ABSTRACT
The multiple drug resistance in MRSA (Methicillin resistant Staphylococcus aureus) has become a major clinical problem worldwide. Methicillin resistance (mediated by PBP2a protein) is a serious issue limiting treatment options and necessitating the search of newer safe and effective alternative treatment regimens. Aim of the present study was to evaluate the potential of the plant product ‘Curcumin’ and its derivatives as effective antibacterial agents by means of insilico based studies. Computer aided drug designing is an initial platform helpful to screen novel inhibitors and has tremendous application in the development of new drugs. In the present study a series of 16 derivatives of curcumin were constructed and optimized using chemsketch software.Molecular docking was performed using the GOLD (Genetic Optimization of Ligand Docking) software which is based on genetic algorithm (GA), to study the binding orientation of these derivatives into the PBP2a structure. Derivative 10 (1E,6E)-1,7-bis(3- hydroperoxy-4-hydroxyphenyl)hepta-1,6-diene-3,5-dione) showed best docking fitness value compared to other derivatives(including Curcumin). The molecular, physicochemical, and biological properties were calculated (through molinspiration cheminformatics software) for compounds showing the best docking scores. These compounds were further subjected to toxicity predictions using the Osiris software.
ABSTRACT
Genetic divergence using D2 statistic of forty genotypes of various agro-climatic region for ten quantitative characters revealed existence of considerable genetic diversity in the material. The genotypes were grouped into eleven clusters. Cluster VIII contained the highest number of nine genotypes followed by cluster V with seven genotypes. The pattern of distribution of genotypes from different geographical location into eleven clusters were random, demonstrating that geographical isolation may not be the only factor causing genetic diversity. The highest intra-cluster distance was observed for cluster VI (112.02) and the lowest was observed for cluster II (6.24). While the highest inter-cluster distance was observed between cluster III and X (493.41). Harvest index contributed maximum to diversity. Cluster IX with WGG-66 recorded the highest mean for yield contributing characters viz., plant height, branches/plant, pods/plant and clusters/plant. Therefore it was suggested that more emphasis should be given this genotype as parents for crossing with genotypes of other clusters which may produce novel recombinants with desirable traits.