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Analysis of natural compounds against the activity of SARS-CoV-2 NSP15 protein towards an effective treatment against COVID-19: a theoretical and computational biology approach
- Source :
- Journal of Molecular Modeling
- Publication Year :
- 2021
- Publisher :
- Springer Berlin Heidelberg, 2021.
-
Abstract
- Coronavirus infectious disease 2019 (COVID-19), a viral infection caused by a novel coronavirus (nCoV), continues to emerge as a serious threat to public health. This pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome–coronavirus-2) has infected globally with 1,550,000 plus deaths to date, representing a high risk to public health. No effective drug or vaccine is available to curb down this deadly virus. The expedition for searching for a potential drug or vaccine against COVID-19 is of massive potential and favour to the community. This study is focused on finding an effective natural compound that can be processed further into a potential inhibitor to check the activity of SARS-CoV-2 with minimal side effects targeting NSP15 protein, which belongs to the EndoU enzyme family. The natural screening suggested two efficient compounds (PubChem ID: 95372568 and 1776037) with dihydroxyphenyl region of the compound, found to be important in the interaction with the viral protein showing promising activity which may act as a potent lead inhibitory molecule against the virus. In combination with virtual screening, modelling, drug likeliness, molecular docking, and 500 ns cumulative molecular dynamics simulations (100 ns for each complex) along with the decomposition analysis to calculate and confirm the stability and fold, we propose 95372568 and 1776037 as novel compounds of natural origin capable of getting developed into potent lead molecules against SARS-CoV-2 target protein NSP15. Supplementary Information The online version contains supplementary material available at 10.1007/s00894-021-04750-z.
- Subjects :
- Virtual screening
Viral protein
NSP15
Computational biology
Biology
Molecular Dynamics Simulation
Viral Nonstructural Proteins
010402 general chemistry
medicine.disease_cause
01 natural sciences
Molecular Docking Simulation
Antiviral Agents
Catalysis
Virus
Inorganic Chemistry
0103 physical sciences
Endoribonucleases
medicine
Humans
Physical and Theoretical Chemistry
Coronavirus
Original Paper
Biological Products
010304 chemical physics
Pandemic
SARS-CoV-2
Organic Chemistry
COVID-19
Computational Biology
0104 chemical sciences
Computer Science Applications
COVID-19 Drug Treatment
Computational Theory and Mathematics
Infectious disease (medical specialty)
Target protein
PubChem
Subjects
Details
- Language :
- English
- ISSN :
- 09485023 and 16102940
- Volume :
- 27
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Journal of Molecular Modeling
- Accession number :
- edsair.doi.dedup.....89d7a314b905430027f66f3bf2bff26a