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Deep Learning in Structure-Based Drug Design

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Artificial Intelligence in Drug Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2390))

Abstract

Computational methods play an increasingly important role in drug discovery. Structure-based drug design (SBDD), in particular, includes techniques that take into account the structure of the macromolecular target to predict compounds that are likely to establish optimal interactions with the binding site. The current interest in machine learning algorithms based on deep neural networks encouraged the application of deep learning to SBDD related problems. This chapter covers selected works in this active area of research.

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  1. Evotec (U.K.) Ltd., Abingdon, Oxfordshire, UK

    Andrew Anighoro

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  1. Andrew Anighoro
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  1. Computational Drug Discovery, Evotec (UK) Ltd., Abingdon, Oxfordshire, UK

    Alexander Heifetz

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Anighoro, A. (2022). Deep Learning in Structure-Based Drug Design . In: Heifetz, A. (eds) Artificial Intelligence in Drug Design. Methods in Molecular Biology, vol 2390. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1787-8_11

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  • DOI: https://doi.org/10.1007/978-1-0716-1787-8_11

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