Biological space approaches

In this chapter, the full BioPrint approach is described, as available from Cerep in terms of both the data set and the ability to have new compounds profiled and the results provided in the context of the BioPrint data set, including the known in vivo side effects of near neighbors in this biological space (see Section 2.5). The results for the differentiation of hit/lead compounds (see Section 2.3.2.1) sometimes use a subset of the 70-100 pharmacological assays that provide the maximum signal. Usually a decision on future work prioritization could be clearly made from the data from these subsets, saving time and money. For key reference/tool compounds, a full profile was used and is recommended to be used, as unexpected off-target activities may be found that cannot usually be predicted. 

We performed a combined 2D and 3D analysis of chemical and biological space to identify ion channel privileged chemotypes. The 2D approach was based on a collection of biologically active compounds and consisted mainly of similarity and substructure searching and of analysis of common frameworks and fragments. Our 3D approach relied on multiple ion channel pharmacophores and homology models, which were used for virtual screening. 

In addition to the choice of relative orientation, conformational flexibility may prove to be more of a problem in future applications than for the systems described here. This is particularly likely when the molecules are very similar. Of course, it is not hard to anticipate situations for which a p-space approach is unlikely to be useful. Obvious examples are those in which the observed activity is largely dependent on the values of bulk physical properties or on well-defined steric effects. We have stressed previously [12] that no single approach to molecular similarity can be expected to be a universal panacea. For example, any comparative methodology, such as that presented here, can only very indirectly provide information concerning interactions with biological receptors. 

Knowledge-driven approaches to explore matches of chemical and biological spaces... 

The chemical genomics/proteomics methods are complemented with a much broader discipline, called chemogenomics, which builds a relationship with the system biology and investigates the matching of the chemical and biological space integrating experimental and in silico approaches. 

A number of studies have used an alternative approach to assess descriptor quality for diversity profiling. In these studies, descriptors were ranked by their ability to discriminate active and inactive compounds within a number of medicinal chemistry project data sets. In the work of Brown and Martin, this discrimination involved the ability to separate one class of compounds from a general pool of compounds. The approach put forward by Patterson et al. i (see also Refs. 132 and 133) introduced the concept of neighborhood behavior that is, compounds close in biological space should have a small difference in descriptor values. In these studies, it was suggested that 2-D fingerprints and simple shape descriptors make better descriptors than other alternatives... 

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