Cyclin dependent protein kinases as drug targets – potential in cardiovascular diseases

Complications of atherosclerosis such as myocardial infarction and stroke are the primary cause of death in Western societies. The development of atherosclerotic lesions is a complex process, including endothelial cell dysfunction, inflammation, extracellular matrix alteration and vascular smooth muscle cell (VSMC) proliferation and migration. Various cell cycle regulatory proteins control VSMC proliferation. Protein kinases called cyclin dependent kinases (CDKs) play a major role in regulation of cell cycle progression. At specific phases of the cell cycle, CDKs pair with cyclins to become catalytically active and phosphorylate numerous substrates contributing to cell cycle progression. CDKs are also regulated by cyclin dependent kinase inhibitors, activating and inhibitory phosphorylation, proteolysis and transcription factors. This tight regulation of cell cycle is essential; thus its deregulation is connected to the development of cancer and other proliferative disorders such as atherosclerosis and restenosis as well as neurodegenerative diseases. Proteins of the cell cycle provide potential and attractive targets for drug development. Consequently, various low molecular weight CDK inhibitors have been identified and are in clinical development. Tylophorine is a phenanthroindolizidine alkaloid, which has been shown to inhibit the growth of several human cancer cell lines. It was used in Ayurvedic medicine to treat inflammatory disorders. The aim of this study was to investigate the effect of tylophorine on human umbilical vein smooth muscle cell (HUVSMC) proliferation, cell cycle progression and the expression of various cell cycle regulatory proteins in order to confirm the findings made with tylophorine in rat cells. We used several methods to determine our hypothesis, including cell proliferation assay, western blot and flow cytometric cell cycle distribution analysis. We demonstrated by cell proliferation assay that tylophorine inhibits HUVSMC proliferation dose-dependently with an IC50 value of 164 nM ± 50. Western blot analysis was used to determine the effect of tylophorine on expression of cell cycle regulatory proteins. Tylophorine downregulates cyclin D1 and p21 expression levels. The results of tylophorine’s effect on phosphorylation sites of p53 were not consistent. More sensitive methods are required in order to completely determine this effect. We used flow cytometric cell cycle analysis to investigate whether tylophorine interferes with cell cycle progression and arrests cells in a specific cell cycle phase. Tylophorine was shown to induce the accumulation of asynchronized HUVSMCs in S phase. Tylophorine has a significant effect on cell cycle, but its role as cell cycle regulator in treatment of vascular proliferative diseases and cancer requires more experiments in vitro and in vivo.

Drug epidemiology, interactions and pharmacogenetics : A post-mortem database study

Use of adverse drug combinations, abuse of medicinal drugs and substance abuse are considerable social problems that are difficult to study. Prescription database studies might fail to incorporate factors like use of over-the-counter drugs and patient compliance, and spontaneous reporting databases suffer from underreporting. Substance abuse and smoking studies might be impeded by poor participation activity and reliability. The Forensic Toxicology Unit at the University of Helsinki is the only laboratory in Finland that performs forensic toxicology related to cause-of-death investigations comprising the analysis of over 6000 medico-legal cases yearly. The analysis repertoire covers most commonly used drugs and drugs of abuse, and the ensuing database contains also background information and information extracted from the final death certificate. In this thesis, the data stored in this comprehensive post-mortem toxicology database was combined with additional metabolite and genotype analyses that were performed to complete the profile of selected cases. The incidence of drug combinations possessing serious adverse drug interactions was generally low (0.71%), but it was notable for the two individually studied drugs, a common anticoagulant warfarin (33%) and a new generation antidepressant venlafaxine (46%). Serotonin toxicity and adverse cardiovascular effects were the most prominent possible adverse outcomes. However, the specific role of the suspected adverse drug combinations was rarely recognized in the death certificates. The frequency of bleeds was observed to be elevated when paracetamol and warfarin were used concomitantly. Pharmacogenetic factors did not play a major role in fatalities related to venlafaxine, but the presence of interacting drugs was more common in cases showing high venlafaxine concentrations. Nicotine findings in deceased young adults were roughly three times more prevalent than the smoking frequency estimation of living population. Contrary to previous studies, no difference in the proportion of suicides was observed between nicotine users and non-nicotine users. However, findings of abused substances, including abused prescription drugs, were more common in the nicotine users group than in the non-nicotine users group. The results of the thesis are important for forensic and clinical medicine, as well as for public health. The possibility of drug interactions and pharmacogenetic issues should be taken into account in cause-of-death investigations, especially in unclear cases, medical malpractice suspicions and cases where toxicological findings are scarce. Post-mortem toxicological epidemiology is a new field of research that can help to reveal problems in drug use and prescription practises.

