Insilico modeling of chitosan as a drug delivery system

Computational modeling of polymeric nanoparticles as drug carriers have been extensively studied due to their varied functionalities, tunable structures and the capability of controlled drug release. Nano particulate polymeric drug delivery systems enable a cell specific targeting with negligible side effects and drug release based on change in physiological conditions. Eight common polymers are modeled and the various properties have been predicted. ADMET, QSAR, thermodynamic and electronic properties have been predicted and compared using SAR as well as quantum mechanical density functional methods. Comparison of the predicted properties suggests that chitosan, which is a natural polymer and has some advantages over others is a promising drug carrier candidate for tumor

Structural Studies of Cu(II) & Ni(II) Complexes with a Chiral Schiff Base

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DESIGN AND DEVELOPMENT OF A PHARMACOGENOMIC MODEL FOR BREAST CANCER TO STUDY THE VARIATION IN DRUG ACTION AND SIDE EFFECTS

Objective: The proneness of disease, as well as drug action and side effects, vary from person to person. This may be due to individual variations in the genome. The individual variation demands the need to design a population-specific 'predictive, preventive, participatory and personalized (p4)' pharmacogenomics drug molecule. The present work aims at designing a pharmacogenomic model for breast cancer to explain the individual variation in the proneness of the diseases and susceptibility towards drug action. Methods: The drug action and side effects of drugs were analyzed from clinical trial reports. The genes responsible for the drug action and the genes responsible for side effects have been identified and included in the variation analysis. The pharmacogenomic gene models have been designed by inducing population-specific genetic variations within the gene sequence. The 3D structures of the 'variation-specific' protein models have been generated by 'homology modelling.' These models have been used further for docking studies with the known drug molecules. The kinetic stability of the protein-ligand complexes obtained out of docking studies has been studied by the molecular dynamic simulation. Results: By the interaction studies and the computational analysis using the 'population-specific protein models,' the drug molecule, Capecitabine showed the highest binding affinity (–6.30kcal/mol) with the African population, Paclitaxel was found to be the most interacting with the European population with a binding affinity of–9.5603 kcal/mol, and Lapatinib is found to be the most suitable ligand for the American population with a binding affinity of–6.90 kcal/mol. These observations agree with the clinical trial data found in the 'ClinTrial database'. Conclusion: The designed models are found to be suitable for representing the respective population-specific target models. The interaction studies of known drug molecules with these population-specific target models correspond to the observations in the 'ClinTrial database.

‘BRCA1' RESPONSIVENESS TOWARDS BREAST CANCER-A POPULATION-WISE PHARMACOGENOMIC ANALYSIS

Objective: In the present pharmacogenomic work, the genetic, epigenetic and environmental factors associated with BRCA1 induced breast cancer, cancer proneness and its variants across different populations like Indian, Netherland, Belgium, Denmark, Austrian, New Zealand, Sweden, Malaysian and Norwegian and the ‘mutation and methylation-prone' region of BRCA1 have been computed.Methods: The global variations associated with the disease have been identified from the ‘Leiden open variation database (LOVD 3.0)' and ‘Indian genome variation database (IGVDB)'. The variants, ‘single nucleotide polymorphisms (SNPs)' are then characterized. The epigenetic factors associated with breast cancer have been identified from the clinical reports and further scrutinized using EpiGRAPH tool. The various contributing environmental factors responsible for the variations have been considered.Results: All the variants across different populations such as Indian, Netherland, Belgium, Denmark, Austrian, New Zealand, Sweden, Malaysian and Norwegian are found to be in a specific transcript of BRCA1 that ranges within 41,196,312-41,277,500 (81,189 base pairs) of the chromosome 17. Two ‘single nucleotide variations (SNVs)' (5266dupC: rs397507246 and 68_69delAG: rs386833395) have been identified as risk factors in hereditary breast and ovarian cancer syndrome in the global population and 39 SNPs have been identified as pathogenic and deleterious. ‘Evolutionary history' seems to be the most significant attribute in the predictability of methylation of BRCA1. Unhealthy dietary habits, obesity, use of unsafe cosmetics, estrogen exposure, ‘hormone replacement therapy (HRT)', use of oral contraceptives and smoking are the major environmental risk factors associated with breast cancer incidence.Conclusion: This chromosome location (41,196,312-41,277,500 (81,189 base pairs)) can be considered as the population-specific sensitive region corresponding to BRCA1 mutation. This supports the fact that stabilization within the region can be a promising technique to control the epigenetic variants associated with the global position. The global variation in the proneness of the disease may be due to a cumulative effect of genetic, epigenetic and environmental factors subject to further experimentations with identical variations and populations.Â