The effects of resistant starch and whole grains on appetite, food intake and metabolic response.

With the rise in obesity, there has been an increased interest in foods which may beneficially affect appetite. Resistant starch (RS) and whole grains (of which RS is a main dietary fibre component) have been proposed to affect satiety and therefore may be beneficial in weight management. There is little direct evidence confirming this in humans. Whilst animal data suggest a positive effect of RS on appetite, the few existing human intervention studies provide inconsistent findings. For whole grains the majority of evidence is from epidemiological work as opposed to intervention studies. Therefore a series of studies was conducted to investigate effects of RS and whole grains on appetite and food intake. Two studies were conducted using RS. The first investigated the acute (24 hours) effects of 48 g RS in healthy adult males compared with an energy and available carbohydrate matched placebo. Following RS there was a significantly lower energy intake compared with placebo. There was also a significantly lower postprandial insulin response with RS, possibly explained by increased hepatic insulin clearance determined by a higher C-peptide to insulin ratio. In the second study 40 g RS consumed daily for 4 weeks was compared with the placebo, in overweight and obese participants. Effects on food intake were assessed and a frequently sampled intravenous glucose tolerance test (FSIVGTT) was conducted. This study found no effect on either appetite or energy intake, but did find significantly higher glucose, insulin and C-peptide concentrations, measured during the FSIVGTT, with the RS compared with the placebo, possibly explained by an improved first-phase insulin response. This finding did not translate into differences in parameters obtained from modelling the FSIVGTT data, but this and the lack of appetite and food intake differences could be explained by the small participant numbers. Two intervention studies were conducted with whole grains incorporated into bread rolls. The first, a crossover study, involved 3 weeks' daily consumption of 48 g milled whole grain or control, in young healthy adults. Whilst no significant difference was found between interventions in energy intake or subjective appetite ratings, a significantly lower systolic blood pressure was observed with the milled whole grains. The second was an 8 week parallel study (48 g intact or 48 g milled whole grains or control) in overweight and obese adults. No significant difference was found between groups on energy intake, subjective appetite ratings, cholesterol or postprandial metabolite concentrations. RS appears to be a possible satiating ingredient when consumed acutely and, whilst this was not confirmed in our chronic study, effects may have been masked by small participant numbers. A novel finding from our RS studies was an effect on the insulin response. These studies suggest that RS could have a beneficial role in weight management and favourable metabolic effects. Our whole grain interventions appear not to agree with epidemiological work that suggests a beneficial role on appetite, but there maybe effects on blood pressure regulation. In all instances further investigations are required in other population groups, with more participants and for longer time periods

An Electrostatic Funnel in the GABA-Binding Pathway

<div><p>The γ-aminobutyric acid type A receptor (GABA_A-R) is a major inhibitory neuroreceptor that is activated by the binding of GABA. The structure of the GABA_A-R is well characterized, and many of the binding site residues have been identified. However, most of these residues are obscured behind the C-loop that acts as a cover to the binding site. Thus, the mechanism by which the GABA molecule recognizes the binding site, and the pathway it takes to enter the binding site are both unclear. Through the completion and detailed analysis of 100 short, unbiased, independent molecular dynamics simulations, we have investigated this phenomenon of GABA entering the binding site. In each system, GABA was placed quasi-randomly near the binding site of a GABA_A-R homology model, and atomistic simulations were carried out to observe the behavior of the GABA molecules. GABA fully entered the binding site in 19 of the 100 simulations. The pathway taken by these molecules was consistent and non-random; the GABA molecules approach the binding site from below, before passing up behind the C-loop and into the binding site. This binding pathway is driven by long-range electrostatic interactions, whereby the electrostatic field acts as a ‘funnel’ that sweeps the GABA molecules towards the binding site, at which point more specific atomic interactions take over. These findings define a nuanced mechanism whereby the GABA_A-R uses the general zwitterionic features of the GABA molecule to identify a potential ligand some 2 nm away from the binding site.</p></div

GABA position distribution compared to random distribution.

<p>(A) The standard deviation of the GABA positions from the NON-BINDING simulations is compared against the standard deviation of a hypothetical random distribution. The dashed red line indicates the position ~2.7–2.8 nm from the binding site where the GABA distribution begins to deviate from random behavior. The edge of the protein is ~1.5 nm from the binding site COM. The non-bonded van der Waals interaction cutoff used for the simulation is 1.2 nm. Thus when GABA is ~2.7 nm from the binding site, it only ‘feels’ the presence of the protein via weak long-range electrostatic effect (A–inset). (B) The average standard deviation of all the binding simulations (BIND, PARTIAL, and NEARBY) is also compared against standard deviation of a hypothetical random distribution. A visual representation of these distributions is also shown (B–inset). The dashed red line indicates where the ‘focusing’ or ‘funneling’ of the GABA distribution occurs at ~1.9–2.0 nm from binding site.</p

Calculation of the GABA pathway.

<p>(A) In order to determine the average location of the GABA molecules for each category, the positions of GABA are binned into windows based upon 0.1 nm increments of the GABA COM to binding site COM distance (i). The positions of all the GABA molecules within a particular bin (ii) are used to calculate an average position and standard deviation of GABA at that particular distance from the binding site COM (iii). These data are represented graphically as a disc with a radius that is proportional to the standard deviation of the GABA positions within that bin, and with its axis aligned to the vector between the average GABA position and the binding site COM (iv). (B) The average binding pathways calculated for each of the simulation categories (L-R: BIND, PARTIAL, NEARBY, NON-BINDING) are shown. The radius of the disc is proportional to the standard deviation of GABA molecule positions at that distance from the binding site. The ligand-binding domain of the β₃-subunit is also illustrated in a grey cartoon format. A red circle represents the binding site COM. The discs used for these figures were constructed by using the draw feature of VMD to create cylinders with defined centers along the vector between the ligand binding site COM and the ligand position COM. The radius of the cylinder is defined as the measured standard deviation at that position.</p

Preliminary dispersion of GABA molecules.

