Visual spatial memory is enhanced in female rats (but inhibited in males) by dietary soy phytoestrogens

Background  

In learning and memory tasks, requiring visual spatial memory (VSM), males exhibit superior performance to females (a difference attributed to the hormonal influence of estrogen). This study examined the influence of phytoestrogens (estrogen-like plant compounds) on VSM, utilizing radial arm-maze methods to examine varying aspects of memory. Additionally, brain phytoestrogen, calbindin (CALB), and cyclooxygenase-2 (COX-2) levels were determined.     

Hydrogen bond networks determine emergent mechanical and thermodynamic properties across a protein family

Background

Gram-negative bacteria use periplasmic-binding proteins (bPBP) to transport nutrients through the periplasm. Despite immense diversity within the recognized substrates, all members of the family share a common fold that includes two domains that are separated by a conserved hinge. The hinge allows the protein to cycle between open (apo) and closed (ligated) conformations. Conformational changes within the proteins depend on a complex interplay of mechanical and thermodynamic response, which is manifested as an increase in thermal stability and decrease of flexibility upon ligand binding.

Results

We use a distance constraint model (DCM) to quantify the give and take between thermodynamic stability and mechanical flexibility across the bPBP family. Quantitative stability/flexibility relationships (QSFR) are readily evaluated because the DCM links mechanical and thermodynamic properties. We have previously demonstrated that QSFR is moderately conserved across a mesophilic/thermophilic RNase H pair, whereas the observed variance indicated that different enthalpy-entropy mechanisms allow similar mechanical response at their respective melting temperatures. Our predictions of heat capacity and free energy show marked diversity across the bPBP family. While backbone flexibility metrics are mostly conserved, cooperativity correlation (long-range couplings) also demonstrate considerable amount of variation. Upon ligand removal, heat capacity, melting point, and mechanical rigidity are, as expected, lowered. Nevertheless, significant differences are found in molecular cooperativity correlations that can be explained by the detailed nature of the hydrogen bond network.

Conclusion

Non-trivial mechanical and thermodynamic variation across the family is explained by differences within the underlying H-bond networks. The mechanism is simple; variation within the H-bond networks result in altered mechanical linkage properties that directly affect intrinsic flexibility. Moreover, varying numbers of H-bonds and their strengths control the likelihood for energetic fluctuations as H-bonds break and reform, thus directly affecting thermodynamic properties. Consequently, these results demonstrate how unexpected large differences, especially within cooperativity correlation, emerge from subtle differences within the underlying H-bond network. This inference is consistent with well-known results that show allosteric response within a family generally varies significantly. Identifying the hydrogen bond network as a critical determining factor for these large variances may lead to new methods that can predict such effects.     

Chemical Synthesis of the Major Constituents of Salmonella Minnesota Monophosphoryl Lipid A

Abstract

Structural investigations have shown that lipid A constitutes the active principle of lipopoly saccharide (LPS, endotoxin), a complex amphipathic molecule located on the cell surface of Gram-negative bacteria.¹ Lipid A elicits not only the typical endotoxic reactions such as fever and lethal shock but also adjuvant, antitumor and other beneficial effects.¹ As a result, there has been a great deal of interest in the synthesis of lipid A derivatives possessing low toxicity.^1,2     

The application of homotopy analysis method to solve nonlinear differential equation governing Jeffery–Hamel flow

In this paper Jeffery–Hamel flow has been studied and its nonlinear ordinary differential equation has been solved through homotopy analysis method (HAM). The obtained solution in comparison with the numerical ones represents a remarkable accuracy. The results also indicate that HAM can provide us with a convenient way to control and adjust the convergence region.     

Neuromodulation by soy diets or equol: Anti-depressive &; anti-obesity-like influences,age- &; hormone-dependent effects

Background  

Soy-derived isoflavones potentially protect against obesity and depression. In five different studies we examined the influence of soy-containing diets or equol injections on depression, serotonin levels, body weight gain (BW) and white adipose tissue (WAT) deposition in female Long-Evans rats at various stages of life [rats were intact, ovariectomized or experienced natural ovarian failure (NOF)].     

At the crossroads of biomacromolecular research: highlighting the interdisciplinary nature of the field

Due to their complexity and wide-ranging utility, biomacromolecular research is an especially interdisciplinary branch of chemistry. It is my goal that the Biomacromolecules subject area of Chemistry Central Journal will parallel this richness and diversity. In this inaugural commentary, I attempt to set the stage for achieving this by highlighting several areas where biomacromolecular research overlaps more traditional chemistry sub-disciplines. Specifically, it is discussed how Materials Science and Biotechnology, Analytical Chemistry, Cell Biology and Chemical Theory are each integral to modern biomacromolecular research. Investigators with reports in any of these areas, or any other dealing with biomacromolecules, are encouraged to submit their research papers to Chemistry Central Journal.     

Predicting the melting point of human C-type lysozyme mutants

A complete understanding of the relationships between protein structure and stability remains an open problem. Much of our insight comes from laborious experimental analyses that perturb structure via directed mutation. The glycolytic enzyme lysozyme is among the most well characterized proteins under this paradigm, due to its abundance and ease of manipulation. To speed up such analyses, efficient computational models that can accurately predict mutation effects are needed. We employ a minimal Distance Constraint Model (mDCM) to predict the stability of a series of lysozyme mutants (specifically, human wild-type C-type lysozyme and 14 point mutations). With three phenomenological parameters that characterize microscopic interactions, the mDCM parameters are determined by obtaining the least squares error between predicted and experimental heat capacity curves. The mutants are chemically and structurally diverse, but have been experimentally characterized under nearly identical thermodynamic conditions (pH, ionic strength, etc.). The parameters found from best fits to heat capacity curves for one or more lysozyme structures are subsequently used to predict the heat capacity on the remaining. We simulate a typical experimental situation, where prediction of relative stabilities in an untested mutated structure is based on known results as they accumulate. From the statistical significance of these simulations, we establish that the mDCM is a viable predictor for relative stability of protein mutants. Remarkably, using parameters from any single fitting yields an average percent error of 4.3%. Across the dataset, the mDCM reproduces experimental trends sufficiently well (R = 0.64) to be of practical value to experimentalists when making decisions about which mutations to invest time and funds for characterization.