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Quantitative structure-property energy descriptors

Because of the large number of chemicals of actual and potential concern, the difficulties and cost of experimental determinations, and scientific interest in elucidating the fundamental molecular determinants of physical-chemical properties, considerable effort has been devoted to generating quantitative structure-property relationships (QSPRs). This concept of structure-property relationships or structure-activity relationships (QSARs) is based on observations of linear free-energy relationships, and usually takes the form of a plot or regression of the property of interest as a function of an appropriate molecular descriptor which can be calculated using only a knowledge of molecular structure or a readily accessible molecular property. [Pg.14]

The structure of a chemical is responsible for the presence and magnitude of its properties. The properties can be energy levels and their derivatives, as well as physicochemical, or biological, properties. To avoid discrimination between the different properties (which are the subject of detailed consideration in Chapters 3, 4, and 6) in the context of quantitative relationships between structural descriptors (i.e., topological indices [TIs]) and various properties, we will use the broader abbreviation QSPR (Quantitative Structure-Property Relationship). [Pg.74]

Recently, Riviere and Brooks (2007) published a method to improve the prediction of dermal absorption of compounds dosed in complex chemical mixtures. The method predicts dermal absorption or penetration of topically applied compounds by developing quantitative structure-property relationship (QSPR) models based on linear free energy relations (LFERs). The QSPR equations are used to describe individual compound penetration based on the molecular descriptors for the compound, and these are modified by a mixture factor (MF), which accounts for the physical-chemical properties of the vehicle and mixture components. Principal components analysis is used to calculate the MF based on percentage composition of the vehicle and mixture components and physical-chemical properties. [Pg.203]

All the techniques described above can be used to calculate molecular structures and energies. Which other properties are important for chemoinformatics Most applications have used semi-empirical theory to calculate properties or descriptors, but ab-initio and DFT are equally applicable. In the following, we describe some typical properties and descriptors that have been used in quantitative structure-activity (QSAR) and structure-property (QSPR) relationships. [Pg.390]

Methods other than thermodynamic cycles are often used to calculate acid dissociation constants. Previous publications implement the theoretical relationship between pKa and structural property [6], bond valence methods and bond lengths [33], pKa correlations with highest occupied molecular orbital (HOMO) energies and frontier molecular orbitals [34], and artificial neural networks [35] to predict pKa values. In addition much work has been done using physical properties as quantitative structure-activity relationship (QSAR) descriptors, and regression equations with such descriptors to yield accurate pKa values for specific classes of molecules [36-47]. The correlation of pKas to various molecular properties, however, is often restricted to specific classes of compounds, and it is... [Pg.120]

Calculated molecular properties from 3D molecular fields of interaction energies are a novel approach to correlate 3D molecular structures with pharmacodynamic, pharmacokinetic and physico-chemical properties. The novel VolSurf descriptors quantitatively characterize size, shape, polarity, hydrophobicity and the balance between them. [Pg.418]


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Energy descriptors

Energy properties

Energy structure

Property quantitative

Structural descriptors

Structure descriptor

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