A generative deep learning approach to de novo antibiotic design

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A generative deep learning approach to de novo antibiotic designA generative AI platform is developed for de novo antibiotic design, yielding lead compounds with selective antibacterial activity, distinct mechanisms of action, and in vivo efficacy against multidrug-resistant N. gonorrhoeae and S. aureus.A generative AI platform is developed for de novo antibiotic design, yielding lead compounds with selective antibacterial activity, distinct mechanisms of action, and in vivo efficacy against multidrug-resistant N. gonorrhoeae and S. aureus.Aarti Krishnan, Melis N. Anahtar, Jacqueline A. Valeri, Wengong Jin, Nina M. Donghia, Leif Sieben, Andreas Luttens, Yu Zhang, Seyed Majed Modaresi, Andrew Hennes, Jenna Fromer, Parijat Bandyopadhyay, Jonathan C. Chen, Danyal Rehman, Ronak Desai, Paige Edwards, Ryan S. Lach, Marie-Stéphanie Aschtgen, Margaux Gaborieau, Massimiliano Gaetani, Samantha G. Palace, Satotaka Omori, Lutete Khonde, Yurii S. Moroz, Bruce Blough, Chunyang Jin, Edmund Loh, Yonatan H. Grad, Amir Ata Saei, Connor W. Coley, Felix Wong, James J. Collinshttps://www.cell.com/cell/fulltext/S0092-8674(25)00855-4?rss=yeshttp://www.cell.com/cell/inpress.rssCellCell RSS feed.Wireless News CampaignAugust 15, 2025

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