Proton transport and torque generation in rotary biomotors

We analyze the dynamics of rotary biomotors within a simple nano-electromechanical model, consisting of a stator part and a ring-shaped rotor having twelve proton-binding sites. This model is closely related to the membrane-embedded F$_0$ motor of adenosine triphosphate (ATP) synthase, which converts the energy of the transmembrane electrochemical gradient of protons into mechanical motion of the rotor. It is shown that the Coulomb coupling between the negative charge of the empty rotor site and the positive stator charge, located near the periplasmic proton-conducting channel (proton source), plays a dominant role in the torque-generating process. When approaching the source outlet, the rotor site has a proton energy level higher than the energy level of the site, located near the cytoplasmic channel (proton drain). In the first stage of this torque-generating process, the energy of the electrochemical potential is converted into potential energy of the proton-binding sites on the rotor. Afterwards, the tangential component of the Coulomb force produces a mechanical torque. We demonstrate that, at low temperatures, the loaded motor works in the shuttling regime where the energy of the electrochemical potential is consumed without producing any unidirectional rotation. The motor switches to the torque-generating regime at high temperatures, when the Brownian ratchet mechanism turns on. In the presence of a significant external torque, created by ATP hydrolysis, the system operates as a proton pump, which translocates protons against the transmembrane potential gradient. Here we focus on the F$_0$ motor, even though our analysis is applicable to the bacterial flagellar motor.Comment: 24 pages, 5 figure

LIVAS: A 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET

We present LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies), a 3-D multi-wavelength global aerosol and cloud optical database, optimized to be used for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. The LIVAS database provides averaged profiles of aerosol optical properties for the potential spaceborne laser operating wavelengths of 355, 532, 1064, 1570 and 2050 nm and of cloud optical properties at the wavelength of 532 nm. The global database is based on CALIPSO observations at 532 and 1064 nm and on aerosol-type-dependent backscatter- and extinction-related Ångström exponents, derived from EARLINET (European Aerosol Research Lidar Network) ground-based measurements for the UV and scattering calculations for the IR wavelengths, using a combination of input data from AERONET, suitable aerosol models and recent literature. The required spectral conversions are calculated for each of the CALIPSO aerosol types and are applied to CALIPSO backscatter and extinction data corresponding to the aerosol type retrieved by the CALIPSO aerosol classification scheme. A cloud optical database based on CALIPSO measurements at 532 nm is also provided, neglecting wavelength conversion due to approximately neutral scattering behavior of clouds along the spectral range of LIVAS. Averages of particle linear depolarization ratio profiles at 532 nm are provided as well. Finally, vertical distributions for a set of selected scenes of specific atmospheric phenomena (e.g., dust outbreaks, volcanic eruptions, wild fires, polar stratospheric clouds) are analyzed and spectrally converted so as to be used as case studies for spaceborne lidar performance assessments. The final global data set includes 4-year (1 January 2008–31 December 2011) time-averaged CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) data on a uniform grid of 1° × 1° with the original high vertical resolution of CALIPSO in order to ensure realistic simulations of the atmospheric variability in lidar end-to-end simulations

Artificial Brownian motors: Controlling transport on the nanoscale

In systems possessing spatial or dynamical symmetry breaking, Brownian motion combined with symmetric external input signals, deterministic or random, alike, can assist directed motion of particles at the submicron scales. In such cases, one speaks of "Brownian motors". In this review the constructive role of Brownian motion is exemplified for various one-dimensional setups, mostly inspired by the cell molecular machinery: working principles and characteristics of stylized devices are discussed to show how fluctuations, either thermal or extrinsic, can be used to control diffusive particle transport. Recent experimental demonstrations of this concept are reviewed with particular attention to transport in artificial nanopores and optical traps, where single particle currents have been first measured. Much emphasis is given to two- and three-dimensional devices containing many interacting particles of one or more species; for this class of artificial motors, noise rectification results also from the interplay of particle Brownian motion and geometric constraints. Recently, selective control and optimization of the transport of interacting colloidal particles and magnetic vortices have been successfully achieved, thus leading to the new generation of microfluidic and superconducting devices presented hereby. Another area with promising potential for realization of artificial Brownian motors are microfluidic or granular set-ups.....Comment: 57 pages, 39 figures; submitted to Reviews Modern Physics, revised versio

Supramolecularly directed rotary motion in a photoresponsive receptor

Stimuli-controlled motion at the molecular level has fascinated chemists already for several decades. Taking inspiration from the myriad of dynamic and machine-like functions in nature, a number of strategies have been developed to control motion in purely synthetic systems. Unidirectional rotary motion, such as is observed in ATP synthase and other motor proteins, remains highly challenging to achieve. Current artificial molecular motor systems rely on intrinsic asymmetry or a specific sequence of chemical transformations. Here, we present an alternative design in which the rotation is directed by a chiral guest molecule, which is able to bind non-covalently to a light-responsive receptor. It is demonstrated that the rotary direction is governed by the guest chirality and hence, can be selected and changed at will. This feature offers unique control of directional rotation and will prove highly important in the further development of molecular machinery

Electrons, Photons, and Force: Quantitative Single-Molecule Measurements from Physics to Biology

Single-molecule measurement techniques have illuminated unprecedented details of chemical behavior, including observations of the motion of a single molecule on a surface, and even the vibration of a single bond within a molecule. Such measurements are critical to our understanding of entities ranging from single atoms to the most complex protein assemblies. We provide an overview of the strikingly diverse classes of measurements that can be used to quantify single-molecule properties, including those of single macromolecules and single molecular assemblies, and discuss the quantitative insights they provide. Examples are drawn from across the single-molecule literature, ranging from ultrahigh vacuum scanning tunneling microscopy studies of adsorbate diffusion on surfaces to fluorescence studies of protein conformational changes in solution

Comparison of Parametric and Semi-Parametric Binary Response Models

A Bayesian semi-parametric estimation of the binary response model using Markov Chain Monte Carlo algorithms is proposed. The performances of the parametric and semi-parametric models are presented. The mean squared errors, receiver operating characteristic curve, and the marginal effect are used as the model selection criteria. Simulated data and Monte Carlo experiments show that unless the binary data is extremely unbalanced the semi-parametric and parametric models perform equally well. However, if the data is extremely unbalanced the maximum likelihood estimation does not converge whereas the Bayesian algorithms do. An application is also presented