Allocating and Splitting Free Energy to Maximize Molecular Machine Flux

Modeling Studies of the Mechanism of Context-Dependent Bidirectional Movements of Kinesin-14 Motors

Kinesin-14s, a subfamily of the large superfamily of kinesin motor proteins, function mainly in spindle assembly and maintenance during mitosis and meiosis. KlpA from Aspergillus nidulans and GiKIN14a from Giardia intestinalis are two types of kinesin-14s. Available experimental results puzzlingly showed that while KlpA moves preferentially toward the minus end in microtubule-gliding setups and inside parallel microtubule overlaps, it moves preferentially toward the plus end on single microtubules. More puzzlingly, the insertion of an extra polypeptide linker in the central region of the neck stalk switches the motility direction of KlpA on single microtubules to the minus end. Prior experimental results showed that GiKIN14a moves preferentially toward the minus end on single microtubules in either tailless or full-length forms. The tail not only greatly enhances the processivity but also accelerates the ATPase rate and velocity of GiKIN14a. The insertion of an extra polypeptide linker in the central region of the neck stalk reduces the ATPase rate of GiKIN14a. However, the underlying mechanism of these puzzling dynamical features for KlpA and GiKIN14a is unclear. Here, to understand this mechanism, the dynamics of KlpA and GiKIN14a were studied theoretically on the basis of the proposed model, incorporating potential changes between the kinesin head and microtubule, as well as the potential between the tail and microtubule. The theoretical results quantitatively explain the available experimental results and provide predicted results. It was found that the elasticity of the neck stalk determines the directionality of KlpA on single microtubules and affects the ATPase rate and velocity of GiKIN14a on single microtubules.

Theoretical efficiency limits and speed-efficiency trade-off in myosin motors

Muscle myosin is a non-processive molecular motor generates mechanical work when cooperating in large ensembles. During its cyle, each individual motor keeps attaching and detaching from the actin filament. The random nature of attachment and detachment inevitably leads to losses and imposes theoretical limits on the energetic efficiency. Here, we numerically determine the theoretical efficiency limit of a classical myosin model with a given number of mechano-chemical states. All parameters that are not bounded by physical limits (like rate limiting steps) are determined by numerical efficiency optimization. We show that the efficiency is limited by the number of states, the stiffness and the rate-limiting kinetic steps. There is a trade-off between speed and efficiency. Slow motors are optimal when most of the available free energy is allocated to the working stroke and the stiffness of their elastic element is high. Fast motors, on the other hand, work better with a lower and asymmetric stiffness and allocate a larger fraction of free energy to the release of ADP. Overall, many features found in myosins coincide with the findings from the model optimization: there are at least 3 bound states, the largest part of the working stroke takes place during the first transition, the ADP affinity is adapted differently in slow and fast myosins and there is an asymmetry in elastic elements.

Energy landscape design principle for optimal energy harnessing by catalytic molecular machines

Under temperature oscillation, cyclic molecular machines such as catalysts and enzymes could harness energy from the oscillatory bath and use it to drive other processes. Using an alternative geometrical approach, under fast temperature oscillation, we derive a general design principle for obtaining the optimal catalytic energy landscape that can harness energy from a temperature-oscillatory bath and use it to invert a spontaneous reaction. By driving the reaction against the spontaneous direction, the catalysts convert low free-energy product molecules to high free-energy reactant molecules. The design principle, derived for arbitrary cyclic catalysts, is expressed as a simple quadratic objective function that only depends on the reaction activation energies, and is independent of the temperature protocol. Since the reaction activation energies are directly accessible by experimental measurements, the objective function can be directly used to guide the search for optimal energy-harvesting catalysts.

