Use of the descriptor fingerprints to clustering of chemical datasets

A novel approach in the area of chemoinformatics, the use of descriptor fingerprints has been applied to the problem of clustering of chemical databases. This approach coupled with the clustering method of Butina (originally created for structural fingerprints) was tested with a set of 96 biodiesel fuels. The influence of the threshold values from 0.0 to 1.0 of the Tanimoto index on the clustering results was studied. The results show a good discrimination power of the method, biodiesels of the same oils fall in one the same clusters. It was also shown that similar cetane number (CN) values of biodiesels within the statistical accuracy fall in the same cluster