QSAR quantitative structure activity methods

Besides the aforementioned descriptors, grid-based methods are frequently used in the field of QSAR quantitative structure-activity relationships) [50]. A molecule is placed in a box and for an orthogonal grid of points the interaction energy values between this molecule and another small molecule, such as water, are calculated. The grid map thus obtained characterizes the molecular shape, charge distribution, and hydrophobicity. 

PW91 (Perdew, Wang 1991) a gradient corrected DFT method QCI (quadratic conhguration interaction) a correlated ah initio method QMC (quantum Monte Carlo) an explicitly correlated ah initio method QM/MM a technique in which orbital-based calculations and molecular mechanics calculations are combined into one calculation QSAR (quantitative structure-activity relationship) a technique for computing chemical properties, particularly as applied to biological activity QSPR (quantitative structure-property relationship) a technique for computing chemical properties... 

Several research techniques are commonly used in the field of QSAR (quantitative structure-activity relationship). Nevertheless, this research area is constantly on the search to develop better, faster, or different methods. In this section, we intend to point out some ongoing research efforts that are exploring unique pathways with the same goal of better understanding the metabolism process of CYPs. 

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. 

It is not yet possible to design a molecule with specific odor (or taste) characteristics because the relations between sensory properties of flavor compounds and their molecular properties are not well understood. As a consequence, the development of compounds with desired flavor qualities has had to rely on relatively tedious synthetic approaches. Recent advances, however, in computer-based methods developed by the pharmaceutical industry to study QSAR (quantitative structure-activity relationships) may ultimately be helpful in the rational design of new flavor-structures with predictable sensory attributes. Results from QSAR studies may also provide insight into the mechanism of the molecule-receptor interaction. 

Quantitative Structure—Activity Relationships (QSAR). Quantitative Structure—Activity Relationships (QSAR) is the name given to a broad spectmm of modeling methods which attempt to relate the biological activities of molecules to specific structural features, and do so in a quantitative manner (see Enzyme inhibitors). The method has been extensively applied. The concepts involved in QSAR studies and a brief overview of the... 

Attempts to quantitatively relate chemical structure to biological action were first initiated in the 19th century, but it was not until the 1960s that Hansch and Fujita devised a method that successfully incorporated quantitative measurements into SAR determinations (see section 4.4). The technique is referred to as QSAR (quantitative structure-activity relationships). One of its most successful uses has been in the development in the 1970s of the antiulcer agents cimetidine and ranitidine. Both SARs and QSARs are important parts of the foundations of medicinal chemistry. 

The epoch of QSAR (Quantitative Structure-Activity Relationships) studies began in 1963-1964 with two seminal approaches the a-p-7i analysis of Hansch and Fujita " and the Free-Wilson method. The former approach involves three types of descriptors related to electronic, steric and hydrophobic characteristics of substituents, whereas the latter considers the substituents themselves as descriptors. Both approaches are confined to strictly congeneric series of compounds. The Free Wilson method additionally requires all types of substituents to be suflficiently present in the training set. A combination of these two approaches has led to QSAR models involving indicator variables, which indicate the presence of some structural fragments in molecules. 

Because of fhe stereospecifity of biological effects, QSAR (quantitative structure-activity relationships) methods must be capable of taking into account atomic chiralities. Indeed, one of fhe most popular 3D-QSAR methods, CoMFA and other CoMFA-like methods take into account chirality by default, since fhe molecular fields of chiral isomers are different If compounds are highly flexible and no experimental structural information about fhe receptor-ligand complexes is available, CoMFA (and CoMFA-like) methods are not always applicable. Several shortcomings and problems have motivated researchers to consider improvements to these techniques. The first idea for improvement was to modify the conventional 2D descriptors to make them chirahty-sensitive [1]. 

QSAR - Quantitative Structure-Activity (or Property) Relation RHF - Restricted Hartree Fock SCF - Self-Consistent Field Method STO - Slater-type Orbital... 

