No Arabic abstract
Membrane tubes are important elements for living cells to organize many functions. Experiments have found that membrane tube can be extracted from giant lipid vesicles by a group of kinesin. How these motors cooperate in extracting the fluid-like membrane tube is still unclear. In this paper, we propose a new cooperation mechanism called two-track-dumbbell model, in which kinesin is regarded as a dumbbell with an end (tail domain) tightly bound onto the fluid-like membrane and the other end (head domain) stepping on or unbinding from the microtubule. Taking account of the elasticity of kinesin molecule and the exclude volume effect of both the head domain and the tail domain of kinesin, which are not considered in previous models, we simulate the growth process of the membrane tube pulled by kinesin motors. Our results indicate that motors along a single microtubule protofilament can generate enough force to extract membrane tubes from vesicles, and the average number of motors pulling the tube is about 8~9. These results are quite different from previous studies (Ref. cite{camp.08}), and further experimental tests are necessary to elucidate the cooperation mechanism.
Intelligence is often discussed in terms of neural networks in the cerebral cortex, whose evolution has presumably been influenced by Darwinian selection. Here we present molecular evidence that one of the many kinesin motors, Kif14, has evolved to exhibit special features in its amino acid sequence that could have evolved to improve neural networks. The improvement is quantified by comparison of Kif14 sequences for 12 species. The special feature is level sets of hydrophobic extrema in water wave profiles based on several hydropathic scales. The most effective scale is a new one based on fractals, indicative of approach of globular curvatures to self-organized criticality.
Switching of the direction of flagella rotations is the key control mechanism governing the chemotactic activity of E. coli and many other bacteria. Power-law distributions of switching times are most peculiar because their emergence cannot be deduced from simple thermodynamic arguments. Recently it was suggested that by adding finite-time correlations into Gaussian fluctuations regulating the energy height of barrier between the two rotation states, one can generate a power-law switching statistics. By using a simple model of a regulatory pathway, we demonstrate that the required amount of correlated `noise can be produced by finite number fluctuations of reacting protein molecules, a condition common to the intracellular chemistry. The corresponding power-law exponent appears as a tunable characteristic controlled by parameters of the regulatory pathway network such as equilibrium number of molecules, sensitivities, and the characteristic relaxation time.
We propose a stochastic model for gene transcription coupled to DNA supercoiling, where we incorporate the experimental observation that polymerases create supercoiling as they unwind the DNA helix, and that these enzymes bind more favourably to regions where the genome is unwound. Within this model, we show that when the transcriptionally induced flux of supercoiling increases, there is a sharp crossover from a regime where torsional stresses relax quickly and gene transcription is random, to one where gene expression is highly correlated and tightly regulated by supercoiling. In the latter regime, the model displays transcriptional bursts, waves of supercoiling, and up-regulation of divergent or bidirectional genes. It also predicts that topological enzymes which relax twist and writhe should provide a pathway to down-regulate transcription. This article has been published in Physical Review Letters, May 2016.
A simple flashing ratchet model in two dimensions is proposed to simulate the hand-over-hand motion of two head molecular motors like kinesin. Extensive Langevin simulations of the model are performed. Good qualitative agreement with the expected behavior is observed. We discuss different regimes of motion and efficiency depending of model parameters.
The effect of ultralow-frequency or static magnetic and electric fields on biological processes is of huge interest for researchers due to the resonant change of the intensity of biochemical reactions although the energy in such fields is small. A simplified model to study the effect of the weak magnetic and electrical fields on fluctuation of the random ionic currents in blood and to solve the $k_BT$ problem in magnetobiology is suggested. The analytic expression for the kinetic energy of the molecules dissolved in certain liquid media is obtained. The values of the magnetic field leading to resonant effects in capillaries are estimated. The numerical estimates showed that the resonant values of the energy of molecular in the capillaries and aorta are different: under identical conditions a molecule of the aorta gets $10^{-9}$ times less energy than the molecules in blood capillaries. So the capillaries are very sensitive to the resonant effect, with an approach to the resonant value of the magnetic field strength, the average energy of the molecule localized in the capillary is increased by several orders of magnitude as compared to its thermal energy, this value of the energy is sufficient for the deterioration of the chemical bonds.