Insights into the mechanism of human erythrocyte hexose transport : a transferred NOE study of glucose binding to GLUT1

This study examines binding of α- and β-D-glucose in their equilibrium mixture to the glucose transporter (GLUT1) in human erythrocyte membrane preparations by an ^1H NMR method, the transferred NOE (TRNOE). This method is shown theoretically and experimentally to be a sensitive probe of weak ligand-macromolecule interactions. The TRNOEs observed are shown to arise solely from glucose binding to GLUT1. Sites at both membrane faces contribute to the TRNOEs. Binding curves obtained are consistent with a homogeneous class of sugar sites, with an apparent K_D which varies (from ~30 mM to ~70 mM for both anomers) depending on the membrane preparation examined. Preparations with a higher proportion of the cytoplasmic membrane face exposed to bulk solution yield higher apparent KK_Ds. The glucose transport inhibitor cytochalasin B essentially eliminates the TRNOE. Nonlinearity was found in the dependence on sugar concentration of the apparent inhibition constant for cytochalasin B reversal of the TRNOE observed in the α anomer (and probably the β anomer); such nonlinearity implies the existence of ternary complexes of sugar, inhibitor and transporter. The inhibition results furthermore imply the presence of a class of relatively high-affinity (K_D < 2mM) sugar sites specific for the α anomer which do not contribute to NMR-observable binding. The presence of two classes of sugar-sensitive cytochalasin B sites is also indicated. These results are compared with predictions of the alternating conformer model of glucose transport. Variation of apparent K_D in the NMR-observable sites, the formation of ternary complexes and the presence of an anomer-specific site are shown to be inconsistent with this model. An alternate model is developed which reconciles these results with the known transport behavior of GLUT1. In this model, the transporter possesses (at minimum) three classes of sugar sites: (i) transport sites, which are alternately exposed to the cytoplasmic or the extracellular compartment, but never to both simultaneously, (ii) a class of sites (probably relatively low-affinity) which are confined to one compartment, and (iii) the high-affinity α anomer-specific sites, which are confined to the cytoplasmic compartment.

Robot navigation in dense crowds : statistical models and experimental studies of human robot cooperation

This thesis explores the problem of mobile robot navigation in dense human crowds. We begin by considering a fundamental impediment to classical motion planning algorithms called the freezing robot problem: once the environment surpasses a certain level of complexity, the planner decides that all forward paths are unsafe, and the robot freezes in place (or performs unnecessary maneuvers) to avoid collisions. Since a feasible path typically exists, this behavior is suboptimal. Existing approaches have focused on reducing predictive uncertainty by employing higher fidelity individual dynamics models or heuristically limiting the individual predictive covariance to prevent overcautious navigation. We demonstrate that both the individual prediction and the individual predictive uncertainty have little to do with this undesirable navigation behavior. Additionally, we provide evidence that dynamic agents are able to navigate in dense crowds by engaging in joint collision avoidance, cooperatively making room to create feasible trajectories. We accordingly develop interacting Gaussian processes, a prediction density that captures cooperative collision avoidance, and a "multiple goal" extension that models the goal driven nature of human decision making. Navigation naturally emerges as a statistic of this distribution.

Most importantly, we empirically validate our models in the Chandler dining hall at Caltech during peak hours, and in the process, carry out the first extensive quantitative study of robot navigation in dense human crowds (collecting data on 488 runs). The multiple goal interacting Gaussian processes algorithm performs comparably with human teleoperators in crowd densities nearing 1 person/m², while a state of the art noncooperative planner exhibits unsafe behavior more than 3 times as often as the multiple goal extension, and twice as often as the basic interacting Gaussian process approach. Furthermore, a reactive planner based on the widely used dynamic window approach proves insufficient for crowd densities above 0.55 people/m². We also show that our noncooperative planner or our reactive planner capture the salient characteristics of nearly any dynamic navigation algorithm. For inclusive validation purposes, we show that either our non-interacting planner or our reactive planner captures the salient characteristics of nearly any existing dynamic navigation algorithm. Based on these experimental results and theoretical observations, we conclude that a cooperation model is critical for safe and efficient robot navigation in dense human crowds.

Finally, we produce a large database of ground truth pedestrian crowd data. We make this ground truth database publicly available for further scientific study of crowd prediction models, learning from demonstration algorithms, and human robot interaction models in general.

Designing conformational control of human tissue transglutaminase

Understanding the mechanisms of enzymes is crucial for our understanding of their role in biology and for designing methods to perturb or harness their activities for medical treatments, industrial processes, or biological engineering. One aspect of enzymes that makes them difficult to fully understand is that they are in constant motion, and these motions and the conformations adopted throughout these transitions often play a role in their function.

Traditionally, it has been difficult to isolate a protein in a particular conformation to determine what role each form plays in the reaction or biology of that enzyme. A new technology, computational protein design, makes the isolation of various conformations possible, and therefore is an extremely powerful tool in enabling a fuller understanding of the role a protein conformation plays in various biological processes.

One such protein that undergoes large structural shifts during different activities is human type II transglutaminase (TG2). TG2 is an enzyme that exists in two dramatically different conformational states: (1) an open, extended form, which is adopted upon the binding of calcium, and (2) a closed, compact form, which is adopted upon the binding of GTP or GDP. TG2 possess two separate active sites, each with a radically different activity. This open, calcium-bound form of TG2 is believed to act as a transglutaminse, where it catalyzes the formation of an isopeptide bond between the sidechain of a peptide-bound glutamine and a primary amine. The closed, GTP-bound conformation is believed to act as a GTPase. TG2 is also implicated in a variety of biological and pathological processes.

To better understand the effects of TG2’s conformations on its activities and pathological processes, we set out to design variants of TG2 isolated in either the closed or open conformations. We were able to design open-locked and closed-biased TG2 variants, and use these designs to unseat the current understanding of the activities and their concurrent conformations of TG2 and explore each conformation’s role in celiac disease models. This work also enabled us to help explain older confusing results in regards to this enzyme and its activities. The new model for TG2 activity has immense implications for our understanding of its functional capabilities in various environments, and for our ability to understand which conformations need to be inhibited in the design of new drugs for diseases in which TG2’s activities are believed to elicit pathological effects.