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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.
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Structure-aware generative molecular design: from 2D or 3D?

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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.
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