Large Scale Mining of Molecular Fragments with Wildcards

The main task of drug discovery is to find novel bioactive molecules, i.e., chemical compounds that, for example, protect human cells against a virus. One way to support solving this task is to analyze a database of known and tested molecules with the aim to build a classifier that predicts whether a novel molecule will be active or inactive, so that future chemical tests can be focused on the most promising candidates. In [1] an algorithm for constructing such a classifier was proposed that uses molecular fragments to discriminate between active and inactive molecules. In this paper we present two extensions of this approach: A special treatment of rings and a method that finds fragments with wildcards based on chemical expert knowledge.

• Type: Conference
• Year: 2003
• Where: IDA
• Authors: Heiko Hofer, Christian Borgelt, Michael R. Berthold
• Keywords: Future Chemical Tests, IDA 2003, Inactive Molecules, Protect Human Cells