledronate at 4 weeks of age does not reduce the incidence of craniofacial fractures in mice with OI. Additional data is needed to assess if zoledronate improves fracture healing or bone quality outcomes (e.g. BMD) in the craniofacial skeleton, as has been demonstrated in limb bones. Additionally, the prevalence of fractures proximal to skeletal attachment sites for feeding muscles suggestions that muscle-bone interactions are a key component for understanding the origin of facial fractures in this model. Previous work has shown that long-term use of bisphosphonates like zoledronate may have negative outcomes for the craniofacial skeleton, including delayed bone formation, altered dental eruption, and osteonecrosis of the jaw (ONJ). This study suggests that craniofacial health is an important consideration, distinct from postcranial health, when planning interventions for patients with OI.
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    Prediction of Ligand Selectivity and Efficacy Using Artificial Intelligence Algorithms
    (2024-03-21) Yeung, Tatiana; Mathew, Ezek; Liu, Kevin; Madugula, Sirisha; Nguyen, Trong; Pham, Tyler; Liu, Jin
    Introduction: Bringing new pharmaceuticals to market is a time-intensive and expensive process. The purpose of this project is to combine computational structure based approaches such as docking and machine learning methodologies to yield ideal pharmaceutical candidates for future exploration. The ligands of interest were those that bind to the Dopamine 4 (D4) and Sigma 1 (S1) receptors, serving as prime candidates for treatment of neurological ailments. Design of more efficacious and selective ligands could allow researchers and clinicians to improve treatment of patients with such conditions. The primary objective is to leverage advancements in computational chemistry to approach the problem of identifying ideal drug candidates using both ligand based and structure-based approaches. Methods: Receptor structures were identified for both the D4 receptor using the PDB 5WIU, and the S1 receptor using the PDB 5HK1. A list of possible ligands was obtained from a DrugBank database, collaborators at the University of Nebraska Medical Center, and a similarity search. The DrugBank database of FDA approved drugs was scanned for ligands to both the D4 and S1 receptors, and a list of 1415 drug ligands was compiled. Using Autodock software, we docked each ligand with 10 poses. After docking, the ligands were ranked by binding affinity. Using Autodock software, the 83 ligands we received from our collaborators were also docked and ranked by binding affinity to the D4 and S1 receptors. To further expand our pool of potential candidates for further study, a similarity search was conducted by screening through a drug database (ZINC) to identify the FDA approved drugs that were most structurally similar to the 83 ligands. Ligands from both the DrugBank and the similarity search were integrated into a machine learning pipeline using graph neural networks to predict the Ki values, thereby identifying compounds with high binding affinity. Once the ligands of highest affinity are identified by the machine learning model, they will be sent to our collaborators for in vitro testing. Results: Of the top 50/1450 FDA approved drugs with the lowest Ki values for both D4, 18 overlapped with the top 50/1450 lowest Ki values for S1. Docking the 83 ligands to the D4 and S1 receptors showed that the ligands were generally more strongly bonded to S1 than D4. We will deliver the top ligand candidates belonging to both D4 and S1 ligand classes as identified by the machine learning model to our collaborators so they can perform further in vitro testing. This will allow us to validate our computational efforts with real world testing. Conclusion: We will leverage the trained machine learning model to search through more databases and identify other prime candidates for future exploration.
