27 resultados para STRUCTURE-BASED DRUG DESIGN


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This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

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Small, synthetic peptides based on specific regions of voltage-gated Ca2+ channels (VGCCs) have been widely used to study Ca2+ channel function and have been instrumental in confirming the contribution of specific amino acid sequences to interactions with putative binding partners. In particular, peptides based on the Ca2+ channel Alpha Interaction Domain (AID) on the intracellular region connecting domains I and II (the I-II loop) and the SYNaptic PRotein INTerction (synprint) site on the II-III loop have been widely used. Emerging evidence suggests that such peptides may themselves possess inherent functionality, a property that may be exploitable for future drug design. Here, we review our recent work using synthetic Ca2+ channel peptides based on sequences within the CaV2.2 amino terminal and I-II loop, originally identified as molecular determinates for G protein modulation, and their effects on VGCC function. These CaV2.2 peptides act as inhibitory modules to decrease Ca2+ influx with direct effects on VGCC gating, ultimately leading to a reduction of synaptic transmission. CaV2.2 peptides also attenuate G protein modulation of VGCCs. Amino acid substitutions generate CaV2.2 peptides with increased or decreased inhibitory effects suggesting that synthetic peptides can be used to further probe VGCC function and, potentially, form the basis for novel therapeutic development.

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Nucleotide-based drug candidates such as antisense oligonucleotides, aptamers, immunoreceptor-activating nucleotides, or (anti)microRNAs hold great therapeutic promise for many human diseases. Phosphorothioate (PS) backbone modification of nucleotide-based drugs is common practice to protect these promising drug candidates from rapid degradation by plasma and intracellular nucleases. Effects of the changes in physicochemical properties associated with PS modification on platelets have not been elucidated so far. Here we report the unexpected binding of PS-modified oligonucleotides to platelets eliciting strong platelet activation, signaling, reactive oxygen species generation, adhesion, spreading, aggregation, and thrombus formation in vitro and in vivo. Mechanistically, the platelet-specific receptor glycoprotein VI (GPVI) mediates these platelet-activating effects. Notably, platelets from GPVI function-deficient patients do not exhibit binding of PS-modified oligonucleotides, and platelet activation is fully abolished. Our data demonstrate a novel, unexpected, PS backbone-dependent, platelet-activating effect of nucleotide-based drug candidates mediated by GPVI. This unforeseen effect should be considered in the ongoing development programs for the broad range of upcoming and promising DNA/RNA therapeutics.

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The cupin superfamily is a group of functionally diverse proteins that are found in all three kingdoms of life, Archaea, Eubacteria, and Eukaryota. These proteins have a characteristic signature domain comprising two histidine- containing motifs separated by an intermotif region of variable length. This domain consists of six beta strands within a conserved beta barrel structure. Most cupins, such as microbial phosphomannose isomerases (PMIs), AraC- type transcriptional regulators, and cereal oxalate oxidases (OXOs), contain only a single domain, whereas others, such as seed storage proteins and oxalate decarboxylases (OXDCs), are bi-cupins with two pairs of motifs. Although some cupins have known functions and have been characterized at the biochemical level, the majority are known only from gene cloning or sequencing projects. In this study, phylogenetic analyses were conducted on the conserved domain to investigate the evolution and structure/function relationships of cupins, with an emphasis on single- domain plant germin-like proteins (GLPs). An unrooted phylogeny of cupins from a wide spectrum of evolutionary lineages identified three main clusters, microbial PMIs, OXDCs, and plant GLPs. The sister group to the plant GLPs in the global analysis was then used to root a phylogeny of all available plant GLPs. The resulting phylogeny contained three main clades, classifying the GLPs into distinct subfamilies. It is suggested that these subfamilies correlate with functional categories, one of which contains the bifunctional barley germin that has both OXO and superoxide dismutase (SOD) activity. It is proposed that GLPs function primarily as SODs, enzymes that protect plants from the effects of oxidative stress. Closer inspection of the DNA sequence encoding the intermotif region in plant GLPs showed global conservation of thymine in the second codon position, a character associated with hydrophobic residues. Since many of these proteins are multimeric and enzymatically inactive in their monomeric state, this conservation of hydrophobicity is thought to be associated with the need to maintain the various monomer- monomer interactions. The type of structure-based predictive analysis presented in this paper is an important approach for understanding gene function and evolution in an era when genomes from a wide range of organisms are being sequenced at a rapid rate.

