The recent advances in the approach of artificial intelligence (AI) towards drug discovery

Mahroza Kanwal Khan; Mohsin Raza; Muhammad Shahbaz; Iftikhar Hussain; Muhammad Farooq Khan; Zhongjian Xie; Syed Shoaib Ahmad Shah; Ayesha Khan Tareen; Zoobia Bashir; Karim Khan

doi:10.3389/fchem.2024.1408740

The recent advances in the approach of artificial intelligence (AI) towards drug discovery

Mahroza Kanwal Khan, Mohsin Raza^*, Muhammad Shahbaz, Iftikhar Hussain, Muhammad Farooq Khan, Zhongjian Xie, Syed Shoaib Ahmad Shah, Ayesha Khan Tareen, Zoobia Bashir, Karim Khan^*

^*Corresponding author for this work

Department of Mechanical Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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Abstract

Artificial intelligence (AI) has recently emerged as a unique developmental influence that is playing an important role in the development of medicine. The AI medium is showing the potential in unprecedented advancements in truth and efficiency. The intersection of AI has the potential to revolutionize drug discovery. However, AI also has limitations and experts should be aware of these data access and ethical issues. The use of AI techniques for drug discovery applications has increased considerably over the past few years, including combinatorial QSAR and QSPR, virtual screening, and denovo drug design. The purpose of this survey is to give a general overview of drug discovery based on artificial intelligence, and associated applications. We also highlighted the gaps present in the traditional method for drug designing. In addition, potential strategies and approaches to overcome current challenges are discussed to address the constraints of AI within this field. We hope that this survey plays a comprehensive role in understanding the potential of AI in drug discovery.

© 2024 Khan, Raza, Shahbaz, Hussain, Khan, Xie, Shah, Tareen, Bashir and Khan.

Original language	English
Article number	1408740
Journal	Frontiers in Chemistry
Volume	12
Online published	31 May 2024
DOIs	https://doi.org/10.3389/fchem.2024.1408740
Publication status	Published - 2024

Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Research Keywords

AI
artificial intelligence
drug discovery
machine learning
structure-activity relationship

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This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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abstract = "Artificial intelligence (AI) has recently emerged as a unique developmental influence that is playing an important role in the development of medicine. The AI medium is showing the potential in unprecedented advancements in truth and efficiency. The intersection of AI has the potential to revolutionize drug discovery. However, AI also has limitations and experts should be aware of these data access and ethical issues. The use of AI techniques for drug discovery applications has increased considerably over the past few years, including combinatorial QSAR and QSPR, virtual screening, and denovo drug design. The purpose of this survey is to give a general overview of drug discovery based on artificial intelligence, and associated applications. We also highlighted the gaps present in the traditional method for drug designing. In addition, potential strategies and approaches to overcome current challenges are discussed to address the constraints of AI within this field. We hope that this survey plays a comprehensive role in understanding the potential of AI in drug discovery.{\textcopyright} 2024 Khan, Raza, Shahbaz, Hussain, Khan, Xie, Shah, Tareen, Bashir and Khan.",

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AU - Khan, Mahroza Kanwal

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AU - Shahbaz, Muhammad

AU - Hussain, Iftikhar

AU - Khan, Muhammad Farooq

AU - Xie, Zhongjian

AU - Shah, Syed Shoaib Ahmad

AU - Tareen, Ayesha Khan

AU - Bashir, Zoobia

AU - Khan, Karim

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N2 - Artificial intelligence (AI) has recently emerged as a unique developmental influence that is playing an important role in the development of medicine. The AI medium is showing the potential in unprecedented advancements in truth and efficiency. The intersection of AI has the potential to revolutionize drug discovery. However, AI also has limitations and experts should be aware of these data access and ethical issues. The use of AI techniques for drug discovery applications has increased considerably over the past few years, including combinatorial QSAR and QSPR, virtual screening, and denovo drug design. The purpose of this survey is to give a general overview of drug discovery based on artificial intelligence, and associated applications. We also highlighted the gaps present in the traditional method for drug designing. In addition, potential strategies and approaches to overcome current challenges are discussed to address the constraints of AI within this field. We hope that this survey plays a comprehensive role in understanding the potential of AI in drug discovery.© 2024 Khan, Raza, Shahbaz, Hussain, Khan, Xie, Shah, Tareen, Bashir and Khan.

AB - Artificial intelligence (AI) has recently emerged as a unique developmental influence that is playing an important role in the development of medicine. The AI medium is showing the potential in unprecedented advancements in truth and efficiency. The intersection of AI has the potential to revolutionize drug discovery. However, AI also has limitations and experts should be aware of these data access and ethical issues. The use of AI techniques for drug discovery applications has increased considerably over the past few years, including combinatorial QSAR and QSPR, virtual screening, and denovo drug design. The purpose of this survey is to give a general overview of drug discovery based on artificial intelligence, and associated applications. We also highlighted the gaps present in the traditional method for drug designing. In addition, potential strategies and approaches to overcome current challenges are discussed to address the constraints of AI within this field. We hope that this survey plays a comprehensive role in understanding the potential of AI in drug discovery.© 2024 Khan, Raza, Shahbaz, Hussain, Khan, Xie, Shah, Tareen, Bashir and Khan.

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KW - machine learning

KW - structure-activity relationship

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The recent advances in the approach of artificial intelligence (AI) towards drug discovery

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