Modeling Study of the Dynamics of Kinesin-14 Molecular Motors

Kinesin-14s constitute a subfamily of the large superfamily of adenosine triphosphate-dependent microtubule-based motor proteins. Kinesin-14s have the motor domain at the C-terminal end of the peptide, playing key roles during spindle assembly and maintenance. Some of them are nonprocessive motors, whereas others can move processively on microtubules. Here, we take budding yeast Cik1-Kar3 and human HSET as examples to study theoretically the dynamics of the processive kinesin-14 motor moving on the single microtubule under load, the dynamics of the motor coupled with an Ndc80 protein moving on the single microtubule, the dynamics of the motor moving in microtubule arrays, and so on. The dynamics of the nonprocessive Drosophila Ncd motor is also discussed. The studies explain well the available experimental data and, moreover, provide predicted results. We show that the processive kinesin-14 motors can move efficiently in microtubule arrays toward the minus ends, and after reaching the minus ends, they can stay there stably, thus performing the function of organizing the microtubules in the bipolar spindle into polar arrays at the spindle poles.

Effect of varying load in moving period of a step on dynamics of molecular motors

During the processive stepping of a molecular motor on its polar track, a step consists of a long dwell period and a very short moving period. In single molecule optical trapping experiments to determine the load dependence of the motor dynamics, although the motor experiences a constant load during the dwell period, it experiences a varying load during the moving period. However, in previous theoretical studies to explain the single molecule optical trapping data, it was simply assumed that the motor experiences a constant load during both the dwell period and the following moving period. Thus, an important but unclear issue is whether the assumption is appropriate in the theoretical studies. Here, we take kinesin and myosin-V as examples to study theoretically the motor dynamics with the consideration of the varying load during the moving period and compare with that with the assumption of the constant load. The studies show that in the optical trapping experiments employed in the literature, for the kinesin with a small step size of about 8 nm it is a good approximation to make the theoretical studies by assuming that the motor experiences the constant load during the moving period. For the myosin-V with a large step size of about 36 nm, there are small but noticeable deviations of the results obtained by considering that the motor experiences the varying load during the moving period from those by assuming that the motor experiences the constant load. .

Evolution of mechanical cooperativity among myosin II motors

Myosin II is a biomolecular machine that is responsible for muscle contraction. Myosin II motors act cooperatively: during muscle contraction, multiple motors bind to a single actin filament and pull it against an external load, like people pulling on a rope in a tug-of-war. We model the dynamics of actomyosin filaments in order to study the evolution of motor-motor cooperativity. We find that filament backsliding-the distance an actin slides backward when a motor at the end of its cycle releases-is central to the speed and efficiency of muscle contraction. Our model predicts that this backsliding has been reduced through evolutionary adaptations to the motor's binding propensity, the strength of the motor's power stroke, and the force dependence of the motor's release from actin. These properties optimize the collective action of myosin II motors, which is not a simple sum of individual motor actions. The model also shows that these evolutionary variables can explain the speed-efficiency trade-off observed across different muscle tissues. This is an example of how evolution can tune the microscopic properties of individual proteins in order to optimize complex biological functions.

Reversible catalysis

We describe as 'reversible' a bidirectional catalyst that allows a reaction to proceed at a significant rate in response to even a small departure from equilibrium, resulting in fast and energy-efficient chemical transformation. Examining the relation between reaction rate and thermodynamic driving force is the basis of electrochemical investigations of redox reactions, which can be catalysed by metallic surfaces and biological or synthetic molecular catalysts. This relation has also been discussed in the context of biological energy transduction, regarding the function of biological molecular machines that harness chemical reactions to do mechanical work. This Perspective describes mean-field kinetic modelling of these three types of systems - surface catalysts, molecular catalysts of redox reactions and molecular machines - with the goal of unifying concepts in these different fields. We emphasize that reversibility should be distinguished from other figures of merit, such as rate or directionality, before its design principles can be identified and used to engineer synthetic catalysts.