Furthermore the odorivectors could be treated the same way, with the same methods, as drug molecules are in QSAR (Quantitative Structure Activity Correlation). A computerized approach to biochemical quantitative structure-activity-correlations was introduced by the HANSCH APPROACH (ll). Definition of all the essential profiles, those capable of being expressed in monoosmatic components, would afford the foundation on which an algorithm for the calculation of odor quality based on the chemical structure of the odorivector conceivably could be designed. 

The WAR package supplements the DIPPR (Design Institute for Physical Property Research) Database of 1,685 chemicals with eight categories of human health and environmental impact data. Data not available for chemicals in this DIPPR database were estimated using molecular methods, such as QSAR (Quantitative Structural Activity Relationships). In order to consider each risk category, the potential environmental impact (Ti ) for a chemical can be determined by summing the specific environmental impacts of chemical ... 

The study of structure-reactivity relationships by the organic chemist Hammett showed that there is often a quantitative relationship between the two-dimensional structure of organic molecules and their chemical reactivity. Specifically, he correlated the changes in chemical properties of a molecule that result from a small change in its chemical structure that is, the quantitative linear relationship between electron density at a certain part of a molecule and its tendency to undergo reactions of various types at that site. For example, there is a linear relationship between the effea of remote substituents on the equilibrium constant for the ionization of an acid with the effect of these substituents on the rate or equilibrium constant for many other types of chemical reaction. The relative value of Hammett substituent constants describes the similarity of molecules in terms of electronic properties. Taft expanded the method to include the steric hindrance of access of reagents to the reaction site by nearby substituents, a quantitation of three-dimensional similarity. In addition, Charton, Verloop, Austel, and others extended and refined these ideas. Finally, Hansch and Fujita showed that biological activity frequently is also quantitatively correlated with the hydrophobic character of the substituents. They coined the term QSAR, Quantitative Structure-Activity Relationships, for this type of analysis. 

Additionally, QSAR (quantitative structure-activity relationship) is used in the optimization process (Seydel et al., 1979 Draber et al., 1992). QSAR represents an attempt to correlate structural or property descriptors of compounds with biological activities. The physicochemical descriptors include parameters to account for hydro-phobicity, topology, electronic properties and steric effects. The method is also used to get informations how to decouple undesired toxic effect from desired biological activity. 

Currently, QSAR (quantitative structure-activity relationship) and SAR (structure-activity relationship) methods are widely used for computational prediction of different toxicity types, such as caidio-, hepato-, renal toxicity, teratogenicity, and carcinogenicity. 

A challenging task in material science as well as in pharmaceutical research is to custom tailor a compound s properties. George S. Hammond stated that the most fundamental and lasting objective of synthesis is not production of new compounds, but production of properties (Norris Award Lecture, 1968). The molecular structure of an organic or inorganic compound determines its properties. Nevertheless, methods for the direct prediction of a compound s properties based on its molecular structure are usually not available (Figure 8-1). Therefore, the establishment of Quantitative Structure-Property Relationships (QSPRs) and Quantitative Structure-Activity Relationships (QSARs) uses an indirect approach in order to tackle this problem. In the first step, numerical descriptors encoding information about the molecular structure are calculated for a set of compounds. Secondly, statistical and artificial neural network models are used to predict the property or activity of interest based on these descriptors or a suitable subset. 

Dudek, A. Z., Arodz, T., Galvez, J. Gomputational methods in developing quantitative structure-activity relationships (QSAR) a review. Comb. Chem. High-Throughput Screen. 2006, 9, 213-228. 

Certain computational methodologies such as some approaches to quantitative structure-activity relationship (QSAR) studies use 3D ligand structures [37, 38]. These methods generally assume that a bioactive conformation has been estab-Hshed for a set of molecules and that these conformers can be ahgned in a maimer that reflects the relative orientation they would adopt in a binding site. It is thus... 

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