Accurate prediction of protein-ligand binding affinity is essential to computational drug discovery. Current approaches are limited by the accuracy of the underlying potential energy model that describes atomic interactions. A more rigorous physical model is critical for evaluating molecular interactions to chemical accuracy. The objective of this thesis research is to develop a polarizable force field with an accurate representation of electrostatic interactions, and apply this model to protein-ligand recognition and to ultimately solve practical problems in computer aided drug discovery. By calculating the hydration free energies of a series of organic small molecules, an optimal protocol is established to develop the electrostatic parameters from quantum mechanics calculations. Next, the systematical development and parameterization procedure of AMOEBA protein force field is presented. The derived force field has gone through extensive validations in both gas phase and condensed phase. The last part of the thesis involves the application of AMOEBA to study protein-ligand interactions. The binding free energies of benzamidine analogs to trypsin using molecular dynamics alchemical perturbation are calculated with encouraging accuracy. AMOEBA is also used to study the thermodynamic effect of constraining and hydrophobicity on binding energetics between phosphotyrosine(pY)-containing tripeptides and the SH2 domain of growth receptor binding protein 2 (Grb2). The underlying mechanism of an "entropic paradox" associated with ligand preorganization is explored. / text

Print culture was a fundamental site in which new ideas about England’s role in world affairs were debated in the latter half of the sixteenth century. Print changed the ways in which new discoveries, proposals, grievances, and questions were assessed, and not always to the desired effect. In the face of the sphinx-like power of the press, a wide array of strategies emerged to control it. But people at many levels of the publishing process could use the rhetoric of the text, and of the printed book, to rearrange the relationships between authors and readers, to upset the thrust of a particular line of argument, to alter the aesthetic, moral, or pragmatic judgment a reader might exercise, or in a more subtle way to change the terms of the issue at hand. In view of the diversity of these possibilities, this report follows figures known to the London print world, some authors, some printers, and examines how they acted, reacted, and worked through, issues that arose from being on the cusp of England’s relationship with a wider world. / text

Syftet med denna studie är att redogöra hur förskollärare ser på och använder sig av naturvetenskapliga experiment i förskolan. Studien ska ta fram vilka motiv och målsättningar en förskollärare har inför en aktivitet med experiment. Tidigare forskning visar att naturvetenskap och teknik inte varit så högt prioriterade i förskolans pedagogiska verksamhet. Därför så reviderade Skolverket Läroplanen för förskolan 2010, då bl.a. naturvetenskap och teknik fick ett större utrymme i den pedagogiska verksamheten. För att introducera naturvetenskap på ett stimulerande och roligt sätt så undersöker jag om experiment kan vara ett bra pedagogiskt verktyg. I denna studie har jag gjort kvalitativa intervjuer med sju olika förskollärare. Jag besökte fem olika förskolor, varav två är belägna i storstad och tre i ett mindre samhälle. Förskolorna drivs med olika profiler som Montessori, Reggio Emilia, kristen och teknik. Studien utgår från arbetet med experiment i den pedagogiska verksamheten med hjälp av John Dewey och Lev S Vygotskij. Resultatet av studien visade att arbetet med experiment i förskolans verksamhet uppfylldes genom att barnen fick en lustfylld erfarenhet av naturvetenskapliga experiment. Att få arbeta med att undersöka, upptäcka och utforska nya fenomen genom experiment tycker respondenterna är viktigt. Respondenterna försökte i största mån att göra experiment utifrån barnens intresse och upptäckarlust.

Advances in genome and proteome research have led to a dramatic increase in the number of macromolecular targets of interest to the life sciences. A solution-phase method to simultaneously reveal all ligand-target binding pairs from a single solution containing libraries of ligands and targets could significantly increase the efficiency and effectiveness of target-oriented screening efforts. Here, we describe interaction-dependent PCR (IDPCR), a solution-phase method to identify binding partners from combined libraries of small-molecule ligands and targets in a single experiment. Binding between DNA-linked targets and DNA-linked ligands induces formation of an extendable duplex. Extension links codes identifying the ligand and target into one selectively amplifiable DNA molecule. In a model selection, IDPCR resulted in the enrichment of DNA encoding all five known protein-ligand pairs out of 67,599 possible sequences.

