Abstract: The invention provides methods, systems and reagents for regulating pH-sensitive protein interaction by incorporating non-natural amino acids into the protein (e.g. an antibody, or its functional fragment, derivative, etc.). The invention also relates to specific uses in regulating pH-sensitive binding of antibodies to tumor site, by conferring enhanced tumor-specificity/selectivity. In that embodiment, the non-natural amino acids preferably have desirable side-chain pKa's, such that at below physiological pH (e.g. about pH 6.3-6.5) the non-natural amino acid confer enhanced binding to tumor antigens in acidic environments. Such non-natural amino acids can be incorporated by any suitable means, such as by utilizing a modified aminoacyl-tRNA synthetase to charge the nonstandard amino acid to a modified tRNA, which forms strict Watson-Crick base-pairing with a codon that normally forms wobble base-pairing with natural tRNAs (e.g. the degenerate codon orthogonal system.

Abstract: A method for practical prediction of the three-dimensional structure of ?-helical membrane proteins (HMPs) is described. The method allows one to predict the binding site and structure for strongly bound ligands. The method combines a protocol of computational methods enabling a complete ensemble of packings to be sampled and systematically reducing this ensemble to progressively more accurate structures until at the end there remain a few that might be functionally relevant and likely to play a role in all binding and activation processes. This method is well suited to automatic operation making it practical to obtain, for example, the ensemble of important structures for all human GPCRs. With this ensemble of all active GPCR structures in the human body, an infimum method is presented to maximize efficacy toward the selected target while minimizing binding to all other GPCRs to eliminate toxicity arising from cross-reacting with other GPCRs (a most common source of drug failure).

Abstract: Functional linkers or anchors interconnecting graphene-like carbon, such as nanotubes or graphite sheets, with a conducting material such as a metal, are shown, together with related structures, devices, methods and systems.

Abstract: Methods and devices for controlling thermal conductivity and thermoelectric power of semiconductor nanowires are described. The thermal conductivity and the thermoelectric power are controlled substantially independently of the electrical conductivity of the nanowires by controlling dimensions and doping, respectively, of the nanowires. A thermoelectric device comprising p-doped and n-doped semiconductor nanowire thermocouples is also shown, together with a method to fabricate alternately p-doped and n-doped arrays of silicon nanowires.

Abstract: Metal-organic frameworks (MOFs) are provided. An exemplary MOF includes a plurality of metal clusters, at least one linking ligand, and at least one dopant. Doped MOFs according to embodiments of the present invention have significantly increased H2 uptake capacity, and some embodiments meet the 2010 DOE H2 storage target of 6 wt % at a temperature ranging from ?30 to 80° C. and a pressure less than or equal to 100 bar.

Abstract: Methods for detecting the breakdown potential of a semiconductor device having a thin dielectric layer are disclosed. The method includes measuring a spectroscopy of the thin dielectric layer and determining whether the spectroscopy exhibits the presence of a breakdown precursor (H2, H interstitial radical, H attached radical, and H attached dimer). Preferably, the method is carried out in the presence of a substantially significant applied electric field across dielectric layer. A semiconductor device tested in accordance with this method is also disclosed. Additionally, methods for reducing dielectric breakdown of a semiconductor device having a thin dielectric layer involving the substitution of a second molecule for H2 molecules present in the dielectric. This second molecule preferably does not react with Si or O to form an undesired attached state and may be an inert gas having a molecular size approximating that of a Hydrogen atom, such as Helium.

Abstract: A fuel cell electrode is provided which comprises catalyst particles and a nanotube composition comprising nanotubes which are predominantly double-walled. The catalyst particles preferably comprise platinum, and are preferably nanoparticles. The nanotubes preferably comprise carbon. A fuel cell is provided comprising an anode, a proton exchange electrolyte membrane, and a cathode, wherein the anode and/or the cathode comprise a catalyst support comprising nanotubes which are predominantly double-walled.

Abstract: Computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the structure of transmembrane proteins such as G-Protein Coupled Receptors, and protein structural models generated according to the protocol. The protocol features a combination of coarse grain sampling methods, such as hydrophobicity analysis, followed by coarse grain molecular dynamics and atomic level molecular dynamics, including accurate continuum solvation, to provide a fast and accurate procedure for predicting GPCR tertiary structure.

Abstract: This invention discloses methods and processes for selectively converting hydrocarbons such as methane to materials such as alcohols or other materials containing more reactive functionalities.

Abstract: Techniques for predicting the behavior of dopant and defect components in a substrate lattice formed from a substrate material can be implemented in hardware or software. Fundamental data for a set of microscopic processes that can occur during one or more material processing operations is obtained. Such data can include data representing the kinetics of processes in the set of microscopic processes and the energetics and structure of possible states in the material processing operations. From the fundamental data and a set of external conditions, distributions of dopant and defect components in the substrate lattice are predicted.

