Cell-based partitioning methods

Xue L, Stahura FL, Bajorath J. Cell-based partitioning. Methods Mol Biol 2004 275 279-90. 

Dissimilarity and clustering methods only describe the compounds that are in the input set voids in diversity space are not obvious, and if compounds are added then the set must be re-analyzed. Cell-based partitioning methods address these problems by dividing descriptor space into cells, and then populating those cells with compounds [67, 68]. The library is chosen to contain representatives from each cell. The use of a partition-based method with BCUT descriptors [69] to design an NMR screening library has recently been described [70]. 

Godden, J.W. and Bajorath, J. (2004) Cell-based partitioning. Methods in Molecular Biology, 275, 279-290. 

In chemoinformatics research, partitioning algorithms are applied in diversity analysis of large compound libraries, subset selection, or the search for molecules with specific activity (1-4). Widely used partitioning methods include cell-based partitioning in low-dimensional chemical spaces (1,3) and decision tree methods, in particular, recursive partitioning (RP) (5-7). Partitioning in low-dimensional chemical spaces is based on various dimension reduction methods (4,8) and often permits simplified three-dimensional representation of... 

In addition to cell-based partitioning, statistical partitioning methods are widely used for compound classification. One of the most popular approaches is recursive partitioning (Rusinko et al. 1999), a decision tree method, as illustrated in Figure 1.8. Recursive partitioning divides data sets along decision trees formed by sequences of molecular descriptors. At each node of the tree, a descriptor-based decision is made and the molecular data set is subdivided. For example, a chosen descriptor could simply detect the presence or absence of a structural fragment in a molecule. Alternatively, the... 

Agrafiolis DK (2003) Stochastic proximity embedding. J Comput Chem 24 1215-1221 Xue L, Stahura PL, Bajorath J (2004) Cell-based partitioning. In Chemoinformatics concepts, methods, and tools for drug discovery. Chapter 9. Humana, Totowa Wickens TD (2009) Multiway contingency tables analysis for the social sciences. Psychology, New York... 

Partitioning or cell-based methods provide an absolute measure of the chemical space covered by a collection of compounds. They are based on the definition of a low-dimensional chemistry space, for example, one based on a small number of physicochemical properties such as molecular weight, calculated logP, and number of hydrogen bond donors [45]. Each property defines an axis of the chemistry-space. The range of values for each property is divided into a set of bins, and the combinatorial product of all bins then defines the set of cells or partitions that make up the space. 

DVS offers a cell-based method for assessing the diversity of compound collections. The orthogonal chemistry space is partitioned into cells, and the occupancy of each cell is easily determined. Diversity voids , or unoccupied regions of chemistry space, are identified with unoccupied cells or cells of low occupancy, which are also easily recognized. Enhancing diversity of a compound collection thus consists of filling empty and low-occupancy cells (see Figure 13.5). 

Many of the early evaluations of the effectiveness of diversity methods used structure-based diversity indices, such as functions of intermolecular dissimilarities in the context of distance-based selection methods or of the numbers of occupied cells in partition-based selection methods (4). A wide range of such indices has been reported, as discussed in the excellent review by Waldman et al. 

An alternative two-part classification has been proposed by Pearlman et al. [90], who characterise methods as either cell-based or distance-based, these classes corresponding to partition-based methods and to all the other types of method, respectively. As Pearlman et al. note, distance-based methods can be used with any type of structural representation but are most effective when the need is to identify subsets (of whatever sort) cell-based... 

Compound selection is a core process of library design, and three main methods can be mentioned. Dissimilarity-based methods select compounds in terms of similar-ity/distance between individuals in chemical space. Clustering methods first group compounds into clusters based on similarity/distance and then choose representative compounds from different clusters. Partitioning methods first create a uniform cell space that subdivides the chemical space, then assign all virtual compounds to the relative cells according to their properties, and finally choose representative compounds from different cells. 

Therefore, partition/cell-based methods are preferred for such library comparison tasks. They provide a common frame of reference in which it is possible to identify voids within the chemistry space of a population. It must be emphasized that the chemistry space... 

Yu S, Li S, Yang H, Lee F, Wu JT, Qian MG. A novel liquid chromatography/tandem mass spectrometry based depletion method for measuring red blood cell partitioning of pharmaceutical compounds in drug discovery. Rapid Commun Mass Spectrom 2005b 19(2) 250-254. 

Property filters are a particular implementation of partitioning methods they are used to select drug-like or lead-like compounds from large chemical libraries. Like the cell-based methods, these filters are based on a partition of the chemical space but each selected molecular descriptor is divided into only two or three subranges of values. While property filters mainly aim at optimizing drug-likeness, cell-based methods at optimizing diversity of chemical libraries. 

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