Biochemical and molecular characterization of diseases linked to motor proteins

Recent studies have revealed that kinesin, dynein and myosin each form large superfamilies and participate in many different intracellular transport systems. Importantly, these motor proteins play significant roles in the pathogenesis of a variety of diseases. Studies using knockout mice for kinesin KIF1B have led to the identification of the cause of a human hereditary neuropathy, Charcot-Marie-Tooth disease type 2A. The function of members of the dynein superfamily whose existence has previously only been confirmed through genome databases, has been revealed by studies of immotile cilia syndrome. Unconventional myosins have been shown to function in the inner-ear cells by examination of hereditary human hearing impairment and studies using mouse models. In addition, some diseases are caused by mutations, not in the motor itself, but in the proteins associated with the motor proteins. Here, we discuss the relationship of these motor proteins and how they contribute to disease in molecular terms.     

Free energy transduction in a chemical motor model

Motor enzymes catalyse chemical reactions, like the hydrolysis of ATP, and in the process they also perform work. Recent studies indicate that motor enzymes perform work with specific biochemical steps in their catalysed reactions, challenging the classical view that work can only be performed within a biochemical state. To address these studies an alternative class of models, often referred to as chemical motor models, has emerged in which motors perform work with biochemical transitions. In this paper, I develop a novel, self-consistent framework for chemical motor models, which accommodates multiple pathways for free energy transfer, predicts rich behaviors from the simplest multi-motor systems, and provides important new insights into muscle and motor function.     

Generation and reshaping of sequences in neural systems

The generation of informational sequences and their reorganization or reshaping is one of the most intriguing subjects for both neuroscience and the theory of autonomous intelligent systems. In spite of the diversity of sequential activities of sensory, motor, and cognitive neural systems, they have many similarities from the dynamical point of view. In this review we discus the ideas, models, and mathematical image of sequence generation and reshaping on different levels of the neural hierarchy, i.e., the role of a sensory network dynamics in the generation of a motor program (hunting swimming of marine mollusk Clione), olfactory dynamical coding, and sequential learning and decision making. Analysis of these phenomena is based on the winnerless competition principle. The considered models can be a basis for the design of biologically inspired autonomous intelligent systems.     

Recurrent cerebellar architecture solves the motor-error problem

Current views of cerebellar function have been heavily influenced by the models of Marr and Albus, who suggested that the climbing fibre input to the cerebellum acts as a teaching signal for motor learning. It is commonly assumed that this teaching signal must be motor error (the difference between actual and correct motor command), but this approach requires complex neural structures to estimate unobservable motor error from its observed sensory consequences. We have proposed elsewhere a recurrent decorrelation control architecture in which Marr-Albus models learn without requiring motor error. Here, we prove convergence for this architecture and demonstrate important advantages for the modular control of systems with multiple degrees of freedom. These results are illustrated by modelling adaptive plant compensation for the three-dimensional vestibular ocular reflex. This provides a functional role for recurrent cerebellar connectivity, which may be a generic anatomical feature of projections between regions of cerebral and cerebellar cortex.     

Computational approaches to motor control

New concepts and computational models that integrate behavioral and neurophysiological observations have addressed several of the most fundamental long-standing problems in motor control. These problems include the selection of particular trajectories among the large number of possibilities, the solution of inverse kinematics and dynamics problems, motor adaptation and the learning of sequential behaviors.     

The emotional motor system.

A large number of new descending motor pathways to caudal brainstem and spinal cord have been recognized recently. Nevertheless all the new pathways seem to belong to one of three motor systems in the central nervous system (CNS). This survey gives an overview of the pathways belonging to the so-called emotional motor system or the third motor system as defined by Holstege. The similarities and differences with the core, median and lateral paracore areas of the CNS as defined by Nieuwenhuys are discussed.     

Bridging the gap - from ion channels to networks and behaviour

A major challenge for current research in neuroscience is to understand the intrinsic operation of the functional modules of the central nervous system, such as those formed by cortical columns and the neuronal networks controlling motor behaviour. Most vertebrate experimental models used in network analyses involve developing nervous systems, which are in rapid transition with regard to their cellular properties and the expression of different ion channels. Recent advances in our understanding of the cellular and circuit properties of motor networks are making it possible to decipher the mechanisms involved in vertebrate motor pattern generation.     

Mathematical and philosophical reflections on motor control systems

In line with the tradition of the Dutch school of functional morphology, an attempt is made to integrate numerical models of sarcomeres, muscle fibres, muscles, bone-connective-tissue systems, joints, muscle spindles and neural networks into one model simulating motor control. There are two purposes for this attempt. Firstly, to indicate whether numerical properties of the organs forming a system of motor control can be explained in terms of its motor functions. Secondly, to indicate properties that emerge from the integration of the organs into a system of motor control: how much more is an integrated motor system than the sum of its functional components. The motor control system of chewing has been taken as an example, particularly that in rats.     

