Dopamine integrated B, N, S doped CQD nanoprobe for rapid and selective detection of fluoride ion.

A simple fluorescence turn on sensor for the detection of fluoride ion in totally aqueous medium has been developed by integrating boronic acid functionalized carbon quantum dot (BNSCQD) and dopamine. The intense emission of BNSCQD is quenched due to photoelectron transfer (PET) from BNSCQD to dopamine. A remarkable enhancement of emission intensity in presence of F- is achieved due to high reactivity of F- towards boron centre of the BNSCQD-dopamine complex and hence restricting PET between BNSCQD and dopamine. The LOD of our sensor is 0.7 pM. The sensor is not cytotoxic and could be utilised to trace fluoride level changes in human serum as well as in living cells.

Highly luminescent, heteroatom-doped carbon quantum dots for ultrasensitive sensing of glucosamine and targeted imaging of liver cancer cells.

A novel fluorescent boronate nanoprobe has been synthesized by judiciously doping boron, nitrogen, and sulphur in carbon quantum dots (BNSCQD). Specifically, the synergistic presence of nitrogen and sulphur along with boronic acid provides excellent luminescence properties and offers recognition sites for specific sensing of glucosamine. Fluorescence intensity enhances in the presence of glucosamine because of agglomeration of luminescent centers, and thus restricts nonradiative emission channels. The detection limit of this turn on fluorescence for glucosamine is 0.7 nM in PBS. Following this protocol, for the first time, a paper based sensor strip has been prepared for naked eye detection of glucosamine with an LOD of 2.5 µM. The developed nanoprobe shows very low cytotoxicity. More interestingly, boronic acid located on the surface of BNSCQD offers molecular recognition sites for the sialyl Lewisa receptor, which is overexpressed on the surface of liver cancer cells (HepG2). The selective uptake of the BNSCQD nanoprobe in HepG2 cells compared to L929, 3T3 and PC3 cells shows its cell targeting capability.

Dynamic properties of molecular motors in the divided-pathway model.

The mechanisms of molecular motors transport are important for understanding multiple biological processes. Recent single-molecule experiments indicate that motor proteins myosin V moves along protein filaments via a complex biochemical pathway that consists of sequentially coupled linear and parallel two-chain segments. We investigate analytically the corresponding discrete-state stochastic divided-pathway model for molecular motors transport. Explicit expressions are obtained for velocities and dispersions. The dynamic properties of motor proteins in the divided-pathway model are compared with those in single-chain linear and parallel-pathway stochastic models. It is argued that modifying biochemical pathways has a strong effect on the dynamic properties, and it allows motor proteins to be more flexible in performing their biological functions.

Spatial fluctuations affect the dynamics of motor proteins.

Motor proteins are active biological molecules that perform their functions by converting chemical energy into mechanical work. They move unidirectionally along rigid protein filaments or DNA and RNA molecules in discrete steps by hydrolyzing ATP (adenosine triphsophate) or related energy-rich compounds. Recent single-molecule experiments have shown that motor proteins experience significant spatial fluctuations during its motion, leading to broad step-size distributions. The effect of these spatial fluctuations is analyzed explicitly by considering discrete-state stochastic models that allow us to compute exactly all dynamic properties. It is shown that for symmetric spatial fluctuations there is no change in mean velocities for weak external forces, while dispersions and stall forces are strongly affected at all conditions. These results are illustrated by several simple examples. Our method is also applied to analyze the effect of step-size fluctuations on dynamics of myosin V motor proteins. It is argued that spatial fluctuations might be used to control and regulate the dynamics of motor proteins.

Interaction between motor domains can explain the complex dynamics of heterodimeric kinesins.

Motor proteins are active enzyme molecules that play a crucial role in many biological processes. They transform chemical energy into mechanical work and move unidirectionally along rigid cytoskeleton filaments. Single-molecule experiments indicate that motor proteins, consisting of two motor domains, move in a hand-over-hand mechanism where each subunit changes between trailing and leading positions in alternating steps, and it is assumed that these subunits do not interact with each other. However, recent experiments on heterodimeric kinesins suggest that the motion of motor domains is not independent, but rather strongly coupled and coordinated, although the mechanism of these interactions is not known. We propose a simple discrete stochastic model to describe the dynamics of homodimeric and heterodimeric two-headed motor proteins. It is argued that interactions between motor domains modify original free energy landscapes for each motor subunit, while motor proteins still move via the hand-over-hand mechanism but with different transition rates specified by the new free energy profiles. Our calculations of biophysical properties agree with experimental observations. Several ways to test the theoretical model are proposed.