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DC Field | Value | Language |
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dc.contributor.author | Sk, Md Fulbabu | en_US |
dc.contributor.author | Kar, Parimal | en_US |
dc.date.accessioned | 2022-03-17T01:00:00Z | - |
dc.date.accessioned | 2022-03-17T15:30:45Z | - |
dc.date.available | 2022-03-17T01:00:00Z | - |
dc.date.available | 2022-03-17T15:30:45Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Masand, V. H., Sk, M. F., Kar, P., Rastija, V., & Zaki, M. E. A. (2021). Identification of food compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations. Chemometrics and Intelligent Laboratory Systems, 217 doi:10.1016/j.chemolab.2021.104394 | en_US |
dc.identifier.issn | 0169-7439 | - |
dc.identifier.other | EID(2-s2.0-85111157528) | - |
dc.identifier.uri | https://doi.org/10.1016/j.chemolab.2021.104394 | - |
dc.identifier.uri | https://dspace.iiti.ac.in/handle/123456789/3824 | - |
dc.description.abstract | SARS-CoV-2 has rapidly emerged as a global pandemic with high infection rate. At present, there is no drug available for this deadly disease. Recently, Mpro (Main Protease) enzyme has been identified as essential proteins for the survival of this virus. In the present work, Lipinski's rules and molecular docking have been performed to identify plausible inhibitors of Mpro using food compounds. For virtual screening, a database of food compounds was downloaded and then filtered using Lipinski's rule of five. Then, molecular docking was accomplished to identify hits using Mpro protein as the target enzyme. This led to identification of a Spermidine derivative as a hit. In the next step, Spermidine derivatives were collected from PubMed and screened for their binding with Mpro protein. In addition, molecular dynamic simulations (200 ns) were executed to get additional information. Some of the compounds are found to have strong affinity for Mpro, therefore these hits could be used to develop a therapeutic agent for SARS-CoV-2. © 2021 Elsevier B.V. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier B.V. | en_US |
dc.source | Chemometrics and Intelligent Laboratory Systems | en_US |
dc.title | Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations | en_US |
dc.type | Journal Article | en_US |
dc.rights.license | All Open Access, Bronze, Green | - |
Appears in Collections: | Department of Biosciences and Biomedical Engineering |
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