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DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery.

Chao ShenJianfei SongChang-Yu HsiehDong-Sheng CaoYu KangWenling YeZhenxing WuJike WangOdin ZhangXujun ZhangHao ZengHeng CaiYu ChenLinkang ChenHao LuoXinda ZhaoTianye JianTong ChenDe-Jun JiangMingyang WangQing YeJialu WuHongyan DuHui ShiYafeng DengTing-Jun Hou
Published in: Journal of chemical information and modeling (2024)
Artificial intelligence (AI)-aided drug design has demonstrated unprecedented effects on modern drug discovery, but there is still an urgent need for user-friendly interfaces that bridge the gap between these sophisticated tools and scientists, particularly those who are less computer savvy. Herein, we present DrugFlow, an AI-driven one-stop platform that offers a clean, convenient, and cloud-based interface to streamline early drug discovery workflows. By seamlessly integrating a range of innovative AI algorithms, covering molecular docking, quantitative structure-activity relationship modeling, molecular generation, ADMET (absorption, distribution, metabolism, excretion and toxicity) prediction, and virtual screening, DrugFlow can offer effective AI solutions for almost all crucial stages in early drug discovery, including hit identification and hit/lead optimization. We hope that the platform can provide sufficiently valuable guidance to aid real-word drug design and discovery. The platform is available at https://drugflow.com.
Keyphrases
  • drug discovery
  • artificial intelligence
  • molecular docking
  • deep learning
  • machine learning
  • high throughput
  • big data
  • structure activity relationship
  • molecular dynamics simulations
  • small molecule