Mode of action of antitumour antibiotics: Spectrophotometric studies on the interaction of chromomycin A3 with DNA and chromatin of normal and neoplastic tissue

The binding of chromomycin A3, an antitumour antibiotic, to various DNA and chromatin isolated from mouse and rat liver, mouse fibrosarcoma and Yoshida ascites sarcoma cells was studied spectrophotometrically at 29°C in 10−2 M Tris-HCl buffer, pH 8.0, containing small amounts of MgCl2 (4.5 · 10−5−25 · 10−5 M). An isobestic point at 415 nm was observed when chromomycin A3 was gradually titrated with Image and its spectrum shifted towards higher wavelength. The rates and extent of these spectral changes were found to be dependent on the concentration of Mg2+. The change in absorbance at 440 nm was used to calculate apparent binding constant (Ka p M−1) and sites per nucleotide (n) from Scatchard plots for various DNA and chromatins. As expected, values of n for chromatin (0.06–0.10) were found to be lower than that found for corresponding DNA (0.10–0.15). Apparently no such correlation exists between binding constants (Ka p M−1 · 10−4) of DNA (6.4–11.2) and of chromatin (3.1–8.3), but Ka p M−1 of chromatin isolated from mouse fibrosarcoma and Yoshida ascites sarcoma are 1.5–3 times higher than that found for mouse and rat liver chromatin. These differences may be taken to indicate structural difference in nucleoprotein complexes caused by neoplasia. The relevance of this finding to tumour suppressive action of chromomycin A3 is discussed.

The purification and properties of peroxidase in Mycobacterium tuberculosis H37Rv and its possible role in the mechanism of action of isonicotinic acid hydrazide

Peroxidase from Mycobacterium tuberculosis H37Rv was purified to homogeneity. The homogeneous protein exhibits catalase and Y (Youatt's)-enzyme activities in addition to peroxidase activity. Further confirmation that the three activities are due to a single enzyme was accomplished by other criteria, such as differential thermal inactivation, sensitivity to different inhibitors, and co-purification. The Y enzyme (peroxidase) was separated from NADase (NAD+ glycohydrolase) inhibitor by gel filtration on Sephadex G-200. The molecular weights of peroxidase and NADase inhibitor, as determined by gel filtration, are 240000 and 98000 respectively. The Y enzyme shows two Km values for both isoniazid (isonicotinic acid hydrazide) and NAD at low and high concentrations. Analysis of the data by Hill plots revealed that the enzyme has one binding site at lower substrate concentrations and more than one at higher substrate concentration. The enzyme contains 6g-atoms of iron/mol. Highly purified preparations of peroxidases from different sources catalyse the Y-enzyme reaction, suggesting that the nature of the reaction may be a peroxidatic oxidation of isoniazid. Moreover, the Y-enzyme reaction is enhanced by O2. Isoniazid-resistant mutants do not exhibit Y-enzyme, peroxidase or catalase activities, and do not take up isoniazid. The Y-enzyme reaction is therefore implicated in the uptake of the drug.

Inhibitory action of norepinephrine on the induction of tryptophan-2,3-dioxygenase by cortisol: Mediation by the I-receptor

Induction of hepatic tryptophan-2,3-dioxygenase in rats by cortisol or corticosterone was inhibited on treatment with norepinephrine. The I-adrenergic blockers showed a small potentiating effect of the norepinephrine-mediated inhibition. The I-adrenergic blockers significantly reversed this inhibition, suggesting that norepinephrine acts Image the I-receptor in inhibition of the cortisol-mediated induction of this enzyme.

Comparison of Prediction Based LSF Quantization Methods using Split VQ

Further improvement in performance, to achieve near transparent quality LSF quantization, is shown to be possible by using a higher order two dimensional (2-D) prediction in the coefficient domain. The prediction is performed in a closed-loop manner so that the LSF reconstruction error is the same as the quantization error of the prediction residual. We show that an optimum 2-D predictor, exploiting both inter-frame and intra-frame correlations, performs better than existing predictive methods. Computationally efficient split vector quantization technique is used to implement the proposed 2-D prediction based method. We show further improvement in performance by using weighted Euclidean distance.

Mode of Action of a Purified Antitumor Protein from the Proteinaceous Crystal of Bacillus thuringiensis subsp. thuringiensis on Yoshida Ascites Sarcoma Cells

A purified antitumor protein from the proteinaceous crystal of Bacillus thuringiensis subsp. thuringiensis inhibits the growth of Yoshida ascites sarcoma both in vivo and in vitro. Exogenous respiration of the tumor cells was unaffected by the protein at a concentration as high as 500 µg/ml. The antitumor protein inhibits the uptake and incorporation of labeled precursors into macromolecules. However, the ratio of incorporation over uptake is not affected by the protein. Further, the protein brings about the leakage of 260-nm-absorbing material, proteins, and 32P-labeled cellular constituents from the Yoshida ascites sarcoma cells. The results show that the action of the antitumor protein appears to alter the cellular permeability of the tumor cells.

