Journal of Computational Chemistry

doi: 10.1002/jcc.25023pmid: N/A

doi: 10.1002/jcc.25020pmid: N/A

Nakata, Hiroya; Fedorov, Dmitri G.

doi: 10.1002/jcc.25360pmid: 30299549

The analytic second derivatives of the energy with respect to nuclear coordinates are developed for restricted Hartree–Fock and density functional theory, based on the two‐body fragment molecular orbital method (FMO) and combined with the electrostatic embedding potential, self‐consistently determined by point charges for far separated fragments and electron densities for near fragments. The accuracy of the method is established with respect to FMO using the exact embedding potential based on electron densities and to full calculations without fragmentation. The computational efficiency of parallelization is measured on the K supercomputer and the method is applied to simulate infrared spectra of two proteins, Trp‐cage (PDB: 1L2Y) and crambin (1CRN). The nature of the vibrations in the Amide I peak of crambin and the Tyr symmetric stretch peak in Trp‐cage are analyzed in terms of localized vibrations. © 2018 Wiley Periodicals, Inc.

Dix, James; Lue, Leo; Carbone, Paola

doi: 10.1002/jcc.25369pmid: 30226923

Experiments of nanoconfined water between graphene sheets at high pressure suggest that it forms a square ice structure (Algara‐Siller et al., Nature, 2015, 519, 443). Molecular dynamics (MD) simulations have been used to attempt to recreate this structure, but there have been discrepancies in the structure formed by the confined water depending on the simulation set‐up that was employed and particularly on the choice of water model. Here, using classical molecular dynamics simulations, we have systematically investigated the effect that three different water models (SPC/E, TIP4P/2005 and TIP5P) have on the structure of water confined between two rigid graphene sheets with a 0.9 nm separation. We show that the TIP4P/2005 and the TIP5P water models form a hexagonal AA‐stacked structure, whereas the SPC/E model forms a rhombic AB‐stacked structure. Our work demonstrates that the formation of these structures is driven by differences in the strength of hydrogen bonds predicted by the three water models, and that the nature of the graphene/water interaction only mildly affects the phase diagram. Considering the available experimental data and first‐principle simulations we conclude that, among the models tested, the TIP4P/2005 and TIP5P force fields are for now the most reliable when simulating water under confinement. © 2018 Wiley Periodicals, Inc.

Sugiura, Yutaro; Suzuki, Kento; Takayanagi, Toshiyuki; Kita, Yukiumi; Tachikawa, Masanori

doi: 10.1002/jcc.25387pmid: 30284294

Positron affinities have been calculated for five amino acid molecules (asparagine, cysteine, glycine, proline, and serine) with the intramolecular COOH···NH2 hydrogen‐bonded motif as a function of the OH distance using two computational methods, namely multicomponent molecular orbital theory and pseudopotential model. Since the elongation of the carboxylic OH bond leads to the formation of highly polarized zwitterionic amino acid with COO−···NH3+ structure, the calculated positron affinity significantly increases with the elongation of the OH distance. This indicates that the OH bond strength is significantly weakened by positron attachment. We discuss the reduction of OH vibrational frequencies using effective one‐dimensional potential energy curves for neutral and positron‐attached amino acid molecules. © 2018 Wiley Periodicals, Inc.

Inakollu, V. S. Sandeep; Yu, Haibo

doi: 10.1002/jcc.25390pmid: 30368840

Computational vibrational spectroscopy serves as an important tool in the interpretation of experimental infrared (IR) spectra. In this article, we present a systematic benchmarking study of DFTB3 with two different computational vibrational spectroscopic methods, based on either normal mode analysis (NMA) or fast Fourier transform dipole autocorrelation function (FT‐DAC). The results were compared with experimental data and theoretical calculations with B3LYP/cc‐pVTZ. The empirical scaling factors for DFTB3/NMA, DFTB3‐freq/NMA, and DFTB3/FT‐DAC methods are 0.9993, 1.0059, and 0.9982, respectively. We also demonstrate the significance of anharmonicity and conformational sampling in vibrational spectroscopic calculations on flexible molecules. As expected, DFTB3/FT‐DAC predicted the anharmonic vibrational peaks more accurately than DFTB3/NMA and NMA spectra are highly dependent on the initial structures. The potential limitations of DFTB3 for vibrational spectroscopic calculations and the challenges in assigning the FT‐DAC spectral peaks were noted. DFTB3/FT‐DAC is expected to serve as a promising technique in computational spectroscopy in complex biomolecular systems. © 2018 Wiley Periodicals, Inc.

