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

Tutkimustuotos: LehtiartikkeliReview Articlevertaisarvioitu

15 Lataukset (Pure)

Abstrakti

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.
AlkuperäiskieliEnglanti
Artikkeli102769
Sivut1-8
Sivumäärä8
JulkaisuCurrent Opinion in Structural Biology
Vuosikerta84
DOI - pysyväislinkit
TilaJulkaistu - helmik. 2024
OKM-julkaisutyyppiA2 Katsausartikkeli tieteellisessä aikakauslehdessä

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