Tutorial Prediction of the Regiochemistry in Pyrazole Synthesis

The application described here shows how a classified data set of reactions producing pyrazole derivatives can be used to predict the correct regioisomer in a pyrazole synthesis before it is carried out practically in the laboratory. 

The synthesis of pyrazolcs starting from a hydrazine and a 1,3-dicarbonyl compound is a well established reaction in organic synthesis. If a mono-suhstituted hydrazine is reacted with an unsymmctrically substituted 1,3-dicarbonyl compound, two different pyrazole products which arc regioisomers could he formed (sec figure 10.3-2). 

Til most cases, only one of the two regioisomers is preferentially formed. Wc will show here how reaction classification by a self-organizing neural network can be used for the prediction of the preferred regioisomer in a pyrazole synthesis. 

Any attempt in learning also needs information on situations where the event to be studied will not occur. This principle, if translated to learning on reactions, would require information on reactions that will not proceed. Unfortunately, such information is not contained in reaction databases, and therefore has to he generated. In our case, we also needed information on which regioisomer is not formed, or is formed only to a minor extent, in a pyrazole synthesis. 

The reactions which have been observed arc well separated from the reactions which arc expected to have no or a low yield. The reaaions leading to the preferred regioisomer arc projected into the upper part of the Kohonen map, whereas the reactions of the non-preferred regioisomer arc projected into the lower part of the Kohonen map. 

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