Chen, Wei; Ferguson, Andrew L.

doi: 10.1002/jcc.25520pmid: 30368832

Macromolecular and biomolecular folding landscapes typically contain high free energy barriers that impede efficient sampling of configurational space by standard molecular dynamics simulation. Biased sampling can artificially drive the simulation along prespecified collective variables (CVs), but success depends critically on the availability of good CVs associated with the important collective dynamical motions. Nonlinear machine learning techniques can identify such CVs but typically do not furnish an explicit relationship with the atomic coordinates necessary to perform biased sampling. In this work, we employ auto‐associative artificial neural networks (“autoencoders”) to learn nonlinear CVs that are explicit and differentiable functions of the atomic coordinates. Our approach offers substantial speedups in exploration of configurational space, and is distinguished from existing approaches by its capacity to simultaneously discover and directly accelerate along data‐driven CVs. We demonstrate the approach in simulations of alanine dipeptide and Trp‐cage, and have developed an open‐source and freely available implementation within OpenMM. © 2018 Wiley Periodicals, Inc.

Tran, Van Tan; Tran, Quoc Tri

doi: 10.1002/jcc.25527pmid: 30207608

The geometrical structures, electron leading configurations, and relative energies of the low‐lying states of VGe n−/0 (n = 5–7) clusters have been investigated with density functional theory and CASSCF/CASPT2 method. The pure GGA BP86 functional gave almost the same relative energy order for the low‐lying states as the CASPT2 method. At the BP86 and CASPT2 levels, the ground states of VGe n−/0 (n = 5–7) clusters were proposed to be the 1A1 and 2A1 of A‐VGe5−/0, 3A″ and 2A″, 2A′ (2E2) of A‐VGe6−/0, and 1A′ and 2A′ of A‐VGe7−/0 isomers. The adiabatic and vertical detachment energies (ADEs and VDEs) of the detachments of one electron from several orbitals of the anionic ground states were reported at the CASPT2 level. The calculated ADEs and VDEs corresponded well with the experimental values as observed in the 266 nm anion photoelectron spectra. © 2018 Wiley Periodicals, Inc.

Roe, Daniel R.; Cheatham, Thomas E.

doi: 10.1002/jcc.25382pmid: 30368859

Advances in biomolecular simulation methods and access to large scale computer resources have led to a massive increase in the amount of data generated. The key enablers have been optimization and parallelization of the simulation codes. However, much of the software used to analyze trajectory data from these simulations is still run in serial, or in some cases many threads via shared memory. Here, we describe the addition of multiple levels of parallel trajectory processing to the molecular dynamics simulation analysis software CPPTRAJ. In addition to the existing OpenMP shared‐memory parallelism, CPPTRAJ now has two additional levels of message passing (MPI) parallelism involving both across‐trajectory processing and across‐ensemble processing. All three levels of parallelism can be simultaneously active, leading to significant speed ups in data analysis of large datasets on the NCSA Blue Waters supercomputer by better leveraging the many available nodes and its parallel file system. © 2018 Wiley Periodicals, Inc.

Sega, Marcello; Hantal, György; Fábián, Balázs; Jedlovszky, Pál

doi: 10.1002/jcc.25384pmid: 30306571

Pytim is a versatile python framework for the analysis of interfacial properties in molecular simulations. The code implements several algorithms for the identification of instantaneous interfaces of arbitrary shape, and analysis tools written specifically for the study of interfacial properties, such as intrinsic profiles. The code is written in the python language, and makes use of the numpy and scipy packages to deliver high computational performances. Pytim relies on the MDAnalysis library to analyze the trajectory file formats of popular simulation packages such as gromacs, charmm, namd, lammps or Amber, and can be used to steer OpenMM simulations. Pytim can write information about surfaces and surface atomic layers to vtk, cube, and pdb files for easy visualization. The classes of Pytim can be easily customized and extended to include new interfacial algorithms or analysis tools. The code is available as open source and is free of charge. © 2018 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc