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人工智能在药物设计中的应用。

Artificial Intelligence in Drug Design.

机构信息

R&D, Integrated Drug Discovery, Industriepark Hoechst, 65926 Frankfurt am Main, Germany.

R&D, Industriepark Hoechst, 65926 Frankfurt am Main, Germany.

出版信息

Molecules. 2018 Oct 2;23(10):2520. doi: 10.3390/molecules23102520.

Abstract

Artificial Intelligence (AI) plays a pivotal role in drug discovery. In particular artificial neural networks such as deep neural networks or recurrent networks drive this area. Numerous applications in property or activity predictions like physicochemical and ADMET properties have recently appeared and underpin the strength of this technology in quantitative structure-property relationships (QSPR) or quantitative structure-activity relationships (QSAR). Artificial intelligence in de novo design drives the generation of meaningful new biologically active molecules towards desired properties. Several examples establish the strength of artificial intelligence in this field. Combination with synthesis planning and ease of synthesis is feasible and more and more automated drug discovery by computers is expected in the near future.

摘要

人工智能(AI)在药物发现中起着关键作用。特别是人工神经网络,如深度神经网络或循环网络,推动了这一领域的发展。最近出现了许多在性质或活性预测方面的应用,如物化和 ADMET 性质,这支持了该技术在定量构效关系(QSAR)或定量构效关系(QSAR)中的优势。人工智能在从头设计中推动了有意义的新生物活性分子朝着预期性质的生成。有几个例子证明了人工智能在这一领域的强大。与合成规划相结合,易于合成是可行的,预计在不久的将来,计算机将越来越多地自动进行药物发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/88e6/6222615/377c09d49b11/molecules-23-02520-g001.jpg

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