The Effects of Anti-Hypertensive Drugs Evaluated Using Markov Modelling for Northern Ireland Chronic Kidney Disease Patients

The aim of this paper is to use Markov modelling to
investigate survival for particular types of kidney patients
in relation to their exposure to anti-hypertensive treatment
drugs. In order to monitor kidney function an intuitive three
point assessment is proposed through the collection of blood
samples in relation to Chronic Kidney Disease for Northern
Ireland patients. A five state Markov Model was devised
using specific transition probabilities for males and
females over all age groups. These transition probabilities
were then adjusted appropriately using relative risk scores
for the event death for different subgroups of patients. The
model was built using TreeAge software package in order to
explore the effects of anti-hypertensive drugs on patients.

Anti-hypertensive drugs have different effects on ventricular hypertrophy regression

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Timing the Emergence of Resistance to Anti-HIV Drugs with Large Genetic Barriers

New antiretroviral drugs that offer large genetic barriers to resistance, such as the recently approved inhibitors of HIV-1 protease, tipranavir and darunavir, present promising weapons to avert the failure of current therapies for HIV infection. Optimal treatment strategies with the new drugs, however, are yet to be established. A key limitation is the poor understanding of the process by which HIV surmounts large genetic barriers to resistance. Extant models of HIV dynamics are predicated on the predominance of deterministic forces underlying the emergence of resistant genomes. In contrast, stochastic forces may dominate, especially when the genetic barrier is large, and delay the emergence of resistant genomes. We develop a mathematical model of HIV dynamics under the influence of an antiretroviral drug to predict the waiting time for the emergence of genomes that carry the requisite mutations to overcome the genetic barrier of the drug. We apply our model to describe the development of resistance to tipranavir in in vitro serial passage experiments. Model predictions of the times of emergence of different mutant genomes with increasing resistance to tipranavir are in quantitative agreement with experiments, indicating that our model captures the dynamics of the development of resistance to antiretroviral drugs accurately. Further, model predictions provide insights into the influence of underlying evolutionary processes such as recombination on the development of resistance, and suggest guidelines for drug design: drugs that offer large genetic barriers to resistance with resistance sites tightly localized on the viral genome and exhibiting positive epistatic interactions maximally inhibit the emergence of resistant genomes.

Interaction of DNA with anti-cancer drugs: copper-thiosemicarbazide system

The interaction of copper-thiosemicarbazide complexes with DNA was investigated using ultraviolet and infrared spectroscopy. Evidence for the interaction of the complexes with nucleic acid bases and with the phosphate group is presented.

Temperature independent mixing rules to correlate the solubilities of antibiotics and anti-inflammatory drugs in SCCO2

The accurate experimental determination of the solubilities of antibiotics and anti-inflammatory drugs in supercritical fluids (SCFs) and correlations are essential for the development of supercritical technologies for the pharmaceuticals industry. In this work, the solubilities of penicillinG, penicillinV, flurbiprofen, ketoprofen, naproxen, ibuprofen, aspirin and diflunisal in supercritical carbon dioxide (SCCO2) were correlated using Peng-Robinson equation of state (PR EOS) with the modified Kwak and Mansoori mixing rules (mKM) and with Bartle model. The ability of mKM rules was compared against the conventional mixing rules of van der Waals in correlating the solubilities. In the present model, vapor pressure was considered as an adjustable parameter along with binary interactions parameters. In the proposed model, the constants used in the mixing rule, and vapor pressure expression coefficients are temperature independent. The optimization of these constants with experimental data gives binary interaction parameters along with vapor pressure correlations. Sublimation enthalpies were estimated with both the models compared with literature reported experimental values.

Effect of thione—thiol tautomerism on the inhibition of lactoperoxidase by anti-thyroid drugs and their analogues

The keto-enol type tautomerism in anti-thyroid drugs and their selenium analogues are described. The commonly used anti-thyroid drug methimazole exists predominantly in its thione form, whereas its selenium analogue exists in a zwitterionic form. To understand the effect of thione/thiol and selone/selenol tautomerism on the inhibition of peroxidase-catalysed reactions, we have synthesized some thiones and selones in which the formation of thiol/selenol forms are blocked by different substituents. These compounds were synthesized by a carbene route utilizing an imidazolium salt. The crystal structures of these compounds reveal that the C=Se bonds in the selones are more polarized than the C=S bonds in the corresponding thiones. The structures of selones were studied in solution by NMR spectroscopy and the 77Se NMR chemical shifts for the selones show large upfield shifts in the signals, confirming their zwitterionic structures in solution. The inhibition of lactoperoxidase by the synthetic thiones indicates that the presence of a free N-H moiety is essential for an efficient inhibition. In contrast, such moiety is not required for an inhibition by the selenium compounds.