Online aggregation is a new trend in today’s world. It is developed from an IT concept to a much broader idea that applies to a variety of areas such as information, human capital, social power, and so on. The power of online aggregation has not only changed the way of business, but also affected the process of social development. The current study identified three models of online aggregation and provided examples of each. Some future implications and downsides of online aggregation are also discussed in this paper. / text

This paper measures the channels by which private information is incorporated in prices in the equity and option markets. Using a mispricing events approach and conditioning on the option market being the cause of the mispricing event, I analyse the subsequent behaviour of both the options and equity markets and I find that options markets play an important role in the price discovery process. When conditioning on option caused mispricing events, the equity price adjusts towards the options price to reconcile the prices. I find that around 40% of the option caused mispricing events contain information, and the equity prices adjust 35-40%, depending on the exchange, of the maximum discrepancy before prices reconcile. When the equity market causes the mispricing, the option market follows due to the autoquote mechanism. Additionally, I use Monte Carlo to assess the suitability of the Hasbrouck (1995) Information Share and Gonzalo-Granger (1995) Component Share measures in the option-equity context. I find that neither metric is suitable, however the Putnins (2013) Information Leadership metric is and the options market has on average a 35% information leadership share.

The research described in this dissertation is focused on the knowledge-based, often in silico assisted design, targeted synthesis, and biological evaluation of small molecules of interest for two translational medicinal chemistry projects. The first project (Part 1) is aimed at the identification of blood brain barrier (BBB) penetrable dual specificity tyrosine phosphorylation regulated kinase-1A (DYRK1A) inhibitors as a potential disease modifying approach to mitigate cognitive deficits associated with Alzheimer's neurodegeneration. Two major series with potent activity against DYRK1A were identified in addition to a number of other chemotype sub-series that also exhibit somewhat promising activity. Extensive profiling of active analogs revealed interesting biological activity and selectivity, which led to the identification of two analogs for in vivo studies and revealed new opportunities for further investigation into other kinase targets implicated in neurodegeneration and polypharmacological approaches. The second project (Part 2) is focused on the development of compounds that inhibit PGE₂ production, while not affecting cyclooxygenase (COX) activity, as a novel approach to treat cancer. Compounds were designed with the intention of inhibiting microsomal prostaglandin E₂ synthase-1 (mPGES-1); however, biological evaluation revealed phenotypically active compounds in a cell based assay with an unknown mechanism of action. Further profiling revealed promising anticancer activity in xenograft mouse models. In addition, PGE₂ has been implicated in an immune evasion mechanism of F. tularensis, a strain of bacteria that remains an exploitable threat in biowarfare, thus a small number of analogs were evaluated in a cell model of F. tularensis infection stimulated PGE₂ production.

With the rapid advance of information technologies, human beings increasingly rely on computers to accumulate, process, and make use of data. Knowledge discovery techniques have been proposed to automatically search large volumes of data for patterns. Knowledge discovery often requires a set of relevant features to represent the specific domain. My dissertation presents a framework of feature engineering for knowledge discovery, including feature construction, feature selection, and feature consolidation.Five essays in my dissertation present novel approaches to construct, select, or consolidate features in various applications. Feature construction is used to derive new features when relevant features are unknown. Chapter 2 focuses on constructing informative features from a relational database. I introduce a probabilistic relational model-based approach to construct personal and social features for identity matching. Experiments on a criminal dataset showed that social features can improve the matching performance. Chapter 3 focuses on identifying good features for knowledge discovery from text. Four types of writeprint features are constructed and shown effective for authorship analysis of online messages. Feature selection is aimed at identifying a subset of significant features from a high dimensional feature space. Chapter 4 presents a framework of feature selection techniques. This essay focuses on identifying marker genes for microarray-based cancer classification. Our experiments on gene array datasets showed excellent performance for optimal search-based gene subset selection. Feature consolidation is aimed at integrating features from diverse data sources or in heterogeneous representations. Chapter 5 presents a Bayesian framework to integrate gene functional relations extracted from heterogeneous data sources such as gene expression profiles, biological literature, and genome sequences. Chapter 6 focuses on kernel-based methods to capture and consolidate information in heterogeneous data representations. I design and compare different kernels for relation extraction from biomedical literature. Experiments show good performances of tree kernels and composite kernels for biomedical relation extraction.These five essays together compose a framework of feature engineering and present different techniques to construct, select, and consolidate relevant features. This feature engineering framework contributes to the domain of information systems by improving the effectiveness, efficiency, and interpretability of knowledge discovery.

