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Interaction pattern

The interaction pattern is exactly the same for ethane. Instead of constructing a pair of [Pg.14]

In the recent past much ejperimental and theoretical effort has been undertaken to understand the microsoopic steps of heterogeneous surface reactions. Ihe main problem oonsists of evaluating the total energy of the reacting coponents (including tiie surface atoms ) as a function of all nuclear coordinates at any reaction time. The solution of this problem is extremely difficult. Detailed studies with model systems, however, can shed same light ipon the various steps of the interaction pattern. [Pg.222]

Fig. 1.9 Bidimensional representation of the interaction pattern between carnosinase and its substrate carnosine. The model shows how the enzyme recognizes (binds) the ammonium group, the carboxylate group and... Fig. 1.9 Bidimensional representation of the interaction pattern between carnosinase and its substrate carnosine. The model shows how the enzyme recognizes (binds) the ammonium group, the carboxylate group and...
Fig. 10= Comparison of the antiaromatic region (i.e., the in-plane n-n interaction pattern at 3 A C1-C6 distance) with the antiaromatic TS of the [2S + 2J cycloaddition. Fig. 10= Comparison of the antiaromatic region (i.e., the in-plane n-n interaction pattern at 3 A C1-C6 distance) with the antiaromatic TS of the [2S + 2J cycloaddition.
Many of the collaborations will follow stereotypical interaction patterns e.g. an interaction which consists of log in, conduct some transactions, and log out or make a selection, and then operate on that selection. These can be abstracted as frameworks (Chapter 9, Model Frameworks and Template Packages (p.371)), then applied and composed to define the system context collaboration... [Pg.612]

Once the protein interaction pattern is translated from Cartesian coordinates into distances from the reactive center of the enzyme and the structure of the ligand has been described with similar fingerprints, both sets of descriptors can be compared [25]. The hydrophobic complementarity, the complementarity of charges and H-bonds for the protein and the substrates are all computed using Carbo similarity indices [26]. The prediction of the site of metabolism (either in CYP or in UGT) is based on the hypothesis that the distance between the reactive center on the protein (iron atom in the heme group or the phosphorous atom in UDP) and the interaction points in the protein cavity (GRID-MIF) should correlate to the distance between the reactive center of the molecule (i.e. positions of hydrogen atoms and heteroatoms) and the position of the different atom types in the molecule [27]. [Pg.284]

Fig. 12. Two through bond orbital interaction patterns. In (a) a dominant ng—ag interaction leads to an A, S order. In (b) a dominant ng— jru interaction leads to the opposite order... Fig. 12. Two through bond orbital interaction patterns. In (a) a dominant ng—ag interaction leads to an A, S order. In (b) a dominant ng— jru interaction leads to the opposite order...
The above discussion is not only appropriate to 1,2-difluoroethylene and 2-butene but to other systems as well. Indeed, the sigma orbital interaction patterns discussed above obtain in diverse molecules. These and other patterns, as well as the types of molecular systems to which they apply, are pictured in Scheme 1. [Pg.40]

The study of stressful life events is a nice example of the type of variable studied in the second domain of environmental measures mentioned previously. Psychologists have for years studied the influences of a wide variety of life events, family interaction patterns, etc., under the hypothesis that they were proximal causal variables with regard to a variety of psychological outcomes. The now discredited hypothesis of the refrigerator mother is a classic example. [Pg.135]

The interactions of depressed persons with others play an important role in the etiology of depression. According to Coyne (1976) depressed persons elicit support behaviors intermixed with rejection from others. Brown (1994) found that depression chronicity is related to a lack of social support. We investigated whether observable behaviors (which may reflect support-seeking and giving) in an interaction of depressed patients and others (i.e., partner and stranger) (1) predict depression outcome and (2) discriminate between patient and others interactional patterns. [Pg.203]

Another retrospective analysis of already known H DAC inhibitors was carried out by You et al. [68]. They generated a 3D chemical-feature-based pharmacophore model and compared the ligand-based model with the structural-functional requirements for the binding of the HDAC inhibitors. Using this model, the interactions between the benzamide MS-275 and HDAC were explored. The result showed that the type and spatial location of chemical features encoded in the pharmacophore are in full agreement with the enzyme-inhibitor interaction pattern identified from molecular docking. However, also in this study no experimental validation of the modeling results was provided. [Pg.66]

This study also suggests that molecular size and structure play a role in this interaction. The binding behaviors of dextrin oligomers for four different pharmaceuticals (ibuprofen, ketoprofen, furosemide, and warfarin) were observed under the same experimental conditions. Ibuprofen and ketoprofen, two compounds that are similar in chemical structure and pharmaceutical use, showed obvious differences in interaction patterns (Fig. 13A and B). Ketoprofen, having an extra aromatic ring, required an octa-saccharide (DP = 8) for binding, whereas ibuprofen required a heptasac-... [Pg.305]

This chapter aims to summarize our efforts to investigate the effects of fluorinated amino acid substitutes on the interactions with natural protein environments. In addition to a rather specific example concerning the interactions of small peptides with a proteolytic enzyme, we present a simple polypeptide model that aids for a systematic investigation of the interaction pattern of amino acids that differ in side chain length as well as fluorine content within both a hydrophobic and hydrophilic protein environment. Amino acid side chain fluoiination highly affects polypeptide folding due to steric effects, polarization, and fluorous interactions. [Pg.739]

The appearance in the previous section of the 4 + 2 and 4r formulas brings to mind the criteria for aromatic and antiaromatic systems discussed in Chapter 1. Furthermore, the HOMO-LUMO interaction patterns discussed in Section 11.2 are reminiscent of those used in Section 10.4 to analyze aromatic stabilization. In this section, we trace the connection between aromaticity and pericyclic reactions, and show how it leads to a third approach to the pericyclic theory. [Pg.602]


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