Noncanonical G protein activation and inactivation, particularly for the Gαi/s protein subfamilies, have long been a focus of chemical research. Combinatorial libraries were already effectively applied to identify modulators of the guanine-nucleotide exchange, as can be exemplified with peptides such as KB-752 and GPM-1c/d, the so-called guanine-nucleotide exchange modulators. In this study, we identified novel bicyclic peptides from a combinatorial library screening that show prominent properties as molecular switch-on/off modulators of Gαi signaling. Among the series of hits, the exceptional paradigm of GPM-3, a protein and state-specific bicyclic peptide, is the first chemically identified GAP (GTPase-activating protein) modulator with a high binding affinity for Gαi protein. Computational analyses identified and assessed the structure of the bicyclic peptides, novel ligand–protein interaction sites, and their subsequent impact on the nucleotide binding site. This approach can therefore lead the way for the development of efficient chemical biological probes targeting Gαi protein modulation within a cellular context.
This paper describes how the genetic algorithms (GAs) can be efficiently used to fuzzy goal programming (FGP) formulation of optimal power flow problems having multiple objectives. In the proposed approach, the different constraints, various relationships of optimal power flow calculations are fuzzily described.In the model formulation of the problem, the membership functions of the defined fuzzy goals are characterized first for measuring the degree of achievement of the aspiration levels of the goals specified in the decision making context. Then, the achievement function for minimizing the regret for under‐deviations from the highest membership value (unity) of the defined membership goals to the extent possible on the basis of priorities is constructed for optimal power flow problems.In the solution process, the GA method is employed to the FGP formulation of the problem for achievement of the highest membership value (unity) of the defined membership functions to the extent possible in the decision making environment. In the GA based solution search process, the conventional Roulette wheel selection scheme, arithmetic crossover and random mutation are taken into consideration to reach a satisfactory decision.The developed method has been tested on IEEE 6‐generator 30‐bus System. Numerical results show that this method is promising for handling uncertain constraints in practical power systems.
Quality of machined parts mainly depends on the manufacturing process. Fixtures are used to hold the workpiece during machining and a typical machining fixture consists of locators and clamps. In a typical machining process the workpiece is first made to contact all the locators by applying clamping forces and then the machining forces are applied. Due to these forces, the workpiece fixture contact point is elastically deformed and the workpiece position is altered. This rigid body motion results in workpiece positional error, which, in turn causes machining error. Contact deformation and workpiece positional error depends on the reaction forces developed at the contact points. The reaction forces largely depend on the contact friction at these points and hence the effect of the same has to be investigated. The objective of this paper is to study the effect of contact friction on contact forces and final machining error of the workpiece. Results show that the contact friction has a definite influence on the machining error of the workpiece. The influence however depends on the cutting conditions and the fixture layout.
Two‐phase gas‐liquid flow through curved pipes is much more complex in nature than straight pipes due to the existence of secondary flow and phase separation. Experimental investigations have been carried out to evaluate the holdup for gas‐non‐Newtonian liquid flow through the helical coils in horizontal orientation. In ANN prediction Multilayer Perceptron (MLP) with backpropagation algorithm and four different conventional transfer functions in the hidden layer is used. The ANN prediction agrees well with the experimental data.
In the present paper an attempt has been made to place the distributed generation at an optimal location so as to improve the technical as well as economical performance. Among technical issues the sag performance and the loss have been considered. Genetic algorithm method has been used as the optimization technique in this problem. For sag analysis the impact of 3‐phase symmetrical short circuit faults is considered. Total load disturbed during the faults is considered as an indicator of sag performance. The solution algorithm is demonstrated on a 34 bus radial distribution system with some lateral branches. For simplicity only one DG of predefined capacity is considered. MATLAB has been used as the programming environment.
Cancer is one of the most complicated and prevalent diseases in the world, and its incidence is growing worldwide. Natural products containing pharmacological activity are widely used in the pharmaceutical industry, especially in anticancer drugs, due to their diverse structures and distinctive functional groups that inspire new drug results by means of synthetic chemistry. Terrestrial medicinal plants have traditionally been the primary source for developing natural products (NPs). However, over the past thirty years, marine organisms such as invertebrates, plants, algae, and bacteria have revealed many new pharmaceutical compounds known as marine NPs. This field constantly evolves as a discipline in molecular targeted drug discovery, incorporating advanced screening tools that have revolutionised and become integral to modern antitumor research. This review discusses recent studies on new natural anticancer alkaloids obtained from marine organisms. The paper illustrates the structure and origin of marine alkaloids and demonstrates the cytotoxic action of new alkaloids from several structural families and their synthetic analogs. The most recent findings about the potential or development of some of them as novel medications, together with the status of our understanding of their current mechanisms of action, are also compiled.
This paper proposes a Satisfiability Modulo Theory based formulation for floorplanning in VLSI circuits. The proposed approach allows a number of fixed blocks to be placed within a layout region without overlapping and at the same time minimizing the area of the layout region. The proposed approach is extended to allow a number of fixed blocks with ability to rotate and flexible blocks (with variable width and height) to be placed within a layout without overlap. Our target in all cases is reduction in area occupied on a chip which is of vital importance in obtaining a good circuit design. Satisfiability Modulo Theory combines the problem of Boolean satisfiability with domains such as convex optimization. Satisfiability Modulo Theory provides a richer modeling language than is possible with pure Boolean SAT formulas. We have conducted our experiments on MCNC and GSRC benchmark circuits to calculate the total area occupied, amount of deadspace and the total CPU time consumed while placing the blocks without overlapping. The results obtained shows clearly that the amount of dead space or wasted space is reduced if rotation is applied to the blocks.
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