Although some progress has been made in the treatment of cancer over the last sixty years, the majority of chemotherapeutics has fallen short. Because general chemotherapies that target DNA replication have only a limited efficacy and significant non-target side-effects, a new paradigm for cancer drug development has been adopted. Using a molecular targeted approach, new gene and protein targets have been identified and the development of chemotherapies that are specific to these targets has already begun. In this study, compounds that interact with two key cancer targets, the G-quadruplex of the c-Myc promoter and p-glycoprotein, have been investigated. By developing such compounds, improvements in treatment efficacy is anticipated with an aspiration for decreased mortality attributable to cancer.Formation of DNA secondary structures, such as the G-quadruplex, in the NHE III1 region of the c-Myc promoter has been shown to repress c-Myc transcription. Because c-Myc is an oncogene that is overexpressed in a variety of cancers, stabilization of the G-quadruplex by small molecules would be advantageous in cancer treatment. Using Fluorescence Resonance Energy Transfer, with Taq Polymerase Stop assays for confirmation, a group of compounds were identified that stabilize the c-Myc G-quadruplex structure. Using a colon cancer model, two compounds were shown to decrease c-Myc gene and protein expression. Also, exposure to the compounds for 48 hours results in an induction of caspase-3, indicative of apoptosis. Furthermore, surface plasmon resonance suggests that compound-induced stabilization of the c-Myc G-quadruplex can prevent sustained binding of the regulatory protein NM23-H2 by increasing its dissociation from the G-quadruplex. This may subsequently prevent unraveling of the G-quadruplex.Because resistance to chemotherapy reduces its effectiveness, development of multidrug resistance (MDR) modulators was also studied. Psorospermin is a topoisomerase II-directed DNA alkylating agent active against MDR cell lines. In a study examining the mechanism of psorospermin's P-glycoprotein modulation, Flow Cytometry demonstrated that doxorubicin-resistant multiple myeloma cells pre-treated with psorospermin enhanced intracellular retention of doxorubicin. Because neither transcription of mdr1 nor translation of P-glycoprotein was downregulated by psorospermin, resistance reversal is most likely due to a direct interaction between the side chain of psorospermin and P-glycoprotein, inhibiting drug efflux.

The past few years have witnessed a significant evolution in mobile computing and communications, in which new trends and applications have the traditional role of computer networks into that of distributed service providers. In this thesis we explore an alternative way to form wireless ad-hoc networks whose topologies can be customized as required by the users’ software applications. In particular, we investigate the applicability of mobile codes to networks created by devices equipped with Bluetooth technology. Computer simulations results suggest that our proposed approach can achieve this task effectively, while matching the level of efficiency seen in other salient proposals in this area. This thesis also addresses the issue of service discovery in mobile ad-hoc networks. We propose the use of a directory whose network location varies in an attempt to reduce traffic overhead driven by users’ hosts looking for service information. We refer to this scheme as the Service Directory Placement Algorithm, or SDPA. We formulate the directory relocation problem as a Markov Decision Process that is solved by using Q-learning. Performance evaluations through computer simulations reveal bandwidth overhead reductions that range between 40% and 48% when compared with a basic broadcast flooding approach for networks comprising hosts moving at pedestrian speeds. We then extend our proposed approach and introduce a multi-directory service discovery system called the Service Directory Placement Protocol, or SDPP. Our findings reveal bandwidth overhead reductions typically ranging from 15% to 75% in networks comprising slow-moving hosts with restricted memory availability. In the fourth and final part of this work, we present the design foundations and architecture of a middleware system that called WISEMAN – WIreless Sensors Employing Mobile Agents. We employ WISEMAN for dispatching and processing mobile programs in Wireless Sensor Networks (WSNs). Our proposed system enables the dynamic creation of semantic relationships between network nodes that cooperate to provide an aggregate service. We present discussions on the advantages of our proposed approach, and in particular, how WISEMAN facilitates the realization of service-oriented tasks in WSNs.