Structure and interactions of aspirin-like drugs

A pre-requisite for the elucidation of the mechanism of action of aspirin-like drugs, which are believed to exert their pharmacological effects through the inhibition of prostaglandin biosynthesis, is an understanding of their molecular geometry, the non-covalent interactions they are likely to be involved in, and the geometrical and the electronic consequences of such interactions. This has been sought to be achieved through the x-ray analysis of these drug molecules and their crystalline complexes with other suitable molecules. The results obtained from such studies have been discussed in terms of specific typical examples. For instance, antipyrine can form metal and hydrogen-bonded complexes; phenylbutazone can form ionic complexes with basic molecules. Complex formation is accompanied by characteristic changes in the molecular geometry and the electronic structure in both the cases. The results obtained so far appear to indicate that the important common invariant structural features of the fenamates, deduced from crystal structures, are retained even when complexation takes place.

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.

Studies on Unsteady Shock Interactions Near a Generic Scramjet Inlet

An experimental and numerical study is presented to show the effect of cowl length and angle on the ramp/cowl shock interaction phenomena fora two-dimensional planar scramjet inlet model. Experiments areconducted in a hypersonic shock tunnel, at Mach 8, at four lengths of owl and three cowl angles. Investigations include schlieren flow Visualization near the cowl region and static pressure and heat transfer rate measurement inside the inlet chamber. Various ramp/cowl shock interaction processes resulted for different cowl configurations have been visualized using a high-speed camera. Edney type-II interference pattern is observed for 131 and 141-mm cowl lengths,whereas it is an Edney type-I interference pattern in case of a 151 mm cowl with all their typical features resulting because of the ramp/cowl shock interaction. Experiments with a cowl configuration other than 0deg show the flow to he established through the inlet because or the reduced contraction ratio. Heat transfer peaks can be observed for the10 and 20-deg cowl cases where flow through the inlet is found to be established. These may serve as the possible locations of fuel injection.

Sequence of reactions leading to cytochrome-p-450 synthesis-effect of drugs

The effect of phenobarbital on the rates of the synthesis of the protein and heme moieties of cytochrome P-450 has been studied. For this purpose, cytochrome P-450 has been partially purified as its P-420 derivative and the labeled amino acid incorporation into the protein has been studied after subjecting a partially purified preparation to sodium dodecyl sulfate gel electrophoresis. The incorporation studies into the protein species after sodium dodecyl sulfate gel electrophoresis reveal that the drug primarily accelerates the rate of apoprotein synthesis followed by an increase in the rate of heme synthesis. The messenger for apocytochrome P-450 appears to be fairly stable.

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.

Relative stability of DNA as a generic criterion for promoter prediction: whole genome annotation of microbial genomes with varying nucleotide base composition

The rapid increase in genome sequence information has necessitated the annotation of their functional elements, particularly those occurring in the non-coding regions, in the genomic context. Promoter region is the key regulatory region, which enables the gene to be transcribed or repressed, but it is difficult to determine experimentally. Hence an in silico identification of promoters is crucial in order to guide experimental work and to pin point the key region that controls the transcription initiation of a gene. In this analysis, we demonstrate that while the promoter regions are in general less stable than the flanking regions, their average free energy varies depending on the GC composition of the flanking genomic sequence. We have therefore obtained a set of free energy threshold values, for genomic DNA with varying GC content and used them as generic criteria for predicting promoter regions in several microbial genomes, using an in-house developed tool `PromPredict'. On applying it to predict promoter regions corresponding to the 1144 and 612 experimentally validated TSSs in E. coli (50.8% GC) and B. subtilis (43.5% GC) sensitivity of 99% and 95% and precision values of 58% and 60%, respectively, were achieved. For the limited data set of 81 TSSs available for M. tuberculosis (65.6% GC) a sensitivity of 100% and precision of 49% was obtained.

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.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

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.

