Folding of Cu, Zn superoxide dismutase and familial amyotrophic lateral sclerosis

Cu, Zn superoxide dismutase (SOD1) has been implicated in the familial form of the neurodegenerative disease amyotrophic lateral sclerosis (ALS). It has been suggested that mutant mediated SOD1 misfolding/aggregation is an integral part of the pathology of ALS. We study the folding thermodynamics and kinetics of SOD1 using a hybrid molecular dynamics approach. We reproduce the experimentally observed SOD1 folding thermodynamics and find that the residues which contribute the most to SOD1 thermal stability are also crucial for apparent two-state folding kinetics. Surprisingly, we find that these residues are located on the surface of the protein and not in the hydrophobic core. Mutations in some of the identified residues are found in patients with the disease. We argue that the identified residues may play an important role in aggregation. To further characterize the folding of SOD1, we study the role of cysteine residues in folding and find that non-native disulfide bond formation may significantly alter SOD1 folding dynamics and aggregation propensity.     

Evaluation of immunostimulatory and growth promoting effect of seed fractions of Achyranthes aspera in common carp Cyprinus carpio and identification of active constituents

Immunostimulatory and growth promoting properties of Achyranthes aspera seeds were studied with larvae of common carp Cyprinus carpio. Four experimental diets were prepared using raw (D1) and alcohol (D2), petroleum ether (D3) and 50% aqueous alcohol (D4) extracts of A. aspera seeds. Diet without seed served as control (D5). Fish were fed with test/control diet for 30 days and then immunized with 10 μl of c-RBC. Blood samples were collected 7 days after immunization. Survival (93 ± 3%) of fish was significantly (P < 0.05) higher in D1 diet fed group compared to others. Highest specific growth rate was found in fish fed with diet D2. Significantly (P < 0.05) higher levels of serum protein and albumin were found in D1 and D3 compared to others. Highest serum globulin level was found in D1, which was followed by D3, D2, D4 and D5. Hemagglutination titer level was 5-18 folds higher in diet D3 fed fish compared to others. SGOT and SGPT levels were significantly (P < 0.05) higher in control group compared to the treated groups. Myeloperoxidase activity was significantly (P < 0.05) higher in D1 (2.513 ± 0.27 λ 450 nm) and D3 (2.38 ± 0.07 λ 450 nm) diets fed groups compared to others. The best performance of fish was found in raw A. aspera seeds incorporated diet fed group and the active constituents were identified as ecdysterone and two essential fatty acids linolenic acid and oleic acid.     

Can contact potentials reliably predict stability of proteins?

The simplest approximation of interaction potential between amino acid residues in proteins is the contact potential, which defines the effective free energy of a protein conformation by a set of amino acid contacts formed in this conformation. Finding a contact potential capable of predicting free energies of protein states across a variety of protein families will aid protein folding and engineering in silico on a computationally tractable time-scale. We test the ability of contact potentials to accurately and transferably (across various protein families) predict stability changes of proteins upon mutations. We develop a new methodology to determine the contact potentials in proteins from experimental measurements of changes in protein's thermodynamic stabilities (DeltaDeltaG) upon mutations. We apply our methodology to derive sets of contact interaction parameters for a hierarchy of interaction models including solvation and multi-body contact parameters. We test how well our models reproduce experimental measurements by statistical tests. We evaluate the maximum accuracy of predictions obtained by using contact potentials and the correlation between parameters derived from different data-sets of experimental (DeltaDeltaG) values. We argue that it is impossible to reach experimental accuracy and derive fully transferable contact parameters using the contact models of potentials. However, contact parameters may yield reliable predictions of DeltaDeltaG for datasets of mutations confined to the same amino acid positions in the sequence of a single protein.     

Effect of Al and heavy metals on enzymes of nitrogen metabolism of fast and slow growing rhizobia under explanta conditions

Most of the legume crops are affected by metal stress present in the soil mainly due to contaminated agrochemicals and sewage sludge. The effect of aluminium, and heavy metals copper, iron and molybdenum on growth and activity of enzymes of fast and slow growing rhizobial sps. was studied. Sinorhizobium meliloti RMP₅ was found to be more tolerant to metal stress than Bradyrhizobium BMP₁. Both the strains were extremely sensitive to Al than other metals. Al was much more deleterious for the enzymatic activities (nitrate reduction, nitrite reduction, nitrogenase and uptake hydrogenase) of strain RMP₅ and BMP₁. Cu showed inhibitory effect on growth and enzyme activities of Bradyrhizobium strain at all concentrations. However, in S. meliloti RMP₅ all the tested enzymatic activities increased up to the concentration of 0.1 mM Cu. Fe enhanced the growth and enzyme activities of S. meliloti RMP₅ and Bradyrhizobium BMP₁ up to 100 mM concentration. Mo enhanced all the tested enzymatic activities of S. meliloti RMP₅ up to 1 mM. Nitrate and nitrite reduction activities of Bradyrhizobium BMP₁ increased up to 1 mM concentration. However, nitrogenase and hydrogenase activities of Bradyrhizobium BMP₁ got enhanced only up to 0.5 mM Mo. Both Fe and Mo are the key components of the enzyme nitrogenase and nitrate reductase and enhanced the growth and enzyme activities of both the sps. The study of physiology of nitrogen fixing ability of both fast and slow growing rhizobial strains reported that the supplementation of Mo and Fe in soils along with the biological formulations will enhance the process of symbiotic nitrogen fixation.     

Proline-Rich Peptide from the Coral Pathogen Vibrio shiloi That Inhibits Photosynthesis of Zooxanthellae

The coral-bleaching bacterium Vibrio shiloi biosynthesizes and secretes an extracellular peptide, referred to as toxin P, which inhibits photosynthesis of coral symbiotic algae (zooxanthellae). Toxin P was produced during the stationary phase when the bacterium was grown on peptone or Casamino Acids media at 29°C. Glycerol inhibited the production of toxin P. Toxin P was purified to homogeneity, yielding the following 12-residue peptide: PYPVYAPPPVVP (molecular weight, 1,295.54). The structure of toxin P was confirmed by chemical synthesis. In the presence of 12.5 mM NH₄Cl, pure natural or synthetic toxin P (10 μM) caused a 64% decrease in the photosynthetic quantum yield of zooxanthellae within 5 min. The inhibition was proportional to the toxin P concentration. Toxin P bound avidly to zooxanthellae, such that subsequent addition of NH₄Cl resulted in rapid inhibition of photosynthesis. When zooxanthellae were incubated in the presence of NH₄Cl and toxin P, there was a rapid decrease in the pH (pH 7.8 to 7.2) of the bulk liquid, suggesting that toxin P facilitates transport of NH₃ into the cell. It is known that uptake of NH₃ into cells can destroy the pH gradient and block photosynthesis. This mode of action of toxin P can help explain the mechanism of coral bleaching by V. shiloi.     

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants

There is great interest in increasing proteins’ stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt’s reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔT _m = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.