Repository logo
Institutional Repository
Communities & Collections
Browse
Quick Links
  • Central Library
  • Digital Library
  • BHU Website
  • BHU Theses @ Shodhganga
  • BHU IRINS
  • Login
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Satish Kumar Rajouria"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    PublicationArticle
    Analogue and structure based approaches for modelling HIV-1 integrase inhibitors
    (Taylor and Francis Ltd., 2023) Anurag Upadhyaya; Bhavana Panthi; Shubham Verma; Suresh Kumar; Satish Kumar Rajouria; Hemant Kumar Srivastava; Pranjal Chandra
    A set of 220 inhibitors belonging to different structure classes and having HIV-1 integrase activity were collected along with their experimental pIC50 values. Geometries of all the inhibitors were fully optimized using B3LYP/6-31 + G(d) level of theory. These ligands were docked against 4 different HIV-1 integrase receptors (PDB IDs: 4LH5, 5KRS, 3ZSQ and 3ZSV). 30 docked poses were generated for all 220 inhibitors and ligand interaction of the first docked pose and the docked pose with the highest score were analysed. Residue GLU170 of 4LH5 receptor shows the highest number of interactions followed by ALA169, GLN168, HIS171 and ASP167 residues. Hydrogen bonding and stacking are mainly responsible for the interactions of these inhibitors with the receptor. We performed Molecular Dynamics (MD) simulation to observe the root-mean-square deviation (RMSD), for measure the average change of displacement between the atoms for a particular frame with respect to a reference and The Root Mean Square Fluctuation (RMSF) for characterization of local changes along the protein chain of the docked complexes. Analogue based models were generated to predict the pIC50 values for integrase inhibitors using various types of descriptors such as constitutional, geometrical, topological, quantum chemical and docking based descriptors. The best models were selected on the basis of statistical parameters and were validated by training and test set division. A few new inhibitors were designed on the basis of structure activity relationship and their pIC50 values were predicted using the generated models. All the designed new inhibitors a very high potential and may be used as potent inhibitors of HIV integrase. These models may be useful for further design and development of new and potent HIV integrase inhibitors. Communicated by Ramaswamy H. Sarma. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
An Initiative by BHU – Central Library
Powered by Dspace