Structure-activity relationships biological

On the other hand, factor analysis involves other manipulations of the eigen vectors and aims to gain insight into the structure of a multidimensional data set. The use of this technique was first proposed in biological structure-activity relationship (i. e., SAR) and illustrated with an analysis of the activities of 21 di-phenylaminopropanol derivatives in 11 biological tests [116-119, 289]. This method has been more commonly used to determine the intrinsic dimensionality of certain experimentally determined chemical properties which are the number of fundamental factors required to account for the variance. One of the best FA techniques is the Q-mode, which is based on grouping a multivariate data set based on the data structure defined by the similarity between samples [1, 313-316]. It is devoted exclusively to the interpretation of the inter-object relationships in a data set, rather than to the inter-variable (or covariance) relationships explored with R-mode factor analysis. The measure of similarity used is the cosine theta matrix, i. e., the matrix whose elements are the cosine of the angles between all sample pairs [1,313-316]. 

We became interested in whether or not biological structure-activity relationships could be developed for any of these sets of compounds. Only the acyclic nitrosamines appeared to constitute a sufficiently extensive and well-defined series, and we consequently carried out computerized multiple regression analyses on this group of compounds, using log (I/D50) the dependent variable analogous to RBR (12). 

This equation is a fairly typical biological structure-activity relationship with a strong dependence on partition coefficients, and it therefore suggests that the nitrosamines, and perhaps other chemical carcinogens as well, are similar - in the pharmacological sense - to analgesics or toxic agents. 

There have been a number of studies which have used the electrostatic potential of a series of compounds in which the biological structure - activity relationship is known in order to infer properties of the biological receptor for these molecules [5]. Since this approach appears promising but is limited by one s ignorance of the nature of the receptor site , we thought it worthwhile to apply the electrostatic potential approach to a situation where the structure of both the small and large molecule are known, i.e., an enzyme-substrate interaction. 

Hansch, C. A. (1969). Aquantitative approach to biological-structure activity relationships. Acta Chem. Res. 2,232—239. 

The fundamental assumption of SAR and QSAR (Structure-Activity Relationships and Quantitative Structure-Activity Relationships) is that the activity of a compound is related to its structural and/or physicochemical properties. In a classic article Corwin Hansch formulated Eq. (15) as a linear frcc-cncrgy related model for the biological activity (e.g.. toxicity) of a group of congeneric chemicals [37, in which the inverse of C, the concentration effect of the toxicant, is related to a hy-drophobidty term, FI, an electronic term, a (the Hammett substituent constant). Stcric terms can be added to this equation (typically Taft s steric parameter, E,). 

Dunn W J III, S Wold, U Edlund, S Hellberg and J Gasteiger 1984. Multivariate Structure-Activib Relationships Between Data from a Battery of Biological Tests and an Ensemble of Structur Descriptors The PLS Method. Quantitative Structure-Activity Relationships 3 131-137. 

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. 

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... 

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. 

J. P. Hu and co-workers. Structure Activity Relationship oJFlavonoids with Superoxide S cavenging Activity, Biological Trace Element Research, Vol. 47, The Humana Press Inc., Clifton, N.J., pp. 327—331, 1995. 

Structure-Activity Relationships. Biological evaluation of peniciUias yields information such as in vitro and in vivo antibacterial activities. 

Hundreds of flavonols have been isolated and characterized many of them are biologically active. Hence a great synthetic interest has arisen. Some of the efforts have concentrated on the synthesis of naturally oecurring flavonols while others have focused on the synthesis of flavonol derivatives for structure activity relationships. ... 

On the other hand, multimodality of biological activities of melatonin is well known. Therefore various derivatives are needed for carrying out its structure-activity relationship study. 1-Hydoxymelatonin (19) would be a suitable seed for developing yet unknown results. 

Structure activity relationships, i.e., the total pattern of change in a biological activity as a function of chemical structure, typically derived from a comparison within a chemical series so that the biological effects of substitution at each structural position may be determined and correlated. 

Smith PW, Sollis SL, Howes PD, Cherry PC, Starkey ID, Cobley KN, Weston H, Scicinski J, Merritt A, Whittington A, Wyatt P, Taylor N, Green D, BetheU R, Madar S, Fenton RJ, Motley PJ, Pateman T, Beresford A (1998) Dihydropyrancarboxamides related to zanamivir a new series of inhibitors of influenza virus sialidases. 1. Discovery, synthesis, biological activity, and structure-activity relationships of 4-guanidino- and 4-amino H-pyran-6-carboxamides. J Med Chem 41 787-797... 

In 1868 two Scottish scientists, Crum Brown and Fraser [4] recognized that a relation exists between the physiological action of a substance and its chemical composition and constitution. That recognition was in effect the birth of the science that has come to be known as quantitative structure-activity relationship (QSAR) studies a QSAR is a mathematical equation that relates a biological or other property to structural and/or physicochemical properties of a series of (usually) related compounds. Shortly afterwards, Richardson [5] showed that the narcotic effect of primary aliphatic alcohols varied with their molecular weight, and in 1893 Richet [6] observed that the toxicities of a variety of simple polar chemicals such as alcohols, ethers, and ketones were inversely correlated with their aqueous solubilities. Probably the best known of the very early work in the field was that of Overton [7] and Meyer [8], who found that the narcotic effect of simple chemicals increased with their oil-water partition coefficient and postulated that this reflected the partitioning of a chemical between the aqueous exobiophase and a lipophilic receptor. This, as it turned out, was most prescient, for about 70% of published QSARs contain a term relating to partition coefficient [9]. 

Despite the work of Overton and Meyer, it was to be many years before structure-activity relationships were explored further. In 1939 Ferguson [10] postulated that the toxic dose of a chemical is a constant fraction of its aqueous solubility hence toxicity should increase as aqueous solubility decreases. Because aqueous solubility and oil-water partition coefficient are inversely related, it follows that toxicity should increase with partition coefficient. Although this has been found to be true up to a point, it does not continue ad infinitum. Toxicity (and indeed, any biological response) generally increases initially with partition coefficient, but then tends to fall again. This can be explained simply as a reluctance of very hydrophobic chemicals to leave a lipid phase and enter the next aqueous biophase [11]. An example of this is shown by a QSAR that models toxicity of barbiturates to the mouse [12] ... 

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