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Chemical functionality descriptors

Martin et al. typically use about 18 substituent properties lipophilicity, about five shape descriptors, about seven chemical functionality descriptors, and about five receptor interaction descriptors. These properties were selected because they are readily calculated for virtually any chemical fragment, while still capturing many of the important efifeas mentioned above. [Pg.79]

Chemical functionality descriptors were developed to create a set of... [Pg.79]

The first three descriptors have been plotted for 27 amines that have similar values in the remaining two dimensions. Carboxylic acids form a tight cluster near, but separate from, the esters. Alcohols are farther away from the acids, and amines are even farther. Aliphatics are widely separated from aromatics. The formation of these clusters is typical and is what justifies calling these dimensions chemical functionality descriptors. ... [Pg.81]

Figure 4 Flower plot of tyramine. There Is one petal for each of the five chemical functionality descriptors, five shape descriptors, five receptor recognition descriptors, and the computed log P... Figure 4 Flower plot of tyramine. There Is one petal for each of the five chemical functionality descriptors, five shape descriptors, five receptor recognition descriptors, and the computed log P...
The HF results generated for representative polyatomic molecules have used the /V-derivatives estimated by finite differences, while the -derivatives have been calculated analytically, by standard methods of quantum chemistry. We have examined the effects of the electronic and nuclear relaxations on specific charge sensitivities used in the theory of chemical reactivity, e.g., the hardness, softness, and Fukui function descriptors. New concepts of the GFFs and related softnesses, which include the effects of molecular electronic and/or nuclear relaxations, have also been introduced. [Pg.475]

Chemometrics can be employed to develop a mathematical relationship between chemical property descriptors (e.g. bond lengths, polarity, steric properties, reactivities, functionalities) and biological functions, via a computational model such as principal components analysis. The question asked is whether it is really necessary to test all... [Pg.17]

This consideration emphasizes the analogy between pharmacophore identification and variable selection QSAR. On the basis of this analogy, we now expand the notion of chemical pharmacophoreto that of the more general descriptor pharmacophore. We shall define descriptor pharmacophore as a special subset of molecular descriptors (of any nature, not only chemical functional groups) optimized in the process of variable selection QSAR, to achieve the most significant correlation between descriptor values and biological activity. [Pg.61]

Several different kinds of quantum-chemical descriptors have been defined, and these can be broadly divided into energy-based descriptors, local quantum-chemical properties, descriptors based on the Density Functional Theory, molecular orbital energies, superdelocalizability indices, frontier orbital electron densities, and polarizabilities [Cartier and Rivail, 1987 Bergmann and Hinze, 1996 Karelson et al, 1996]. [Pg.354]

Once a decision of the chemical functionality or host structure is made and a sensing film is included in a sensor device, the next goal would be to model the sensor response of the film in the device. Sensor response to an analyte is a complex function of the partitioning of the target analytes based on the interactions within the film as well as the transport properties of the analyte in the sensor. The sensor responses for polymer-based sensors have been modeled by various approaches using (1) first principles techniques such as Hansen solubilities, (2) multivariate techniques such as QSAR to correlate sensor response with molecular descriptors, and (3) simulations and empirical formulations used to calculate the partition coefficient, such as linear solvation energy relationships, to provide a measure of selectivity and sensitivity of the material under consideration. [Pg.475]

Gatti C (2012) The source function descriptor as a tool to extract chemical information from theoretical and experimental electron densities. Struct Bond 147 193-286... [Pg.125]


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See also in sourсe #XX -- [ Pg.79 , Pg.81 , Pg.82 , Pg.87 , Pg.95 ]




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