In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL) for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures.

A compact Modular Chemical Descriptor Language (MCDL) chemical structure editor (Java applet) is described. The small size (approximately 200 KB) of the applet allows its use to display and edit chemical structures in various Internet applications. The editor supports the MCDL format, in which structures are presented in compact canonical form and is capable of restoring bond orders as well as of managing atom and bond drawing overlap. A small database of cage and large cyclic fragment is used for optimal representation of difficult-to-draw molecules. The improved algorithm of the structure diagram generation can be used for other chemical notations that lack atomic coordinates (SMILES, InChI).

A system is described that provides autonomous searching for information by various characteristics of chemical compounds in the Structural Chemical Database of the All-Russian Institute for...

Two new features are added to existing algorithms for kekulization of chemical structures, i.e., handling of triple and cumulene bonds in cycles and use of random atom sorting to remove unmatched atoms. Handling of triple and cumulene bonds enables kekulization of graphynes and graphdiynes. Random sorting speeds up the calculation time, i.e., kekulization of large chemical structures containing about 107 atoms takes ≤1 min on a typical PC. Source codes (Pascal, GNU GPL license) are included as a compiled application (Windows 64). Calculation times and unmatched atom statistics are provided for graphenes, graphynes, nanotubes, graphyne nanotubes and fullerenes. Benchmark comparisons are made for some data.

The results of the comparison of two big chemical databases PubChem-Compound (general chemical information) and Aurora Fine Chemical (commercially available compounds) are presented. Each database contains about 115M records. The performed comparison shows that about 50% of the structures in these databases are identical while the rest are unique to each database, which is unexpected for such large samples. The PubChem compounds database contains many structures that are unstable at room temperature. For a more detailed comparison, the chemical structures are decomposed into circular fragments with a radius of up to 3 chemical bonds. It was found that the PubChem compounds database contains 1.5 times more fragments, than AFC. It is explained that the average size of a chemical structure in PubChem Compounds is larger than in Aurora Fine Chemicals. We also find that among the 30 most distributed fragments, 28 are common to both databases. Analysis of the unique fragments allowed us to find structures that are poorly represented in each of the databases. These are triple-bonded compounds in the PubChem Compounds database and organosilicon compounds in the Aurora Fine Chemicals database. Our study provides important information for the development of in silico engineering approaches for new polymers based on virtual synthesis from simple chemical fragments.