Cheminformantics

  TL;DR: The Molecular Exploration (MolExp) is a new benchmark integrated into MolScore. This leverages the converse similarity principle to probe a generative model's ability to explore chemical space. This benchmark is much more difficult than current benchmarks. Hopefully, this helps to guide algorithm development to a future where all molecules in chemical space can be found quickly, for a given context. Preprint and code links below.

TL;DR: I compared recent structure-explicit (3D) algorithms vs. structure-implicit (typically 2D) algorithms for structure-aware generative molecular design. I found that from a practical perspective structure-implicit (2D) methods are currently more useful, but, scoring function is important. See details and future outlook below, or jupyter notebook for data and analysis.