A Hub System for Cloud-Computing Based Business-Collaboration: Automating Ontology-Enabled Electronic Business-Service Discovery

The management and coordination of business-process collaboration experiences changes because of globalization, specialization, and innovation. Service-oriented computing (SOC) is a means towards businessprocess automation and recently, many industry standards emerged to become part of the service-oriented architecture (SOA) stack. In a globalized world, organizations face new challenges for setting up and carrying out collaborations in semi-automating ecosystems for business services. For being efficient and effective, many companies express their services electronically in what we term business-process as a service (BPaaS). Companies then source BPaaS on the fly from third parties if they are not able to create all service-value inhouse because of reasons such as lack of reasoures, lack of know-how, cost- and time-reduction needs. Thus, a need emerges for BPaaS-HUBs that not only store service offers and requests together with information about their issuing organizations and assigned owners, but that also allow an evaluation of trust and reputation in an anonymized electronic service marketplace. In this paper, we analyze the requirements, design architecture and system behavior of such a BPaaS-HUB to enable a fast setup and enactment of business-process collaboration. Moving into a cloud-computing setting, the results of this paper allow system designers to quickly evaluate which services they need for instantiationg the BPaaS-HUB architecture. Furthermore, the results also show what the protocol of a backbone service bus is that allows a communication between services that implement the BPaaS-HUB. Finally, the paper analyzes where an instantiation must assign additional computing resources vor the avoidance of performance bottlenecks.

Diastereomeric Drug Glucuronides: Enzymatic Glucuronidation and Analysis by Capillary Electrophoresis and Liquid Chromatography-Mass Spectrometry

Foreign compounds, such as drugs are metabolised in the body in numerous reactions. Metabolic reactions are divided into phase I (functionalisation) and phase II (conjugation) reactions. Uridine diphosphoglucuronosyltransferase enzymes (UGTs) are important catalysts of phase II metabolic system. They catalyse the transfer of glucuronic acid to small lipophilic molecules and convert them to hydrophilic and polar glucuronides that are readily excreted from the body. Liver is the main site of drug metabolism. Many drugs are racemic mixtures of two enantiomers. Glucuronidation of a racemic compound yields a pair of diastereomeric glucuronides. Stereoisomers are interesting substrates in glucuronidation studies since some UGTs display stereoselectivity. Diastereomeric glucuronides of O-desmethyltramadol (M1) and entacapone were selected as model compounds in this work. The investigations of the thesis deal with enzymatic glucuronidation and the development of analytical methods for drug metabolites, particularly diastereomeric glucuronides. The glucuronides were analysed from complex biological matrices, such as urine or from in vitro incubation matrices. Various pretreatment techniques were needed to purify, concentrate and isolate the analytes of interest. Analyses were carried out by liquid chromatography (LC) with ultraviolet (UV) or mass spectrometric (MS) detection or with capillary electromigration techniques. Commercial glucuronide standards were not available for the studies. Enzyme-assisted synthesis with rat liver microsomes was therefore used to produce M1 glucuronides as reference compounds. The glucuronides were isolated by LC/UV and ultra performance liquid chromatography (UPLC)/MS, while tandem mass spectrometry (MS/MS) and nuclear magnetic resonance (NMR) spectroscopy were employed in structural characterisation. The glucuronides were identified as phenolic O-glucuronides of M1. To identify the active UGT enzymes in (±)-M1 glucuronidation recombinant human UGTs and human tissue microsomes were incubated with (±)-M1. The study revealed that several UGTs can catalyse (±)-M1 glucuronidation. Glucuronidation in human liver microsomes like in rat liver microsomes is stereoselective. The results of the studies showed that UGT2B7, most probably, is the main UGT responsible for (±)-M1 glucuronidation in human liver. Large variation in stereoselectivity of UGTs toward (±)-M1 enantiomers was observed. Formation of M1 glucuronides was monitored with a fast and selective UPLC/MS method. Capillary electromigration techniques are known for their high resolution power. A method that relied on capillary electrophoresis (CE) with UV detection was developed for the separation of tramadol and its free and glucuronidated metabolites. The suitability of the method to identify tramadol metabolites in an authentic urine samples was tested. Unaltered tramadol and four of its main metabolites were detected in the electropherogram. A micellar electrokinetic chromatography (MEKC) /UV method was developed for the separation of the glucuronides of entacapone in human urine. The validated method was tested in the analysis of urine samples of patients. The glucuronides of entacapone could be quantified after oral entacapone dosing.

