How Interactions Control Molecular Transport in Channels

The motion of molecules across channels is critically important for understanding mechanisms of cellular processes. Here we investigate the mechanism of interactions in the molecular transport by analyzing exactly solvable discrete stochastic models. It is shown that the strength and spatial distribution of molecule/channel interactions can strongly modify the particle current. Our analysis indicates that the most optimal transport is achieved when the binding sites are near the entrance or exit of the pore. In addition, the role of intermolecular interactions is studied, and it is argued that an increase in flux can be observed for some optimal interaction strength. The mechanism of these phenomena is discussed

Cooperative mechanisms in coupled motor proteins transport

Subcellular cargos are transported by enzyme molecules called molecular motors by using the chemical energy from hydrolysis of ATP and performing mechanical work in non-equilibrium. Certain motors tread on cytoskeleton structures i.e. microtubules and actin filaments in a linear manner. Due to the polarity of the cytoskeleton structures the motors can accomplish cellular transport along one direction. Cargos often rely upon the collective action of more than one motor to transport them in order to surmount the crowding and visco-elastic effects of the surrounding medium through higher force generation. To understand the mechanism of cargo transport by precisely two kinesin-1 motors a combination of experimental and theoretical approaches were employed. This thesis focuses on understanding the mechanism of transport by considering interactions between closely spaced motors on the microtubules. The main finding of this thesis is that motors under the influence of each other's interaction with microtubules do affect the cargo dynamics

Electron Nuclear Dynamics Simulations of Proton Cancer Therapy Reactions: Water Radiolysis and Proton-and Electron-Induced DNA Damage in Computational Prototypes

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Proton cancer therapy (PCT) utilizes high-energy proton projectiles to obliterate cancerous tumors with low damage to healthy tissues and without the side effects of X-ray therapy. The healing action of the protons results from their damage on cancerous cell DNA. Despite established clinical use, the chemical mechanisms of PCT reactions at the molecular level remain elusive. This situation prevents a rational design of PCT that can maximize its therapeutic power and minimize its side effects. The incomplete characterization of PCT reactions is partially due to the health risks associated with experimental/clinical techniques applied to human subjects. To overcome this situation, we are conducting time-dependent and non-adiabatic computer simulations of PCT reactions with the electron nuclear dynamics (END) method. Herein, we present a review of our previous and new END research on three fundamental types of PCT reactions: water radiolysis reactions, proton-induced DNA damage and electron-induced DNA damage. These studies are performed on the computational prototypes: proton + H2O clusters, proton + DNA/RNA bases and + cytosine nucleotide, and electron + cytosine nucleotide + H2O. These simulations provide chemical mechanisms and dynamical properties of the selected PCT reactions in comparison with available experimental and alternative computational results

Analysis of Cooperative Behavior in Multiple Kinesins Motor Protein Transport by Varying Structural and Chemical Properties

Intracellular transport is a fundamental biological process during which cellular materials are driven by enzymatic molecules called motor proteins. Recent optical trapping experiments and theoretical analysis have uncovered many features of cargo transport by multiple kinesin motor protein molecules under applied loads. These studies suggest that kinesins cooperate negatively under typical transport conditions, although some productive cooperation could be achieved under higher applied loads. However, the microscopic origins of this complex behavior are still not well understood. Using a discrete-state stochastic approach we analyze factors that affect the cooperativity among kinesin motors during cargo transport. Kinesin cooperation is shown to be largely unaffected by the structural and mechanical parameters of a multiple motor complex connected to a cargo, but much more sensitive to biochemical parameters affecting motor-filament affinities. While such behavior suggests the net negative cooperative responses of kinesins will persist across a relatively wide range of cargo types, it is also shown that the rates with which cargo velocities relax in time upon force perturbations are influenced by structural factors that affect the free energies of and load distributions within a multiple kinesin complex. The implications of these later results on transport phenomena where loads change temporally, as in the case of bidirectional transport, are discussed

Productive Cooperation among Processive Motors Depends Inversely on Their Mechanochemical Efficiency

Subcellular cargos are often transported by teams of processive molecular motors, which raises questions regarding the role of motor cooperation in intracellular transport. Although our ability to characterize the transport behaviors of multiple-motor systems has improved substantially, many aspects of multiple-motor dynamics are poorly understood. This work describes a transition rate model that predicts the load-dependent transport behaviors of multiple-motor complexes from detailed measurements of a single motor's elastic and mechanochemical properties. Transition rates are parameterized via analyses of single-motor stepping behaviors, load-rate-dependent motor-filament detachment kinetics, and strain-induced stiffening of motor-cargo linkages. The model reproduces key signatures found in optical trapping studies of structurally defined complexes composed of two kinesin motors, and predicts that multiple kinesins generally have difficulties in cooperating together. Although such behavior is influenced by the spatiotemporal dependence of the applied load, it appears to be directly linked to the efficiency of kinesin's stepping mechanism, and other types of less efficient and weaker processive motors are predicted to cooperate more productively. Thus, the mechanochemical efficiencies of different motor types may determine how effectively they cooperate together, and hence how motor copy number contributes to the regulation of cargo motion

How the interplay between mechanical and non-mechanical interactions affects multiple kinesin dynamics

Intracellular transport is supported by enzymes called motor proteins that are often coupled to the same cargo and function collectively. Recent experiments and theoretical advances have been able to explain certain behaviors of multiple motor systems by elucidating how unequal load sharing between coupled motors changes how they bind, step, and detach. However, non-mechanical interactions are typically overlooked despite several studies suggesting that microtubule-bound kinesins interact locally via short-range non-mechanical potentials. This work develops a new stochastic model to explore how these types of interactions influence multiple kinesin functions in addition to mechanical coupling. Non-mechanical interactions are assumed to affect kinesin mechanochemistry only when the motors are separated by less than three microtubule lattice sites, and it is shown that relatively weak interaction energies (~2 kBT) can have an appreciable influence over collective motor velocities and detachment rates. In agreement with optical trapping experiments on structurally-defined kinesin complexes, the model predicts that these effects primarily occur when cargos are transported against loads exceeding single-kinesin stalling forces. Overall, these results highlight the inter-dependent nature of factors influencing collective motor functions, namely, that the way the bound configuration of a multiple motor system evolves under load determines how local non-mechanical interactions influence motor cooperation