Publications

We present a two-step approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only sparse distance constraints, such as those derived from chemical cross-linking, dipolar EPR and FRET experiments. In Step 1, using an algorithm, we developed, the conformational space of membrane protein folds matching a set of distance constraints is explored to provide initial structures for local conformational searches. In Step 2, these structures refined against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. We begin by describing the statistical analysis of the solved membrane protein structures from which the theoretical portion of the penalty function was derived. We then describe the penalty function, and, using a set of six test cases, demonstrate that it is capable of distinguishing helical bundles that are close to the native bundle from those that are far from the native bundle. Finally, using a set of only 27 distance constraints extracted from the literature, we show that our method successfully recovers the structure of dark-adapted rhodopsin to within 3.2 Å of the crystal structure.

A deterministic algorithm for enumeration of transmembrane protein folds is presented. Using a set of sparse pairwise atomic distance constraints (such as those obtained from chemical cross-linking, FRET, or dipolar EPR experiments), the algorithm performs an exhaustive search of secondary structure element packing conformations distributed throughout the entire conformational space. The end result is a set of distinct protein conformations, which can be scored and refined as part of a process designed for computational elucidation of transmembrane protein structures.

Abstract not provided.

This report summarizes the development of sensor particles for remote detection of trace chemical analytes over broad areas, e.g residual trinitrotoluene from buried landmines or other unexploded ordnance (UXO). We also describe the potential of the sensor particle approach for the detection of chemical warfare (CW) agents. The primary goal of this work has been the development of sensor particles that incorporate sample preconcentration, analyte molecular recognition, chemical signal amplification, and fluorescence signal transduction within a ''grain of sand''. Two approaches for particle-based chemical-to-fluorescence signal transduction are described: (1) enzyme-amplified immunoassays using biocompatible inorganic encapsulants, and (2) oxidative quenching of a unique fluorescent polymer by TNT.