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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Geometrical analysis of Cys-Cys bridges in proteins and their prediction from incomplete structural information

Analysis of C-alpha atom positions from cysteines involved in disulphide bridges in protein crystals shows that their geometric characteristics are unique with respect to other Cys-Cys, non-bridging pairs. They may be used for predicting disulphide connections in incompletely determined protein structures, such as low resolution crystallography or theoretical folding experiments. The basic unit for analysis and prediction is the 3 x 3 distance matrix for Cx positions of residues (i - 1), Cys(i), (i +1) with (j - 1), Cys(j), (j + 1). In each of its columns, row and diagonal vector--outer distances are larger than the central distance. This analysis is compared with some analytical models.

NASA Discipline Exobiology↗
NASA NTRS2004

Macromolecular Crystallization in Microgravity

The key concepts that attracted crystal growers, macromolecular or solid state, to microgravity research is that density difference fluid flows and sedimentation of the growing crystals are greatly reduced. Thus, defects and flaws in the crystals can be reduced, even eliminated, and crystal volume can be increased. Macromolecular crystallography differs from the field of crystalline semiconductors. For the latter, crystals are harnessed for their electrical behaviors. A crystal of a biological macromolecule is used instead for diffraction experiments (X-ray or neutron) to determine the three-dimensional structure of the macromolecule. The better the internal order of the crystal of a biological macromolecule then the more molecular structure detail that can be extracted. This structural information that enables an understanding of how the molecule functions. This knowledge is changing the biological and chemical sciences with major potential in understanding disease pathologies. Macromolecular structural crystallography in general is a remarkable field where physics, biology, chemistry, and mathematics meet to enable insight to the basic fundamentals of life. In this review, we examine the use of microgravity as an environment to grow macromolecular crystals. We describe the crystallization procedures used on the ground, how the resulting crystals are studied and the knowledge obtained from those crystals. We address the features desired in an ordered crystal and the techniques used to evaluate those features in detail. We then introduce the microgravity environment, the techniques to access that environment, and the theory and evidence behind the use of microgravity for crystallization experiments. We describe how ground-based laboratory techniques have been adapted to microgravity flights and look at some of the methods used to analyze the resulting data. Several case studies illustrate the physical crystal quality improvements and the macromolecular structural advances. Finally, limitations and alternatives to microgravity and future directions for this research are covered.

Snell, Edward H.↗
NASA NTRS1991

Statistics of contractive cracking patterns

The statistics of convective soil patterns are analyzed using statistical crystallography. An underlying hierarchy of order is found to span four orders of magnitude in characteristic pattern length. Strict mathematical requirements determine the two-dimensional (2D) topology, such that random partitioning of space yields a predictable statistical geometry for polygons. For all lengths, Aboav's and Lewis's laws are verified; this result is consistent both with the need to fill 2D space and most significantly with energy carried not by the patterns' interior, but by the boundaries. Together, this suggests a common mechanism of formation for both micro- and macro-freezing patterns.

Noever, David A.↗
NASA NTRS2015

Free-Energy Calculations. A Mathematical Perspective

Ion channels are pore-forming assemblies of transmembrane proteins that mediate and regulate ion transport through cell walls. They are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses. They are also essential to cardiac processes, muscle contraction and epithelial transport. Ion channels from lower organisms can act as toxins or antimicrobial agents, and in a number of cases are involved in infectious diseases. Because of their important and diverse biological functions they are frequent targets of drug action. Also, simple natural or synthetic channels find numerous applications in biotechnology. For these reasons, studies of ion channels are at the forefront of biophysics, structural biology and cellular biology. In the last decade, the increased availability of X-ray structures has greatly advanced our understanding of ion channels. However, their mechanism of action remains elusive. This is because, in order to assist controlled ion transport, ion channels are dynamic by nature, but X-ray crystallography captures the channel in a single, sometimes non-native state. To explain how ion channels work, X-ray structures have to be supplemented with dynamic information. In principle, molecular dynamics (MD) simulations can aid in providing this information, as this is precisely what MD has been designed to do. However, MD simulations suffer from their own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. To assess the reliability of MD simulations it is only natural to turn to the main function of channels - conducting ions - and compare calculated ionic conductance with electrophysiological data, mainly single channel recordings, obtained under similar conditions. If this comparison is satisfactory it would greatly increase our confidence that both the structures and our computational methodologies are sufficiently accurate. Channel conductance, defined as the ratio of ionic current through the channel to applied voltage, can be calculated in MD simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. If the current is small, a voltage significantly higher than the experimental one needs to be applied to collect sufficient statistics of ion crossing events. Then, the calculated conductance has to be extrapolated to the experimental voltage using procedures of unknown accuracy. Instead, we propose an alternative approach that applies if ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. Then, it is possible to test the assumptions of the equation, recover the full voltage/current dependence, determine the reliability of the calculated conductance and reconstruct the underlying (equilibrium) free energy profile, all from MD simulations at a single voltage. We will present the underlying theory, model calculations that test this theory and simulations on ion conductance through a channel that has been extensively studied experimentally. To our knowledge this is the first case in which the complete, experimentally measured dependence of the current on applied voltage has been reconstructed from MD simulations.

free energy↗
NASA NTRS1995

Finding the global minimum: a fuzzy end elimination implementation

The 'fuzzy end elimination theorem' (FEE) is a mathematically proven theorem that identifies rotameric states in proteins which are incompatible with the global minimum energy conformation. While implementing the FEE we noticed two different aspects that directly affected the final results at convergence. First, the identification of a single dead-ending rotameric state can trigger a 'domino effect' that initiates the identification of additional rotameric states which become dead-ending. A recursive check for dead-ending rotameric states is therefore necessary every time a dead-ending rotameric state is identified. It is shown that, if the recursive check is omitted, it is possible to miss the identification of some dead-ending rotameric states causing a premature termination of the elimination process. Second, we examined the effects of removing dead-ending rotameric states from further considerations at different moments of time. Two different methods of rotameric state removal were examined for an order dependence. In one case, each rotamer found to be incompatible with the global minimum energy conformation was removed immediately following its identification. In the other, dead-ending rotamers were marked for deletion but retained during the search, so that they influenced the evaluation of other rotameric states. When the search was completed, all marked rotamers were removed simultaneously. In addition, to expand further the usefulness of the FEE, a novel method is presented that allows for further reduction in the remaining set of conformations at the FEE convergence. In this method, called a tree-based search, each dead-ending pair of rotamers which does not lead to the direct removal of either rotameric state is used to reduce significantly the number of remaining conformations. In the future this method can also be expanded to triplet and quadruplet sets of rotameric states. We tested our implementation of the FEE by exhaustively searching ten protein segments and found that the FEE identified the global minimum every time. For each segment, the global minimum was exhaustively searched in two different environments: (i) the segments were extracted from the protein and exhaustively searched in the absence of the surrounding residues; (ii) the segments were exhaustively searched in the presence of the remaining residues fixed at crystal structure conformations. We also evaluated the performance of the method for accurately predicting side chain conformations. We examined the influence of factors such as type and accuracy of backbone template used, and the restrictions imposed by the choice of potential function, parameterization and rotamer database. Conclusions are drawn on these results and future prospects are given.

NASA Program Exobiology↗