Getting around the cell: physical transport in the intracellular world

Eukaryotic cells face the challenging task of transporting a variety of particles through the complex intracellular milieu in order to deliver, distribute, and mix the many components that support cell function. In this review, we explore the biological objectives and physical mechanisms of intracellular transport. Our focus is on cytoplasmic and intra-organelle transport at the whole-cell scale. We outline several key biological functions that depend on physically transporting components across the cell, including the delivery of secreted proteins, support of cell growth and repair, propagation of intracellular signals, establishment of organelle contacts, and spatial organization of metabolic gradients. We then review the three primary physical modes of transport in eukaryotic cells: diffusive motion, motor-driven transport, and advection by cytoplasmic flow. For each mechanism, we identify the main factors that determine speed and directionality. We also highlight the efficiency of each transport mode in fulfilling various key objectives of transport, such as particle mixing, directed delivery, and rapid target search. Taken together, the interplay of diffusion, molecular motors, and flows supports the intracellular transport needs that underlie a broad variety of biological phenomena.

Optimal control of protein copy number

Cell-cell communication is often achieved by secreted signaling molecules that bind membrane-bound receptors. A common class of such receptors are G-protein coupled receptors, where extracellular binding induces changes on the membrane affinity near the receptor for certain cytosolic proteins, effectively altering their chemical potential. We analyze the minimum-dissipation schedules for dynamically changing chemical potential to induce steady-state changes in protein copy-number distributions, and illustrate with analytic solutions for linear chemical reaction networks. Protocols that change chemical potential on biologically relevant timescales are experimentally accessible using optogenetic manipulations, and our framework provides nontrivial predictions about functional dynamical cell-cell interactions.

Opposing Pressures of Speed and Efficiency Guide the Evolution of Molecular Machines

Many biomolecular machines need to be both fast and efficient. How has evolution optimized these machines along the tradeoff between speed and efficiency? We explore this question using optimizable dynamical models along coordinates that are plausible evolutionary degrees of freedom. Data on 11 motors and ion pumps are consistent with the hypothesis that evolution seeks an optimal balance of speed and efficiency, where any further small increase in one of these quantities would come at great expense to the other. For F_oF₁-ATPases in different species, we also find apparent optimization of the number of subunits in the c-ring, which determines the number of protons pumped per ATP synthesized. Interestingly, these ATPases appear to more optimized for efficiency than for speed, which can be rationalized through their key role as energy transducers in biology. The present modeling shows how the dynamical performance properties of biomolecular motors and pumps may have evolved to suit their corresponding biological actions.

Theory of Nonequilibrium Free Energy Transduction by Molecular Machines

Biomolecular machines are protein complexes that convert between different forms of free energy. They are utilized in nature to accomplish many cellular tasks. As isothermal nonequilibrium stochastic objects at low Reynolds number, they face a distinct set of challenges compared with more familiar human-engineered macroscopic machines. Here we review central questions in their performance as free energy transducers, outline theoretical and modeling approaches to understand these questions, identify both physical limits on their operational characteristics and design principles for improving performance, and discuss emerging areas of research.

Breaking time-reversal symmetry for ratchet models of molecular machines

Biomolecular machines transduce free energy from one form to another to fulfill many important roles inside cells, with dissipation required to achieve directed progress. We investigate how to break time-reversal symmetry at a given dissipation cost by using deterministic protocols to drive systems over sawtooth potentials, which have frequently been used to model molecular machines as ratchets. Time asymmetry increases for sawtooth potentials with higher barriers and for driving potentials of intermediate width. For systems driven over a sawtooth potential according to a protocol, we find that symmetric sawtooths maximize time asymmetry, whereas earlier work examining ratchet models of molecular machines required asymmetric sawtooth potentials to achieve directed behavior. This distinction arises because deterministically driven machines are externally provided with direction, whereas autonomous machines must generate directed behavior.

Mechanisms for achieving high speed and efficiency in biomolecular machines

How does a biomolecular machine achieve high speed at high efficiency? We explore optimization principles using a simple two-state dynamical model. With this model, we establish physical principles-such as the optimal way to distribute free-energy changes and barriers across the machine cycle-and connect them to biological mechanisms. We find that a machine can achieve high speed without sacrificing efficiency by varying its conformational free energy to directly link the downhill, chemical energy to the uphill, mechanical work and by splitting a large work step into more numerous, smaller substeps. Experimental evidence suggests that these mechanisms are commonly used by biomolecular machines. This model is useful for exploring questions of evolution and optimization in molecular machines.