Molecular similarity, dissimilarity, and diversity

Molecular diversity is a global concept, which is applicable to the analysis of large compound distributions, but not to the study of pair-wise molecular relationships. This 

Dissimilarity analysis plays a major role in compound selection. Typical tasks include the selection of a maximally dissimilar subset of compounds from a large set or the identification of compounds that are dissimilar to an existing collection. Such issues have played a major role in compound acquisition in the pharmaceutical industry. A typical task would be to select a subset of maximally dissimilar compounds from a data set containing n molecules. This represents a non-trivial challenge because of the combinatorial problem involved in exploring all possible subsets. Therefore, other dissimilarity-based selection algorithms have been developed (Lajiness 1997). The basic idea of such approaches is to initially select a seed compound (either randomly or, better, based on dissimilarity to others), then calculate dissimilarity between the seed compound and all others and select the most dissimilar one. In the next step, the database compound most dissimilar to these two compounds is selected and added to the subset, and the process is repeated until a subset of desired size is obtained. 

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