Quantitative structure-activity concept

Quantitative Structure—Activity Relationships (QSAR). Quantitative Stmcture—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 stmctural features, and do so in a quantitative manner (see Enzyme INHIBITORS). The method has been extensively appHed. The concepts involved in QSAR studies and a brief overview of the methodology and appHcations are given here. 

There is a continuing effort to extend the long-established concept of quantitative-structure-activity-relationships (QSARs) to quantitative-structure-property relationships (QSPRs) to compute all relevant environmental physical-chemical properties (such as aqueous solubility, vapor pressure, octanol-water partition coefficient, Henry s law constant, bioconcentration factor (BCF), sorption coefficient and environmental reaction rate constants from molecular structure). 

The concept of the similarity of molecules has important ramifications for physical, chemical, and biological systems. Grunwald (7) has recently pointed out the constraints of molecular similarity on linear free energy relations and observed that Their accuracy depends upon the quality of the molecular similarity. The use of quantitative structure-activity relationships (2-6) is based on the assumption that similar molecules have similar properties. Herein we present a general and rigorous definition of molecular structural similarity. Previous research in this field has usually been concerned with sequence comparisons of macromolecules, primarily proteins and nucleic acids (7-9). In addition, there have appeared a number of ad hoc definitions of molecular similarity (10-15), many of which are subsumed in the present work. Difficulties associated with attempting to obtain precise numerical indices for qualitative molecular structural concepts have already been extensively discussed in the literature and will not be reviewed here. 

Quantitative Structure-Activity Relationship models are used increasingly in chemical data mining and combinatorial library design [5, 6]. For example, three-dimensional (3-D) stereoelectronic pharmacophore based on QSAR modeling was used recently to search the National Cancer Institute Repository of Small Molecules [7] to find new leads for inhibiting HIV type 1 reverse transcriptase at the nonnucleoside binding site [8]. A descriptor pharmacophore concept was introduced by us recently [9] on the basis of variable selection QSAR the descriptor pharmacophore is defined as a subset of... 

In this chapter, we will give a brief introduction to the basic concepts of chemoinformatics and their relevance to chemical library design. In Section 2, we will describe chemical representation, molecular data, and molecular data mining in computer we will introduce some of the chemoinformatics concepts such as molecular descriptors, chemical space, dimension reduction, similarity and diversity and we will review the most useful methods and applications of chemoinformatics, the quantitative structure-activity relationship (QSAR), the quantitative structure-property relationship (QSPR), multiobjective optimization, and virtual screening. In Section 3, we will outline some of the elements of library design and connect chemoinformatics tools, such as molecular similarity, molecular diversity, and multiple objective optimizations, with designing optimal libraries. Finally, we will put library design into perspective in Section 4. 

Common unspecific mode of action of all organic compounds has been taken up in quantitative structure-activity relationships (QSARs see Chapter 5) as the concept of baseline toxicity and in toxicokinetics as the body burden concept (see Chapter 2). Baseline toxicity refers to the idea that a minimum toxicity expectation may be formulated for any given organic compound based on considerations of a compound s partition properties between hydrophilic and lipophilic chemicals (e.g., between water and octanol). Commonly, this is expressed in terms of the octanol-water partition coefficient (K0,J of a chemical. The partition coefficient allows estimations of a local concentration or body burden for each individual chemical in the mixture. Assuming that this produces the same toxic effect (disturbances of cell membranes), it is then possible to anticipate joint narcotic action by adding together the respective local concentrations or body burdens for each individual mixture component. 

Devillers J. Statistical analyses in drug design and environmental chemistry Basic concepts. In Coccini T, Giannoni L, Karcher W, Manzo L and R. Roi R, editors, Quantitative structure/activity relationships (QSAR) in toxicology. JRC-Ispra CEC, 1992. p. 27-41. 

Aminoacids, where principal properties have been used to establish quantitative structure-activity relations (QSAR) for peptides.[29] In this context, a more elaborate concept, dedicated principal properties[ iO] has been suggested where the modelling process is carried out in several steps to achieve maximum predictability of the QSAR models. We do not go into details on this. 

The resulting hypothetical receptor model is named minireceptor or pseudo-receptor and can be used to derive three-dimensional quantitative structure-activity relationships (3D-QSAR). The concept was originally developed in the 1980s by several groups. ... 

Rogers, D. (1995) Genetic function approximation a genetic approach to building quantitative structure-activity relationship models, in QSAR and Molecular Modelling Concepts, Computational Tools and Biological Applications (eds F. Sanz, J. Giraldo and F. Manaut), Prous Science, Barcelona (Spain), pp. 420-426. 

The field of Molecular Similarity has experienced remarkable progress in the last decade. The main topics covered by this area of research include Linear Free Energy Relationships (LFER) [13] and Quantitative Structure-Activity Rela-tionshii (QSAR) [14], although a large number of chemical definitions and concepts involve the Similarity Notion [15]. 

Chemistry and Environmental Chemistry are confronted with the crucial question how to obtain numerically information about properties of interest. The scientific discipline how to achieve this is associated with the concept Quantitative Structure Activity Relationships (abbreviation QSARs). Already in the first section the reader could be introduced to the way of thinking in this field of research. In the chapters in this section the focus is to establish structure - activity relationships by means of order relations. The order relations in turn are derived from sets of properties of the chemicals. 

If an active compound is detected by biological tests, then several of its derivates are prepared, in order to choose the one which shows the best biological characteristics. In this phase of research an opportunity offers itself even on the basis of our present knowledge to rate theoretical concepts into consideration. When a certain number of derivatives has been prepared, the computerised mathematical processing of data about them can reveal quantitative structure-activity relationships, on the basis of which the efficiency of compounds not yet prepared can be predicted with a high probability, and the compound which promises to be the most efficient can be selected. The rapid development of these mathematical molecule-design methods and the consequent increased success rate make it possible to work out the structure of effective compounds, and considerably fewer compounds have to be prepared than formerly. 

---