This dataset contains additional material related to the article: "MiMiC: A Novel Framework for Multiscale Modeling in Computational Chemistry". The preprint is available at https://doi.org/10.26434/chemrxiv.7635986. Final article is available at https://doi.org/10.1021/acs.jctc.9b00093.
<div>We present a flexible and efficient framework for multiscale modeling in computational chemistry (MiMiC). It is based on a multiple-program multiple-data (MPMD) model with loosely coupled programs. Fast data exchange between programs is achieved through the use of MPI intercommunicators. This allows exploiting the existing parallelization strategies used by the coupled programs while maintaining a high degree of flexibility. MiMiC has been used in a new electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) implementation coupling the highly efficient CPMD and GROMACS programs but it can also be extended to use other programs. The framework can also be utilized to extend the partitioning of the system into several domains that can be treated using different models, such as models based on wavefunction or density functional theory as well as coarse-graining and continuum models. The new QM/MM implementation treats long-range electrostatic QM-MM interactions through the multipoles of the QM subsystem which substantially reduces the computational cost without loss of accuracy compared to an exact treatment. This enables QM/MM molecular dynamics (MD) simulations of very large systems.</div>
MiMiC is a flexible and efficient framework for multiscale simulations in which different subsystems are treated by individual client programs. In this work, we present a new interface with OpenMM to be used as an MM client program and we demonstrate its efficiency for QM/MM MD simulations. Apart from its high performance, especially on GPUs, and a wide selection of features, OpenMM is a highly-flexible and easily-extensible program, ideal for the development of novel multiscale methods. Thanks to the open-ended design of MiMiC, the OpenMM-MiMiC interface will automatically support any new QM client program interfaced with MiMiC for QM/MM and, with minimal changes needed, new multiscale methods implemented, opening up new research directions beyond electrostatic embedding QM/MM.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Identification of the most stable structure(s) of a system is a prerequisite for the calculation of any of its properties from first-principles. However, even for relatively small molecules, exhaustive explorations of the potential energy surface (PES) are severely hampered by the dimensionality bottleneck. In this work, we address the challenging task of efficiently sampling realistic low-lying peptide coordinates by resorting to a surrogate based genetic algorithm (GA)/density functional theory (DFT) approach (sGADFT) in which promising candidates provided by the GA are ultimately optimized with DFT. We provide a benchmark of several computational methods (GAFF, AMOEBApro13, PM6, PM7, DFTB3-D3(BJ)) as possible prescanning surrogates and apply sGADFT to two test case systems that are (i) two isomer families of the protonated Gly-Pro-Gly-Gly tetrapeptide, and (ii) the doubly-protonated cyclic decapeptide gramicidin S. We show that our GA procedure can correctly identify low-energy minima in as little as a few hours. Subsequent refinement of surrogate low-energy structures within a given energy threshold (≤ 10 kcal/mol (i), ≤ 5 kcal/mol (ii)) via DFT relaxation invariably led to the identification of the most stable structures as determined from high-resolution infrared (IR) spectroscopy at low temperature. The sGADFT method therefore constitutes a highly efficient route for the screening of realistic low-lying peptide structures in the gas phase as needed for instance for the interpretation and assignment of experimental IR spectra.