Using insects to drive mobile robots — hybrid robots bridge the gap between biological and artificial systems

The use of mobile robots is an effective method of validating sensory–motor models of animals in a real environment. The well-identified insect sensory–motor systems have been the major targets for modeling. Furthermore, mobile robots implemented with such insect models attract engineers who aim to avail advantages from organisms. However, directly comparing the robots with real insects is still difficult, even if we successfully model the biological systems, because of the physical differences between them. We developed a hybrid robot to bridge the gap. This hybrid robot is an insect-controlled robot, in which a tethered male silkmoth (Bombyx mori) drives the robot in order to localize an odor source. This robot has the following three advantages: 1) from a biomimetic perspective, the robot enables us to evaluate the potential performance of future insect-mimetic robots; 2) from a biological perspective, the robot enables us to manipulate the closed-loop of an onboard insect for further understanding of its sensory–motor system; and 3) the robot enables comparison with insect models as a reference biological system. In this paper, we review the recent works regarding insect-controlled robots and discuss the significance for both engineering and biology.     

Insights from models of rhythmic motor systems

Computational models of rhythmic motor systems are valuable tools for the study of motor pattern generation and control. Recent modeling advances, together with experimental results, suggest that rhythmic behaviors, such as breathing or walking, are influenced by complex interactions among motor system components. Such interactions occur at all levels of organization, from the subcellular through to the cellular, synaptic, and network levels to the level of neuromuscular interactions and that of the whole organism. Simultaneously, safety mechanisms at all levels contribute to network stability and the generation of robust motor patterns.     

A mathematical model of the adaptive control of human arm motions

This paper discusses similarities between models of adaptive motor control suggested by recent experiments with human and animal subjects, and the structure of a new control law derived mathematically from nonlinear stability theory. In both models, the control actions required to track a specified trajectory are adaptively assembled from a large collection of simple computational elements. By adaptively recombining these elements, the controllers develop complex internal models which are used to compensate for the effects of externally imposed forces or changes in the physical properties of the system. On a motor learning task involving planar, multi-joint arm motions, the simulated performance of the mathematical model is shown to be qualitatively similar to observed human performance, suggesting that the model captures some of the interesting features of the dynamics of low-level motor adaptation. Received: 20 September 1994 / Accepted in revised form: 18 November 1998     

Some elementary considerations of neural models

The outputs of nervous systems (as expressed in motor activity) are viewed as mathematical transformations on the inputs which enter via the sensory nerves. Simple nerve-ganglion models are exhibited which theoretically account for the arithmetic computations necessary to expedite such transformations.     

Statistical analysis of multipath neural systems

Peripheral sensory and motor systems may be characterized by models consisting of multiple parallel convergent pathways, each described by the same set of equations, but having different parameter values in each path. Such models, although deterministic, are best analyzed using a statistical approach, which is illustrated here by analysis of several simple multipath models composed of linear dynamic elements and static non-linear elements. Relationships between instantaneous means of signals at different points in such systems are used to show that a multipath system can exhibit behaviour which would not be expected from observations of individual pathways. Mechanisms for linearization of static non-linearities are briefly described. Important implications for neurophysiologists are discussed.     

Quantitative Study of the Chiral Organization of the Phage Genome Induced by the Packaging Motor

Molecular motors that translocate DNA are ubiquitous in nature. During morphogenesis of double-stranded DNA bacteriophages, a molecular motor drives the viral genome inside a protein capsid. Several models have been proposed for the three-dimensional geometry of the packaged genome, but very little is known of the signature of the molecular packaging motor. For instance, biophysical experiments show that in some systems, DNA rotates during the packaging reaction, but most current biophysical models fail to incorporate this property. Furthermore, studies including rotation mechanisms have reached contradictory conclusions. In this study, we compare the geometrical signatures imposed by different possible mechanisms for the packaging motors: rotation, revolution, and rotation with revolution. We used a previously proposed kinetic Monte Carlo model of the motor, combined with Brownian dynamics simulations of DNA to simulate deterministic and stochastic motor models. We find that rotation is necessary for the accumulation of DNA writhe and for the chiral organization of the genome. We observe that although in the initial steps of the packaging reaction, the torsional strain of the genome is released by rotation of the molecule, in the later stages, it is released by the accumulation of writhe. We suggest that the molecular motor plays a key role in determining the final structure of the encapsidated genome in bacteriophages.     

