Publications by authors named "Randy J Zauhar"

Less than one in thirty of the RNA sequences transcribed in humans are translated into protein. The noncoding RNA (ncRNA) functions in catalysis, structure, regulation, and more. However, for the most part, these functions are poorly characterized.

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Age-related macular degeneration (AMD), the leading cause of irreversible blindness among Americans over 50, is characterized by dysfunction and death of retinal pigment epithelial (RPE) cells. The RPE accumulates iron in AMD, and iron overload triggers RPE cell death in vitro and in vivo. However, the mechanism of RPE iron accumulation in AMD is unknown.

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Recent Genome-wide Association Studies (GWASs) for eye diseases/traits have delivered a number of novel findings across a diverse range of diseases, including age-related macular degeneration (AMD), glaucoma and refractive error. However, despite this astonishing rate of success, the major challenge still remains to not only confirm that the genes implicated in these studies are truly the genes conferring protection from or risk of disease but also to define the functional roles these genes play in disease. Ongoing evidence is accumulating that the single nucleotide polymorphisms (SNPs) used in GWAS and fine mapping studies have causal effects through their influence on gene expression rather than affecting protein function.

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The Epstein-Barr Nuclear Antigen 1 (EBNA1) is a critical protein encoded by the Epstein-Barr Virus (EBV). During latent infection, EBNA1 is essential for DNA replication and transcription initiation of viral and cellular genes and is necessary to immortalize primary B-lymphocytes. Nonetheless, the concept of EBNA1 as drug target is novel.

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Methicillin resistant Staphylococcus aureus (MRSA) is a major drug resistant bacteria that persists in both community and clinical settings due to growing resistance to current drug regimens. Thus, there is a continued need for novel compounds that are active against this organism. Previously, we reported that various rhodanine derivatives inhibited the supercoiling activity of DNA gyrase.

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Liver damage occurred in some patients who took troglitazone (TGZ) for type II diabetes. The 2,4-thiazolidinedione (TZD) ring in TGZ's structure has been implicated in its hepatotoxicity. To further examine the potential role of a TZD ring in toxicity we used HepG2 cells to evaluate two series of compounds containing different cyclic imides.

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The signal transducer and activator of transcription 5 (STAT5) is a member of the STAT family of proteins, implicated in cell growth and differentiation. STAT activation is regulated by phosphorylation of protein monomers at conserved tyrosine residues, followed by binding to phospho-peptide pockets and subsequent dimerization. STAT5 is implicated in the development of severe pathological conditions, including many cancer forms.

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Methicillin resistant Staphylococcus aureus (MRSA) is among the major drug resistant bacteria that persist in both the community and clinical settings due to resistance to commonly used antimicrobials. This continues to fuel the need for novel compounds that are active against this organism. For this purpose we have targeted the type IIA bacterial topoisomerase, DNA gyrase, an essential enzyme involved in bacterial replication, through the ATP-dependent supercoiling of DNA.

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Since its introduction in 2003, the Shape Signatures method has been successfully applied in a number of drug design projects. Because it uses a ray-tracing approach to directly measure molecular shape and properties (as opposed to relying on chemical structure), it excels at scaffold hopping, and is extraordinarily easy to use. Despite its advantages, a significant drawback of the method has hampered its application to certain classes of problems; namely, when the chemical structures considered are large and contain heterogeneous ring-systems, the method produces descriptors that tend to merely measure the overall size of the molecule, and begin to lose selective power.

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Prostate Cancer (PCa), a leading cause of cancer death worldwide (www.cancer.gov), is a complex malignancy where a spectrum of targets leads to a diversity of PCa forms.

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Purpose: In this study, two unreported estrogen antagonists were identified using a combination of computational screening and a simple bacterial estrogen sensor.

Methods: Molecules here presented were initially part of a group obtained from a library of over a half million chemical compounds, using the Shape Signatures method. The structures within this group were then clustered and compared to known antagonists based on their physico-chemical parameters, and possible binding modes of the compounds to the Estrogen Receptor alpha (ER alpha) were analyzed.

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Identifying potential lead molecules is becoming a more automated process. We review Shape Signatures, a tool that is effective and easy to use compared with most computer aided drug design techniques. Laboratory researchers can apply this in silico technique cost-effectively without the need for specialized computer backgrounds.

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Increasing attention is being paid to the role of selenium, both as an essential component required for the activity of many enzymes and in the context of selenium-based pharmaceutical agents. A wide range of therapeutics that include selenium are on the market and under development, such as antihypertensive, anticancerogenic, antiviral, and immunosuppressive agents. Computer-aided drug design (CADD) has proven to be an important tool for the development of new drugs.

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This study analyzes 16 molecular dynamic simulations of a biophysical model for beta(2)-adrenergic (B2AR) and G protein-coupled receptor (GPCR) activation. In this model, a highly conserved cysteine residue, C106 (C3.25 or CysIII:01), provides a free sulfhydryl or thiol group in an acid-base equilibrium between uncharged (RSH) and charged (RS(-)) states that functions as an electrostatic molecular switch for receptor activation.

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Predictions of the metabolic sites for new chemical entities, synthesized or only virtual, are important in the early phase of drug discovery to guide chemistry efforts in the synthesis of new compounds with reduced metabolic liability. This information can now be obtained from in silico predictions, and therefore, a thorough and unbiased evaluation of the computational techniques available is needed. Several computational methods to predict the metabolic hot spots are emerging.

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A unifying principle of rational drug design is the use of either shape similarity or complementarity to identify compounds expected to be active against a given target. Shape similarity is the underlying foundation of ligand-based methods, which seek compounds with structure similar to known actives, while shape complementarity is the basis of most receptor-based design, where the goal is to identify compounds complementary in shape to a given receptor. These approaches can be extended to include molecular descriptors in addition to shape, such as lipophilicity or electrostatic potential.

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