CORA - Classification of Organic Reactions for Applications


Reaction databases provide a rich source of information on organic reactions. A combination of a Bayes classifier with a self-organizing neural network is used to group individual reactions into reaction types on the basis of physicochemical description of the reaction center. This allows to detect and visualize the important characteristics - and the driving forces - of a class of reactions.
A set of chemical reactions characterized by physicochemical properties of the atoms and bonds of the reacting center is entered into a Kohonen neural network. This results in a two-dimensional landscape of organic reactions. Similar reactions are grouped into reaction types, dissimilar reactions are separated from each other. Furthermore, this method can recognize special reactions, thus outlining the scope of a reaction type and can locate unusual reactions.
The automatic classification of reactions can be used for an efficient reaction database searching and derive knowledge on chemical reactions form a series of individual reactions. Such knowledge can be utilized in systems for reaction prediction (such as EROS) and synthesis planning (WODCA).


L. Chen, J. Gasteiger
Organic Reactions Classified by Neural Networks: Michael Additions, Friedel-Crafts Alkylations by Alkenes, and Related Reactions,
Angew. Chem. Intern. Ed. Engl., 1996, 35, 763-765; Angew. Chem., 1996, 108, 844-846.

L. Chen, J. Gasteiger,
Knowledge Discovery in Reaction Databases: Landscaping Organic Reactions by a Self-Organizing Neural Network,
J. Am. Chem. Soc., 1997, 119, 4033-4042.

H. Satoh, O. Sacher, T. Nakata, L. Chen, J. Gasteiger, K. Funatsu
Classification of Organic Reactions: Similarity of Reactions Based on Changes in the Electronic Features of Oxygen Atoms at the Reaction Sites,
J. Chem. Inf. Comput. Sci., 1998, 38, 210-219.


Prof. Dr. Johann Gasteiger

Dr. Oliver Sacher