Similarity searching in large virtual chemistry spaces derived from synthetically accessible combinatorial libraries

CINF 11

Markus Boehm, Markus.Boehm1@pfizer.com, Gregory A. Bakken, Gregory.A.Bakken@pfizer.com, and Alan M. Mathiowetz, Alan.M.Mathiowetz@pfizer.com. Computational Chemistry, Pfizer Global Research and Development, Eastern Point Road, Groton, CT 06340
Fast molecular similarity searching is widely established as part of the drug discovery process. At the same time large collections of validated high-speed synthetic protocols are an integral element in today's pharmaceutical industry. It would be of great interest to perform similarity searches against a database of all virtual compounds that are synthetically accessible by any of such combinatorial library protocols. However, the number of possible compounds easily exceeds - by many orders of magnitude - the number of compounds that can be stored and searched by conventional searching methods. We have developed a software tool that converts large numbers of combinatorial libraries into an enclosed "virtual chemistry space". Feature Trees Fragment Spaces are capable of searching those libraries without ever enumerating all possible molecular structures. The result of the similarity search is a set of compounds which are synthetically accessible by one or more of the existing synthetic protocols. Such output can provide library design ideas for tasks like hit follow-up from high-throughput screening or lead hopping from one compound to another attractive series.