Deep Machine Learning for Computer-Aided Drug Design

Bajorath, Jürgen (2022) Deep Machine Learning for Computer-Aided Drug Design. Frontiers in Drug Discovery, 2. ISSN 2674-0338

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Official URL: https://doi.org/10.3389/fddsv.2022.829043

Abstract

In recent years, deep learning (DL) has led to new scientific developments with immediate implications for computer-aided drug design (CADD). These include advances in both small molecular and macromolecular modeling, as highlighted herein. Going forward, these developments also challenge CADD in different ways and require further progress to fully realize their potential for drug discovery. For CADD, these are exciting times and at the very least, the dynamics of the discipline will further increase.

Item Type:	Article
Subjects:	Institute Archives > Medical Science
Depositing User:	Managing Editor
Date Deposited:	27 Feb 2023 04:37
Last Modified:	10 Jul 2024 13:01
URI:	http://eprint.subtopublish.com/id/eprint/749

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