Yungok Ihm

Topological Defects: Origin of Nanopores and Enhanced Adsorption Performance in Nanoporous Carbon

A scanning transmission electron microscopy investigation of two nanoporous carbon materials, wood-based ultramicroporous carbon and poly(furfuryl alcohol)-derived carbon, is reported. Atomic-resolution images demonstrate they comprise isotropic, three-dimensional networks of wrinkled one-atom-thick graphene sheets. In each graphene plane, nonhexagonal defects are frequently observed as connected five- and seven-atom rings. Atomic-level modeling shows that these topological defects induce localized rippling of graphene sheets, which interferes with their graphitic stacking and induces nanopores that lead to enhanced adsorption of H(2) molecules. The poly(furfuryl alcohol)-derived carbon contains larger regions of stacked layers, and shows significantly smaller surface area and pore volume than the ultramicroporous carbon.

Modern approaches to studying gas adsorption in nanoporous carbons

Conventional approaches to understanding the gas adsorption capacity of nanoporous carbons have emphasized the relationship with the effective surface area, but more recent work has demonstrated the importance of local structures and pore-size-dependent adsorption. These developments provide new insights into local structures in nanoporous carbon and their effect on gas adsorption and uptake characteristics. Experiments and theory show that appropriately tuned pores can strongly enhance local adsorption, and that pore sizes can be used to tune adsorption characteristics. In the case of H2 adsorbed on nanostructured carbon, quasielastic and inelastic neutron scattering probes demonstrate novel quantum effects in the motion of adsorbed molecules.

Predicting binding sites of hydrolase-inhibitor complexes by combining several methods

BackgroundProtein-protein interactions play a critical role in protein function. Completion of many genomes is being followed rapidly by major efforts to identify interacting protein pairs experimentally in order to decipher the networks of interacting, coordinated-in-action proteins. Identification of protein-protein interaction sites and detection of specific amino acids that contribute to the specificity and the strength of protein interactions is an important problem with broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks.ResultsIn order to increase the power of predictive methods for protein-protein interaction sites, we have developed a consensus methodology for combining four different methods. These approaches include: data mining using Support Vector Machines, threading through protein structures, prediction of conserved residues on the protein surface by analysis of phylogenetic trees, and the Conservatism of Conservatism method of Mirny and Shakhnovich. Results obtained on a dataset of hydrolase-inhibitor complexes demonstrate that the combination of all four methods yield improved predictions over the individual methods.ConclusionsWe developed a consensus method for predicting protein-protein interface residues by combining sequence and structure-based methods. The success of our consensus approach suggests that similar methodologies can be developed to improve prediction accuracies for other bioinformatic problems.

The influence of dispersion interactions on the hydrogen adsorption properties of expanded graphite

We demonstrate the importance of London dispersion forces in defining the adsorption capacity within expanded graphite, a simple model of the more complex experimental geometries of activated carbon, using a combination of the non-local correlation functional of Dion et al paired with a recent exchange functional of Cooper (vdW-DF(C09x)) and a classical continuum model. Our results indicate that longer ranged interactions due to dispersion forces increase the volume over which molecules interact with a porous medium. This significantly enhances the adsorption density within a material, and explains recent experimental work showing that the densification of H(2) in carbon nanopores is sensitive to the pore size. Remarkably, our slit pore geometries give adsorption densities of up to 3 wt% at 298 K and 20 MPa which correlates well with experimental values for 9 Å pores-a value that could not be predicted using local density approximation (LDA) calculations. In its entirety, this work presents a powerful approach for assessing molecular uptake in porous media and may have serious impacts on efforts to optimize the properties of these materials.

Microstructure-Dependent Gas Adsorption: Accurate Predictions of Methane Uptake in Nanoporous Carbons

We present a framework for rapidly predicting gas adsorption properties based on van der Waals density functional calculations and thermodynamic modeling. Utilizing this model and experimentally determined pore size distributions, we are able to accurately predict uptakes in five activated carbon materials without empirical potentials or lengthy simulations. Our results demonstrate that materials with smaller pores and higher heats of adsorption can still have poor adsorption characteristics due to relatively low densities of highly adsorbent pores.

Structural Model of the Rev Regulatory Protein from Equine Infectious Anemia Virus

Rev is an essential regulatory protein in the equine infectious anemia virus (EIAV) and other lentiviruses, including HIV-1. It binds incompletely spliced viral mRNAs and shuttles them from the nucleus to the cytoplasm, a critical prerequisite for the production of viral structural proteins and genomic RNA. Despite its important role in production of infectious virus, the development of antiviral therapies directed against Rev has been hampered by the lack of an experimentally-determined structure of the full length protein. We have used a combined computational and biochemical approach to generate and evaluate a structural model of the Rev protein. The modeled EIAV Rev (ERev) structure includes a total of 6 helices, four of which form an anti-parallel four-helix bundle. The first helix contains the leucine-rich nuclear export signal (NES). An arginine-rich RNA binding motif, RRDRW, is located in a solvent-exposed loop region. An ERLE motif required for Rev activity is predicted to be buried in the core of modeled structure where it plays an essential role in stabilization of the Rev fold. This structural model is supported by existing genetic and functional data as well as by targeted mutagenesis of residues predicted to be essential for overall structural integrity. Our predicted structure should increase understanding of structure-function relationships in Rev and may provide a basis for the design of new therapies for lentiviral diseases.