975 resultados para Constrained


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Nature has used the all-alpha-polypeptide backbone of proteins to create a remarkable diversity of folded structures. Sequential patterns of 20 distinct amino adds, which differ only in their side chains, determine the shape and form of proteins. Our understanding of these specific secondary structures is over half a century old and is based primarily on the fundamental elements: the Pauling alpha-helix and beta-sheet. Researchers can also generate structural diversity through the synthesis of polypeptide chains containing homologated (omega) amino acid residues, which contain a variable number of backbone atoms. However, incorporating amino adds with more atoms within the backbone introduces additional torsional freedom into the structure, which can complicate the structural analysis. Fortunately, gabapentin (Gpn), a readily available bulk drug, is an achiral beta,beta-disubstituted gamma amino add residue that contains a cyclohexyl ring at the C-beta carbon atom, which dramatically limits the range of torsion angles that can be obtained about the flanking C-C bonds. Limiting conformational flexibility also has the desirable effect of increasing peptide crystallinity, which permits unambiguous structural characterization by X-ray diffraction methods. This Account describes studies carried out in our laboratory that establish Gpn as a valuable residue in the design of specifically folded hybrid peptide structures. The insertion of additional atoms into polypeptide backbones facilitates the formation of intramolecular hydrogen bonds whose directionality is opposite to that observed in canonical alpha-peptide helices. If hybrid structures mimic proteins and biologically active peptides, the proteolytic stability conferred by unusual backbones can be a major advantage in the area of medicinal chemistry. We have demonstrated a variety of internally hydrogen-bonded structures in the solid state for Gpn-containing peptides, including the characterization of the C-7 and C-9 hydrogen bonds, which can lead to ribbons in homo-oligomeric sequences. In hybrid alpha gamma sequences, district C-12 hydrogen-bonded turn structures support formation of peptide helices and hairpins in longer sequences. Some peptides that include the Gpn residue have hydrogen-bond directionality that matches alpha-peptide helices, while others have the opposite directionality. We expect that expansion of the polypeptide backbone will lead to new classes of foldamer structures, which are thus far unknown to the world of alpha-polypeptides. The diversity of internally hydrogen-bonded structures observed in hybrid sequences containing Gpn shows promise for the rational design of novel peptide structures incorporating hybrid backbones.

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The crystal structures of three conformationally locked esters, namely the centrosymmetric tetrabenzoate of all-axial per-hydronaphthalene- 2,3,4a, 6,7,8a-hexaol, viz. trans-4a, 8a-dihydroxyperhydronaphthalene-2,3,6,7-tetrayl tetrabenzoate, C38H34O10, and the diacetate and dibenzoate of all-axial perhydronaphthalene-2,3,4a, 8a-tetraol, viz. (2R*,3R*,4aS*,8aS*)-4a, 8a-dihydroxyperhydronaphthalene-2,3-diyl diacetate, C-14-H22O6, and (2R*, 3R*, 4aS*, 8aS*)-4a, 8a-dihydroxyperhydronaphthalene- 2,3-diyl dibenzoate, C24H26O6, have been analyzed in order to examine the preference of their supramolecular assemblies towards competing inter-and intramolecular O-H center dot center dot center dot O hydrogen bonds. It was anticipated that the supramolecular assembly of the esters under study would adopt two principal hydrogen-bonding modes, namely one that employs intermolecular O-H center dot center dot center dot O hydrogen bonds (mode 1) and another that sacrifices those for intramolecular O-H center dot center dot center dot O hydrogen bonds and settles for a crystal packing dictated by weak intermolecular interactions alone (mode 2). Thus, while the molecular assembly of the two crystalline diacyl derivatives conformed to a combination of hydrogen-bonding modes 1 and 2, the crystal packing in the tetrabenzoate preferred to follow mode 2 exclusively.

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he crystal structure of 12 peptides containing the conformationally constrained 1-(aminomethyl)cyclohexaneacetic acid, gabapentin (Gpn), are reported. In all the 39 Gpn residues conformationally characterized so far, the torsion angles about the C-alpha-C-beta and C-beta-C-gamma bonds are restricted to the gauche conformation (+/- 60 degrees). The Gpn residue is constrained to adopt folded conformations resulting in the formation of intramolecularly hydrogen-bonded structures even in short peptides. The peptides Boc-Ac(6)c-Gpn-OMe 1 and Boc-Gpn-Aib-Gpn-Aib-OMe 2 provide examples of C-7 conformation; peptides Boc-Gpn-Aib-OH 3, Boc-Ac(6)c-Gpn-OH 4, Boc-Val-Pro-Gpn-OH 5, Piv-Pro-Gpn-Val-OMe 6, and Boc-Gpn-Gpn-Leu-OMe 7 provide examples of C-9 conformation; peptide Boc-Ala-Aib-Gpn-Aib-Ala-OMe 8 provides an example of C-12 conformation and peptides Boc-beta Leu-Gpn-Val-OMe 9 and Boc-beta Phe-Gpn-Phe-OMe 10 provide examples of C-13 conformation. Gpn peptides provide examples of backbone expanded mimetics for canonical alpha-peptide turns like the gamma (C-7) and the beta (C-10) turns. The hybrid beta gamma sequences provide an example of a mimetic of the C-13 alpha-turn formed by three contiguous alpha-amino acid residues. Two examples of folded tripeptide structures, Boc-Gpn-beta Phe-Leu-OMe 11 and Boc-Aib-Gpn-beta Phg-NHMe 12, lacking internal hydrogen bonds are also presented. An analysis of available Gpn residue conformations provides the basis for future design of folded hybrid peptides.