Effect of membrane action on the plastic collapse load of circular orthotropic slabs with fixed edges

In the case of reinforced concrete slabs fixed at the boundaries, considerable enhancement in the load carrying capacity takes place due to compressive membrane action. In this paper a method is presented to analyse the effects of membrane action in fixed orthotropic circular slabs, carrying uniformly distributed loads. Depending on the radial moment capacity being greater or less than the circumferential moment capacity, two cases of orthotropy have been considered. Numerical results are worked out for certain assumed physical parameters and for different coefficients of orthotropy. Variations of load and bending moments with the central deflection are presented.

Site of action of iron in the induction of δ-aminolevulinate dehydratase in Neurospora crassa

δ-Aminolevulinate (ALA) dehydratase, the second and rate limiting enzyme of the heme biosynthetic pathway in the mold Neurospora crassa is induced maximally in 30 min by the addition of iron to iron-deficient cultures. The induction of the enzyme is blocked by cycloheximide, protoporphyrin, 8-azaguanine and cordycepin. Iron also brings about an increase in poly(A)-containing RNA synthesis under conditions of induction. The iron dependent increase in poly(A)-containing RNA synthesis is blocked by protoporphyrin. It is suggested that at the time intervals examined, bulk of the messenger RNA synthesized in response to iron addition represents the messenger for ALA dehydratase.

Calculating the bound spectrum by path summation in action-angle variables

The density of states n(E) is calculated for a bound system whose classical motion is integrable, starting from an expression in terms of the trace of the time-dependent Green function. The novel feature is the use of action-angle variables. This has the advantages that the trace operation reduces to a trivial multiplication and the dependence of n(E) on all classical closed orbits with different topologies appears naturally. The method is contrasted with another, not applicable to integrable systems except in special cases, in which quantization arises from a single closed orbit which is assumed isolated and the trace taken by the method of stationary phase.

Mechanism of action of selenious acid in the electrodeposition of manganese

The effect of selenious acid as an addition agent in the electrodeposition of manganese was studied by analysing the current-potential curves for manganese deposition. The mechanism of action of this addition agent was found to be essentially similar to that proposed for sulphur dioxide, namely to affect the manganese deposition indirectly by influencing the hydrogen evolution reaction which is a parallel reaction at the electrode surface.

A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces

Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples. We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.

Prediction of protein-protein interactions between Helicobacter pylori and a human host

A lack of information on protein-protein interactions at the host-pathogen interface is impeding the understanding of the pathogenesis process. A recently developed, homology search-based method to predict protein-protein interactions is applied to the gastric pathogen, Helicobacter pylori to predict the interactions between proteins of H. pylori and human proteins in vitro. Many of the predicted interactions could potentially occur between the pathogen and its human host during pathogenesis as we focused mainly on the H. pylori proteins that have a transmembrane region or are encoded in the pathogenic island and those which are known to be secreted into the human host. By applying the homology search approach to protein-protein interaction databases DIP and iPfam, we could predict in vitro interactions for a total of 623 H. pylori proteins with 6559 human proteins. The predicted interactions include 549 hypothetical proteins of as yet unknown function encoded in the H. pylori genome and 13 experimentally verified secreted proteins. We have recognized 833 interactions involving the extracellular domains of transmembrane proteins of H. pylori. Structural analysis of some of the examples reveals that the interaction predicted by us is consistent with the structural compatibility of binding partners. Examples of interactions with discernible biological relevance are discussed.

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.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Cytotoxicity of half sandwich ruthenium(II) complexes with strong hydrogen bond acceptor ligands and their mechanism of action

Neutral and cationic organometallic ruthenium(II) piano stool complexes of the type [(eta(6)-cymene)R-uCl(X)(Y)] (complexes R1-R8) has been synthesized and characterized. In cationic complexes, X, Y is either a eta(2) phosphorus ligand such as 1,1-bis(diphenylphosphino)methane (DPPM) and 1,2-bis(diphenylphosphino)ethane (DPPE) or partially oxidized ligands such as 1,2-bis(diphenylphosphino)methane monooxide (DPPMO) and 1,2-bis(diphenylphosphino)ethane monooxide (DPPEO) which are strong hydrogen bond acceptors. In neutral complexes. X is chloride and Y is a monodentate phosphorous donor. Complexes with DPPM and DPPMO ligands ([(eta(6)-cymene)Ru(eta(2)-DPPM)Cl]PF6 (R2), [(eta(6)-cymene)Ru(eta(2)-DPPMO)Cl]PF6 (R3), [(eta(6)-cymene)Ru(eta(1)-DPPM)Cl-2] (R5) and [(eta(6)-cymene)Ru(eta(1)-DPPMO)Cl-2] (R6) show good cytotoxicity. Growth inhibition study of several human cancer cell lines by these complexes has been carried out. Mechanistic studies for R5 and R6 show that inhibition of cancer cell growth involves both cell cycle arrest and apoptosis induction. Using an apoptosis PCR array, we identified the sets of antiapoptotic genes that were down regulated and pro-apoptotic genes that were up regulated. These complexes were also found to be potent metastasis inhibitors as they prevented cell invasion through matrigel. The complexes were shown to bind DNA in a non intercalative fashion and cause unwinding of plasmid DNA in cell-free medium by competitive ethidium bromide binding, viscosity measurements, thermal denaturation and gel mobility shift assays.