The frequency of calculated scaffolds or skeletons is given for each group - which in turn allows you to spot unique patterns, identify commonalities, and gain valuable insights into the composition and diversity of your compound dataset. The much requested introduction of Bemis-Murcko scaffold clustering augments this step: Given a set of compounds in the Analyzer Mode (e.g., infiniSee results from the Scaffold Hopper or the Analog Hunter Mode, individual molecule libraries, SMILES, …), entries can be categorized by molecular scaffolds and skeletons in the data visualization window. The novel compound clustering feature in the Analyzer Mode: Create groups of molecules based on their Bemis-Murcko scaffold or their mere skeletons. Diversity within a set offers the added benefit that, ideally, multiple individual molecular scaffolds are discovered, which can serve as potential starting points for an optimization series. Introducing Bemis-Murcko ClusteringĪ key element driving the compound selection process is the selection of a chemically diverse set of molecules to increase the chances of finding actives. Among the standout additions in this update is a sleek Bemis-Murcko scaffold clustering within infiniSee’s Analyzer Mode. Vast Chemical Space Navigation: We are thrilled to share the launch of infiniSee ‘Artemis’ 5.1, which comes with numerous innovative enhancements designed to enhance the compound selection process.
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