Modeling Biomolecular Transport Processes

University Of North Carolina At Chapel Hill, Chapel Hill NC

Investigators

Abstract

Elston 0075821 The broad goal of this project is to gain a mechanistic understanding of energy transduction in biomolecular transport processes. The project focuses on three specific systems: the bacterial flagellar motor, the motor protein dynein, and protein translocation systems found in membranes of the endoplasmic reticulum and mitochondria. While the biology involved in these systems is very different, the same mathematical techniques are applicable for analyzing theoretical models of all three. To model these systems requires the use of Langevin or stochastic differential equations. The randomness in these equations comes from two sources, thermal diffusion and chemical kinetics. Thermal fluctuations are characterized by the diffusion coefficient, which can be measured experimentally, and many of the important reaction rates are known from biochemical studies. In addition to molecular collisions, electrostatic interactions are the other dominant forces involved in these transport systems. If available, structural data are used to determine the relevant electrostatic potentials. Once model equations for the systems have been developed, numerical and analytical techniques are used to compare their behavior with experimental data. The final phase of the analysis is to use the mathematical models to produce experimentally testable predictions. Biological molecular motors are nanometer-sized engines that use chemical energy to generate force. A well known molecular motor is myosin, which is the protein responsible for muscle contraction. Other examples include the flagellar motor, which is used by bacteria for swimming, and dynein, which produces the force necessary for cilia motion. The broad goal of this project is to gain a mechanistic understanding of force generation in both these systems. Current experimental techniques are allowing biophysicists to study molecular motors at the single molecule level, thereby allowing the mechanical properties of motor proteins to be measured. These new physical data in conjunction with structural data provide the impetus for renewed theoretical investigations into molecular motor function. An important reason for performing a mathematical analysis of force generation is that it allows a quantitative comparison between experimental data and model behavior to be made. The results of such a comparison not only are important for model validation, but also can be used to uncover errors in the assumptions underlying the model. However, the significance of mathematical modeling goes beyond model validation and lies in its predictive power. Once a theoretical model has been developed that is consistent with current experimental data, it is straightforward to extend the analysis to include situations that have not yet been investigated in the laboratory. If model predictions are borne out by experiment, further confidence in the reality of the model is gained. For the systems under consideration in this project, this means a mechanistic understanding of force generation has been achieved. From a technological standpoint, the results of these investigations should be relevant for designing and fabricating manmade nanomachines.