Real-World Applications and Experiences of AI/ML Deployment for Drug Discovery

IF 6.8 1区 医学 Q1 CHEMISTRY, MEDICINAL
Will R. Pitt, Jonathan Bentley, Christophe Boldron, Lionel Colliandre, Carmen Esposito, Elizabeth H. Frush, Jola Kopec, Stéphanie Labouille, Jerome Meneyrol, David A. Pardoe, Ferruccio Palazzesi, Alfonso Pozzan, Jacob M. Remington, René Rex, Michelle Southey, Sachin Vishwakarma, Paul Walker
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引用次数: 0

Abstract

Figure 1. Secret sauce of excellence in molecular design at Evotec. Figure 2. How AI/ML techniques fit into the Design-Decide-Make-Test-Learn (D2MTL) cycle. absorption, distribution, metabolism, excretion, and toxicity artificial intelligence electronic lab notebook design-make-test-analyze computer-aided synthesis planning machine learning contract research organization virtual screening quantitative structure–activity relationship deep generative chemistry Bayesian optimization particle swarm optimization quantitative structure–property relationship random forest recurrent neural networks autoencoder graph neural networks transfer learning continuous and data-driven descriptors relative binding free energies fragment molecular orbital active learning multiparameter optimization molecular dynamics AlphaFold 2 AlphaFold 3 crystallography or cryogenic electron microscopy drug-induced liver injury high-performance computing bile salt export pump quantum mechanics This article references 76 other publications. This article has not yet been cited by other publications.

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来源期刊
Journal of Medicinal Chemistry
Journal of Medicinal Chemistry 医学-医药化学
CiteScore
4.00
自引率
11.00%
发文量
804
审稿时长
1.9 months
期刊介绍: The Journal of Medicinal Chemistry is a prestigious biweekly peer-reviewed publication that focuses on the multifaceted field of medicinal chemistry. Since its inception in 1959 as the Journal of Medicinal and Pharmaceutical Chemistry, it has evolved to become a cornerstone in the dissemination of research findings related to the design, synthesis, and development of therapeutic agents. The Journal of Medicinal Chemistry is recognized for its significant impact in the scientific community, as evidenced by its 2022 impact factor of 7.3. This metric reflects the journal's influence and the importance of its content in shaping the future of drug discovery and development. The journal serves as a vital resource for chemists, pharmacologists, and other researchers interested in the molecular mechanisms of drug action and the optimization of therapeutic compounds.
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