Abstract: The instant invention provides methods and implementing computer software for designing mutant proteins (or “Target Protein or TP”) that will preferentially bind one list of prespecified ligands (Active Ligands or AL) with respect to another list of ligands (The Inactive Ligands or IL).

Abstract: A fuel cell is provided comprising an anode, a cathode, a catalyst, and a polymer electrolyte membrane comprising a heterocyclic compound with a nitrogen heteroatom and at least one electron-withdrawing substituent. The fuel cell operates at temperatures above about 100° C., preferably above about 150° C. The heterocyclic compound is preferably a substituted imidazole or benzoimidazole, most preferably a fluorinated imidazole. The heterocyclic compound is preferably liquid at the fuel cell operating temperature. The catalyst preferably contains platinum. The polymer electrolyte membrane preferably has a conductivity of 10?2 S/cm2 or higher. For efficient fuel cell operation the catalyst should not be poisoned to an undue degree by the heterocyclic compound, and so the binding energy of the heterocyclic compound to the catalyst should be low.

Abstract: The methods of the invention relate to improved methods for determining the optimal sequence alignments between a first protein sequence and a second protein sequence based upon the information from multiple reference structure-structure alignments.

Abstract: The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.

Abstract: The invention provides methods, systems and reagents for regulating pH-sensitive protein interaction by incorporating non-natural amino acids into the protein (e.g. an antibody, or its functional fragment, derivative, etc.). The invention also relates to specific uses in regulating pH-sensitive binding of antibodies to tumor site, by conferring enhanced tumor-specificity/selectivity. In that embodiment, the non-natural amino acids preferably have desirable side-chain pKa's, such that at below physiological pH (e.g. about pH 6.3-6.5) the non-natural amino acid confer enhanced binding to tumor antigens in acidic environments. Such non-natural amino acids can be incorporated by any suitable means, such as by utilizing a modified aminoacyl-tRNA synthetase to charge the nonstandard amino acid to a modified tRNA, which forms strict Watson-Crick base-pairing with a codon that normally forms wobble base-pairing with natural tRNAs (e.g. the degenerate codon orthogonal system.

Abstract: The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the structure of transmembrane proteins such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a combination of coarse grain sampling methods, such as hydrophobicity analysis, followed by coarse grain molecular dynamics and atomic level molecular dynamics, including accurate continuum solvation. Also included are energy optimization to determine the rotation of helices in the (seven-helical) TM bundle, and optimization of the helix translations along their axes and rotational optimization using hydrophobic moment of the helices, to provide a fast and accurate procedure for predicting GPCR tertiary structure.

Abstract: Carbon-based hydrogen storage compositions comprising a pillared carbon material doped with a metal, including compositions containing a pillared carbon material combined with alkali metals and/or alkaline earth metals for use in reversible hydrogen storage applications, are described. Methods of making such compositions and applications of such compositions are also described.

Abstract: Methods for detecting the breakdown potential of a semiconductor device having a thin dielectric layer are disclosed. The method includes measuring a spectroscopy of the thin dielectric layer and determining whether the spectroscopy exhibits the presence of a breakdown precursor (H2, H interstitial radical, H attached radical, and H attached dimer). Preferably, the method is carried out in the presence of a substantially significant applied electric field across dielectric layer. A semiconductor device tested in accordance with this method is also disclosed. Additionally, methods for reducing dielectric breakdown of a semiconductor device having a thin dielectric layer involving the substitution of a second molecule for H2 molecules present in the dielectric. This second molecule preferably does not react with Si or O to form an undesired attached state and may be an inert gas having a molecular size approximating that of a Hydrogen atom, such as Helium.

Abstract: Techniques for predicting the behavior of dopant and defect components in a substrate lattice formed from a substrate material can be implemented in hardware or software. Fundamental data for a set of microscopic processes that can occur during one or more material processing operations is obtained. Such data can include data representing the kinetics of processes in the set of microscopic processes and the energetics and structure of possible states in the material processing operations. From the fundamental data and a set of external conditions, distributions of dopant and defect components in the substrate lattice are predicted.

Abstract: Rational combinatorial computational methods use accurate quantum mechanical and molecular modeling techniques to identify optimum polymerization catalysts for polar olefins. Using mechanistic information to model the polymerization reaction, the methods systematically vary components of a catalyst template to calculate a potential energy surface for a number of catalyst candidates. The potential energy surfaces are compared to identify a catalyst for the catalytic polymerization reaction. Internal Lewis acid single site polar olefin polymerization catalyst compositions and compounds for polymerizing polar olefins are also described.