887 resultados para LIGAND-BASED DRUG DESIGN
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In drug discovery, different methods exist to create new inhibitors possessing satisfactory biological activity. The multisubstrate adduct inhibitor (MAI) approach is one of these methods, which consists of a covalent combination between analogs of the substrate and the cofactor or of the multiple substrates used by the target enzyme. Adopted as the first line of investigation for many enzymes, this method has brought insights into the enzymatic mechanism, structure, and inhibitory requirements. In this review, the MAI approach, applied to different classes of enzyme, is reported from the point of view of biological activity.
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Introduction: Infections by multidrug-resistant bacteria are of great concern worldwide. In many cases, resistance is not due to the presence of specific antibiotic-modifying enzymes, but rather associated with a general impermeability of the bacterial cell envelope. The molecular bases of this intrinsic resistance are not completely understood. Moreover, horizontal gene transfers cannot solely explain the spread of intrinsic resistance among bacterial strains. Areas covered: This review focuses on the increased intrinsic antibiotic resistance mediated by small molecules. These small molecules can either be secreted from bacterial cells of the same or different species (e.g., indole, polyamines, ammonia, and the Pseudomonas quinolone signal) or be present in the bacterial cell milieu, whether in the environment, such as indole acetic acid and other plant hormones, or in human tissues and body fluids, such as polyamines. These molecules are metabolic byproducts that act as infochemicals and modulate bacterial responses toward antibiotics leading to increasing or decreasing resistance levels. Expert opinion: The non-genetic mechanisms of antibiotic response modulation and communication discussed in this review should reorient our thinking of the mechanisms of intrinsic resistance to antibiotics and its spread across bacterial cell populations. The identification of chemical signals mediating increased intrinsic antibiotic resistance will expose novel critical targets for the development of new antimicrobial strategies.
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Environmental problems, especially climate change, have become a serious global issue waiting for people to solve. In the construction industry, the concept of sustainable building is developing to reduce greenhouse gas emissions. In this study, a building information modeling (BIM) based building design optimization method is proposed to facilitate designers to optimize their designs and improve buildings’ sustainability. A revised particle swarm optimization (PSO) algorithm is applied to search for the trade-off between life cycle costs (LCC) and life cycle carbon emissions (LCCE) of building designs. In order tovalidate the effectiveness and efficiency of this method, a case study of an office building is conducted in Hong Kong. The result of the case study shows that this method can enlarge the searching space for optimal design solutions and shorten the processing time for optimal design results, which is really helpful for designers to deliver an economic and environmental friendly design scheme.
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We present a novel data analysis strategy which combined with subcellular fractionation and liquid chromatography-mass spectrometry (LC-MS) based proteomics provides a simple and effective workflow for global drug profiling. Five subcellular fractions were obtained by differential centrifugation followed by high resolution LC-MS and complete functional regulation analysis. The methodology combines functional regulation and enrichment analysis into a single visual summary. The workflow enables improved insight into perturbations caused by drugs. We provide a statistical argument to demonstrate that even crude subcellular fractions leads to improved functional characterization. We demonstrate this data analysis strategy on data obtained in a MS-based global drug profiling study. However, this strategy can also be performed on other types of large scale biological data.
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Variations of manufacturing process parameters and environmental aspects may affect the quality and performance of composite materials, which consequently affects their structural behaviour. Reliability-based design optimisation (RBDO) and robust design optimisation (RDO) searches for safe structural systems with minimal variability of response when subjected to uncertainties in material design parameters. An approach that simultaneously considers reliability and robustness is proposed in this paper. Depending on a given reliability index imposed on composite structures, a trade-off is established between the performance targets and robustness. Robustness is expressed in terms of the coefficient of variation of the constrained structural response weighted by its nominal value. The Pareto normed front is built and the nearest point to the origin is estimated as the best solution of the bi-objective optimisation problem.
Resumo:
In all biological processes, protein molecules and other small molecules interact to function and form transient macromolecular complexes. This interaction of two or more molecules can be described by a docking event. Docking is an important phase for structure-based drug design strategies, as it can be used as a method to simulate protein-ligand interactions. Various docking programs exist that allow automated docking, but most of them have limited visualization and user interaction. It would be advantageous if scientists could visualize the molecules participating in the docking process, manipulate their structures and manually dock them before submitting the new conformations to an automated docking process in an immersive environment, which can help stimulate the design/docking process. This also could greatly reduce docking time and resources. To achieve this, we propose a new virtual modelling/docking program, whereby the advantages of virtual modelling programs and the efficiency of the algorithms in existing docking programs will be merged.
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This paper presents the notion of Context-based Activity Design (CoBAD) that represents context with its dynamic changes and normative activities in an interactive system design. The development of CoBAD requires an appropriate context ontology model and inference mechanisms. The incorporation of norms and information field theory into Context State Transition Model, and the implementation of new conflict resolution strategies based on the specific situation are discussed. A demonstration of CoBAD using a human agent scenario in a smart home is also presented. Finally, a method of treating conflicting norms in multiple information fields is proposed.
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Norms are a set of rules that govern the behaviour of human agent, and how human agent behaves in response to the given certain conditions. This paper investigates the overlapping of information fields (set of shared norms) in the Context State Transition Model, and how these overlapping fields may affect the choices and actions of human agent. This paper also includes discussion on the implementation of new conflict resolution strategies based on the situation specification. The reasoning about conflicting norms in multiple information fields is discussed in detail.)
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Two targets, reverse transcriptase (RT) and protease from HIV-1, were used during the past two decades to the discovery of non-nucleoside reverse transcriptase inhibitors (NNRTI) and protease inhibitors (PI) that belong to the arsenal of the antiretroviral therapy. Herein these enzymes were chosen as templates for conducting a computer-aided ligand design. Ligand and structure-based drug designs were the starting points to select compounds from a database bearing more than five million compounds by means of cheminformatic tools. New promising lead structures are retrieved from the database, which are open to acquisition and test. Classes of molecules already described as NNRTI or PI in the literature also came out and were useful to prove the reliability of the workflow, and thus validating the work carried out so far. (c) 2007 Elsevier Masson SAS. All rights reserved.
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The desire to conquer markets through advanced product design and trendy business strategies are still predominant approaches in industry today. In fact, product development has acquired an ever more central role in the strategic planning of companies, and it has extended its influence to R&D funding levels as well. It is not surprising that many national R&D project frameworks within the EU today are dominated by product development topics, leaving production engineering, robotics, and systems on the sidelines. The reasons may be many but, unfortunately, the link between product development and the production processes they cater for are seldom treated in depth. The issue dealt with in this article relates to how product development is applied in order to attain the required production quality levels a company may desire, as well as how one may counter assembly defects and deviations through quantifiable design approaches. It is recognized that product verifications (tests, inspections, etc.) are necessary, but the application of these tactics often result in lead-time extensions and increased costs. Modular architectures improve this by simplifying the verification of the assembled product at module level. Furthermore, since Design for Assembly (DFA) has shown the possibility to identify defective assemblies, it may be possible to detect potential assembly defects already in the product and module design phase. The intention of this paper is to discuss and describe the link between verifications of modular architectures, defects and design for assembly. The paper is based on literature and case studies; tables and diagrams are included with the intention of increasing understanding of the relation between poor designs, defects and product verifications.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)