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    Studies Directed Toward the Synthesis of Novel Bitopic Ligands of the Muscarinic Acetylcholine Receptor Subtype 4
    (2024-03-21) Gruber, Jennifer; Hayatshahi, Hamed; Liu, Jin; Emmitte, Kyle
    Purpose: Alzheimer’s disease (AD) is characterized by amyloid deposits that build up in the brain and cause neurodegeneration. It is estimated that 6.7 million Americans currently have AD and at age 45, the lifetime probability of developing AD are 1 in 5 for women and 1 in 10 for men. Cognitive and behavioral impairments in AD are associated with dysregulation of cholinergic signaling that occurs due to neuronal damage and a decreased availability of the acetylcholine neurotransmitter. Muscarinic acetylcholine receptors are a family of G protein-coupled receptors (GPCRs) with five subtypes (M₁₋₅). Clinical trials with the M₁/M₄-preferring orthosteric agonist xanomeline previously demonstrated promise in treating cognitive and behavioral impairments in AD patients; however, further advancement of the experimental drug was prevented due to adverse effects associated with activation of M₂ and/or M₃ receptors. Achieving subtype selectivity with orthosteric agonists remains challenging due to high homology at the binding site. On the other hand, positive allosteric modulators (PAMs) have demonstrated more promising selectivity profiles. We hypothesize that bitopic ligands that engage both the orthosteric and allosteric binding sites of M₄ will selectively and directly activate the receptor, offering a pharmacological profile advantageous for the treatment of the cognitive and behavioral symptoms associated with AD. We will utilize published crystal structures and molecular docking studies to design bitopic ligands of M₄ that consist of xanomeline covalently linked to known M₄ PAMs. The objective of the current study is to design and execute viable syntheses of select putative M₄ bitopic ligands to enable their pharmacological evaluation. Methods: Autodock tools were used to prepare the model of M₄ using the published crystal structure (PDB code 5DSG), and potential ligands were docked with Autodock Vina. Compounds were synthesized using solution phase chemistry and microwave-assisted organic synthesis (MAOS) when possible. Automated normal and/or reverse phase chromatography were used to purify intermediates and final products as needed. All compounds were characterized to confirm structure and purity utilizing Bruker Fourier 300HD for ¹H and ¹³C nuclear magnetic resonance (NMR) and Agilent 6230 time-of-flight (TOF) LC/MS for high resolution mass spectrometry (HRMS). Results: Molecular docking studies revealed multiple putative M₄ bitopic ligands predicted to have a high affinity for the receptor. Included among these compounds are analogs with xanomeline linked to known M₄ PAMs VU6003130 and VU0152100. Synthetic approaches to select analogs have been designed and their execution initiated. Conclusions: Progress toward the synthesis of novel M₄ bitopic ligands has been made. Next steps for the project include completion of the synthesis of select ligands and their evaluation in functional assays to determine potency at M₄ and selectivity versus other family members.
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    Contact angle, a potential screening tool for anticancer drug delivery systems and breast cancer tumor tissues.
    (2024-03-21) Spano, Giacomo; Banda, Brenda Natalia
    Purpose: Breast cancer is one the most commonly diagnosed cancers in the United States and the second leading cause of cancer death among women. Despite progress in treatments and early detection reducing mortality, there is a continuous increase in annual cases, particularly among certain patient populations, causing persistent health disparities. The tumor extracellular matrix (ECM), which provides mechanical support, modulates the microenvironment, and supplies signaling molecules for cancer growth, has been linked to breast cancer health disparities. In this study, we propose an innovative approach to characterize and quantify the physiochemical properties of breast cancer ECM. Additionally, we hypothesize that drug delivery nano-therapies' interactions with tumor ECM can be quantified using this method. We aim to understand how drug delivery systems, such as liposomal doxorubicin (Doxil®), interact with ECM and affect breast cancer therapy outcomes. Methods: Liposomes with different Doxil-like compositions (varying PEG content, molecular weight, and end-cap group) were prepared using the thin-film layer hydration method followed by sonication for particle size reduction. De-identified breast cancer fixed tissue sections (with demographic data) purchased from US Biomax Inc. were deparaffinized in xylene, ethanol, and water in consecutive washing cycles. Tissues were decellularized by up to three freeze-thaw cycles in water. Water contact angles were measured on decellularized tissue sections using a customized optical goniometer. Tissue sections were treated with liposomes by incubating them for 2 min in liposomal suspensions and rinsed with DI water 3 times. Results: Liposomes