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Chemotherapeutic options for androgen-independent prostate cancer are extremely limited with minimum survival advantage. The benzyl-substituted unbridged titanocene bis-[(p-methoxybenzyl) cyclopentadienyl] titanium(IV) dichloride (Titanocene Y) was tested in vitro against the human prostate cancer androgen-independent cell, PC-3, which demonstrated an IC50 value of 56 x 10(-6) mol/L compared to 5.6 x 10(-6) mol/L for cisplatin. Then Titanocene Y was given at the maximum tolerable dose of 40 mg/kg/d on five consecutive days to one cohort of eight PC3 tumor-bearing male NMRI: nu/nu mice, while a second cohort was treated similarly with 3 mg/kg/d of cisplatin. Both of these mouse cohorts showed a statistically significant tumor growth reduction with respect to the third solvent-treated control group, which led to T/C values of 42% for cisplatin and 52% for Titanocene Y at the end of the experiment. This encouraging activity of Titanocene Y against prostate tumors in vivo, which is almost comparable with respect to cisplatin hopefully leads to further development of Titanocene Y in the future.

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PURPOSE: Since its introduction in 2006, messages posted to the microblogging system Twitter have provided a rich dataset for researchers, leading to the publication of over a thousand academic papers. This paper aims to identify this published work and to classify it in order to understand Twitter based research. DESIGN/METHODOLOGY/APPROACH: Firstly the papers on Twitter were identified. Secondly, following a review of the literature, a classification of the dimensions of microblogging research was established. Thirdly, papers were qualitatively classified using open coded content analysis, based on the paper’s title and abstract, in order to analyze method, subject, and approach. FINDINGS: The majority of published work relating to Twitter concentrates on aspects of the messages sent and details of the users. A variety of methodological approaches are used across a range of identified domains. RESEARCH LIMITATIONS/IMPLICATIONS: This work reviewed the abstracts of all papers available via database search on the term “Twitter” and this has two major implications: 1) the full papers are not considered and so works may be misclassified if their abstract is not clear, 2) publications not indexed by the databases, such as book chapters, are not included. ORIGINALITY/VALUE: To date there has not been an overarching study to look at the methods and purpose of those using Twitter as a research subject. Our major contribution is to scope out papers published on Twitter until the close of 2011. The classification derived here will provide a framework within which researchers studying Twitter related topics will be able to position and ground their work

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The surfactant-like peptide (Ala)6(Arg) is found to self-assemble into 3 nm-thick sheets in aqueous solution. Scanning transmission electron microscopy measurements of mass per unit area indicate a layer structure based on antiparallel dimers. At higher concentration the sheets wrap into unprecedented ultrathin helical ribbon and nanotube architectures.

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A series of amphiphilic copolymers were synthesized by free-radical copolymerization of N-vinylpyrrolidone (NVP) with vinyl propyl ether (VPE), and the structure of the copolymers was characterized by elemental analysis and gel permeation chromatography. The reactivity of VPE in copolymerization was found to be significantly lower than the reactivity of NVP, which resulted in a decrease of copolymers’ yields and molecular weights with higher content of VPE in the feed mixture. An investigation of the behavior of the copolymers in aqueous solutions at different temperatures by dynamic light scattering revealed the presence of lower critical solution temperature, which depending on the content of VPE ranged within 23−38 °C. Aqueous solutions of these copolymers were studied by fluorescent spectroscopy with pyrene as a polarity probe to reveal the formation of hydrophobic domains. The copolymers were found to be useful for enhancing the solubility of riboflavin in water.

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As a continuing effort to establish the structure-activity relationships (SARs) within the series of the angiotensin II antagonists (sartans), a pharmacophoric model was built by using novel TOPP 3D descriptors. Statistical values were satisfactory (PC4: r(2)=0.96, q(2) ((5) (random) (groups))=0.84; SDEP=0.26) and encouraged the synthesis and consequent biological evaluation of a series of new pyrrolidine derivatives. SAR together with a combined 3D quantitative SAR and high-throughput virtual screening showed that the newly synthesized 1-acyl-N-(biphenyl-4-ylmethyl)pyrrolidine-2-carboxamides may represent an interesting starting point for the design of new antihypertensive agents. In particular, biological tests performed on CHO-hAT(1) cells stably expressing the human AT(1) receptor showed that the length of the acyl chain is crucial for the receptor interaction and that the valeric chain is the optimal one.

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A very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model robustness and adequacy. The derived model parameters are estimated via forward orthogonal least squares, but the model subset selection cost function includes a D-optimality design criterion that maximizes the determinant of the design matrix of the subset to ensure the model robustness, adequacy, and parsimony of the final model. The proposed approach is based on the forward orthogonal least square (OLS) algorithm, such that new D-optimality-based cost function is constructed based on the orthogonalization process to gain computational advantages and hence to maintain the inherent advantage of computational efficiency associated with the conventional forward OLS approach. Illustrative examples are included to demonstrate the effectiveness of the new approach.

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A very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model adequacy. The derived model parameters are estimated via forward orthogonal least squares, but the subset selection cost function includes an A-optimality design criterion to minimize the variance of the parameter estimates that ensures the adequacy and parsimony of the final model. An illustrative example is included to demonstrate the effectiveness of the new approach.