10 research outputs found

    Lead optimization for new antimalarials and Successful lead identification for metalloproteinases: A Fragment-based approach Using Virtual Screening

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    Lead optimization for new antimalarials and Successful lead identification for metalloproteinases: A Fragment-based approach Using Virtual Screening Computer-aided drug design is an essential part of the modern medicinal chemistry, and has led to the acceleration of many projects. The herein described thesis presents examples for its application in the field of lead optimization and lead identification for three metalloproteins. DOXP-reductoisomerase (DXR) is a key enzyme of the mevalonate independent isoprenoid biosynthesis. Structure-activity relationships for 43 DXR inhibitors are established, derived from protein-based docking, ligand-based 3D QSAR and a combination of both approaches as realized by AFMoC. As part of an effort to optimize the properties of the established inhibitor Fosmidomycin, analogues have been synthesized and tested to gain further insights into the primary determinants of structural affinity. Unfortunately, these structures still leave the active Fosmidomycin conformation and detailed reaction mechanism undetermined. This fact, together with the small inhibitor data set provides a major challenge for presently available docking programs and 3D QSAR tools. Using the recently developed protein tailored scoring protocol AFMoC precise prediction of binding affinities for related ligands as well as the capability to estimate the affinities of structurally distinct inhibitors has been achieved. Farnesyltransferase is a zinc-metallo enzyme that catalyzes the posttranslational modification of numerous proteins involved in intracellular signal transduction. The development of farnesyltransferase inhibitors is directed towards the so-called non-thiol inhibitors because of adverse drug effects connected to free thiols. A first step on the way to non-thiol farnesyltransferase inhibitors was the development of an CAAX-benzophenone peptidomimetic based on a pharmacophore model. On its basis bisubstrate analogues were developed as one class of non-thiol farnesyltransferase inhibitors. In further studies two aryl binding and two distinct specificity sites were postulated. Flexible docking of model compounds was applied to investigate the sub-pockets and design highly active non-thiol farnesyltransferase inhibitor. In addition to affinity, special attention was paid towards in vivo activity and species specificity. The second part of this thesis describes a possible strategy for computer-aided lead discovery. Assembling a complex ligand from simple fragments has recently been introduced as an alternative to traditional HTS. While frequently applied experimentally, only a few examples are known for computational fragment-based approaches. Mostly, computational tools are applied to compile the libraries and to finally assess the assembled ligands. Using the metalloproteinase thermolysin (TLN) as a model target, a computational fragment-based screening protocol has been established. Starting with a data set of commercially available chemical compounds, a fragment library has been compiled considering (1) fragment likeness and (2) similarity to known drugs. The library is screened for target specificity, resulting in 112 fragments to target the zinc binding area and 75 fragments targeting the hydrophobic specificity pocket of the enzyme. After analyzing the performance of multiple docking programs and scoring functions forand the most 14 candidates are selected for further analysis. Soaking experiments were performed for reference fragment to derive a general applicable crystallization protocol for TLN and subsequently for new protein-fragment complex structures. 3-Methylsaspirin could be determined to bind to TLN. Additional studies addressed a retrospective performance analysis of the applied scoring functions and modification on the screening hit. Curios about the differences of aspirin and 3-methylaspirin, 3-chloroaspirin has been synthesized and affinities could be determined to be 2.42 mM; 1.73 mM und 522 ÎĽM respectively. The results of the thesis show, that computer aided drug design approaches could successfully support projects in lead optimization and lead identification. fragments in general, the fragments derived from the screening are docke

    Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies.

