Mining electronic laboratory notebooks: analysis, retrosynthesis, and reaction based enumeration.
An approach to automatically analyze and use the knowledge contained in electronic laboratory notebooks (ELNs) has been developed. Reactions were reduced to their reactive center and converted to a string representation (SMIRKS) which formed the basis for reaction classification and in silico (retro-)synthesis. Of the SMIRKS that occurred at least five times, 98% successfully regenerated the original product. The extracted reaction rules (SMIRKS) and corresponding reactants span a virtual chemical space which showed a strong dependence on the size of the reactive center. Whereas relatively few robust reaction types were sufficient to describe a large part of all reactions, considerably more reaction rules were necessary to cover all reactions in the ELN. Furthermore, reaction sequences were extracted to identify frequent combinations and diversifying reaction steps. Based on the extracted knowledge a (retro-)synthesis tool was built allowing for de novo design of compounds which have a high chance of being synthetically accessible. In an example application of the de novo design tool, various feasible retrosynthetic routes to the query molecule were obtained. Reaction based enumeration along the top ranked route yielded a library of 29 920 compounds with diverse properties, 99.9% of which are novel in the sense that they are unknown to the public domain.
Department of Lead Identification and Optimization Support, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstrasse 65, 88397 Biberach an der Riss, Germany. clara.christ@boehringer-ingelheim.com
Clara D
CD
Christ
Matthias
M
Zentgraf
Jan M
JM
Kriegl
D002626:Chemistry, Pharmaceutical / Q000379:methods*; D057225:Data Mining; D004282:Documentation / Q000379:methods*; D055615:Electrical Equipment and Supplies; D013677:Medical Laboratory Science; D015394:Molecular Structure