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The overall performance of random early detection (RED) routers in the Internet is determined by the settings of their associated parameters. The non-availability of a functional relationship between the RED performance and its parameters makes it difficult to implement optimization techniques directly in order to optimize the RED parameters. In this paper, we formulate a generic optimization framework using a stochastically bounded delay metric to dynamically adapt the RED parameters. The constrained optimization problem thus formulated is solved using traditional nonlinear programming techniques. Here, we implement the barrier and penalty function approaches, respectively. We adopt a second-order nonlinear optimization framework and propose a novel four-timescale stochastic approximation algorithm to estimate the gradient and Hessian of the barrier and penalty objectives and update the RED parameters. A convergence analysis of the proposed algorithm is briefly sketched. We perform simulations to evaluate the performance of our algorithm with both barrier and penalty objectives and compare these with RED and a variant of it in the literature. We observe an improvement in performance using our proposed algorithm over RED, and the above variant of it.

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Polymeric adhesive layers are employed for bonding two components in a wide variety of technological applications, It has been observed that, unlike in metals, the yield behavior of polymers is affected by the state of hydrostatic stress. In this work, the effect of pressure sensitivity of yielding and layer thickness on quasistatic interfacial crack growth in a ductile adhesive layer is investigated. To this end, finite deformation, finite element analyses of a cracked sandwiched layer are carried out under plane strain, small-scale yielding conditions for a wide range of mode mixities. The Drucker-Prager constitutive equations are employed to represent the behavior of the layer. Crack propagation is simulated through a cohesive zone model, in which the interface is assumed to follow a prescribed traction-separation law. The results show that for a given mode mixity, the steady state Fracture toughness [K](ss) is enhanced as the degree of pressure sensitivity increases. Further, for a given level of pressure sensitivity, [K](ss) increases steeply as mode Il loading is approached. (C) 2000 Elsevier Science Ltd. All rights reserved.

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Capacity region for two-user Gaussian Broadcast Channels (GBC) is well known with the optimal input being Gaussian. In this paper we explore the capacity region for GBC when the users' symbols are taken from finite complex alphabets (like M-QAM, M-PSK). When the alphabets for both the users are the same we show that rotation of one of the alphabets enlarges the capacity region. We arrive at an optimal angle of rotation by simulation. The effect of rotation on the capacity region at different SNRs is also studied using simulation results. Using the setup of Fading Broadcast Channel (FBC) given by [Li and Goldsmith, 2001], we study the ergodic capacity region with inputs from finite complex alphabets. It is seen that, using the procedure for optimum power allocation obtained in [Li and Goldsmith, 2001] for Gaussian inputs, to allocate power to symbols from finite complex alphabets, relative rotation between the alphabets does not improve the capacity region. Simulation results for a modified heuristic power allocation procedure for finite-constellation case, show that Constellation Constrained capacity region enlarges with rotation.

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Stability results are given for a class of feedback systems arising from the regulation of time-varying discrete-time systems using optimal infinite-horizon and moving-horizon feedback laws. The class is characterized by joint constraints on the state and the control, a general nonlinear cost function and nonlinear equations of motion possessing two special properties. It is shown that weak conditions on the cost function and the constraints are sufficient to guarantee uniform asymptotic stability of both the optimal infinite-horizon and movinghorizon feedback systems. The infinite-horizon cost associated with the moving-horizon feedback law approaches the optimal infinite-horizon cost as the moving horizon is extended.

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Conformational energy calculations on the model system N-acetyl- 1 -aminocyclohexanecarboxylic acid N'methylamide (Ac-Acc6-NHMe), using an average geometry derived from 13 crystallographic observations, establish that the Acc6 residue is constrained to adopt conformations in the helical regions of In contrast, the a,a-dialkylated residue with linear hydrocarbon side chains, a,a-di-n-propylglycine favors fully extended backbone structures (6 1= $ = 180'). The crystal structures of two model peptides, Boc-(Acc6),-OMe (type 111 @-turn at -Acc6(1)-Acc6(2)-) and Boc-Pro-Acc6-Ala-OMe (type I1 P-turn at -Pro-Acc6-), establish that Acc6 residues can occupy either position of type 111 P-turns and the i + 2 position of type I1 @-turns. The stereochemical rigidity of these peptides is demonstrated in solution by NMR studies, which establish the presence of one intramolecular hydrogen bond in each peptide in CDCI, and (CDJ2S0. Nuclear Overhauser effects permit characterization of the @-turn conformations in solution and establish their similarity to the solid-state structures. The implications for the use of Acc6 residues in conformational design are considered.