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    HIGHLIGHTS Many CNS targets are being explored for multi-target drug designNew databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compoundsQSAR, virtual screening and docking methods increase the potential of rational drug design The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer's disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D1-R/D2-R/5-HT2A -R/H3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to design MTDLs

    Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets

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    Accurately predicting relative binding affinities and biological potencies for ligands that interact with proteins remains a significant challenge for computational chemists. Most evaluations of docking and scoring algorithms have focused on enhancing ligand affinity for a protein by optimizing docking poses and enrichment factors during virtual screening. However, there is still relatively limited information on the accuracy of commercially available docking and scoring software programs for correctly predicting binding affinities and biological activities of structurally related inhibitors of different enzyme classes. Presented here is a comparative evaluation of eight molecular docking programs (Autodock Vina, Fitted, FlexX, Fred, Glide, GOLD, LibDock, MolDock) using sixteen docking and scoring functions to predict the rank-order activity of different ligand series for six pharmacologically important protein and enzyme targets (Factor Xa, Cdk2 kinase, Aurora A kinase, COX-2, pla2g2a, β Estrogen receptor). Use of Fitted gave an excellent correlation (Pearson 0.86, Spearman 0.91) between predicted and experimental binding only for Cdk2 kinase inhibitors. FlexX and GOLDScore produced good correlations (Pearson > 0.6) for hydrophilic targets such as Factor Xa, Cdk2 kinase and Aurora A kinase. By contrast, pla2g2a and COX-2 emerged as difficult targets for scoring functions to predict ligand activities. Although possessing a high hydrophobicity in its binding site, β Estrogen receptor produced reasonable correlations using LibDock (Pearson 0.75, Spearman 0.68). These findings can assist medicinal chemists to better match scoring functions with ligand-target systems for hit-to-lead optimization using computer-aided drug design approaches

    Investigating LXR as a therapeutic target in triple negative breast cancer.

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    The development of hormone therapies, such as tamoxifen, have substantially improved breast cancer outcomes for hormone receptor positive breast cancers. A subtype of breast cancers known as the triple negative breast cancers (TNBC) however, cannot benefit from these therapies due to their lack of receptors or overexpression of HER2 (ER-/PR-/HER2-). The triple negative subtype is associated with poorer prognosis and earlier relapse; novel therapies are urgently required for this cancer of unmet clinical need. The liver X receptor (LXR) is a ligand induced transcription factor with essential roles in cholesterol metabolism. LXRα and its binding partner RXRβ were found to be expressed at significantly higher levels in triple negative breast cancers relative to ER-positive breast cancers. I hypothesised that LXRα activity was altered between breast cancer subtypes and may influence chemotherapy efficacy. Enhanced LXRα response to ligand was identified in the TNBC subtype relative to the Luminal A subtype. Furthermore, LXRα was identified as a mediator of chemotherapy resistance through the control of the p-glycoprotein/ABCB1 in TNBC. I further hypothesised that the p-glycoprotein/ABCB1 may be targetable through phytosterol treatments which were shown to antagonise oxysterol-induced LXRα activity and expression of its targets which, we have been shown to include p-gp/ABCB1. In summary, I have identified a novel LXRα target gene (p-gp/ABCB1) in TNBC which confers chemotherapy resistance through enhanced export of the chemotherapy drug epirubicin. I have also established a mechanism to impair the oxysterol:LXRα axis through phytosterol treatment. The data presented here may have important implications to aid better treatment plans for patients undergoing chemotherapy treatment. It may also help identify individuals at risk of therapy failure

