Artificial intelligence in drug design: algorithms, applications, challenges and ethics-Reference-Cited by-同舟云学术

Artificial intelligence in drug design: algorithms, applications, challenges and ethics

Published:2021-06 Issue:2 Volume:3 Page:
ISSN:2631-3316
Container-title:Future Drug Discovery
language:en
Short-container-title:Future Drug Discovery

Author:

Arabi Alya A¹²^ORCID

Affiliation:

1. Department of Biochemistry, College of Medicine & Health Sciences, United Arab Emirates University, AlAin PO Box 17666, UAE

2. Centre for Computational Science, University College London, 20 Gordon St, London, UK

Abstract

The discovery paradigm of drugs is rapidly growing due to advances in machine learning (ML) and artificial intelligence (AI). This review covers myriad faces of AI and ML in drug design. There is a plethora of AI algorithms, the most common of which are summarized in this review. In addition, AI is fraught with challenges that are highlighted along with plausible solutions to them. Examples are provided to illustrate the use of AI and ML in drug discovery and in predicting drug properties such as binding affinities and interactions, solubility, toxicology, blood–brain barrier permeability and chemical properties. The review also includes examples depicting the implementation of AI and ML in tackling intractable diseases such as COVID-19, cancer and Alzheimer’s disease. Ethical considerations and future perspectives of AI are also covered in this review.

Publisher

Future Science Ltd

Link

https://www.future-science.com/doi/pdf/10.4155/fdd-2020-0028

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