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The ability of DNA sequences to adopt unusual structures under the superhelical torsional stress has been studied. Sequences that are forced to adopt unusual conformation in topologically constrained pBR322 form V DNA (Lk=0) were mapped using restriction enzymes as probes. Restriction enzymes such as BamHI, Pstl, Aval and HindIII could not cleave their recognition sequences. The removal of topological constraint relieved this inhibition. The influence of neighbouring sequences on the ability of a given sequence to adopt unusual DNA structure, presumably left handed Z conformation, was studied through single hit analysis. Using multiple cut restriction enzymes such as Narl and Fspl, it could be shown that under identical topological strain, the extent of structural alteration is greatly influenced by the neighbouring sequences. In the light of the variety of sequences and locations that could be mapped to adopt non-6 conformation in pBR322 form V DNA, restriction enzymes appear as potential structural probes for natural DNA sequences.

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The design of folded structures in peptides containing the higher homologues of alpha-amino acid residues requires the restriction of the range of local conformational choices In alpha-amino acids stereochemically constrained residues like alpha,alpha-dialkylated residue, aminoisobutyric acid (Aib), and D-Proline ((D)Pro) have proved extremely useful in the design of helices and hairpins in short peptides Extending this approach, backbone substitution and cyclization are anticipated to bc useful in generating conformationally constrained beta- and gamma-residues This brief review provides a survey of work on hybrid peptide sequences concerning the conformationally constrained gamma-amino acid residue 1-aminomethyl cyclohexane acetic acid, gabapentin (Gpn) This achiral, beta,beta-disubstituted, gamma-residue strongly favors gauche-gauche conformations about the C-alpha-C-beta (0(2)) and C-alpha-C-gamma (0(1)) bonds, facilitating local folding The Gpn residue can adopt both C-7 (NH1 -> CO1) and C-9 (CO1 (I)<- NH1+I) hydrogen bonds which are analogous to the C-5 and C7 (gamma-turn) conformations at alpha-residues In conjunction with adjacent residues, Gpn may be used in ay and gamma alpha segments to generate C-12 hydrogen bonded conformations which may be considered as expanded analogs of conventional beta-turns The structural characterization of C-12 helices, C-12/C-10 helices with mixed hydrogen bond directionalities and beta-hairpins incorporating Gpn residues at the turn segment is illustrated (C) 2010 Wiley Periodicals, Inc Biopolymers (Pept Sci) 94 733-741 2010

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We develop four algorithms for simulation-based optimization under multiple inequality constraints. Both the cost and the constraint functions are considered to be long-run averages of certain state-dependent single-stage functions. We pose the problem in the simulation optimization framework by using the Lagrange multiplier method. Two of our algorithms estimate only the gradient of the Lagrangian, while the other two estimate both the gradient and the Hessian of it. In the process, we also develop various new estimators for the gradient and Hessian. All our algorithms use two simulations each. Two of these algorithms are based on the smoothed functional (SF) technique, while the other two are based on the simultaneous perturbation stochastic approximation (SPSA) method. We prove the convergence of our algorithms and show numerical experiments on a setting involving an open Jackson network. The Newton-based SF algorithm is seen to show the best overall performance.

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We develop in this article the first actor-critic reinforcement learning algorithm with function approximation for a problem of control under multiple inequality constraints. We consider the infinite horizon discounted cost framework in which both the objective and the constraint functions are suitable expected policy-dependent discounted sums of certain sample path functions. We apply the Lagrange multiplier method to handle the inequality constraints. Our algorithm makes use of multi-timescale stochastic approximation and incorporates a temporal difference (TD) critic and an actor that makes a gradient search in the space of policy parameters using efficient simultaneous perturbation stochastic approximation (SPSA) gradient estimates. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal policy. (C) 2010 Elsevier B.V. All rights reserved.

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This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out to be intractable. The key novelty is in employing Bernstein bounding schemes to relax the CCP as a convex second order cone program whose solution is guaranteed to satisfy the probabilistic constraint. Prior to this work, only the Chebyshev based relaxations were exploited in learning algorithms. Bernstein bounds employ richer partial information and hence can be far less conservative than Chebyshev bounds. Due to this efficient modeling of uncertainty, the resulting classifiers achieve higher classification margins and hence better generalization. Methodologies for classifying uncertain test data points and error measures for evaluating classifiers robust to uncertain data are discussed. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle data uncertainty and outperform state-of-the-art in many cases.