Regularity and Synchrony in Motor Proteins

We investigate the origin of the regularity and synchrony which have been observed in numerical experiments of two realistic models of molecular motors, namely Fisher–Kolomeisky’s model of myosin V for vesicle transport in cells and Duke’s model of myosin II for sarcomere shortening in muscle contraction. We show that there is a generic organizing principle behind the emergence of regular gait for a motor pulling a large cargo and synchrony of action of many motors pulling a single cargo. These results are surprising in that the models used are inherently stochastic, and yet they display regular behaviors in the parameter range relevant to experiments. Our results also show that these behaviors are not tied to the particular models used in these experiments, but rather are generic to a wide class of motor protein models.     

Hill muscle model errors during movement are greatest within the physiologically relevant range of motor unit firing rates

This study evaluated the accuracy of Hill-type muscle models during movement. Hill-type models are ubiquitous in biomechanical simulations. They are attractive because of their computational simplicity and close relation to commonly measured experimental variables, but there have been surprisingly few experimental validations of these models during functionally relevant conditions. Our hypothesis was that model errors during movement are largest at the low motor unit firing rates most relevant to normal movement conditions. This hypothesis was evaluated in the cat soleus muscle activated either by electrical stimulation at physiological rates or via the crossed-extension reflex (CXR) thereby obtaining normal patterns of motor unit recruitment and rate modulation. These activation paradigms were applied during continuous movements approximately matched to locomotor length changes. The resulting muscle force was modeled using a common Hill model incorporating independent activation, tetanic length-tension and tetanic force-velocity properties. Errors for this model were greatest for stimulation rates between approximately 10-20Hz. Errors were especially large for muscles activated via the CXR, where most motor units appear to fire within this range. For large muscle excursions, such as those seen during normal locomotion, the errors for naturally activated muscle typically exceeded 50%, supporting our hypothesis and indicating that the Hill model is not appropriate for these conditions. Subsequent analysis suggested that model errors were due to the common Hill model's inability to account for the coupling between muscle activation and force-velocity properties that is most prevalent at the low motor unit firing rates relevant to normal activation.     

The mechanisms of morphological-motor functioning in elementary school female first- to fourth-graders

Four morphological and 7 motor variables were assessed in a sample of 2,235 female children (subdivided into 4 groups) aged 7-11 years, elementary school first- to fourth-graders from the Primorje-Gorski Kotar County, Republic of Croatia. The study objective was to analyze the morphological-motor structures according to age. Factor analysis was done for each of the four subject groups. Results clearly showed the morphological-motor functioning of the girls to change with age. Developmental processes lead to the formation of a general morphological factor defined as ectomesomorph and two general mechanisms responsible for motor efficiency in the form of strength regulation and speed regulation. The results obtained were found to be consistent with the existing relevant models related to the morphological, motor, functional and cognitive systems. The more so, these results allow for a supramodel to design, which will integrate relevant elements of all these models to define the function of the body as a whole.     

Langevin dynamics simulation of DNA ejection from a phage

We have performed Langevin dynamics simulations of a coarse-grained model of ejection of dsDNA from Φ29 phage. Our simulation results show significant variations in the local ejection speed, consistent with experimental observations reported in the literature for both in vivo and in vitro systems. In efforts to understand the origin of such variations in the local speed of ejection, we have investigated the correlations between the local ejection kinetics and the packaged structures created at various motor forces and chain flexibility. At lower motor forces, the packaged DNA length is shorter with better organization. On the other hand, at higher motor forces typical of realistic situations, the DNA organization inside the capsid suffers from significant orientational disorder, but yet with long orientational correlation times. This in turn leads to lack of registry between the direction of the DNA segments just to be ejected and the direction of exit. As a result, a significant amount of momentum transfer is required locally for successful exit. Consequently, the DNA ejection temporarily slows down exhibiting pauses. This slowing down occurs at random times during the ejection process, completely determined by the particular starting conformation created by prescribed motor forces. In order to augment our inference, we have additionally investigated the ejection of chains with deliberately changed persistence length. For less inflexible chains, the demand on the occurrence of large momentum transfer for successful ejection is weaker, resulting in more uniform ejection kinetics. While being consistent with experimental observations, our results show the nonergodic nature of the ejection kinetics and call for better theoretical models to portray the kinetics of genome ejection from phages.     

Viscoelasticity of living materials: mechanics and chemistry of muscle as an active macromolecular system

At the molecular and cellular level, mechanics and chemistry are two aspects of the same macromolecular system. We present a bottom-up approach to such systems based on Kramers' diffusion theory of chemical reactions, the theory of polymer dynamics, and the recently developed models for molecular motors. Using muscle as an example, we develop a viscoelastic theory of muscle in terms of an simple equation for single motor protein movement. Both A.V. Hill's contractile component and A.F. Huxley's equation of sliding-filament motion are shown to be special cases of the general viscoelastic theory of the active material. Some disparity between the mechanical and the chemical views of cross-bridges and motor proteins are noted, and a duality between force and energy in discrete states and transitions of macromolecular systems is discussed.