Generative AI for graph-based drug design: Recent advances and the way forward

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Abstract

Discovering new promising molecule candidates that could translate into effective drugs is a key scientific pursuit. However, factors such as the vastness and discreteness of the molecular search space pose a formidable technical challenge in this quest. AI-driven generative models can effectively learn from data, and offer hope to streamline drug design. In this article, we review state of the art in generative models that operate on molecular graphs. We also shed light on some limitations of the existing methodology and sketch directions to harness the potential of AI for drug design tasks going forward.
Original languageEnglish
Article number102769
Pages (from-to)1-8
Number of pages8
JournalCurrent Opinion in Structural Biology
Volume84
DOIs
Publication statusPublished - Feb 2024
MoE publication typeA2 Review article, Literature review, Systematic review

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