Pratigya Silakari

Dr. Harisingh Gour University, Sāgar, State of Madhya Pradesh, India

Are you Pratigya Silakari?

Claim your profile

Publications (2)5.04 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Three-dimensional quantitative structure activity relationship (3D-QSAR) models was developed using molecular field analysis (MFA) for 36 anilinoquinazoline derivatives, inhibiting c-Src kinase. The QSAR model was developed using 29 compounds and its predictive ability was assessed using a test set of seven compounds. The predictive 3D-QSAR model has conventional r 2 values of 0.961 while the cross-validated coefficient q 2 and bootstrap correlation coefficient r BS2 values of 0.910 and 0.957, respectively. The developed model provides a powerful tool to design potent c-Src inhibitors as novel antitumor agents. Six new inhibitors were designed and their pIC50 were predicted. Keywordsc-Src kinase–Molecular Fields Analysis–QSAR–Anilinoquinazolines
    Medicinal Chemistry Research 01/2011; 20(2):158-167. · 1.61 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Quantitative structure-activity relationship (QSAR) analysis was performed on a series of 1,3-diaryl-4,5,6,7-tetrahydro-2H-isoindole for their cyclooxygenase-2 (COX-2) inhibition. QSAR investigations were based on Hansch's extra thermodynamic multi-parameter approach and receptor surface analysis (RSA). QSAR investigations reveal that steric and electrostatic interactions are primarily responsible for COX-2 enzyme-ligand interaction. QSAR model derived from Hansch analysis demonstrated that COX-2 inhibitory activity is correlated with sum of atomic polarizability (Apol), number of hydrogen-bond donor groups (HBD), energy of the highest occupied molecular orbital (HOMO), desolvation free energy for water (F(H(2)O)) and fraction of areas of molecular shadow in the XY and ZX planes over area of enclosing rectangle (Sxyf and Sxzf) with r ranges 0.870-0.904. The best model was obtained from RSA model having r = 0.940 with good predictive ability (predicted compounds in training set and test set within +/- 1.0 unit of pIC(50)) and can be used in designing better selective COX-2 inhibitors among the congeners in future.
    European Journal of Medicinal Chemistry 08/2008; 43(7):1559-69. · 3.43 Impact Factor