<p>The ‘midpoint’ is ~2.5 nm from the average starting position of the GABA molecules. To compare the initial distribution of the GABA molecules in the 100 independent simulations, their positions were calculated when they first reach a point 2.5 nm from the average starting position (A), essentially the surface of a sphere of radius 2.5 nm. The average starting position of the GABA molecules is shown as a blue circle. These locations where the GABA molecules first reach 2.5 nm from the starting position reveal that not all of the surface area of the 2.5 nm sphere is actually accessible (B). The red hashed area is devoid of GABA molecules. This is due to the region being occluded by part of the GABA_A-R itself (C), specifically, the α₆-subunit that comprises part of the binding site. This α₆-subunit is shown in dark grey. The relative position of the GABA binding site COM is illustrated as a red circle, and the rest of the protein is shown in light grey, from a viewpoint looking down on the protein. Thus, excluding this protein-occluded region, the calculated accessible area on this 2.5 nm shell is ~73 nm². The number of GABA molecules that first reach the 2.5 nm shell within 1.0 nm of the midpoint was calculated (D). The binding site COM is shown as a red circle, and the β₃-subunit of the binding site is shown in grey. We are essentially measuring the number of GABA molecules within a specific circle of radius 1 nm on the surface of a sphere of radius 2.5 nm. 32 additional, ‘random’ overlapping sampling points were measured (E), and represented as colored patches on the surface of the 2.5 nm sphere (F and G). The chance of a molecule randomly reaching any sample point is ~4.3%. This is the area of sample point (approximately a circle of radius 1 nm–3.14 nm²) as a fraction of the available area (calculated as ~73 nm²). The numbers measured for the sample points (4.55 ± 1.80) portrayed in (F) and (G) indicate that there is no preference for the GABA molecules to initially travel to the midpoint, and that the positions of the GABA molecules are consistent with a random distribution.</p

The electrostatic field surrounding the GABA_A-R.

<p>(A) The top view of the GABA_A-R is illustrated (α₆-subunits in red, β₃-subunits in orange, and the δ-subunit in yellow) with all the surrounding electrostatic field lines shown. (B) The representation of the field lines is reduced to just show the strongest field lines, which converge on the GABA binding sites (highlighted by the white dashed circles). (C) This representation is also shown from the side view. (D) Finally, the electrostatic surface of a β₃-subunit and a α₆-subunit is presented to illustrate the dense electronegative region just below the binding site. The binding site is highlighted by a white dashed circle, and the electronegative region is highlighted by a red circle.</p

The random starting positions of the GABA molecules.

<p>The initial starting locations of GABA in each of the 100 simulations are superimposed to show their positions relative to the GABA_A-R. The ligand binding domains of the α₆-subunit (red) and β₃-subunit (orange) are also represented.</p

Calculation of the average dipole.

<p>(A) The influence of the electrostatic field on GABA was measured by calculating the net strength and direction of the dipole on the GABA molecules as they approach the binding site. Using the same positional bins (A.i and A.ii) as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004831#pcbi.1004831.g003" target="_blank">Fig 3</a> (GABA molecules binned into windows based upon 0.1 nm increments of the GABA COM to binding site COM distance), the dipoles on all the GABA molecules within a particular bin were measured as vectors (A.iii) and averaged to calculate a net dipole on GABA at that particular distance from the binding site COM. These data are represented graphically as an arrow, centered on the average GABA position in that bin, pointing in the direction of the net dipole, and whose length is proportional to the dipole strength within that bin (A.iv). (B) The net dipole experienced by GABA at these positions, and their location relative to the protein and the electrostatic field is shown for each of the simulation categories (L-R: BIND, PARTIAL, NEARBY, NON-BINDING). The orientation of the dipole on the GABA molecule is represented by an arrow, with the length of the arrow proportional to the strength of the dipole. The electronegative end of the dipole arrow is colored red, while the electropositive end of the dipole is colored blue. A red circle represents the binding site COM.</p

The angular positions of the GABA molecules.

<p>The average angular positions of all the GABA molecules within a simulation category are shown as a function of their distance from the binding site COM. These angles are presented for both the XY (A) and YZ (B) planes. The red dashed line indicates the distance at which the GABA molecules converge at the same point.</p

Breakdown of GABA simulations by category.

<p>The 100 independent GABA simulations are broken down into four categories based upon their distance from the GABA binding site. Those that enter the binding site (< 0.70 nm from the binding site COM) and remain there fall into the ‘BIND’ category (red). Those that enter the binding site and leave again fall into the ‘PARTIAL’ category (orange). Those that partially enter the binding site (< 1.3 nm from the binding site COM) fall into the ‘NEARBY’ category (green). Those that do not even partly enter the binding site (never < 1.3 nm from the binding site COM) fall into the ‘NON-BINDING’ category (blue). The radial representation on the right shows the populations of each of the categories (with the corresponding color) and the relative proximity they reach to the binding site COM (shown as a red circle). The number next to the category is the number of simulations that are in that category.</p