DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design
Abstract
:1. Introduction
2. Methods
2.1. Compound Collection and Preprocessing
2.2. Protein Preparation for Molecular Docking
2.3. Docking Protocol
2.4. Structure Analysis of Compounds
2.5. The Web Server of DrugDevCovid19
3. Results
3.1. Molecular Docking Is the Most Popular CADD Method against COVID-19
3.2. CADD Studies Predicted Diverse Compounds against COVID-19
3.3. Comparison Studies between CADD Compounds and Co-Crystallized Inhibitors
3.3.1. Molecular Similarity
3.3.2. Drug-Likeness
3.3.3. Binding Modes
3.4. An Atlas of the Inhibitors against SARS-CoV-2
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Sample Availability
References
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Targets | Short Name | Organism | Solved Structures (Solved Complexes) |
---|---|---|---|
Host translation inhibitor nsp1 | nsp1 | SARS-CoV-2 | 21 (0) |
Non-structural protein 3 | nsp3, PLpro | SARS-CoV-2 | 308 (262) |
3C-like proteinase | nsp5, 3CLpro, Mpro | SARS-CoV-2 | 369 (177) |
Non-structural protein 9 | nsp9 | SARS-CoV-2 | 12 (0) |
RNA-directed RNA polymerase | nsp12, RdRp | SARS-CoV-2 | 28 (9) |
Helicase | nsp13, Hel | SARS-CoV-2 | 67 (58) |
Proofreading exoribonuclease | nsp14, ExoN | SARS-CoV-2 | 11 (0) |
Uridylate-specific endoribonuclease | nsp15 | SARS-CoV-2 | 44 (26) |
2’-O-methyltransferase | nsp16 | SARS-CoV-2 | 28 (24) |
Spike glycoprotein | S | SARS-CoV-2 | 466 (13) |
Nucleoprotein | N | SARS-CoV-2 | 21 (0) |
Angiotensin-converting enzyme 2 | ACE2 | Homo sapiens | 58 (1) |
Transmembrane protease serine 2 | TMPRSS2 | Homo sapiens | 1 (1) |
Dihydroorotate dehydrogenase | DHODH | Homo sapiens | 79 (75) |
Proteinase-activated receptor 1 | PAR-1 | Homo sapiens | 5 (1) |
Target | #Refs | #Hits | Target | #Refs | Hits |
---|---|---|---|---|---|
nsp1 | 2 | 14 | nsp16 | 2 | 25 |
PLpro | 12 | 74 | S | 34 | 114 |
Mpro | 124 | 457 | N | 5 | 18 |
nsp9 | 2 | 9 | ACE2 | 16 | 69 |
RdRp | 23 | 70 | TMPRSS2 | 6 | 29 |
Helicase | 2 | 5 | DHODH | 1 | 27 |
ExoN | 2 | 2 | PAR-1 | 1 | 2 |
NendoU | 2 | 12 |
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Liu, Y.; Gan, J.; Wang, R.; Yang, X.; Xiao, Z.; Cao, Y. DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design. Molecules 2022, 27, 683. https://doi.org/10.3390/molecules27030683
Liu Y, Gan J, Wang R, Yang X, Xiao Z, Cao Y. DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design. Molecules. 2022; 27(3):683. https://doi.org/10.3390/molecules27030683
Chicago/Turabian StyleLiu, Yang, Jianhong Gan, Rongqi Wang, Xiaocong Yang, Zhixiong Xiao, and Yang Cao. 2022. "DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design" Molecules 27, no. 3: 683. https://doi.org/10.3390/molecules27030683