Pacific Northwest National Laboratory

About: Pacific Northwest National Laboratory is a facility organization based out in Richland, Washington, United States. It is known for research contribution in the topics: Catalysis & Aerosol. The organization has 11581 authors who have published 27934 publications receiving 1120489 citations. The organization is also known as: PNL & PNNL.

Methodology for Formulating Diesel Surrogate Fuels with Accurate Compositional, Ignition-Quality, and Volatility Characteristics

Abstract: In this study, a novel approach was developed to formulate surrogate fuels having characteristics that are representative of diesel fuels produced from real-world refinery streams. Because diesel fuels typically consist of hundreds of compounds, it is difficult to conclusively determine the effects of fuel composition on combustion properties. Surrogate fuels, being simpler representations of these practical fuels, are of interest because they can provide a better understanding of fundamental fuel-composition and property effects on combustion and emissions-formation processes in internal-combustion engines. In addition, the application of surrogate fuels in numerical simulations with accurate vaporization, mixing, and combustion models could revolutionize future engine designs by enabling computational optimization for evolving real fuels. Dependable computational design would not only improve engine function, it would do so at significant cost savings relative to current optimization strategies that rel...

Distance restraints from crosslinking mass spectrometry: Mining a molecular dynamics simulation database to evaluate lysine–lysine distances

Abstract: Integrative structural biology attempts to model the structures of protein complexes that are challenging or intractable by classical structural methods (due to size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such experimental method is chemical crosslinking mass spectrometry (XL-MS), in which protein complexes are crosslinked and characterized using liquid chromatography-mass spectrometry to pinpoint specific amino acid residues in close structural proximity. The commonly used lysine-reactive N-hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS3) have a linker arm that is 11.4 A long when fully extended, allowing Cα (alpha carbon of protein backbone) atoms of crosslinked lysine residues to be up to ∼24 A apart. However, XL-MS studies on proteins of known structure frequently report crosslinks that exceed this distance. Typically, a tolerance of ∼3 A is added to the theoretical maximum to account for this observation, with limited justification for the chosen value. We used the Dynameomics database, a repository of high-quality molecular dynamics simulations of 807 proteins representative of diverse protein folds, to investigate the relationship between lysine–lysine distances in experimental starting structures and in simulation ensembles. We conclude that for DSS/BS3, a distance constraint of 26–30 A between Cα atoms is appropriate. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL-MS results to structures or in modeling. We also discuss the comparison of XL-MS results to MD simulations and known structures as a means to test and validate experimental XL-MS methods.

PROGRESS IN THE PREDICTION OF pKa VALUES IN PROTEINS

Abstract: The pK(a) -cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pK(a) values and protein electrostatics in general. The first round of the pK(a) -cooperative, which challenged computational labs to carry out blind predictions against pK(a) s experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6-10, 2009). This article serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here, we briefly outline existing approaches for pK(a) calculations, emphasizing methods that were used by the participants in calculating the blind pK(a) values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pK(a) calculations.