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用于严重急性呼吸综合征冠状病毒2的人工智能驱动的药物重新利用与结构生物学

Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2.

作者信息

Prasad Kartikay, Kumar Vijay

机构信息

Amity Institute of Neuropsychology & Neurosciences, Amity University, Noida, UP, 201303, India.

出版信息

Curr Res Pharmacol Drug Discov. 2021;2:100042. doi: 10.1016/j.crphar.2021.100042. Epub 2021 Jul 28.


DOI:10.1016/j.crphar.2021.100042
PMID:34870150
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8317454/
Abstract

It has been said that COVID-19 is a generational challenge in many ways. But, at the same time, it becomes a catalyst for collective action, innovation, and discovery. Realizing the full potential of artificial intelligence (AI) for structure determination of unknown proteins and drug discovery are some of these innovations. Potential applications of AI include predicting the structure of the infectious proteins, identifying drugs that may be effective in targeting these proteins, and proposing new chemical compounds for further testing as potential drugs. AI and machine learning (ML) allow for rapid drug development including repurposing existing drugs. Algorithms were used to search for novel or approved antiviral drugs capable of inhibiting SARS-CoV-2. This paper presents a survey of AI and ML methods being used in various biochemistry of SARS-CoV-2, from structure to drug development, in the fight against the deadly COVID-19 pandemic. It is envisioned that this study will provide AI/ML researchers and the wider community an overview of the current status of AI applications particularly in structural biology, drug repurposing, and development, and motivate researchers in harnessing AI potentials in the fight against COVID-19.

摘要

有人说,新冠疫情在很多方面都是一场代际挑战。但与此同时,它也成为了集体行动、创新和发现的催化剂。实现人工智能(AI)在未知蛋白质结构测定和药物发现方面的全部潜力就是其中一些创新成果。人工智能的潜在应用包括预测传染性蛋白质的结构、识别可能有效靶向这些蛋白质的药物,以及提出新的化合物作为潜在药物进行进一步测试。人工智能和机器学习(ML)有助于快速开展药物研发,包括对现有药物进行重新利用。算法被用于搜索能够抑制新冠病毒的新型或已获批抗病毒药物。本文综述了在抗击致命的新冠疫情中,人工智能和机器学习方法在新冠病毒的各种生物化学研究中,从结构到药物研发的应用情况。预计这项研究将为人工智能/机器学习研究人员和更广泛的群体提供人工智能应用现状的概述,特别是在结构生物学、药物重新利用和研发方面,并激励研究人员在抗击新冠疫情中发挥人工智能的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/21a6d2030034/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/891998660060/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/3244d32e0d80/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/0af0e5f33a71/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/21a6d2030034/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/891998660060/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/3244d32e0d80/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/0af0e5f33a71/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ab0/8663978/21a6d2030034/gr3.jpg

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本文引用的文献

[1]
Prediction of Potential Commercially Available Inhibitors against SARS-CoV-2 by Multi-Task Deep Learning Model.

Biomolecules. 2022-8-21

[2]
AI-Aided Design of Novel Targeted Covalent Inhibitors against SARS-CoV-2.

Biomolecules. 2022-5-25

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B.1.526 SARS-CoV-2 Variants Identified in New York City are Neutralized by Vaccine-Elicited and Therapeutic Monoclonal Antibodies.

mBio. 2021-8-31

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Inf Syst Front. 2021

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Network medicine framework for identifying drug-repurposing opportunities for COVID-19.

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An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19.

Signal Transduct Target Ther. 2021-4-24

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Euro Surveill. 2021-4

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Inform Med Unlocked. 2021

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Accelerated Repurposing and Drug Development of Pulmonary Hypertension Therapies for COVID-19 Treatment Using an AI-Integrated Biosimulation Platform.

Molecules. 2021-3-29

[10]
Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development.

Front Artif Intell. 2020-8-18

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