Steric and rotational constraints in the X-ray structure of the animalarial drug amodiaquine

In the crystal structure of the antimalarial drug amodiaquine, the bonds linking the quinoline and the phenyl groups show partial double-bond character. The partial double-bond character of the two exocyclic bonds, together with stereochemical constraints, reduce flexibility of the two ring systems of the molecule. The dihedral angle between the two ring planes is lowest compared to those in the antileukaemic drug amsacrine and its derivatives. CPK-modelling studies suggest the way amodiaquine can bind to DNA. Stacking interaction between the quinoline and phenyl groups of independent molecules and the hydrogen-bond network stabilize the crystal structure.

Poly propyl ether imine (PETIM) dendrimer: A novel non-toxic dendrimer for sustained drug delivery

In the present study, an attempt was made to study the acute and sub-acute toxicity profile of G3-COOH Poly (propyl ether imine) PETIM] dendrimer and its use as a carrier for sustained delivery of model drug ketoprofen. Drug-dendrimer complex was prepared and characterized by FTIR, solubility and in vitro drug release study. PETIM dendrimer was found to have significantly less toxicity in A541 cells compared to Poly amido amine (PAMAM) dendrimer. Further, acute and 28 days sub-acute toxicity measurement in mice showed no mortality, hematological, biochemical or histopathological changes up to 80 mg/kg dose of PETIM dendrimer. The results of study demonstrated that G3-COOH PETIM dendrimer can be used as a safe and efficient vehicle for sustained drug delivery. (C) 2010 Elsevier Masson SAS. All rights reserved.

Heat Shock Protein 90 as a Drug Target against Protozoan Infections Biochemical characterization of HSP90 From plasmodium falciparum and trypanosoma evansi and evaluation of its inhibitor as a candidate drug

Using a pharmacological inhibitor of Hsp90 in cultured malarial parasite, we have previously implicated Plasmodium falciparum Hsp90 (PfHsp90) as a drug target against malaria. In this study, we have biochemically characterized PfHsp90 in terms of its ATPase activity and interaction with its inhibitor geldanamycin (GA) and evaluated its potential as a drug target in a preclinical mouse model of malaria. In addition, we have explored the potential of Hsp90 inhibitors as drugs for the treatment of Trypanosoma infection in animals. Our studies with full-length PfHsp90 showed it to have the highest ATPase activity of all known Hsp90s; its ATPase activity was 6 times higher than that of human Hsp90. Also, GA brought about more robust inhibition of PfHsp90 ATPase activity as compared with human Hsp90. Mass spectrometric analysis of PfHsp90 expressed in P. falciparum identified a site of acetylation that overlapped with Aha1 and p23 binding domain, suggesting its role in modulating Hsp90 multichaperone complex assembly. Indeed, treatment of P. falciparum cultures with a histone deacetylase inhibitor resulted in a partial dissociation of PfHsp90 complex. Furthermore, we found a well known, semisynthetic Hsp90 inhibitor, namely 17-(allylamino)-17-demethoxygeldanamycin, to be effective in attenuating parasite growth and prolonging survival in a mouse model of malaria. We also characterized GA binding to Hsp90 from another protozoan parasite, namely Trypanosoma evansi. We found 17-(allylamino)-17-demethoxygeldanamycin to potently inhibit T. evansi growth in a mouse model of trypanosomiasis. In all, our biochemical characterization, drug interaction, and animal studies supported Hsp90 as a drug target and its inhibitor as a potential drug against protozoan diseases.

