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This article is from International Journal of Molecular Sciences , volume 15 . Abstract Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis.

This report details the collaboration between the University of Minnesota and the Von Karman Institute. There were two main goals to this collaborative project: (1) To use the US3D code to validate the LHTS approach employed by VKI. Since LHTS is a very useful and widely used technique used to interpret ICP data, a better understanding of its accuracy and potential limitations would be a valuable contribution. (2) To use the US3D code to directly interpret ICP data and thereby develop new high-fidelity models for high-temperature gas-surface interactions. This report details the collaboration which occurred August 2011-February 2012.

This DURIP-funded Beowulf cluster will enhance our AFOSR-funded research in several areas. Large-scale modeling of complex systems in the areas of corrosion and catalysis is a vital Air Force need. Our previous computational resources alone would not allow us to pursue the most important and complex portions of our current contact with AFOSR. The DURIP funding has now provided our personnel with the computational capability to examine the corrosion of aluminum alloys, to understand the role of stress fields in materials and in the multi-scale modeling of fatigue and fracture, and to study reactivity on patterned surfaces including superlattice, nanoparticles, and piezoelectric oxide supported metal. To perform this research, we will use ab-initio density functional theory (DFT), which gives quantitative results by detailed modeling of the valence electrons in materials. The DFT has reportedly proven itself as a highly accurate and highly efficient first-principles computational tool. However, since DFT is a quantum-mechanical method, high accuracy on real-world systems requires significant computational cost. This grant, by funding a Beowulf cluster supercomputing environment, has provided a novel computer architecture which will enable AFOSR-funded researchers to gain new insights into materials of Air Force needs.