A Neural Device for Searching Direct Correlations between Structures and Properties of Chemical Compounds

A scheme of a neural device intended for searching direct correlations between structures and properties of organic compounds without preliminary computation of molecular descriptors (that are invariant with respect to renumbering atoms in a molecule) is suggested. The invariance of a property with respect to renumbering atoms in a molecule is ensured by the architecture of the neural device, which is constructed by analogy with biological vision systems. A model software of the neural device was tested on several examples. The descriptive and predictive performances of the device are shown to be comparable and even overcome the performances of using molecular descriptors, such as topological indexes and substructural descriptors, especially for analyzing heterogeneous data sets including inorganic compounds. The neural device can be advantageously used in the cases when more traditional approaches fail to work or “good” molecular descriptors have not been devised yet.