Antithyroid Drugs and their Analogues Protect Against Peroxynitrite-Mediated Protein Tyrosine Nitration-A Mechanistic Study

In this paper, the effect of some commonly used antithyroid drugs and their analogues on peroxynitrite-mediated nitration of proteins is described. The nitration of tyrosine residues in bovine serum albumin (BSA) and cytochromec was studied by Western blot analysis. These studies reveal that the antithyroid drugs methimazole (MMI), 6-n-propyl-2-thiouracil (PTU), and 6-methyl-2-thiouracil (MTU), which contain thione moieties, significantly reduce the tyrosine nitration of both BSA and cytochrome c. While MMI exhibits good peroxynitrite (PN) scavenging activity, the thiouracil compounds PTU and MTU are slightly less effective than MMI. The S- and Se-methylated compounds show a weak inhibitory effect in the nitration of tyrosine, indicating that the presence of a thione or selone moiety is important for an efficient inhibition. Similarly, the replacement of N-H moiety in MMI by N-methyl or N-m-methoxybenzyl substituents dramatically reduces the antioxidant activity of the parent compound. Theoretical studies indicate that the substitution of N-H moiety by N-Me significantly increases the energy required for the oxidation of sulfur center by PN. However, such substitution in the selenium analogue of MMI increases the activity of parent compound. This is due to the facile oxidation of the selone moiety to the corresponding selenenic and seleninic acids. Unlike N,N'-disubstituted thiones, the corresponding selones efficiently scavenge PN, as they predominantly exist in their zwitterionic forms in which the selenium atom carries a large negative charge.

Interaction of cationic amphiphilic drugs with lipid A: Implications for development of endotoxin antagonists

This report presents evidence for the interactions of several classes of cationic amphiphilic drugs including the phenothiazines, aminoquinolines, biguanides, and aromatic diamidines, with lipid A, the endotoxic principle of lipopolysaccharides. The interactions of the drugs were quantitatively assessed by fluorescence methods. The affinities of the drugs for lipid A parallel their endotoxin-antagonistic effects in the Limulus gelation assay. Dicationic compounds bind lipid A with greater affinity; the affinity of such molecules increases exponentially as a function of the distance between the basic moieties. The bis-amidine drug - pentamidine - examined in greater detail, binds lipid A with high affinity (apparent K-d: 0.12 mu M), and LPS, probably due to simultaneous interactions of the terminal amidine groups with the anionic phosphates on lipid A. The sequestration of endotoxin by pentamidine reduces its propensity to bind to cells, and the complex exhibits attenuated toxicity in biological assays. These results have implications in the development of therapeutic strategies against endotoxin-related disease states.

Generic Routing Rules and a Scalable Access Enhancement for the Network-on-Chip RECONNECT

RECONNECT is a Network-on-Chip using a honeycomb topology. In this paper we focus on properties of general rules applicable to a variety of routing algorithms for the NoC which take into account the missing links of the honeycomb topology when compared to a mesh. We also extend the original proposal [5] and show a method to insert and extract data to and from the network. Access Routers at the boundary of the execution fabric establish connections to multiple periphery modules and create a torus to decrease the node distances. Our approach is scalable and ensures homogeneity among the compute elements in the NoC. We synthesized and evaluated the proposed enhancement in terms of power dissipation and area. Our results indicate that the impact of necessary alterations to the fabric is negligible and effects the data transfer between the fabric and the periphery only marginally.

Effective treatment of infectious diseases: A nonlinear adaptive control theoretic approach

A nonlinear adaptive system theoretic approach is presented in this paper for effective treatment of infectious diseases that affect various organs of the human body. The generic model used does not represent any specific disease. However, it mimics the generic immunological dynamics of the human body under pathological attack, including the response to external drugs. From a system theoretic point of view, drugs can be interpreted as control inputs. Assuming a set of nominal parameters in the mathematical model, first a nonlinear controller is designed based on the principle of dynamic inversion. This treatment strategy was found to be effective in completely curing "nominal patients". However, in some cases it is ineffective in curing "realistic patients". This leads to serious (sometimes fatal) damage to the affected organ. To make the drug dosage design more effective, a model-following neuro-adaptive control design is carried out using neural networks, which are trained (adapted) online. From simulation studies, this adaptive controller is found to be effective in killing the invading microbes and healing the damaged organ even in the presence of parameter uncertainties and continuing pathogen attack.