PhD Thesis: Development of techniques for studying QSAR of peptides

        Three methods developed based on QSAR principles to explain positional SAR in small                   peptides
  • First Peptide QSAR Method: Using the classical Hansch and Free-Wilson approaches. Different properties compiled from literature were used to develop QSAR model to explain and predict the specific nature and type of amino acids at different positions in a given peptide sequence to optimize the activity. This approach was tested on Major Histocompatibility Complex (MHC) binding peptides. (QSAR. & Comb. Sci. 2007, 26, 189-203)
  • Second Peptide QSAR Method: Implemented to reduce the uncertainties associated with the 3D-alignment of peptides (a critical step in 3D-QSAR studies).  This was achieved using principles of homology modelling to align the peptides using a multiple sequence alignment protocol.  The models were developed using Similarity indices calculated at every position of every peptide.  The method is coined as HomoSAR.  This approach was initially tested on nonamer peptide dataset belonging to MHC binding peptides (Sch. Res. Exch. 2008, 2008, Article ID 360572, 1-13) and later expanded to multiple datasets (J. Comput. Chem.  2013, 34, 2635–2646)
  • Third Peptide QSAR Method: Developed to address the conformational ensemble issue which is the improvement to the classical ‘one chemical–one structure–one parameter value’.  This method was referred to as ensemble QSAR (eQSAR) uses an ensemble of conformations for every peptide in the dataset.  A conformational ensembles of peptides generated using molecular dynamic simulation was processed using Physicochemical Distance matrices (PD-matrices) to generate PD-Eigen values unique to every conformation of every peptide which were treated using statistics to develop QSAR models.  This method was tested on multiple peptide datasets. (J. Comput. Chem. 2011, 32, 2204–2218)
Research Projects carried out at Bombay College of Pharmacy
  • Virtual screening of database (iResearch database) for Antimalarial targets viz. Enoyl Reductase (Mol. Divers. 2009, 13, 501-17) and Lactate Dehydrogenase (Anti-Infect. Agents 2012, 10, 55-71), to identify several new and potent hits for these targets. 
  • NMR and MD simulation of GIP/N-terminus GIPR (J. Pept. Sci. 2010, 16, 383-391)
  • Interaction studies of novel antidepressants with SERT. (Cent. Nerv. Syst. Agents – Med. Chem. 2011, 11, 228-237)
  • Pharmacophore Modeling and Virtual Screening of ZINC Database for Acetylcholine Esterase Inhibitors (J. Biomol. Struct. Dyn. 2014)
  • Drug β-cyclodextrin complexation studies for improved solubilization, coupled with computational studies for estimation of binding energies (On-Going)
  • Studies on polymeric micelles and drug loading (On-Going)
Research Projects carried out in collaboration with other Academic and Research Institutes

Department of Chemistry, University of Mumbai
  • Semi empirical calculations on Furo-fused BINOL based Crown Ethers in complex with phenylethyl amine and valine helped us understand enantioselective recognition in crown ethers (J. Org. Chem. 2007, 72, 5709-5714)
Department of Chemistry, Saurashtra University
  • 3D QSAR studies (CoMFA and CoMSIA) were carried out on molecules synthesized as anti-cancer, anti-diabetic, anti-malarial and anti-tubercular agents to extract those substituents that improve on the activity; this helped us design new molecules with improved activity. (Mol. Divers. 2010, 14, 285-305; Eur. J. Med. Chem. 2008, 43, 2103-2115)
Department of Chemistry, Panjab University
  • Computing binding energies of cyclodextrin complexes by molecular dynamics (Carbohydr. Polym. 2014, 101, 614-622; Results in Pharma Sci. 2011, 1, 38-48)
Department of Biological Sciences, University of Mumbai - Centre for Excellence in Basic Sciences
  • Ongoing Research Projects Protein-Protein Interaction studies on Glutaredoxins and BolA like Peptides
Department of Chemical Sciencess, University of Mumbai - Centre for Excellence in Basic Sciences
  • Studies on Interaction of multimicrobial synthetic inhibitor (PLoS ONE 2013, 8, e53499)
  • Studies on Prevention of Lysozyme fibril Formation (BBA - Prot. & Proteom. 2014, 1844, 670)
Indian Institute of Technology, Mumbai
  • Studies of covalently linked meso-furyl boron-dipyrromethene-ferrocene conjugates (J. Organomet. Chem. 2012, 697, 65)