Literature Review: Investigating Drug Transport at the Blood-Brain Barrier and the Effects of P-glycoprotein on the Brain Distribution of Drugs.

The blood-brain barrier (BBB) is a unique barrier that strictly regulates the entry of endogenous substrates and xenobiotics into the brain. This is due to its tight junctions and the array of transporters and metabolic enzymes that are expressed. The determination of brain concentrations in vivo is difficult, laborious and expensive which means that there is interest in developing predictive tools of brain distribution. Predicting brain concentrations is important even in early drug development to ensure efficacy of central nervous system (CNS) targeted drugs and safety of non-CNS drugs. The literature review covers the most common current in vitro, in vivo and in silico methods of studying transport into the brain, concentrating on transporter effects. The consequences of efflux mediated by p-glycoprotein, the most widely characterized transporter expressed at the BBB, is also discussed. The aim of the experimental study was to build a pharmacokinetic (PK) model to describe p-glycoprotein substrate drug concentrations in the brain using commonly measured in vivo parameters of brain distribution. The possibility of replacing in vivo parameter values with their in vitro counterparts was also studied. All data for the study was taken from the literature. A simple 2-compartment PK model was built using the Stella™ software. Brain concentrations of morphine, loperamide and quinidine were simulated and compared with published studies. Correlation of in vitro measured efflux ratio (ER) from different studies was evaluated in addition to studying correlation between in vitro and in vivo measured ER. A Stella™ model was also constructed to simulate an in vitro transcellular monolayer experiment, to study the sensitivity of measured ER to changes in passive permeability and Michaelis-Menten kinetic parameter values. Interspecies differences in rats and mice were investigated with regards to brain permeability and drug binding in brain tissue. Although the PK brain model was able to capture the concentration-time profiles for all 3 compounds in both brain and plasma and performed fairly well for morphine, for quinidine it underestimated and for loperamide it overestimated brain concentrations. Because the ratio of concentrations in brain and blood is dependent on the ER, it is suggested that the variable values cited for this parameter and its inaccuracy could be one explanation for the failure of predictions. Validation of the model with more compounds is needed to draw further conclusions. In vitro ER showed variable correlation between studies, indicating variability due to experimental factors such as test concentration, but overall differences were small. Good correlation between in vitro and in vivo ER at low concentrations supports the possibility of using of in vitro ER in the PK model. The in vitro simulation illustrated that in the simulation setting, efflux is significant only with low passive permeability, which highlights the fact that the cell model used to measure ER must have low enough paracellular permeability to correctly mimic the in vivo situation.

Algorithms for Exact Structure Discovery in Bayesian Networks

Bayesian networks are compact, flexible, and interpretable representations of a joint distribution. When the network structure is unknown but there are observational data at hand, one can try to learn the network structure. This is called structure discovery. This thesis contributes to two areas of structure discovery in Bayesian networks: space--time tradeoffs and learning ancestor relations. The fastest exact algorithms for structure discovery in Bayesian networks are based on dynamic programming and use excessive amounts of space. Motivated by the space usage, several schemes for trading space against time are presented. These schemes are presented in a general setting for a class of computational problems called permutation problems; structure discovery in Bayesian networks is seen as a challenging variant of the permutation problems. The main contribution in the area of the space--time tradeoffs is the partial order approach, in which the standard dynamic programming algorithm is extended to run over partial orders. In particular, a certain family of partial orders called parallel bucket orders is considered. A partial order scheme that provably yields an optimal space--time tradeoff within parallel bucket orders is presented. Also practical issues concerning parallel bucket orders are discussed. Learning ancestor relations, that is, directed paths between nodes, is motivated by the need for robust summaries of the network structures when there are unobserved nodes at work. Ancestor relations are nonmodular features and hence learning them is more difficult than modular features. A dynamic programming algorithm is presented for computing posterior probabilities of ancestor relations exactly. Empirical tests suggest that ancestor relations can be learned from observational data almost as accurately as arcs even in the presence of unobserved nodes.

