RESUMO
Computing the free energies of molecular mechanisms in multidimensional space relies on combinations of geometrically complex reaction coordinates. We show how a graph theory implementation reduces complexity, and illustrate this on the arrangements of hydrogen bonding of a water dimer. The reaction coordinates and forces are computed using graphs that define the dependencies on the atoms in the Free Energy from Adaptive Reaction Coordinate Forces (FEARCF) library. The library can be interfaced with classical molecular dynamics as well as quantum molecular dynamics packages. Multidimensional interdependent reaction coordinates are constructed to produce complex free energy hypersurfaces. The reaction coordinates are graphed from atomic and molecular components to define points, distances, vectors, angles, planes and combinations thereof. The resultant free energy surfaces that are a function of the distance, angles, planes, and so on, can represent molecular mechanisms in reduced dimensions from the component atomic Cartesian coordinate degrees of freedom. The FEARCF library can be interfaced with any molecular package. Here, we demonstrate the link to NWChem to compute a hyperdimensional DFT (aug-cc-pVDZ basis set and X3LYP exchange correlation functionals) free energy space of a water dimer. Analysis of the water dimer free energy hypervolume reveals that while the chain and cyclic hydrogen bonding configurations are located in stable minimum energy wells, the bifurcated hydrogen bond configuration is a gateway to instability and dimer dissociation.
RESUMO
Enzyme reactions are complex to simulate accurately, and none more so than glycoenzymes (glycosyltransferase and glycosidases). A rigorous sampling of the protein frame and the conformationally plural carbohydrate substrate coupled with an unbiased treatment of the electron dynamics is needed to discover the true reaction landscapes. Here, we demonstrate the effectiveness of two computational methods ported in libraries that we have developed. The first is a flat histogram free energy method called FEARCF capable of multidimensional sampling and rapidly converging to a complete coverage of phase space. The second, the Quantum Supercharger Library (QSL), is a method that accelerates the computation of the ab initio electronic wave function as well as the integral derivatives on graphical processing units (GPUs). These QSL accelerated computations form the core components needed for direct quantum dynamics and QM/MM dynamics when coupled with legacy codes such as GAMESS and NWCHEM, making state of the art hyper-parallel electronic computations in chemistry and chemical biology possible. The combination of QSL (acceleration of ab initio QM computation) and FEARCF (multidimensional hyper-parallel reaction dynamics) makes the simulation of ab initio QM/MM reaction dynamics of enzyme catalysis feasible. Enzymes that process carbohydrates pose an added challenge as their pyranose ring substrates span multidimensional conformational space whose sampling is an intimate function of the catalytic mechanism. Here, we use the pairing of FEARCF and QSL to simulate the catalytic effect of the glycoenzyme ß-N-acetylglucosamine transferase (OGT). The reaction mechanism is discovered from a variable three bond reaction surface using SCCDFTB. The role of the OGT in distorting the pyranose ring of ß-N-acetylglucosamine (GlcNAc) away from the equilibrium 4C1 chair conformation toward the E3 envelope needed for the transition state is discovered from its pucker free energy hypersurfaces (or free energy volume, FEV). A complete GlcNAc ring pucker HF 6-31g FEV is constructed from ab initio QM dynamics in vacuum and ab initio QM/MM dynamics in the OGT catalytic domain. The OGT is shown to clearly lower the pathway toward the transition state E3 ring conformer as well as stabilize it by 1.63 kcal/mol. Illustrated here is the use of QSL accelerated ab initio QM/MM dynamics that thoroughly explores carbohydrate catalyzed reactions through a FEARCF multidimensional sampling of the interdependence between reaction and conformational space. This demonstrates how experimentally inaccessible molecular and electronic mechanisms that underpin enzyme catalysis can be discovered by directly modeling the dynamics of these complex reactions.
