Vote for your favorite mineral in #MinCup25! - Stibnite vs. Okenite
It's a battle of dark and light as soft, dramatic stibnite goes up against adorable cottonballs of Okenite.
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Kashyap, Jatin, Datta, Dibakar (2022) Drug repurposing for SARS-CoV-2: a high-throughput molecular docking, molecular dynamics, machine learning, and DFT study. Journal of Materials Science, 57 (23) 10780-10802 doi:10.1007/s10853-022-07195-8

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleDrug repurposing for SARS-CoV-2: a high-throughput molecular docking, molecular dynamics, machine learning, and DFT study
JournalJournal of Materials Science
AuthorsKashyap, JatinAuthor
Datta, DibakarAuthor
Year2022 (June)Volume57
Issue23
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s10853-022-07195-8Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15052703Long-form Identifiermindat:1:5:15052703:1
GUID0
Full ReferenceKashyap, Jatin, Datta, Dibakar (2022) Drug repurposing for SARS-CoV-2: a high-throughput molecular docking, molecular dynamics, machine learning, and DFT study. Journal of Materials Science, 57 (23) 10780-10802 doi:10.1007/s10853-022-07195-8
Plain TextKashyap, Jatin, Datta, Dibakar (2022) Drug repurposing for SARS-CoV-2: a high-throughput molecular docking, molecular dynamics, machine learning, and DFT study. Journal of Materials Science, 57 (23) 10780-10802 doi:10.1007/s10853-022-07195-8
In(2022, June) Journal of Materials Science Vol. 57 (23) Springer Science and Business Media LLC

See Also

These are possibly similar items as determined by title/reference text matching only.

Srisongkram, Tarapong, Weerapreeyakul, Natthida (2022) Drug Repurposing against KRAS Mutant G12C: A Machine Learning, Molecular Docking, and Molecular Dynamics Study. International Journal of Molecular Sciences, 24 (1) 669 doi:10.3390/ijms24010669
Solanky, Priyanka, Sharma, Vidushi, Ghatak, Kamalika, Kashyap, Jatin, Datta, Dibakar (2019) The inherent behavior of graphene flakes in water: A molecular dynamics study. Computational Materials Science, 162. 140-147 doi:10.1016/j.commatsci.2019.02.021
Mannodi-Kanakkithodi, Arun, Chan, Maria K. Y. (2022) Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning. Journal of Materials Science, 57 (23) 10736-10754 doi:10.1007/s10853-022-06998-z
Erdogan, Taner (2021) DFT, molecular docking and molecular dynamics simulation studies on some newly introduced natural products for their potential use against SARS-CoV-2. Journal of Molecular Structure, 1242. 130733 doi:10.1016/j.molstruc.2021.130733
Faria, Sergio H.D.M., Teleschi, João G. (2021) Computational search for drug repurposing to identify potential inhibitors against SARS-COV-2 using Molecular Docking, QTAIM and IQA methods in viral Spike protein – Human ACE2 interface. Journal of Molecular Structure, 1232. 130076 doi:10.1016/j.molstruc.2021.130076
Khadka, Rajan, Keblinski, Pawel (2022) Molecular dynamics study of domain switching dynamics in KNbO3 and BaTiO3. Journal of Materials Science, 57 (27) 12929-12946 doi:10.1007/s10853-022-07407-1
Rampogu, Shailima, Lee, Gihwan, Park, Jun Sung, Lee, Keun Woo, Kim, Myeong Ok (2022) Molecular Docking and Molecular Dynamics Simulations Discover Curcumin Analogue as a Plausible Dual Inhibitor for SARS-CoV-2. International Journal of Molecular Sciences, 23 (3) 1771pp. doi:10.3390/ijms23031771
Datta, Joy, Datta, Dibakar, Sharma, Vidushi (2023) Transferable and robust machine learning model for predicting stability of Si anodes for multivalent cation batteries. Journal of Materials Science, 58 (27) Springer Science and Business Media LLC. 11085-11099 doi:10.1007/s10853-023-08705-y
Chhetri, Sandeep Poudel, Bhandari, Vishal Singh, Maharjan, Rajesh, Lamichhane, Tika Ram (2024) Identification of lead inhibitors for 3CLpro of SARS-CoV-2 target using machine learning based virtual screening, ADMET analysis, molecular docking and molecular dynamics simulations. RSC Advances, 14 (40). doi:10.1039/d4ra04502e
Zhang, Chunye, Liu, Jiazheng, Sui, Yuxiang, Liu, Shuai, Yang, Ming (2023) In silico drug repurposing carvedilol and its metabolites against SARS-CoV-2 infection using molecular docking and molecular dynamic simulation approaches. Scientific Reports, 13 (1) doi:10.1038/s41598-023-48398-6
You, Wanli, Chen, Yuandao (2023) Exploring the inhibition mechanism of SARS‐CoV‐2 main protease by ebselen: A molecular docking, molecular dynamics simulation and DFT approach. Journal of Computational Chemistry, 44 (26) Wiley. 2086-2095 doi:10.1002/jcc.27181
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 2, 2025 21:50:48
Go to top of page