Application of Artificial Intelligence and Machine Learning for COVID-19 Drug Discovery and Vaccine Design

Overview

Journal Brief Bioinform

Publisher Oxford University Press

Specialty Biology

Date 2021 Aug 19

PMID 34410360

Citations 36

Authors

Hao Lv

Lei Shi

Joshua William Berkenpas

Fu-Ying Dao

Hasan Zulfiqar

Hui Ding

Yang Zhang

Liming Yang

Renzhi Cao

Affiliations

Soon will be listed here.

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.

Citing Articles

Emerging and reemerging infectious diseases: global trends and new strategies for their prevention and control.

Wang S, Li W, Wang Z, Yang W, Li E, Xia X Signal Transduct Target Ther. 2024; 9(1):223.

PMID: 39256346 PMC: 11412324. DOI: 10.1038/s41392-024-01917-x.

Fostering Tomorrow: Uniting Artificial Intelligence and Social Pediatrics for Comprehensive Child Well-being.

Gulsen M, Yalcin S Turk Arch Pediatr. 2024; 59(4):345-352.

PMID: 39110287 PMC: 11332429. DOI: 10.5152/TurkArchPediatr.2024.24076.

mRNA therapeutics: New vaccination and beyond.

Wei H, Zheng L, Wang Z Fundam Res. 2024; 3(5):749-759.

PMID: 38933291 PMC: 10017382. DOI: 10.1016/j.fmre.2023.02.022.

Tribulations and future opportunities for artificial intelligence in precision medicine.

Carini C, Seyhan A J Transl Med. 2024; 22(1):411.

PMID: 38702711 PMC: 11069149. DOI: 10.1186/s12967-024-05067-0.

AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods.

Usman Tariq M, Ismail S Osong Public Health Res Perspect. 2024; 15(2):115-136.

PMID: 38621765 PMC: 11082441. DOI: 10.24171/j.phrp.2023.0287.

References

Belyaeva A, Cammarata L, Radhakrishnan A, Squires C, Yang K, Shivashankar G . Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing. Nat Commun. 2021; 12(1):1024. PMC: 7884845. DOI: 10.1038/s41467-021-21056-z. View

Liang P, Yang W, Chen X, Long C, Zheng L, Li H . Machine Learning of Single-Cell Transcriptome Highly Identifies mRNA Signature by Comparing F-Score Selection with DGE Analysis. Mol Ther Nucleic Acids. 2020; 20:155-163. PMC: 7066034. DOI: 10.1016/j.omtn.2020.02.004. View

Wei L, Hu J, Li F, Song J, Su R, Zou Q . Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms. Brief Bioinform. 2018; 21(1):106-119. DOI: 10.1093/bib/bby107. View

Hasan M, Schaduangrat N, Basith S, Lee G, Shoombuatong W, Manavalan B . HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation. Bioinformatics. 2020; 36(11):3350-3356. DOI: 10.1093/bioinformatics/btaa160. View

Wang H, Liang P, Zheng L, Long C, Li H, Zuo Y . eHSCPr discriminating the cell identity involved in endothelial to hematopoietic transition. Bioinformatics. 2021; 37(15):2157-2164. DOI: 10.1093/bioinformatics/btab071. View

Thomson E, Rosen L, Shepherd J, Spreafico R, da Silva Filipe A, Wojcechowskyj J . Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity. Cell. 2021; 184(5):1171-1187.e20. PMC: 7843029. DOI: 10.1016/j.cell.2021.01.037. View

Wang S, Sun Q, Xu Y, Pei J, Lai L . A transferable deep learning approach to fast screen potential antiviral drugs against SARS-CoV-2. Brief Bioinform. 2021; 22(6). PMC: 8195169. DOI: 10.1093/bib/bbab211. View

Liu L, Zhang L, Dao F, Yang Y, Lin H . A computational framework for identifying the transcription factors involved in enhancer-promoter loop formation. Mol Ther Nucleic Acids. 2021; 23:347-354. PMC: 7779541. DOI: 10.1016/j.omtn.2020.11.011. View

Cheng L, Han X, Zhu Z, Qi C, Wang P, Zhang X . Functional alterations caused by mutations reflect evolutionary trends of SARS-CoV-2. Brief Bioinform. 2021; 22(2):1442-1450. PMC: 7953981. DOI: 10.1093/bib/bbab042. View

10.

Liu L, Li Q, Jin W, Lv H, Lin H . Revealing Gene Function and Transcription Relationship by Reconstructing Gene-Level Chromatin Interaction. Comput Struct Biotechnol J. 2019; 17:195-205. PMC: 6383185. DOI: 10.1016/j.csbj.2019.01.011. View

11.

Wei L, Zhou C, Chen H, Song J, Su R . ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides. Bioinformatics. 2018; 34(23):4007-4016. PMC: 6247924. DOI: 10.1093/bioinformatics/bty451. View

12.

Morselli Gysi D, Do Valle I, Zitnik M, Ameli A, Gan X, Varol O . Network medicine framework for identifying drug-repurposing opportunities for COVID-19. Proc Natl Acad Sci U S A. 2021; 118(19). PMC: 8126852. DOI: 10.1073/pnas.2025581118. View

13.

Cheng L, Zhu Z, Wang C, Wang P, He Y, Zhang X . 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; 118(21). PMC: 8166110. DOI: 10.1073/pnas.2102960118. View

14.

Wang Z, Liu D, Xu B, Tian R, Zuo Y . Modular arrangements of sequence motifs determine the functional diversity of KDM proteins. Brief Bioinform. 2020; 22(3). DOI: 10.1093/bib/bbaa215. View

15.

Ong E, Wong M, Huffman A, He Y . COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning. Front Immunol. 2020; 11:1581. PMC: 7350702. DOI: 10.3389/fimmu.2020.01581. View

16.

Tang B, He F, Liu D, He F, Wu T, Fang M . AI-Aided Design of Novel Targeted Covalent Inhibitors against SARS-CoV-2. Biomolecules. 2022; 12(6). PMC: 9220321. DOI: 10.3390/biom12060746. View

17.

Li F, Luo M, Zhou W, Li J, Jin X, Xu Z . Single cell RNA and immune repertoire profiling of COVID-19 patients reveal novel neutralizing antibody. Protein Cell. 2020; 12(10):751-755. PMC: 7686823. DOI: 10.1007/s13238-020-00807-6. View

18.

Methods In Medicine C . Retracted: Screening of Prospective Plant Compounds as H1R and CL1R Inhibitors and Its Antiallergic Efficacy through Molecular Docking Approach. Comput Math Methods Med. 2023; 2023:9832631. PMC: 10356469. DOI: 10.1155/2023/9832631. View

19.

Prachar M, Justesen S, Steen-Jensen D, Thorgrimsen S, Jurgons E, Winther O . Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools. Sci Rep. 2020; 10(1):20465. PMC: 7686376. DOI: 10.1038/s41598-020-77466-4. View

20.

Majumdar S, Nandi S, Ghosal S, Ghosh B, Mallik W, Roy N . Deep Learning-Based Potential Ligand Prediction Framework for COVID-19 with Drug-Target Interaction Model. Cognit Comput. 2021; :1-13. PMC: 7852055. DOI: 10.1007/s12559-021-09840-x. View