Benchmarking chemical exploration in de novo drug design with MolExp
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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. Background Generative molecular design has already moved beyond the theoretical with many workflows already experimentally validated (Du et al., 2024). I want to take a small step back and re-evaluate the common objective of goal-directed generative algorithms in the context of drug design... Goal-directed drug design: Automatically 'build' molecules such as to maximise an oracle score / fitness function / scoring function / desirability criteria, usually a combination of predicted molecular properties. We generally task our models wit...