Rationalization and prediction of drug resistant mutations in targets for clinical anti-tubercular drugs

Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.

Coronavirus Main Proteinase (3CLpro) Structure: Basis for Design of Anti-SARS Drugs

A novel coronavirus has been identified as the causative agent of severe acute respiratory syndrome (SARS). The viral main proteinase (Mpro, also called 3CLpro), which controls the activities of the coronavirus replication complex, is an attractive target for therapy. We determined crystal structures for human coronavirus (strain 229E) Mpro and for an inhibitor complex of porcine coronavirus [transmissible gastroenteritis virus (TGEV)] Mpro, and we constructed a homology model for SARS coronavirus (SARS-CoV) Mpro. The structures reveal a remarkable degree of conservation of the substrate-binding sites, which is further supported by recombinant SARS-CoV Mpro-mediated cleavage of a TGEV Mpro substrate. Molecular modeling suggests that available rhinovirus 3Cpro inhibitors may be modified to make them useful for treating SARS.

Use of antigen mimics to produce specific antibodies to anti-coccidial drugs

A range of polyclonal antibodies was successfully produced to the coccidiostatic drugs diclazuril and robenidine. Initial attempts to make immunogenic complexes of both drugs were ineffective due to difficulties encountered while trying to couple the compounds to large carrier proteins. Structural mimics, which could act as haptens for each drug, were sought and identified. The compounds identified were more open to chemical manipulation and were conjugated to carrier proteins to produce effective immunogens. The most sensitive antisera produced displayed IC(50)s of 1.5 ng/ml and 13 ng/ml for diclazuril and robenidine respectively. The antibody for diclazuril was shown to be specific, cross-reacting only with clazuril by 15%. The robenidine antibody displayed a low cross-reactivity of 1.2% to the compound used to produce the antibody. (C) 2007 Elsevier B.V. All rights reserved.

Development of a rapid, multi-class method for the confirmatory analysis of anti-inflammatory drugs in bovine milk using liquid chromatography tandem mass spectrometry

A rapid liquid chromatography tandem mass spectrometry (LC-MS/MS) method has been developed and validated for the simultaneous identification, confirmation and quantitation of seven licensed anti-inflammatory drugs (AIDS) in bovine milk. The method was validated in accordance with the criteria defined in Commission Decision 2002/657/EC. Two classes of AIDS were investigated, corticosteroids and non-steroidal anti-inflammatory drugs (NSAIDs). The developed method is capable of detecting and confirming dexamethasone (DXM), betamethasone (BTM), prednisolone (FRED), tolfenamic acid (TV), 5-hydroxy flunixin (5-OH-FLU). meloxicam (MLX) and 4-methyl amino antipyrine (4-MAA) at their associated maximum residue limits (MRLs). These compounds represent all the corticosteroids and NSAIDs licensed for use in bovine animals producing milk for human consumption. These compounds have never been analysed before in the same method and also 4-methyl amino antipyrine has never been analysed with the other licensed NSAIDs. The method can be considered rapid as permits the analysis of up to 30 samples in one day. Milk samples are extracted with acetonitrile; sodium chloride is added to aid partition of the milk and acetonitrile mixture. The acetonitrile extract is then subjected to liquid-liquid purification by the addition of hexane. The purified extract is finally evaporated to dryness and reconstituted in a water/acetonitrile mixture and determination is carried out by LC-MS/MS. Decision limit (CC alpha) values and detection capability (CC beta) values have been established for each compound. (C) 2009 Elsevier B.V. All rights reserved.

Changing profile in the use of anti-asthma drugs

Data regarding the total number of anti-asthma drugs dispensed via community pharmacies within Northern Ireland from 1980 to 1997 were collected and analysed. The use of anti-asthma drugs within this population increased markedly over the study period from 19.84 DDDs/1000/day to 84.07 DDDs/1000/day. With the exception of the non-selective beta(2)-agonists, there has been an overall increasing trend in the utilization of all of the anti-asthma drugs during the study period. Most of the increase is attributable to the increase in prescribing of the selective beta(2)-agonists and the glucocorticoids, This increase in the utilization of anti-asthma drugs may be explained by an increasing prevalence of the condition, increased adherence to asthma management protocols or to the prescribing of more intensive drug therapies.