Dipak Chetia (D Chetia)

Publication Activity (10 Years)

Years Active: 2021-2023
Publications (10 Years): 7

Top Topics

Machine Learning

Plasmodium Falciparum

Molecular Docking

Top Venues

SAR and QSAR in environmental research

Journal of biomolecular structure & dynamics

Structural chemistry

Future journal of pharmaceutical sciences

This page only lists publications with an associated author ORCID identifier.

Publications

James H Zothantluanga, Dipak Chetia, Sanchaita Rajkhowa, Abd Kakhar Umar
Unsupervised machine learning, QSAR modelling and web tool development for streamlining the lead identification process of antimalarial flavonoids. SAR and QSAR in environmental research (2023)
James H Zothantluanga, Dipak Chetia, Sanchaita Rajkhowa, Abd Kakhar Umar
Unsupervised machine learning, QSAR modelling and web tool development for streamlining the lead identification process of antimalarial flavonoids. SAR and QSAR in environmental research 34 (2) (2023)
James H Zothantluanga, Dipak Chetia, Sanchaita Rajkhowa, Abd Kakhar Umar
Unsupervised machine learning, QSAR modelling and web tool development for streamlining the lead identification process of antimalarial flavonoids. SAR and QSAR in environmental research 34 (2) (2023)
Malita Sarma, Mohnad Abdalla, James H Zothantluanga, Felwa Abdullah Thagfan, Abd Kakhar Umar, Dipak Chetia, Taghreed N Almanaa, Samia T Al-Shouli
Multi-target molecular dynamic simulations reveal glutathione-S-transferase as the most favorable drug target of knipholone in Plasmodium falciparum . Journal of biomolecular structure & dynamics (2023)
James H Zothantluanga, Dipak Chetia, Sanchaita Rajkhowa, Abd Kakhar Umar
Unsupervised machine learning, QSAR modelling and web tool development for streamlining the lead identification process of antimalarial flavonoids. SAR and QSAR in environmental research 34 (2) (2023)
Abd Kakhar Umar, James H Zothantluanga, Keerthic Aswin, Saipul Maulana, Muhammad Sulaiman Zubair, H Lalhlenmawia, Mithun Rudrapal, Dipak Chetia
Antiviral phytocompounds "ellagic acid" and "(+)-sesamin" of Bridelia retusa identified as potential inhibitors of SARS-CoV-2 3CL pro using extensive molecular docking, molecular dynamics simulation studies, binding free energy calculations, and bioactivity prediction. Structural chemistry 33 (5) (2022)
James H Zothantluanga, Neelutpal Gogoi, Anshul Shakya, Dipak Chetia, H Lalthanzara
Computational guided identification of potential leads from Acacia pennata (L.) Willd. as inhibitors for cellular entry and viral replication of SARS-CoV-2. Future journal of pharmaceutical sciences 7 (1) (2021)