887 resultados para LIGAND-BASED DRUG DESIGN


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DNA topoisomerases are ubiquitous group of enzymes altering the topology of DNA by concerted breakage and rejoining of the phosphodiester backbone of DNA. The enzymes are classified based on the pattern of DNA cleavage. Type IA enzymes found in all bacteria nick the DNA and attach themselves covalently to the 5' side of the nick during the first transesterification reaction. Most of the information on this group of enzymes comes from studies with E. coli topoisomerase I and III. Members of type IA group are single subunit Zn++ metalloenzymes recognizing single stranded DNA without high degree of sequence specificity during relaxation reaction of negatively super coiled DNA. So far no inhibitors are known for this group of enzymes inspite of their important role in maintaining homeostasis of DNA topology. Molecular characterization of DNA topoisomerase I from mycobacteria has revealed some of the important features of type IA enzymes hitherto unknown and provide scope for identifying novel inhibitors. The present review describes the recent developments in the area summarizing the distinctive features of mycobacterial topoisomerase I. The enzyme has several properties not shared by either type IA or 113 enzymes with respect to DNA binding, recognition, sequence specificity and interaction pattern. The physiological basis of the unusual features is discussed. The unique properties described would aid in developing the enzyme as a target molecule in pharmaceutical design. In addition, the findings lead to address some fundamental questions on the intracellular role of topoisomerase I in the biology of mycobacteria which are one of the most formidable group of pathogenic organisms.

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The design and synthesis of agents that can abstract zinc from their [CCXX] (C=cysteine; X=cysteine/histidine) boxes by thioldisulfide exchange-having as control, the redox parities of the core sulfur ligands of the reagent and the enzyme, has been illustrated, and their efficiency demonstrated by monitoring the inhibition of the transcription of calf thymus DNA by E. coli RNA polymerase, which harbors two zinc atoms in their [CCXX] boxes of which one is exchangeable. Maximum inhibition possible with removal of the exchangeable zinc was seen with redox-sulfanilamide-glutamate composite. In sharp contrast, normal chelating agents (EDTA, phenanthroline) even in a thousand fold excess showed only marginal inhibition, thus supporting an exchange mechanism for the metal removal. (C) 2002 Elsevier Science Ltd. All rights reserved.

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Seismic design of reinforced soil structures involves many uncertainties that arise from the backfill soil properties and tensile strength of the reinforcement which is not addressed in current design guidelines. This paper highlights the significance of variability in the internal stability assessment of reinforced soil structures. Reliability analysis is applied to estimate probability of failure and pseudo‐static approach has been used for the calculation of the tensile strength and length of the reinforcement needed to maintain the internal stability against tension and pullout failures. Logarithmic spiral failure surface has been considered in conjunction with the limit equilibrium method. Two modes of failure namely, tension failure and pullout failure have been considered. The influence of variations of the backfill soil friction angle, the tensile strength of reinforcement, horizontal seismic acceleration on the reliability index against tension failure and pullout failure of reinforced earth structure have been discussed.

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In the near future, robots and CG (computer graphics) will be required to exhibit creative behaviors that reflect designers’ abstract images and emotions. However, there are no effective methods to develop abstract images and emotions and support designers in designing creative behaviors that reflect their images and emotions. Analogy and blending are two methods known to be very effective for designing creative behaviors. The aim of this study is to propose a method for developing designers’ abstract behavioral images and emotions and giving shape to them by constructing a computer system that supports a designer in the creation of the desired behavior. This method focuses on deriving inspiration from the behavioral aspects of natural phenomena rather than simply mimicking it. We have proposed two new methods for developing abstract behavioral images and emotions by which a designer can use analogies from natural things such as animals and plants even when there is a difference in the number of joints between the natural object and the design target. The first method uses visual behavioral images, the second uses rhythmic behavioral images. We have demonstrated examples of designed behaviors to verify the effectiveness of the proposed methods.

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Based on the an earlier CFD analysis of the performance of the gas-dynamically controlled laser cavity [1]it was found that there is possibility of optimizing the geometry of the diffuser that can bring about reductions in both size and cost of the system by examining the critical dimensional requirements of the diffuser. Consequently,an extensive CFD analysis has been carried out for a range of diffuser configurations by simulating the supersonic flow through the arrangement including the laser cavity driven by a bank of converging – diverging nozzles and the diffuser. The numerical investigations with 3D-RANS code are carried out to capture the flow patterns through diffusers past the cavity that has multiple supersonic jet interactions with shocks leading to complex flow pattern. Varying length of the diffuser plates is made to be the basic parameter of the study. The analysis reveals that the pressure recovery pattern during the flow through the diffuser from the simulation, being critical for the performance of the laser device shows its dependence on the diffuser length is weaker beyond a critical lower limit and this evaluation of this limit would provide a design guideline for a more efficient system configuration.The observation based on the parametric study shows that the pressure recovery transients in the near vicinity of the cavity is not affected for the reduction in the length of the diffuser plates up to its 10% of the initial size, indicating the design in the first configuration that was tested experimentally has a large factor of margin. The flow stability in the laser cavity is found to be unaffected since a strong and stable shock is located at the leading edge of the diffuser plates while the downstream shock and flow patterns are changed, as one would expect. Results of the study for the different lengths of diffusers in the range of 10% to its full length are presented, keeping the experimentally tested configuration used in the earlier study [1] as the reference length. The conclusions drawn from the analysis is found to be of significance since it provides new design considerations based on the understanding of the intricacies of the flow, allowing for a hardware optimization that can lead to substantial size reduction of the device with no loss of performance.

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Pulse Forming Line (PFL) based high voltage pulsed power systems are well suited for low impedance High Power Microwave (HPM) sources such as a virtual cathode oscillator (VIRCATOR) operating in nanosecond regimes. The system under development consists of a primary voltage source that charges the capacitor bank of a Marx pulser over a long time duration. The Marx pulser output is then conditioned by a PFL to match the requirement of the HPM diode load. This article describes the design and construction of an oil insulated pulse forming line for a REB (Relativistic Electron Beam) diode used in a VIRCATOR for the generation of high power microwaves. Design of a 250 kV/10 kA/60 ns PFL, including the PSPICE simulation for various load conditions are described.

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Biologically triggered exploding microcapsules were synthesized by layer-by-layer assembly of biopolymers. The microcapsules showed controlled rupturing behaviour upon exposure to a pathologically relevant biomolecule, trypsin. These microcapsules offer significant potential for clinical applications.

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The current paper suggests a new procedure for designing helmets for head impact protection for users such as motorcycle riders. According to the approach followed here, a helmet is mounted on a featureless Hybrid 3 headform that is used in assessing vehicles for compliance to the FMVSS 201 regulation in the USA for upper interior head impact safety. The requirement adopted in the latter standard, i.e. not exceeding a threshold HIC(d) limit of 1000, is applied in the present study as a likely criterion for adjudging the efficacy of helmets. An impact velocity of 6 m/s (13.5 mph) for the helmet-headform system striking a rigid target can probably be acceptable for ascertaining a helmet's effectiveness as a countermeasure for minimizing the risk of severe head injury. The proposed procedure is demonstrated with the help of a validated LS-DYNA model of a featureless Hybrid 3 headform in conjunction with a helmet model comprising an outer polypropylene shell to the inner surface of which is bonded a protective polyurethane foam padding of a given thickness. Based on simulation results of impact on a rigid surface, it appears that a minimum foam padding thickness of 40 mm is necessary for obtaining an acceptable value of HIC(d).

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This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.