    CLUSTER HOMOLOG OF IMMUNOGLOBULIN-LIKE RECEPTOR GENES IN CHICKEN IMMUNE RESPONSES

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    This dissertation explores the identity and role of immunoglobulin-like (Ig-like) receptors in chickens, with focus on their implications in disease and disease progression. These receptors, wisely expressed across immune cells, interact with the major histocompatibility complex (MHC) class I molecules to modulate immune responses in mammals. Due to the insufficient representation of chicken Ig-like receptors in online databases, this study systematically annotates the chicken Cluster Homolog of Immunoglobulin-like Receptors (CHIR) genes using advanced bioinformatic techniques, aligning with the release of the 7th edition of the chicken genome assembly that comprises builds for a broiler and layer chicken. The analysis identifies over 150 CHIR genes, refining functional classifications of activatory (CHIRA), inhibitory (CHIRB), bifunctional (CHIRAB), and CHIR-like (CHIRL) genes through InterProScan, phylogeny and motif searches. Variations in CHIR gene counts across different chicken lines (broiler, N = 124, layer, N = 70) suggest links to selective breeding demands, emphasizing their importance in poultry health and production. Phylogenetically, CHIRs show close relationships with other poultry Ig-like receptors, and structural comparisons indicate analogous roles to Ig-like receptors in the human and rat. As an outcome of the analysis, CHIR genes were renamed with the Chicken Genome Nomenclature Consortium from “chicken homolog of Ig-like receptors” to “cluster homolog of Ig-like receptors”. Reanalyzing next-generation sequencing data reveals CHIR genes are expressed across all tissues of a UCD001 line, with generally higher expression in blood-containing organs. Examination of CHIR gene single nucleotide polymorphisms across various in inbred lines (UCD001, UCD003, Line 0, Line 6, Line 7, Line 15, Line N, Line P, Line C, and Line W) indicates an overall variant rarity and slightly more occurrence in CHIRB genes. Over 1,000 protein-encoding variants are associated with differential resistance and susceptibility to Marek’s disease (P \u3c 0.05). Two in vitro approaches assessed the roles of CHIR molecules in modulating immune responses or targeting pathogens. Re-examination of RNA-sequencing data of MHC-I types B2 and B19 macrophages, temporally stimulated with interferon-gamma, revealed dynamic and opposite CHIR expression trends, with B2s showing an increase and B19s displaying a decrease until returning to basal levels at 24 to 48 hours. These findings suggest nuanced and distinct regulatory patterns of CHIRs in different haplotypes during immune responses. Additionally, CHIR sequences were aligned for the design of small interfering RNA molecules targeting the CHIRB functional group on macrophages retrieved from birds of congenic (UCD331 and UCD335) and mixed (WVU1952) backgrounds. CHIRB silencing was observed to enhance cellular nitrate release and impact H2O2, particularly in specific MHC-I haplotypes and in different genetic backbones, in avian influenza virus infection. While this dissertation enhances our understanding of chicken Ig-like receptors and cellular involvement, it also acknowledges certain limitations, such as variations in gene annotations. Nevertheless, CHIRs merit a sizeable acknowledgment as pivotal contributors to the immune response, particularly in their intricate interactions with the MHC. Future studies integrating this understanding into breeding plans or other interventions becomes a strategic imperative for optimizing poultry health and immunity, ensuring wellbeing, and in turn, a more resilient and sustainable food supply

    Modulation of cell-mediated immunity by HIV-1 infection of macrophages

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    Cell-mediated immunity (CMI) is central to the host response to intracellular pathogens such as Mycobacterium tuberculosis (Mtb). The function of CMI can be modulated by human immunodeficiency virus (HIV)-1 via its pleiotropic effects on the immune response, including modulation of macrophages, which are parasitized by both HIV-1 and Mtb. HIV-1 infection is associated with increased risk of tuberculosis (TB), and so in this thesis I sought to explore the host/pathogen interactions through which HIV-1 dysregulates CMI, and thus changes the natural history of TB. Using an in vitro model of human monocyte-derived macrophages (MDMs), I characterise a phenotype wherein HIV-1 specifically attenuates production of the immunoregulatory cytokine interleukin (IL)-10 in response to Mtb and other innate immune stimuli. I show that this phenotype requires HIV-1 integration and gene expression, and may result from a function of the HIV-1 accessory proteins. I identify that the phosphoinositide 3-kinase (PI3K) pathway specifically regulates IL-10 production in human MDMs, and thus may be a target for HIV-1 to mediate IL-10 attenuation. I show that HIV-1 may attenuate IL-10 to maximise its own replication, and identify potential consequences of IL-10 attenuation for CMI. By using the tuberculin skin test (TST) as a human challenge model, I evaluate HIV-1 modulation of CMI in vivo in active TB patients, and demonstrate IL-10 attenuation in this context. I identify a role for type I inteferons (IFNs) in HIV-1 anergy, and observe exaggerated T helper 2 responses associated with the immune reconstitution inflammatory syndrome (IRIS). To fully explore CMI in vivo by transcriptional profiling, I utilize the transcriptional heterogeneity of stimulated macrophages to develop a modular analysis strategy for transcriptional profiles, and apply this in the TST model. My results delineate novel modulatory effects of HIV-1 on the function of CMI, and thus provide insights into immunopathogenesis in HIV-1/TB co-infection
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