Quantitative structure-activity parameters used

The CHI index is reportedly a relevant parameter in quantitative structure-activity relationship (QSAR) studies [41]. With this approach, log P could be determined in the range -0.45more than 25000 compounds with excellent reproducibility (within 2 index units) and reported in a GlaxoSmithKline database [11]. Two main drawbacks were identified using this approach (i) the assumptions used in Ref [7], i.e. that S is constant for all compounds and that the system dwell volume is excluded in calculations, yield some discrepancies in the resulting log P, and (ii) the set of gradient calibration... 

Thiadiazole 1 and its derivatives were used as model compounds for the calculation of molecular parameters related to physical properties for their use in quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) studies <1999EJM41, 2003IJB2583, 2005JMT27>. 

For both nonspecific and structure-based approaches, physicochemical solvation parameters may be used directly, or they may be embedded in quantitative structure-activity relationships.3 This chapter starts with a review of the thermodynamic equations that may be used for a quantitative description of the free energy of solutes in fluid media. Then it provides an... 

As the chemical models mentioned here refer to some fundamental thermochemical and electronic effects of molecules, their application is not restricted to the prediction of chemical reactivity data. In fact, in the development of the models extensive comparisons were made with physical data, and thus such data can also be predicted from our models. Furthermore, some of the mechanisms responsible for binding substrates to receptors are naturally enough founded on quite similar electronic effects to those responsible for chemical reactivity. This suggest the use of the models developed here to calculate parameters for quantitative structure-activity relationships (QSAR). 

The observed differences create a basis for a rational selection of building blocks for synthesis of combinatorial libraries enriched in target-specific motifs. The quantitative structure-activity discrimination function found at this stage of our study can be used for effective search of reactive monomers possessing the desired physicochemical and spatial parameters. 

To overcome this weakness, we are developing a quantitative structure-activity strategy that is conceptually applicable to all chemicals. To be applicable, at least three criteria are necessary. First, we must be able to calculate the descriptors or Independent variables directly from the chemical structure and, presumably, at a reasonable cost. Second, the ability to calculate the variables should be possible for any chemical. Finally, and most importantly, the variables must be related to a parameter of Interest so that the variables can be used to predict or classify the activity or behavior of the chemical (j ) One important area of research is the development of new variables or descriptors that quantitatively describe the structure of a chemical. The development of these indices has progressed into the mathematical areas of graph theory and topology and a large number of potentially valuable molecular descriptors have been described (7-9). Our objective is not concerned with the development of new descriptors, but alternatively to explore the potential applications of a group of descriptors known as molecular connectivity indices (10). 

Use of STERIMOL, MTD, and MTD Steric Parameters in Quantitative Structure-Activity Relationships... 

Odor and taste quality can be mapped by multidimensional scaling (MDS) techniques. Physicochemical parameters can be related to these maps by a variety of mathematical methods including multiple regression, canonical correlation, and partial least squares. These approaches to studying QSAR (quantitative structure-activity relationships) in the chemical senses, along with procedures developed by the pharmaceutical industry, may ultimately be useful in designing flavor compounds by computer. 

Fugate, H.N. 1989. Using total molecular surface area in quantitative structure activity relationships to estimate environmental fate and transport parameters. Master s thesis, Utah State University, Logan, UT. 

Structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs), referred to collectively as QSARs, can be used for the prediction of physicochemical properties, environmental fate parameters (e.g., accumulation and biodegradation), human health effects, and ecotoxicological effects. A SAR is a (qualitative) association between a chemical substructure and the potential of a chemical containing the substructure to exhibit a certain physical or biological effect. A QS AR is a mathematical model that relates a quantitative measure of chemical structure (e.g., a physicochemical property) to a physical property or to a biological effect (e.g., a toxicological endpoint). 

Sanghvi, T., Ni, N., Mayersohn, M., and Yalkowsky, S., Predicting passive intestinal absorption using a single parameter, Quantitative Structure Activity Relationships and Combinatorial Science, Vol. 22, No. 2, 2003, pp. 247-257. 

Linear and non-linear correlations of structural parameters and strain energies with various molecular properties have been used for the design of new compounds with specific properties and for the interpretation of structures, spectra and stabilities 661. Quantitative structure-activity relationships (QSAR) have been used in drug design for over 30 years 2881 and extensions that include information on electronic features as a third dimension (the electron topological approach, ET) have been developed and tested 481 (see Section 2.3.5). Correlations that are used in the areas of electron transfer, ligand field properties, IR, NMR and EPR spectroscopy are discussed in various other Chapters. Here, we will concentrate on quantitative structure-property relationships (QSPR) that involve complex stabilities 124 289-2911. 

Hudson BD, Hyde RM, Rahr E et at. (1996) Parameter based methods for compound selection from chemical databases. Quant Struct-Act Relat 15 285-289 Matter H, Schwab W, Barbier D et al. (1999) Quantitative structure-activity relationship of human neutrophil col-lagenase (MMP-8) inhibitors using comparative molecular field and X-ray structure analysis. J Med Chem 42 1908-1920... 

QSAR Quantitative structure-activity relationship. Quantitative structure-bio-logical activity model derived using regression analysis and containing as parameters physical-chemical constants, indicator variables, or theoretically calculated values. 

We chose 60 compounds with pl50 values ranging from 7.1 to 4.9 and subjected them to regression analysis using several physicochemical parameters (Table I). The 60 compounds contained variations in six positions of the basic structure. Quantitative structure-activity correlations with as many individual uncouplers in one equation have not yet been published. As far as we know, the Hansch approach has been applied to uncouplers of oxidative phosphorylation only twice first in 1965 by Hansch and co-workers to phenols and recently by Muraoka and Terada to N-phenylanthranilic acids. From Muraoka s data we recalculated the correlation with w and o- and obtained an equation which gave the best fit (last equation, Figure 3). 

---