The "thrifty" gene encoding Ahsg/Fetuin-A meets the insulin receptor: Insights into the mechanism of insulin resistance

Ahsg (fetuin-A) is a 55-59 kDa phosphorylated glycoprotein synthesized in the adult predominantly by hepatocytes, from which it enters the circulation. When dysregulated, this glycoprotein operates to influence the clinical sequelae of insulin resistance-type 2 diabetes and cardiovascular disease. The pathological sequelae likely arise from two separable molecular “faces” of Ahsg—one acting at the level of the insulin receptor and a second face influencing ectopic biomineralization in the intima. A detailed understanding of these two functional faces of Ahsg is not yet clear for lack of structural studies. Ahsg has a physiological role in the biomineralization of bone, which when dysregulated can lead to ectopic calcification of soft tissues in the vasculature. Ahsg has a second physiological function in regulating how insulin signals through its receptor, a transmembrane tyrosine kinase. Dysregulation of this “face” of Ahsg results in morbid sequelae such as impaired glucose disposal and fatty liver. Ahsg binds to tandem fibronectin type 3 (Fn3) domains present in the 194 amino acid residue extracellular portion of the β-subunit of the insulin receptor, distant from the high-affinity pocket formed by two complementing α-subunits where insulin binds. Only two proteins are known to bind directly to the insulin receptor ectodomain - insulin and Ahsg - the former turns on the receptor's intrinsic tyrosine kinase (TK) activity, and the latter shuts it down. Recent X-ray crystallographic studies of the ectodomain of the insulin receptor now sharpen our understanding of the receptor's extracellular α-subunit and linked β-subunit. Ahsg genotype and its circulating level have been correlated with body morphometrics (obese versus lean and visceral adiposity) in epidemiological studies enrolling thousands of patients. Epidemiological studies from the clinic reveal high levels of circulating Ahsg in insulin resistance and diabetes. This review endeavors to explain how one protein can mediate diverse pathologies, but specifically addresses its metabolic “face” blunting insulin receptor activity, an action leading to insulin resistance.     

Virtual screening using molecular simulations

Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery.     

研究SIR传染病数学模型的Lagrange-Noether方法

应用分析力学的方法讨论了SIR传染病数学模型方程,得到了与其对应的Lagrange函数和Noether守恒量,并根据Noether守恒量具体探讨了对感染病者和易感染病者人群的隔离率与患病者人数最大值的关系.     

Carnivorous Utricularia: The buckling scenario

We review recent results about the functioning of aquatic carnivorous traps from the genus Utricularia. The use of high speed cameras has helped to elucidate the mechanism at the origin of the ultra fast capture process of Utricularia, at a millisecond time scale. As water is pumped out of the trap, pressure decreases inside the trap and elastic energy is stored due to the change of shape of the trap body. This energy is suddenly released when the trap is fired: the trap door undergoes an elastical instability: buckling, which allows its fast and passive opening and closure. This mechanism is used by Utricularia both to catch preys touching its trigger hairs and to fire spontaneously at regular time intervals. The results leading to this interpretation are reviewed and discussed and suggestions for further work are briefly presented.     

Statistical mechanics analysis of sparse data

Inferential structure determination uses Bayesian theory to combine experimental data with prior structural knowledge into a posterior probability distribution over protein conformational space. The posterior distribution encodes everything one can say objectively about the native structure in the light of the available data and additional prior assumptions and can be searched for structural representatives. Here an analogy is drawn between the posterior distribution and the canonical ensemble of statistical physics. A statistical mechanics analysis assesses the complexity of a structure calculation globally in terms of ensemble properties. Analogs of the free energy and density of states are introduced; partition functions evaluate the consistency of prior assumptions with data. Critical behavior is observed with dwindling restraint density, which impairs structure determination with too sparse data. However, prior distributions with improved realism ameliorate the situation by lowering the critical number of observations. An in-depth analysis of various experimentally accessible structural parameters and force field terms will facilitate a statistical approach to protein structure determination with sparse data that avoids bias as much as possible.     

Mechanical adaptations of cleavers (Galium aparine)

BACKGROUND AND AIMS: Cleavers (Galium aparine) is a fast-growing herbaceous annual with a semi-self-supporting, scrambling-ascending growth habit. Mature plants often use upright species for support. It is common in hedgerows and on waste ground. This study aims to characterize the mechanical behaviour of the stem and roots of cleavers and relate this to the arrangement of structural tissue, the net microfibrillar orientations in the cell walls, and plant growth habit. METHODS: The morphology and mechanics of mature cleavers was investigated using plants grown in pots and ones collected from the grounds at the University of Lincoln, Lincoln, UK. Tensile tests were carried out on the stem and the basal section of the first-order lateral roots. The net orientation of cellulose microfibrils in the cell walls was investigated using polarized light microscopy. KEY RESULTS: Results show that the basal regions of the stem and first-order lateral roots were highly extensible. Breaking strains of 24 +/- 7% were recorded for the stem base and 28 +/- 6% for the roots. Anatomical observations showed that the lower stem (base + 100 mm) was circular in cross-section with a solid central core of vascular tissue, whereas further up the stem the transverse section showed a typical four-angled shape with a ring-like arrangement of vascular tissue and sclerenchyma bundles in the corners. The net orientation of wall microfibrils in the secondary xylem diverges from the longitudinal by between 8 and 9 degrees . CONCLUSIONS: The basal region of the stem of cleavers is highly extensible, but the mechanism by which the stem is able to withstand such high breaking strains is unclear; reorientation of the cellulose fibrils in the stem along the axis of loading is not thought to be responsible.     

