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人工智能和机器学习在 COVID-19 药物发现和疫苗设计中的应用。

Application of artificial intelligence and machine learning for COVID-19 drug discovery and vaccine design.

机构信息

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.

Department of Spine Surgery, Changzheng Hospital, Naval Medical University, Shanghai 200433, China.

出版信息

Brief Bioinform. 2021 Nov 5;22(6). doi: 10.1093/bib/bbab320.


DOI:10.1093/bib/bbab320
PMID:34410360
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8511807/
Abstract

The global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has led to a dramatic loss of human life worldwide. Despite many efforts, the development of effective drugs and vaccines for this novel virus will take considerable time. Artificial intelligence (AI) and machine learning (ML) offer promising solutions that could accelerate the discovery and optimization of new antivirals. Motivated by this, in this paper, we present an extensive survey on the application of AI and ML for combating COVID-19 based on the rapidly emerging literature. Particularly, we point out the challenges and future directions associated with state-of-the-art solutions to effectively control the COVID-19 pandemic. We hope that this review provides researchers with new insights into the ways AI and ML fight and have fought the COVID-19 outbreak.

摘要

2019 年冠状病毒病(COVID-19)的全球大流行是由严重急性呼吸系统综合症冠状病毒 2 引起的,它导致了全世界范围内的大量生命损失。尽管付出了很多努力,但开发针对这种新型病毒的有效药物和疫苗仍需要相当长的时间。人工智能(AI)和机器学习(ML)提供了有希望的解决方案,可以加速新抗病毒药物的发现和优化。受此启发,本文基于迅速涌现的文献,对人工智能和机器学习在抗击 COVID-19 中的应用进行了广泛的调查。特别是,我们指出了与最先进解决方案相关的挑战和未来方向,以有效控制 COVID-19 大流行。我们希望本综述能为研究人员提供新的见解,了解人工智能和机器学习在抗击 COVID-19 爆发中的作用和已经发挥的作用。

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本文引用的文献

[1]
Retracted: Screening of Prospective Plant Compounds as H1R and CL1R Inhibitors and Its Antiallergic Efficacy through Molecular Docking Approach.

Comput Math Methods Med. 2023

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

Biomolecules. 2022-5-25

[3]
Integrated biomarker profiling of the metabolome associated with impaired fasting glucose and type 2 diabetes mellitus in large-scale Chinese patients.

Clin Transl Med. 2021-6

[4]
Target identification among known drugs by deep learning from heterogeneous networks.

Chem Sci. 2020-1-13

[5]
A transferable deep learning approach to fast screen potential antiviral drugs against SARS-CoV-2.

Brief Bioinform. 2021-11-5

[6]
Artificial Intelligence-Guided Molecular Design Targeting COVID-19.

ACS Omega. 2021-5-4

[7]
NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning.

Brief Bioinform. 2021-11-5

[8]
COVID-19 induces lower levels of IL-8, IL-10, and MCP-1 than other acute CRS-inducing diseases.

Proc Natl Acad Sci U S A. 2021-5-25

[9]
StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides.

Brief Bioinform. 2021-11-5

[10]
Network medicine framework for identifying drug-repurposing opportunities for COVID-19.

Proc Natl Acad Sci U S A. 2021-5-11

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