A Toolkit for the analysis of virtual combinatorial libraries and patent Markush structures
Markush or generic structures are widely used in combinatorial libraries and chemical patents to define large chemical spaces. ChemAxon provides the most advanced Markush technology, including rapid structure searches in Markush space, enumeration, and automatic Markush composition. Markush analysis features are available as add-ons for many ChemAxon products, like JChem Engines and Instant JChem.
Markush representation supports all important structure variations, and even enables advanced Markush features to handle combinatorial virtual libraries and complex patent Markush structures. ChemAxon’s .mrv file format fully supports all current Markush features. Highlighted features that the technology can handle:
- Atom and bond lists
- Position variation bonds
- Link nodes
- Repetition units
- Multiply connected R-groups
- Heavily nested R-groups
- R-group bridges
- Homology groups
A Markush structure can be generated automatically using Markush Composer. Markush Composer can calculate optimal scaffold automatically, and it can generate simple combinatorial, or complex patent Markush structures. A created Markush structure covers all possible combinations of starting compounds. Generated Markush structures can be ideal starting points to finding new potentially effective compounds or for creating your own patent Markush structure.
Markush Enumeration is a robust tool for Markush structure analysis. By interactively guiding each Markush enumeration structure, users can quickly identify the relevant Markush that suits their needs. Current enumeration types include:
- Full, partial, and random enumeration
- Library size calculation
- Homology enumeration
Markush non-hit visualizations
Markush non-hit visualization is a visual analysis technology for comparing a Markush structure and a compound. It can highlight both the matching and non-matching parts in a query structure and in R-groups of a target Markush structure. The differentiating parts can be easily recognized and analyzed in this way.