The retro-articular process, streptostyly and the caecilian jaw closing system

Caecilians have two functionally separate sets of jaw closing muscles. The jaw adductor muscles are parallel fibered muscles positioned close to the jaw joint and their lever mechanics suggests they are well suited to rapidly closing the jaws. A second set of muscles, the hypaxial interhyoideus posterior (IHP), levers the jaws closed by pulling on the retroarticular process (RA) of the lower jaw. Models of the lower jaw point out that the angle and length of the RA has a profound effect on the closure force exerted by the IHP. The caecilian skull is streptostylic – the quadrate-squamosal apparatus (QSA) moves relative to the rest of the skull, a condition that seems at odds with a well-ossified cranium. Modeling the contribution of this streptostylic suspension of the lower jaw shows that rotational freedom of the QSA amplifies the force of the IHP by redirecting force applied along the low axis of the lower jaw. Measurements from several species and life stages of preserved caecilians reveal a large variation in predicted bite force (as a multiple of IHP force) with age and phylogeny.     

How actin crosslinking and bundling proteins cooperate to generate an enhanced cell mechanical response

Actin-crosslinking proteins organize actin filaments into dynamic and complex subcellular scaffolds that orchestrate important mechanical functions, including cell motility and adhesion. Recent mutation studies have shown that individual crosslinking proteins often play seemingly non-essential roles, leading to the hypothesis that they have considerable redundancy in function. We report live-cell, in vitro, and theoretical studies testing the mechanical role of the two ubiquitous actin-crosslinking proteins, alpha-actinin and fascin, which co-localize to stress fibers and the basis of filopodia. Using live-cell particle tracking microrheology, we show that the addition of alpha-actinin and fascin elicits a cell mechanical response that is significantly greater than that originated by alpha-actinin or fascin alone. These live-cell measurements are supported by quantitative rheological measurements with reconstituted actin filament networks containing pure proteins that show that alpha-actinin and fascin can work in concert to generate enhanced cell stiffness. Computational simulations using finite element modeling qualitatively reproduce and explain the functional synergy of alpha-actinin and fascin. These findings highlight the cooperative activity of fascin and alpha-actinin and provide a strong rationale that an evolutionary advantage might be conferred by the cooperative action of multiple actin-crosslinking proteins with overlapping but non-identical biochemical properties. Thus the combination of structural proteins with similar function can provide the cell with unique properties that are required for biologically optimal responses.     

Reversible and repeatable linear local cell force response under large stretches

Large stretching and un-stretching force response of adherent fibroblasts is measured by micromachined mechanical force sensors. The force sensors are composed of a probe and flexible beams. The probe, functionalized by fibronectin, is used to contact the cells. The flexible beams are the sensing element. The sensors are made of single crystal silicon and fabricated by the SCREAM process. The maximum cell stretch reached is approximately 50 microm, which is about twice of the cell initial size, and the time delay between two consecutive stretching/un-stretching steps is 75 s unless otherwise stated. We find that the force response of the cells is strongly linear, reversible, and repeatable, with a small stiffening at the initial deformation stage. Force response of single cells measured before and after cytochalasin D treatment suggests that actin filaments take almost all the cell internal forces due to stretch. These findings may shed light on the increasing understanding on the mechanical behavior of cells and provide clues for making new classes of biological materials having uncommon properties.     

Comparison between Generalized-Born and Poisson–Boltzmann methods in physics-based scoring functions for protein structure prediction

Continuum solvent models such as Generalized-Born and Poisson–Boltzmann methods hold the promise to treat solvation effect efficiently and to enable rapid scoring of protein structures when they are combined with physics-based energy functions. Yet, direct comparison of these two approaches on large protein data set is lacking. Building on our previous work with a scoring function based on a Generalized-Born (GB) solvation model, and short molecular-dynamics simulations, we further extended the scoring function to compare with the MM-PBSA method to treat the solvent effect. We benchmarked this scoring function against seven publicly available decoy sets. We found that, somewhat surprisingly, the results of MM-PBSA approach are comparable to the previous GB-based scoring function. We also discussed the effect to the scoring function accuracy due to presence of large ligands and ions in some native structures of the decoy sets.