reduce the water contact angle on glass slides and tissue sections in a concentration-dependent and composition-dependent manner. Doxil-like liposomes decrease the water contact angle for concentrations higher than 0.5 mg/ml. This reduction increases proportionally as the concentration rises, reaching a plateau for concentrations higher than 1.5 mg/ml. Peg-free liposomes exhibit the lowest activity in contact angle reduction, suggesting PEG's central role in the surfactant-like activity of liposomes. Changes in PEG end-cap and molecular weight, influence both liposome surface activity and tissue retention. The contact angle varies among different tissues, with a notable tendency for fibrotic tissues, such as metastatic tumor tissue, to have a higher contact angle and therefore higher hydrophobicity. PEGylated liposomes are more retained by metastatic tissues and highly hydrophobic tissues, indicating that PEG enhances liposome adsorption in more hydrophobic environments. Conclusion: The contact angle method for tumor ECM characterization developed in our laboratory enables the quantification of tumor ECM features through a liquid-solid dynamic interaction approach. Our data highlight and quantify the importance of PEG as a surface molecule on contact angle-measured interactions between anti-cancer liposomes and breast cancer tumors, consistent with clinical testing of Doxil® where the inclusion of PEG was crucial for therapeutic efficacy. In addition to liposome composition, tumor type (grade or metastatic) can be quantified with this method, permitting an increased understanding of the role tissue surface properties play in the efficacy of anti-cancer nano-therapies. The described method can serve as a preclinical tool to screen drug delivery systems and predict their efficacy by quantifying their target tissue interactions.
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    Preclinical Characterization of Novel Drug Candidates for Ocular Drug Delivery
    (2024-03-21) Garrett, Meredith; Kastellorizios, Michail
    Purpose: Retinitis pigmentosa (RP) is the leading cause of vision loss and blindness for people under 60 years old. RP is an inherited disease causing progressive and irreversible deterioration of the retina. To date, over 150 mutations in 90 genes have been identified to contribute to the disease through various pathways. Except for a single mutation responsible for less than 5% of cases, RP is incurable. Currently available treatments largely focus on slowing progression by relieving oxidative stress and are met with limited success. The sigma 2 receptor, also established as transmembrane protein 97 of the endoplasmic reticulum (s2r/TMEM97), has been shown to have neuroprotective effects on retinal cells and is a potential drug target for RP. Recently, a series of novel drug compounds have been identified to modulate the s2r/TMEM97 protein and are under investigation as possible candidates for treatment of RP. Here, as part of preclinical evaluation, we performed thermal analysis of the novel compounds, including thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). These techniques give insight to drug behavior at different temperatures and provide information on stability and structure. We also conducted a series of drug release studies which monitored movement of the compounds from vitreous humor through a dialysis membrane. This will allow for correlation with previously collected data. Methods: TGA was performed on a TGA550 thermogravimetric analyzer from TA Instruments. The instrument measured the mass of the pan as the temperature was increased from 20°C to 700°C at a rate of 10°C/min. DSC was completed using a DSC250 from TA Instruments. The instrument was programed to increase the temperature of the sample chamber from 10°C to 200°C at a rate of 5°C/min while measuring the heat flux of each pan. A series of drug release studies were performed using a specialized dialysis plate. Drug movement from vitreous humor across a membrane was evaluated over a 12-hour period. Results: The data collected here for the novel compounds did not show any red flags which would indicate a poor drug candidate. TGA data showed all compounds were thermally stabile until approximately 175°C, at which point they began to lose mass. DSC differential thermograms did not exhibit crystalline behavior. Drug release studies did not show a strong interaction between the compounds and vitreous humor. Conclusion: Our goal is to aid in narrowing the series of novel drug compounds by providing robust preclinical characterization. TGA thermograms obtained demonstrated the compounds were thermally stabile up to approximately 175°C, which is standard for small molecules. DSC results reveal the compounds are not crystalline and indicate the need for a special formulation. The drug release studies show there were no strong interactions with the compounds and vitreous humor. The data here was included with stability, solubility, and in vitro and in vivo pharmacokinetic analysis and used to select the two leading candidates to advance to in vivo efficacy studies in a transgenic rat model for retinitis pigmentosa.