Chemical space is a set of all possible chemically stable organic compounds. Its size is enormous, e.g. a number of structures with the molecular weight lower than 500 Da is estimated to be 1060. However, the majority of these compounds was not suggested, not to say synthesized and chacterized. Therefore, we have developed the method of molecular morphing [Hoksza D. et al. Journal of Cheminformatics 6 : 7 2014. DOI: 10.1186/1758-2946-6-7] that systematically generates chemical subspaces between two selected structures. This method is implemented in a freely available program Molpher and programatically accessible using the Python library molpher-lib.
For the classification of compounds as easy and hard to syntesize it is necessary to have examples from both classes. While it is straightforward to obtain easy to synthesize structures from chemical vendors catalogues, hard to synthesize structures are not avilable in any database. Thus, for the design of hard to synthesize compounds, we have developed a Nonpher methodology [Voršilák M. et al. Journal of Cheminformatics 9:20 2017. DOI: 10.1186/s13321-017-0206-2], that is based on our molecular morphing approach.
MolMiner is a freely available Python application for the extraction of chemical compound formulas and names from scientific publications. It can be used not only from a command line, but also as a Python library. MolMiner's input is a PDF or image file with the document, the output is a set of chemical structures (in SMILES/InChI/SDF formats) names or 2D formulas of which were identified in the text .
Chemical probes are small organic molecules commonly used to study gene function, validate molecular targets or dissect complex processes within cells and organisms. Compared to drugs, a probe’s main attributes reside in its potency, selectivity and well-defined mechanism of action. Yet identifying suitable chemical probes is not a trivial task because information on candidate probes is typically scattered over various sources. Thus, our colleagues from the Laboratory of Cell Differentiation IMG AS CR have developed, with our small contribution, the Probes & Drugs (P&D) portal [Škuta C. et al., Nature Methods 14 (8) 758-759 2017. DOI: 10.1038/nmeth.4365], which set of almost 30,000 probes & drugs is assembled from 29 established public and commercial libraries. The P&D portal is update monthly and it enables users to identify high-quality chemical tools for the use in chemical biology and drug discovery research.
Local variations in DNA structure play an important role in DNA recognition by its interacting partners, such as proteins. In cooperation with the Laboratory of biomolecular recognition from the Biotechnology Institute of the Czech Academy of Sciences, we analyzed the spatial arrangement of dinucleotide units available in the PDB database. The result of our analysis is a set of uniquely defined conformational classes that laid the foundations for the Dolbico database. Appart from this classification, Dolbico also contains many additional data further describing DNA structure.