Indiana University-Purdue University Indianapolis (IUPUI) / Protein-protein interactions are fundamental in cell signaling and cancer progression. An increasing prevalent idea in cancer therapy is the development of small molecules to disrupt protein-protein interactions. Small molecules impart their action by binding to pockets on the protein surface of their physiological target. At protein-protein interactions, these pockets are often too large and tight to be disrupted by conventional design techniques. Residues that contribute a disproportionate amount of energy at these interfaces are known as hot spots. The successful disruption of protein-protein interactions with small molecules is attributed to the ability of small molecules to mimic and engage these hot spots. Here, the role of hot spots is explored in existing inhibitors and compared with the native protein ligand to explore how hot spot residues can be leveraged in protein-protein interactions. Few studies have explored the use of interface residues for the identification of hit compounds from structure-based virtual screening. The tight uPAR•uPA interaction offers a platform to test methods that leverage hot spots on both the protein receptor and ligand. A method is described that enriches for small molecules that both engage hot spots on the protein receptor uPAR and mimic hot spots on its protein ligand uPA. In addition, differences in chemical diversity in mimicking ligand hot spots is explored. In addition to uPAR•uPA, there are additional opportunities at unperturbed protein-protein interactions implicated in cancer. Projects such as TCGA, which systematically catalog the hallmarks of cancer across multiple platforms, provide opportunities to identify novel protein-protein interactions that are paramount to cancer progression. To that end, a census of cancer-specific binding sites in the human proteome are identified to provide opportunities for drug discovery at the system level. Finally, tumor genomic, protein-protein interaction, and protein structural data is integrated to create chemogenomic libraries for phenotypic screening to uncover novel GBM targets and generate starting points for the development of GBM therapeutic agents. / 2020-10-03

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Malaria afflicts about 500 million people worldwide thus causing significant global economic toll. The drugs available to treat the disease are rapidly losing their efficacy because of widespread prevalence of drug resistant parasites. Thus there is an urgent need to discover novel malaria therapeutics. This research is focused on to study the properties of a novel naturallike synthetic scaffold and analyze its selectivity, and cellular mechanism of action in Plasmodium falciparum. We have identified a novel compound, 3-amino-2-piperidinequinoline (APQ), which we termed UCF401. APQ demonstrated IC[sub50] at submicromolar concentrations against Plasmodium falciparum using the SYBR Green-I fluorescence assay measuring cellular proliferation. This compound also demonstrated low cytotoxicity against the NIH3T3 and HEPG2 cells using MTS assays, showing an IC50 of 174 [micro]M and 125 [micro]M respectively, suggesting of excellent selectivity. We evaluated the compliance of APQ with Lipinski's parameters and determined the in vitro physicochemical profiles of the compound. Our results show that APQ is a Lipinski parameter compliant and has good physicochemical properties. The cellular mechanism of action of APQ was characterized through the assessment of the effects of the compound at different stages of the parasite's intraerythrocytic life cycle. This assay was done by treating a synchronized cell line with the compound at 5X the IC50 value and then imaging the cells at 12-hour intervals. We found that APQ arrests parasite development at the trophozoite stage. In addition we determined that APQ is parasitocidal after a 96 h exposure. These results demonstrate that APQ can be considered as a validated hit and/or early lead.

In a short dialogue, philosopher Paul Feyerabend made some remarks regarding the interpretation of Plato’s theory of writing in the Phaedrus, which boil down to the suggestion that written works are didactically valuable when having the right kind of resemblance to “live exchanges”, adding that Plato in this respect resembles modern philosophies of science. In the present thesis, I flesh out and vindicate Feyerabend’s suggestions by a thematic reading of Phaedrus 274c–278b and a subsequent comparison of the interpreted theory with a few relevant modern philosophies of science.  My reading focuses on Plato’s philosophical use of the words ζῆν ‘live’, εἴδωλον ‘idol/image/representation/eidōlon’ and παιδιά ‘play’. Through them I show how Plato constructs a three-tiered value ranking of didactic processes, with live exchanges as the best, traditional monographs in the style of Lysias’ written speech as the worst, and Plato’s own original conception of “playful” writing in the middle: “a kind of eidōlon” of a live exchange that nevertheless does not pretend to be the real thing. Plato’s three tiers correspond well to the modern distinction between everyday scientific work, scientific papers and the different suggestions for in-betweens, such as the one made by Peter Medawar or the one contained in the so-called strong programme of David Bloor. I also identify four characteristics of Plato’s theory, including its emphasis on imitative learning, the necessity of the prescribed didactics, non-propositionality and reflexivity, which are found in the modern philosophies of the just-mentioned authors, as well as in that of Ludwik Fleck.

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With an ever-growing number of publications in the biomedical domain, it becomes likely that important implicit connections between individual concepts of biomedical knowledge are overlooked. Literature based discovery (LBD) is in practice for many years to identify plausible associations between previously unrelated concepts. In this paper, we present a new, completely automatic and interactive system that creates a graph-based knowledge base to capture multifaceted complex associations among biomedical concepts. For a given pair of input concepts, our system auto-generates a list of ranked subgraphs uncovering possible previously unnoticed associations based on context information. To rank these subgraphs, we implement a novel ranking method using the context information obtained by performing random walks on the graph. In addition, we enhance the system by training a Neural Network Classifier to output the likelihood of the two concepts being likely related, which provides better insights to the end user.

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The Bluetooth Scatternet Formation (BSF) problem can be defined as the problem of forming wireless networks of Bluetooth devices in an efficient manner. A number of restrictions imposed by the Bluetooth specifications make the BSF problem challenging and unique. Many interesting solution algorithms have been proposed in the literature to solve this problem. In this thesis, we investigate the BSF problem. We concentrate on problems introduced by the procedures of device discovery of the Bluetooth specifications and on the different solutions used by BSF algorithms to deal with these problems. We study also in this thesis problems introduced by the specifications of link establishment in Bluetooth due to their close interaction with the device discovery specifications. We survey and categorize the different device discovery techniques used by BSF algorithms. This categorization is then used as a basis to identify the different theoretical computational models used to study BSF algorithms. We argue, in this thesis, that the currently available models for Bluetooth wireless networks do not model adequately, in most cases, the complexities of the Bluetooth specifications and we show that these models were oversimplified in many cases. A general computational model will be useful as a starting point to design BSF algorithms and to compare the different and numerous BSF algorithms – especially in term of the execution time efficiency. In this thesis, we provide a set of suggestions that will help in the creation of such model. We survey a number of studies that examined in more depth the specifications of device discovery in Bluetooth. We survey also other studies that attempted to simplify the Bluetooth network model, either by suggesting modifications on the Bluetooth specifications or by the use of communication technologies other than Bluetooth. Finally, we present some experiments accompanied with analyzes to show the complexities of the Bluetooth specifications and their sensitivity to minor changes (whether in the specifications or in their implementation).