A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

Autor: Tang, Xiangru, Dai, Howard, Knight, Elizabeth, Wu, Fang, Li, Yunyang, Li, Tianxiao, Gerstein, Mark

Artificial intelligence (AI)-driven methods can vastly improve the historically costly drug design process, with various generative models already in widespread use. Generative models for de novo drug design, in particular, focus on the creation of n

Externí odkaz: http://arxiv.org/abs/2402.08703

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A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation.

Autor: Tang X; Department of Computer Science, Yale University, New Haven, CT 06520, United States., Dai H; Department of Computer Science, Yale University, New Haven, CT 06520, United States., Knight E; School of Medicine, Yale University, New Haven, CT 06520, United States., Wu F; Computer Science Department, Stanford University, CA 94305, United States., Li Y; Department of Computer Science, Yale University, New Haven, CT 06520, United States., Li T; Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT 06520, United States., Gerstein M; Department of Computer Science, Yale University, New Haven, CT 06520, United States.; Program in Computational Biology & Bioinformatics, Yale University, New Haven, CT 06520, United States.; Department of Statistics & Data Science, Yale University, New Haven, CT 06520, United States.; Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT 06520, United States.; Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT 06520, United States.

Publikováno v: Briefings in bioinformatics [Brief Bioinform] 2024 May 23; Vol. 25 (4).