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Applications of Deep Learning in Molecule Generation and Molecular Property Prediction
Accounts of Chemical Research ( IF 16.4 ) Pub Date : 2020-12-28 , DOI: 10.1021/acs.accounts.0c00699 W. Patrick Walters 1 , Regina Barzilay 2
Accounts of Chemical Research ( IF 16.4 ) Pub Date : 2020-12-28 , DOI: 10.1021/acs.accounts.0c00699 W. Patrick Walters 1 , Regina Barzilay 2
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Recent advances in computer hardware and software have led to a revolution in deep neural networks that has impacted fields ranging from language translation to computer vision. Deep learning has also impacted a number of areas in drug discovery, including the analysis of cellular images and the design of novel routes for the synthesis of organic molecules. While work in these areas has been impactful, a complete review of the applications of deep learning in drug discovery would be beyond the scope of a single Account. In this Account, we will focus on two key areas where deep learning has impacted molecular design: the prediction of molecular properties and the de novo generation of suggestions for new molecules.
中文翻译：
深度学习在分子生成和分子性质预测中的应用
计算机硬件和软件的最新进展导致了深度神经网络的一场革命，该革命已影响到从语言翻译到计算机视觉的各个领域。深度学习还影响了药物发现的许多领域，包括细胞图像分析和有机分子合成新途径的设计。尽管这些领域的工作产生了影响，但对深度学习在药物发现中的应用进行全面的审查将超出单个帐户的范围。在此帐户中，我们将重点关注深度学习影响分子设计的两个关键领域：分子特性的预测和从头产生新分子的建议。
更新日期：2021-01-19
中文翻译：
深度学习在分子生成和分子性质预测中的应用
计算机硬件和软件的最新进展导致了深度神经网络的一场革命，该革命已影响到从语言翻译到计算机视觉的各个领域。深度学习还影响了药物发现的许多领域，包括细胞图像分析和有机分子合成新途径的设计。尽管这些领域的工作产生了影响，但对深度学习在药物发现中的应用进行全面的审查将超出单个帐户的范围。在此帐户中，我们将重点关注深度学习影响分子设计的两个关键领域：分子特性的预测和从头产生新分子的建议。
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