Energy-nitrogen balances and protein turnover in small and appropriate for gestational age low birthweight infants.

The aim of the present study was to compare, under the same nursing conditions, the energy-nitrogen balance and the protein turnover in small for gestational age (SGA) and appropriate for gestational age (AGA) low birthweight infants. We compared 8 SGA's (mean +/- s.d.: gestational age 35 +/- 2 weeks, birthweight 1520 +/- 330 g) to 11 AGA premature infants (32 +/- 2 weeks, birthweight 1560 +/- 240 g). When their rate of weight gain was above 15 g/kg/d (17.6 +/- 3.0 and 18.2 +/- 2.6 g/kg/d, mean postnatal age 18 +/- 10 and 20 +/- 9 d respectively) they were studied with respect to their metabolizable energy intake, their energy expenditure, their energy and protein gain and their protein turnover. Energy balance was assessed by the difference between metabolizable energy and energy expenditure as measured by indirect calorimetry. Protein gain was calculated from the amount of retained nitrogen. Protein turnover was estimated by a stable isotope enrichment technique using repeated nasogastric administration of 15N-glycine for 72 h. Although there was no difference in their metabolizable energy intakes (110 +/- 12 versus 108 +/- 11 kcal/kg/d), SGA's had a higher rate of resting energy expenditure (64 +/- 8 versus 57 +/- 8 kcal/kg/d, P less than 0.05). Protein gain and composition of weight gain was very similar in both groups (2.0 +/- 0.4 versus 2.1 +/- 0.4 g protein/kg/d; 3.5 +/- 1.1 versus 3.3 +/- 1.4 g fat/kg/d in SGA's and AGA's respectively). However, the rate of protein synthesis was significantly lower in SGA's (7.7 +/- 1.6 g/kg/d) as compared to AGA's (9.7 +/- 2.8 g/kg/d; P less than 0.05). It is concluded that SGA's have a more efficient protein gain/protein synthesis ratio since for the same weight and protein gains, SGA's show a 20 per cent slower protein turnover. They might therefore tolerate slightly higher protein intakes. Postconceptional age seems to be an important factor in the regulation of protein turnover.

Protein energy malnutrition increases arginase activity in monocytes and macrophages.

BACKGROUND: Protein energy malnutrition is commonly associated with immune dysfunctions and is a major factor in susceptibility to infectious diseases. METHODS: In this study, we evaluated the impact of protein energy malnutrition on the capacity of monocytes and macrophages to upregulate arginase, an enzyme associated with immunosuppression and increased pathogen replication. RESULTS: Our results show that monocytes and macrophages are significantly increased in the bone marrow and blood of mice fed on a protein low diet. No alteration in the capacity of bone marrow derived macrophages isolated from malnourished mice to phagocytose particles, to produce the microbicidal molecule nitric oxide and to kill intracellular Leishmania parasites was detected. However, macrophages and monocytes from malnourished mice express significantly more arginase both in vitro and in vivo. Using an experimental model of visceral leishmaniasis, we show that following protein energy malnutrition, the increased parasite burden measured in the spleen of these mice coincided with increased arginase activity and that macrophages provide a more permissive environment for parasite growth. CONCLUSIONS: Taken together, these results identify a novel mechanism in protein energy malnutrition that might contributes to increased susceptibility to infectious diseases by upregulating arginase activity in myeloid cells.

Whole-body protein turnover and resting energy expenditure in obese, prepubertal children.

BACKGROUND: Obesity is becoming more frequent in children; understanding the extent to which this condition affects not only carbohydrate and lipid metabolism but also protein metabolism is of paramount importance. OBJECTIVE: We evaluated the kinetics of protein metabolism in obese, prepubertal children in the static phase of obesity. DESIGN: In this cross-sectional study, 9 obese children (x +/- SE: 44+/-4 kg, 30.9+/-1.5% body fat) were compared with 8 lean (28+/-2 kg ,16.8+/-1.2% body fat), age-matched (8.5+/-0.2 y) control children. Whole-body nitrogen flux, protein synthesis, and protein breakdown were calculated postprandially over 9 h from 15N abundance in urinary ammonia by using a single oral dose of [15N]glycine; resting energy expenditure (REE) was assessed by indirect calorimetry (canopy) and body composition by multiple skinfold-thickness measurements. RESULTS: Absolute rates of protein synthesis and breakdown were significantly greater in obese children than in control children (x +/- SE: 208+/-24 compared with 137+/-14 g/d, P < 0.05, and 149+/-20 compared with 89+/-13 g/d, P < 0.05, respectively). When these variables were adjusted for fat-free mass by analysis of covariance, however, the differences between groups disappeared. There was a significant relation between protein synthesis and fat-free mass (r = 0.83, P < 0.001) as well as between protein synthesis and REE (r = 0.79, P < 0.005). CONCLUSIONS: Obesity in prepubertal children is associated with an absolute increase in whole-body protein turnover that is consistent with an absolute increase in fat-free mass, both of which contribute to explaining the greater absolute REE in obese children than in control children.

Changes in protein turnover and resting energy expenditure after treatment of malaria in Gambian children.

To explore the changes in resting energy expenditure (REE) and whole body protein turnover induced by malaria, 23 children aged 6 to 14 y (23.9 +/- 1.0 kg, 1.3 +/- 0.02 m) were studied on three separate days after treatment (d 1, d 2, and 15 d later). REE was assessed by indirect calorimetry (hood), whereas whole body protein turnover was estimated using a single dose of [15N]glycine administered p.o. by measuring the isotopic enrichment of [15N]ammonia in urine over 12 h. Within the first 3.5 h after treatment, the body temperature dropped from 39.8 +/- 0.1 to 37.8 +/- 0.1 degrees C (p < 0.0001), and REE followed the same pattern, decreasing rapidly from 223 +/- 6 to 187 +/- 4 kJ/kg/d (p < 0.0001). Whole body protein synthesis and breakdown were significantly higher during the 1st day (5.65 +/- 0.38 and 6.21 +/- 0.43 g/kg/d, respectively) than at d 15 (2.95 +/- 0.17 and 2.77 +/- 0.2 g/kg/d). It is concluded that Gambian children suffering from an acute episode of malaria have an increased REE averaging 37% of the control value (d 15) and that this was associated with a substantial increase (by a factor of 2) in whole body protein turnover. A rapid normalization of the hypermetabolism and protein hypercatabolism states after treatment was observed.

Protein-ligand binding free energy estimation using molecular mechanics and continuum electrostatics. Application to HIV-1 protease inhibitors.

A method is proposed for the estimation of absolute binding free energy of interaction between proteins and ligands. Conformational sampling of the protein-ligand complex is performed by molecular dynamics (MD) in vacuo and the solvent effect is calculated a posteriori by solving the Poisson or the Poisson-Boltzmann equation for selected frames of the trajectory. The binding free energy is written as a linear combination of the buried surface upon complexation, SASbur, the electrostatic interaction energy between the ligand and the protein, Eelec, and the difference of the solvation free energies of the complex and the isolated ligand and protein, deltaGsolv. The method uses the buried surface upon complexation to account for the non-polar contribution to the binding free energy because it is less sensitive to the details of the structure than the van der Waals interaction energy. The parameters of the method are developed for a training set of 16 HIV-1 protease-inhibitor complexes of known 3D structure. A correlation coefficient of 0.91 was obtained with an unsigned mean error of 0.8 kcal/mol. When applied to a set of 25 HIV-1 protease-inhibitor complexes of unknown 3D structures, the method provides a satisfactory correlation between the calculated binding free energy and the experimental pIC5o without reparametrization.

Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape.

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.