Physicochemical-activity relations in practice. 2. Rational selection of benzenoid substituents

Abstract

A rational method is presented for the selection of substituents to be introduced into a benzenoid ring system of a biologically active compound in order to a defined physicochemical parameter space. The method, which may be readily programmed for use on a computer, relies on maintaining a minimum distance between compounds in the multidimensional physicochemical parameter space. The series of compounds produced will then have a well-spread set of minimally correlated physicochemical parameter values and could thus be used for the reliable correlation of the variation in the biological activities of the members of the series with changes in these physicochemical parameters. Some examples of the use of the present method under various conditions are given, and it is compared with alternatives in the literature.

Structural‐Similarity‐Based Approaches for the Development of Clustering and QSPR/QSAR Models in Chemical Databases

“…One of the firsts and most intuitive cluster method is based on the sphere exclusion theory [46]. The sphere exclusion procedure selects one item from the dataset and excludes from further considerations all items that are within a given similarity/ distance threshold to the selected item.…”

Experimental Design: Experiment and Set Selection

“…Table 2.8 lists some of the substituent members of the ten cluster set. Another approach which makes use of the distances between points in a multidimensional space was published by Wootton and co-workers [13]. In this method the distances between each pair of substituents is calculated, as described for cluster analysis, and substituents are chosen in a stepwise fashion such that they exceed a certain preset minimum distance.…”

“…One of the problems with the use of factorial methods for compound selection is that it may be difficult or impossible to obtain a compound required for a particular treatment combination, either because the a The methods are: h -maximization of information content, D -D-optimal design, V(1) maximal variance [13] and V(2) maximal variance [12].…”

“…Example of the choice of substituents by multidimensional mapping (reproduced from ref [13]. with permission of the American Chemical Society).…”

Quantitative Series Enrichment Analysis (QSEA): a novel procedure for 3D-QSAR analysis

“…Traditionally the main focus in model building has been which method to choose or better which method successfully provides a quantitative relationship. However the composition of the dataset plays an important role as well [8][9][10]. Model building can fail or even worse good statistical models with poor predictivity may result if structural information is not varied independently and continuously.…”