There are two way of a library generation
in ChemoSoft. The first route starts with a generic structure, at which positions of substituents
are marked, and radicals (building block residues). The residues can be loaded from an SD file or their abbreviations can be typed to load them from an internal user-predefined ChemoSoft file of special type.
This is a way to create optimization libraries so common for a medicinal chemist. The second approach involves recombination of two libraries of building blocks from either a ChemoSoft file or an SD one.

As you may have already guessed, the first step in generation of a virtual combinatorial library is the obtaining of building block residues. ChemoSoft resolves the problem by "ChemoSoft\Split\Generate radicals automatically" where you can define rules for generations of residue libraries from building blocks and generate the residues.

Another possibility is to obtain residues from an existing database by splitting its structures (generic structures) into scaffolds and residues. This is of special significance for an optimization or biased library when the nature of scaffolds and residues should be quite limited. The work of the corresponding ChemoSoft utility is illustrated below.

The second step is to use the gotten residues for a combinatorial library generation. As it is pointed out above, there are two ways to perform this operation. The method, which involves a generic structure and residues, is shown in the slides below.

The path of generation of combinatorial libraries from two building block residue libraries is easy and does not require much comment. An application of this approach is displayed below.

ChemoSoft tools for work with combinatorial libraries also include an instrument for the analysis of them. The utility enables you to intelligently derive interesting fragments library compounds consist of. In particular, it allows easy division of structures into scaffolds and residues. As compared to the tool for splitting discussed above, this function can analyze obtained results for different features. (Therefore, it can be considered as a ChemoSoft instrument for data mining or knowledge discovery in databases.) An example is given below.