Ring Resonators and Micro Fluidics: Novel Design for Drug/Disease Detection

MEMS systems are technologically developed from integrated circuit industry to create miniature sensors and actuators. Originally these semiconductor processes and materials were used to build electrical and mechanical systems, but expanded to include biological, optical fluidic magnetic and other systems 12]. Here a novel approach is suggested where in two different fields are integrated via moems, micro fluidics and ring resonators. It is well known at any preliminary stage of disease onset, many physiological changes occur in the body fluids like saliva, blood, urine etc. The drawback till now was that current calibrations are not sensitive enough to detect the minor physiological changes. This is overcome using optical detector techniques 1]. The basic concepts of ring resonators, with slight variations can be used for optical detection of these minute disease markers. A well known fact of ring resonators is that a change in refractive index will trigger a shift in the resonant wavelength 5]. The trigger for the wavelength shift in the case discussed will be the presence of disease agents. To trap the disease agents specific antibody has to be used (e. g. BSA).

Effective drug dosage design for treatment of infectious diseases using dynamic inversion

A generic nonlinear mathematical model describing the human immunological dynamics is used to design an effective automatic drug administration scheme. Even though the model describes the effects of various drugs on the dynamic system, this work is confined to the drugs that kill the invading pathogen and heal the affected organ. From a system theoretic point of view, the drug inputs can be interpreted as control inputs, which can be designed based on control theoretic concepts. The controller is designed based on the principle of dynamic inversion and is found to be effective in curing the �nominal model patient� by killing the invading microbes and healing the damaged organ. A major advantage of this technique is that it leads to a closed-form state feedback form of control. It is also proved from a rigorous mathematical analysis that the internal dynamics of the system remains stable when the proposed controller is applied. A robustness study is also carried out for testing the effectiveness of the drug administration scheme for parameter uncertainties. It is observed from simulation studies that the technique has adequate robustness for many �realistic model patients� having off-nominal parameter values as well.

Drug-drug co-crystals: Temperature-dependent proton mobility in the molecular complex of isoniazid with 4-aminosalicylic acid

Two drug-drug co-crystals of the anti-tuberculosis drugs isoniazid (INH), pyrazinamide (PYR) and 4-aminosalicylic acid (PAS) are reported. The first is the 1 : 1 molecular complex of INH and PAS. The second is the monohydrate of the 1 : 1 complex of PYR and PAS. The crystal structures of both co-crystals are characterized by a number of hydrogen bonded synthons. Hydrogen bonding of the COOH center dot center dot center dot N-pyridine type is found in both cases. In the INH : PAS co-crystal, there are two symmetry independent COOH center dot center dot center dot center dot N-pyridine hydrogen bonds. In one of these, the H-atom is located on the carboxylic group and is indicative of a co-crystal. In the second case, partial proton transfer occurs across the hydrogen bond, and the extent of proton transfer depends on the temperature. This is more indicative of a salt. Drug-drug co-crystals may have some bearing in the treatment of tuberculosis.

Context based service discovery for ubiquitous applications

Service discovery is vital in ubiquitous applications, where a large number of devices and software components collaborate unobtrusively and provide numerous services without user intervention. Existing service discovery schemes use a service matching process in order to offer services of interest to the users. Potentially, the context information of the users and surrounding environment can be used to improve the quality of service matching. To make use of context information in service matching, a service discovery technique needs to address certain challenges. Firstly, it is required that the context information shall have unambiguous representation. Secondly, the devices in the environment shall be able to disseminate high level and low level context information seamlessly in the different networks. And thirdly, dynamic nature of the context information be taken into account. We propose a C-IOB(Context-Information, Observation and Belief) based service discovery model which deals with the above challenges by processing the context information and by formulating the beliefs based on the observations. With these formulated beliefs the required services will be provided to the users. The method has been tested with a typical ubiquitous museum guide application over different cases. The simulation results are time efficient and quite encouraging.

Discovery of Application Workloads from Network File Traces

An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.