ABSTRACT
Organisms that are commonly used as biofertilizers component are nitrogen fixers (N-fixer), potassium solubilizer (K-solubilizer) and phosphorus solubilizer (P- solubilizer), or with the combination of molds or fungi. Most of the bacteria included in biofertilizer have close relationship with plant roots. In this work we have selected plumbago zeylanica.L plant to study the effect of Azotobacter on the growth of roots, stem, and leaves. Also biochemical characterization was done to identify the effect of Azotobacter in Plumbago. The maximum shoot length was recorded in T4 plants (43.51) on 90th days of plant growth after transplanting the plants. There was a significant increase at 5 % level in the root length from 30th days to 90th days in all the treatments. The maximum number of leaves were found in T4 treatment followed by T3 and T2. Minimum numbers of leaves were found in T1 (1083). On 60th day and 90th day also the total chlorophyll content was maximum in T4 treated plants followed by T3, T2 plants. The amount of reducing sugars (μg/g) in shoots of T4, T3 and T2 plants on 30th, 60th and 90th days were significantly high when compared to T1 plants. The content of protein in roots of T2, T3 and T4 plants on 30th, 60th and 90th days were significantly high when compared to protein content of T1 plants.
ABSTRACT
Most of the antigens of Mycobacterium leprae that have been identified are members of stress protein families. 18kDa antigen of M. leprae is an important antigen in the immune response to leprosy. This protein antigen of M. leprae is related to the family of small heat shock protein. To predict the structure of 18kDa antigen and to understand the mechanisms of inhibitors interaction, a threedimensional model was generated based on the Crystal Structure and assembly of eukaryotic small heat shock protein (PDB: 1GME) by using MODELLER7v7. The structure having a least modeller objective function was used as a starting point for picoseconds-duration molecular dynamics simulations. With the aid of the molecular dynamics and minimization methods, the final refined model was obtained and was further assessed by ERRAT, WHATCHECK and PROCHECK, which suggested that the refined model was reliable. Docking studies were performed by using the models with 2-mercaptoethanol and 3-amino- 5-methylhexanoic acid inhibitors. The results indicate that the 3-amino-5,5-diphenylpentanoic acid has more affinity than the other drug derivatives. The docking studies also suggest that MET-03, ARG-04, ASP-31, ALA-32, TRP-33, ARG-34, GLU-35 ARG-89, GLN-90 LEU-91 and VAL-92 are important determinant residues in binding with ligands. From the docking studies, we also suggest that GLU-35, in 18kDa protein domain is an important residue in binding.