QSPR quantitative structure-property


Two approaches to quantify/fQ, i.e., to establish a quantitative relationship between the structural features of a compoimd and its properties, are described in this section quantitative structure-property relationships (QSPR) and linear free energy relationships (LFER) cf. Section 3.4.2.2). The LFER approach is important for historical reasons because it contributed the first attempt to predict the property of a compound from an analysis of its structure. LFERs can be established only for congeneric series of compounds, i.e., sets of compounds that share the same skeleton and only have variations in the substituents attached to this skeleton. As examples of a QSPR approach, currently available methods for the prediction of the octanol/water partition coefficient, log P, and of aqueous solubility, log S, of organic compoimds are described in Section 10.1.4 and Section 10.15, respectively.  [c.488]

Quantitative Structure-Property Relationships (QSPR)  [c.489]

Quantitative structure property relationships (QSPR) and, when applied to biological activity, quantitative structure activity relationships (QSAR) are methods for determining properties due to very sophisticated mechanisms purely by a curve ht of that property to aspects of the molecular structure. This allows a property to be predicted independent of having a complete knowledge of its origin. For example, drug activity can be predicted without knowing the nature of the binding site for that drug. QSPR is covered in more detail in Chapter 30.  [c.108]

When the property being described is a physical property, such as the boiling point, this is referred to as a quantitative structure-property relationship (QSPR). When the property being described is a type of biological activity, such as drug activity, this is referred to as a quantitative structure-activity relationship (QSAR). Our discussion will first address QSPR. All the points covered in the QSPR section are also applicable to QSAR, which is discussed next.  [c.243]

QSPR See Quantitative structure-property relationship.  [c.834]

Quantitative structure-property relationship (QSPR)  [c.834]

This is the domain of establishing Structure-Property or Structure-Activity Relationships (SPR or SAR), or even of finding such relationships in a quantitative manner (QSPR or QSAR).  [c.3]

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.  [c.390]

Furthermore, QSPR models for the prediction of free-energy based properties that are based on multilinear regression analysis are often referred to as LFER models, especially, in the wide field of quantitative structure-activity relationships (QSAR).  [c.489]

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  [c.367]

The abbreviation QSAR stands for quantitative structure-activity relationships. QSPR means quantitative structure-property relationships. As the properties of an organic compound usually cannot be predicted directly from its molecular structure, an indirect approach Is used to overcome this problem. In the first step numerical descriptors encoding information about the molecular structure are calculated for a set of compounds. Secondly, statistical methods and artificial neural network models are used to predict the property or activity of interest, based on these descriptors or a suitable subset. A typical QSAR/QSPR study comprises the following steps structure entry or start from an existing structure database), descriptor calculation, descriptor selection, model building, model validation.  [c.432]

To characterize the complete arrangement of atoms in a molecule, the entire molecule can be regarded as a connectivity graph where the edges represent the bonds and the nodes represent the atoms. By adding the number of bonds or the sum of bond lengths between aU pairs of atoms, it is possible to calculate a descriptor that defines the constitution of a molecule independently of conformational changes. The resulting descriptor is not restricted regarding the number of atoms. Clerc and Terkovics [8] used this method based on the number of bonds for the investigation of quantitative structure-property relationships (QSPR).  [c.516]

Applications of neural networks are becoming more diverse in chemistry [31-40]. Some typical applications include predicting chemical reactivity, acid strength in oxides, protein structure determination, quantitative structure property relationship (QSPR), fluid property relationships, classification of molecular spectra, group contribution, spectroscopy analysis, etc. The results reported in these areas are very encouraging and are demonstrative of the wide spectrum of applications and interest in this area.  [c.10]

A quantitative structure-activity relationship (QSAR) relates numerical properties of tl molecular structure to its activity by a mathematical model. The term quantitative stru ture-property relationship (QSPR) is also used, particularly when some property oth( than biological activity is concerned. In drug design, QSAR methods have often bee used to consider qualities beyond in vitro potency. The most potent enzyme inhibitor is ( little use as a drug if it cannot reach its target. The in vivo activity of a molecule is often composite of many factors. A structure-activity study can help to decide which featurt of a molecule give rise to its overall activity and help to make modihed compounds wil enhanced properties. The relationship between these numerical properties and the activil is often described by an equation of the general form  [c.711]


See pages that mention the term QSPR quantitative structure-property : [c.208]   
Molecular modelling Principles and applications (2001) -- [ c.0 ]