Cell-based method

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. 

The importance of drug ionization using cell-based methods such as Caco-2 in the in vitro prediction of in vivo absorption was discussed [45]. It was observed that when the apical pH used in Caco-2 studies was lowered from 7.4 to 6.0 a better correlation was obtained with in vivo data, demonstrating that careful selection of experimental conditions in vitro is crucial to produce a reUable model. Studies with Caco-2 monolayers also suggested that the ionic species might contribute considerably to overall drug transport [46]. 

There are several approaches to estimating absorption using in vitro methods, notably Caco-2 and MDCK cell-based methods or using methods that assess passive permeability, for example the parallel artificial membrane permeation assay (PAMPA) method. These are reviewed elsewhere in this book. The assays are very useful, and usually have an important role in the screening cascades for drug discovery projects. However, as discussed below, the cell-based assays are not without their drawbacks, and it is often appropriate to use ex vivo and/or in vivo absorption assays. 

Schnur, D.M. Design and diversity analysis of large combinatorial libraries using cell-based methods. /. Chem. Inf. Comput. Sci. 1999, 39, 36-45. 

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). 

Rush, J. A. (1999) Cell-based methods for sampling high-dimensional spaces. In Rational drug design, Truhlar, D. G., Howe, W. J., et al. (eds.), Springer, New York, pp. 73-79. 

The selections of compounds are made using a variety of methods, such as dissimilarity selection (16), optiverse library selection (17), Jarvis-Park clustering (18), and cell-based methods (19). All these methods attempt to choose a set of compounds that represent the molecular diversity of the available compounds as efficiently as possible. A consequence of this is that only a few compounds around any given molecular scaffold may be present in a HTS screening... 

In a standard cell-based method, the range of each of k numerical descriptors is subdivided into m bins, yielding mk cells. To select a representative set of molecules from a database, one molecule is selected at random from each cell... 

As it is essentially impossible to cover a high-dimensional space finely with a modest number of compounds, Lam and co-workers proposed a cell-based method that uniformly covers all low-dimensional subspaces formed by subsets of descriptors (19,20). Typically, they would consider all one-dimensional (ID), 2D, and 3D subspaces. In addition to practical feasibility, this is consistent with Pearlman and Smith s notion of a relevant subspace (21) a particular activity mechanism will likely involve only a few relevant descriptor variables. 

Stickler, M., Mucha, J., Estell, D., Power, S., and Harding, F. 2003. A human dendritic cell-based method to identify CD4+ T-cell epitopes in potential protein allergens. Environ Health Perspect 111(2) 251—254. 

Diversity is typically measured using a distance-based or cell-based method cost is typically given as reactant cost/gm and physiochemical properties such as AMW are typically measured as the difference in the distribution of the property in the library compared to the distribution of the same property in a collection of known drugs. The weights, wl5 w2j w3> are user-defined and are typically set so that diversity is maximized, while the cost and physicochemical properties are minimized. This weighted-sum approach leads to a single solution that represents one particular compromise in the objectives. Several other groups have also adopted this approach [67, 71 73]. 

There are two main strategies developed to select diverse and representative subsets of molecules, namely, cell-based methods and distance-based methods. 

A diversity metric is a function to aid the quantification of the diversity of a set of compounds in some predefined chemical space. Diversity metrics fall into three main classes (1) Distance-based methods, which express diversity as a function of the pairwise molecular dissimilarities defined through measurement. (2) Cell-based methods, which define diversity in terms of occupancy of a finite number of cells that represent disjoint regions of chemical space. (3) Variance-based methods, which quantify diversity based on the degree of correlation between a compound s important features. 

A special case of cell-based methods is a diversity measure proposed for binary fingerprints. Unlike continuous descriptors, binary descriptors such as structural keys and hashed fingerprints can be compared using fast binary operations to give rapid estimates of molecular similarity, diversity, and complementarity. The most common example of a diversity measure applied to binary descriptors is the binary union (inclusive or ). This can be exploited in a number of different ways elegant examples can be found in the following references. ... 

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... 

Schnur, D. (1999). Design and Diversity Analysis of Large Combinatorial Libraries Using Cell-Based Methods. J.Chem.Inf.Comput.ScL, 39,36-45. 

Cell-based methods, as well as clustering or distance-based methods, aim at extracting representative structurally diverse subsets of compounds from large chemical databases [Cummins, Andrews et al, 1996 Mason and Pickett, 1997 Pearlman and Smith, 1999 Earnum, Desjarlais et al, 2003]. They are mainly used in design and optimization of combinatorial libraries the most important aspect being here to ensure maximum diversity within and between libraries before they are produced. Moreover, cell-based methods are used for lead discovery purposes allowing the selection of the compounds most similar to the active reference target. 

An advantage of cell-based methods is that they allow the explicit identification of those regions of the chemical space that are underrepresented, or, even unrepresented (i.e., diversity voids), in a database thus suggesting alternative potential structures to those of the existing chemicals [Pearlman and Smith, 1998]. 

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