A solvent screening model for the molecular electrostatic potential is developed for the fragment molecular orbital method combined with the polarizable continuum model at the Hartree−Fock and density functional theory levels. The accuracy of the generated potentials is established in comparison to calculations without fragmentation. Solvent effects upon the molecular electrostatic potential and electron density of solute are discussed. The method is applied to two proteins: chignolin (PDB: 1UAO) and ovine prostaglandin H(2) synthase-1 (1EQG).

Enzymatic reactions play key role in metabolism of all living organisms. Recent advances in computational methods allow detailed study of enzyme-catalyzed processes, providing data on all intermediate states along reaction path. Furthermore, experimental data on the structure of the reaction intermediates become more available due to advancing of ultrafast X-Ray spectroscopy. These data describes electronic density of intermediates, sometimes even in time series. Currently, prominent Protein Data Bank (PDB) keeps records on the raw crystallographic data on electron density, but usually describes only enzymes or enzymes-inhibitor complexes. A database service where the both experimental and simulated data can be stored and analyzed simultaneously will be a valuable scientific tool for bringing theory and experiment together. There are hundreds of enzymes known and one should expect large volumes of data on three-dimensional property like electronic density. At the same time, quantum chemistry simulations of large biomolecules require extensive computing resources. Thus, we turned into service model using Nautilus environment of Cognitive Hardware And Software Ecosystem Community Infrastructure (CHASE-CI) project as a blueprint. In that environment, each participating organization can donate their hardware resources, like storage or compute elements, while retaining flexible access control to running services and datasets. We have installed and tested a small-scale environment prototype using resources of LCC laboratory at Chemistry Department Lomonosov Moscow State University, Joint Institute of Nuclear Research (Dubna) and RSC Group company (Moscow). As it was efficiently implemented in Sloan Digital Sky Survey (SDSS) project, we identified basic search queries and structured database accordingly.