THE COMPARISON OF GEOMETRIC AND ELECTRONIC-PROPERTIES OF MOLECULAR-SURFACES BY NEURAL NETWORKS - APPLICATION TO THE ANALYSIS OF CORTICOSTEROID-BINDING GLOBULIN ACTIVITY OF STEROIDS

It is shown how a self-organizing neural network such as the one intro duced by Kohonen can be used to analyze features of molecular surfaces , such as shape and the molecular electrostatic potential. On the one hand, two-dimensional maps of molecular surface properties can be gene rated and used for the comparison of a set of molecules. On the other hand, the surface geometry of one molecule can be stored in a network and this network can be used as a template for the analysis of the sha pe of various other molecules, The application of these techniques to a series of steroids exhibiting a range of binding activities to the c orticosteroid-binding globulin receptor allows one to pinpoint the ess ential features necessary for biological activity.