Record Details

Predictive modeling and therapeutic repurposing of natural compounds against the receptor-binding domain of SARS-CoV-2

KRISHI: Publication and Data Inventory Repository

View Archive Info
 
 
Field Value
 
Title Predictive modeling and therapeutic repurposing of natural compounds against the receptor-binding domain of SARS-CoV-2
Not Available
 
Creator Manoj Kumar Yadav
Shaban Ahmad
Khalid Raza
Sunil Kumar
Murugesh Eswaran
Mussuvir Pasha KM
 
Subject SARS-CoV-2
receptor binding domain
machine learning models
deep screening
molecular dynamics simulation
 
Description Not Available
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a member of the Coronaviridae fam ily, causing major destructions to human life directly and indirectly to the economic crisis around the
world. Although there is significant reporting on the whole genome sequences and updated data for
the different receptors are widely analyzed and screened to find a proper medication. Only a few bio assay experiments were completed against SARS-CoV-2 spike protein. We collected the compounds
dataset from the PubChem Bioassay database having 1786 compounds and split it into the ratio of
80–20% for model training and testing purposes, respectively. Initially, we have created 11 models
and validated them using a fivefold validation strategy. The hybrid consensus model shows a predict ive accuracy of 95.5% for training and 94% for the test dataset. The model was applied to screen a vir tual chemical library of Natural products of 2598 compounds. Our consensus model has successfully
identified 75 compounds with an accuracy range of 70–100% as active compounds against SARS-CoV 2 RBD protein. The output of ML data (75 compounds) was taken for the molecular docking and
dynamics simulation studies. In the complete analysis, the Epirubicin and Daunorubicin have shown
the docking score of 9.937 and 9.812, respectively, and performed well in the molecular dynamics
simulation studies. Also, Pirarubicin, an analogue of anthracycline, has widely been used due to its
lower cardiotoxicity. It shows the docking score of 9.658, which also performed well during the com plete analysis. Hence, after the following comprehensive pipeline-based study, these drugs can be fur ther tested in vivo for further human utilization.
Not Available
 
Date 2022-05-21T05:00:59Z
2022-05-21T05:00:59Z
2021-12-01
 
Type Research Paper
 
Identifier Manoj Kumar Yadav, Shaban Ahmad, Khalid Raza, Sunil Kumar, Murugesh Eswaran & Mussuvir Pasha KM (2022) Predictive modeling and therapeutic repurposing of natural compounds against the receptor-binding domain of SARS-CoV-2, Journal of Biomolecular Structure and Dynamics, DOI: 10.1080/07391102.2021.2021993
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/72346
 
Language English
 
Relation Not Available;
 
Publisher Taylor & Francis