Pseudopotentials for the chemical cross-links comprising the glutamic- and aspartic-acid side chains bridged with adipic- (ADH) or pimelic-acid hydrazide (PDH), and the lysine side chains bridged with glutaric (BS2 G) or suberic acid (BS3 ) for coarse-grained cross-link-assisted simulations were determined by canonical molecular dynamics with the Amber14sb force field. The potentials depend on the distance between side-chain ends and on side-chain orientation, this preventing from making cross-link contacts across the globule in simulations. The potentials were implemented in the UNRES coarse-grained force field and their effect on the quality of models was assessed with 11 monomeric and 1 dimeric proteins, using synthetic or experimental cross-link data. Simulations with the new potentials resulted in improvement of the generated models compared to unrestrained simulations in more instances compared to those with the statistical potentials.

We have implemented pseudospectral density-functional theory (DFT) with long-range corrected DFT functionals (PS-LRC) in quantum mechanics package Jaguar, and applied it in the calculations of geometry optimizations, dimmer interaction energies, polarizabilities and first-order hyperpolarizabilities, harmonic vibrational frequencies, S1 and T1 excitation energies, singlet-triplet gaps, charge transfer numbers, oscillator strengths, reaction barrier heights, electron-transfer couplings, and charge-transfer excitation energies. From our accuracy benchmark analysis, PS grids, PS dealiasing functions, PS atomic corrections, PS multigrid strategy, PS length scales, and PS cutoff scheme perform well in PS DFT with LRC density functionals with very small and ignorable deviations when compared to the conventional spectral (CS) method. The timing benchmark study of S1 excitation energy calculations of fullerenes (Cn , n up to 540) demonstrates that PS-LRC achieves 1.4-8.4-fold speedups in SCF, 22-32-fold speedups in Tamm-Dancoff approximation, and 6-15-fold speedups in total wall clock time with an average error 0.004 eV of excitation energies compared to the CS method.

Most often, the substituent effects are described using rather troublesome Hammett constants. Quite recently, it has been proposed to use the so-called substituent energy, which is based on total energies of the X-substituted polycyclic aromatic hydrocarbon and phenyl. This article concerns the influence of the applied level of theory (i.e., both the basis set and the method) on the determined values of the substituent energies. For this purpose, the energies of the NH2 and NO2 groups in 16 unique positions of naphthalene, anthracene, tetracene, phenanthrene, and pyrene were calculated using 10 different basis sets and 23 various exchange-correlation functionals representing the entire Jacob's Ladder, from local, through gradient- and meta-gradient-corrected, to hybrid and double-hybrid ones. Additionally, using even larger 6-311++G(2df,2p) basis set, the energies of NH2 , NO2 , CN, and Cl were also computed. Both the basis set and the method used have little effect on the substituent energy if the substituent is in the benzene-like position. On the contrary, the effect of the level of theory is pronounced especially in the case of the most spatially crowded 4-substituted phenanthrene. Substituent energies have been shown to be very useful theoretical parameters describing the proximity effect in the substituted derivatives of polycyclic aromatic hydrocarbons.

Molecular interaction fields (MIFs), describing molecules in terms of their ability to interact with any chemical entity, are one of the most established and versatile concepts in drug discovery. Improvement of this molecular description is highly desirable for in silico drug discovery and medicinal chemistry applications. In this work, we revised a well-established molecular mechanics' force field and applied a hybrid quantum mechanics and machine learning approach to parametrize the hydrogen-bonding (HB) potentials of small molecules, improving this aspect of the molecular description. Approximately 66,000 molecules were chosen from available drug databases and subjected to density functional theory calculations (DFT). For each atom, the molecular electrostatic potential (EP) was extracted and used to derive new HB energy contributions; this was subsequently combined with a fingerprint-based description of the structural environment via partial least squares modeling, enabling the new potentials to be used for molecules outside of the training set. We demonstrate that parameter prediction for molecules outside of the training set correlates with their DFT-derived EP, and that there is correlation of the new potentials with hydrogen-bond acidity and basicity scales. We show the newly derived MIFs vary in strength for various ring substitution in accordance with chemical intuition. Finally, we report that this derived parameter, when extended to non-HB atoms, can also be used to estimate sites of reaction.

The metal-ligand bond in a set of 60 σ-complexes has been investigated by electronic structure computations. These σ-complexes originate from the unique combination of 12 stannylenes (SnX2 ) with five azabenzene ligands (pyridine, pyrazine, pyrimidine, pyridazine, and s-triazine), where the nitrogen center of the ligand acts as σ-donor and the tin(II) center as σ-acceptor in a 1:1 fashion. The Sn ← N bond and the total interaction between the stannylene and azabenzene moieties of the σ-complexes are characterized in depth to relate the Sn ← N strength to the substitution pattern at SnX2 and to the number and the positioning of N atoms in the azabenzenes. Such X substituents as (iso)cyano and trifluoromethyl groups enhance the interaction strength, while the presence of alkyl, phenyl, and silyl substituents in SnX2 diminishes the stability of σ-complexes. A gradual weakening of the total interaction is associated with the growing number of N atoms in the azabenzenes, while the N-atom positioning in pyridazine is particularly effective in strengthening the interaction with stannylenes. Variations in the Sn ← N bond strength usually follow those in the total interaction between the moieties but the interacting quantum atoms picture of Sn ← N reveals certain intriguing exceptions.

We present a modular and extendable software suite, DJMol, for performing molecular simulations and it is demonstrated with DFTB+, Siesta, Atomic Simulation Environment, and OpenMD codes. It supports many of the standard features of an integrated development environment and consists of a structure builder and viewer, which could be connected with these electronic structure codes along with a set of data analyzers. This program comprises Java and Python modules and its libraries to carry out a different set of modeling tasks in materials science and chemistry. By adopting a Python interpreter into the software, a range of scriptable Python codes, such as Pymatgen can be incorporated into this programmable modeling platform. DJMol, through its common application programming interface (API), supports multiple modeling codes in the backend and several post-processing tools. It benefits an experienced user by increasing efficiency, while a nonexpert user by easy to use API.

The SBO4-DZ(d,p)-3G basis sets introduced in a previous paper have been modified to improve their performance in the calculation of the atomization energies of organic molecules (pure or substituted hydrocarbons). The first step was to explore the possibility of improving those basis sets by adding a second D shell. The scale factor for an additional "D-3G" shell was first studied by minimizing the total energies. In a second step, the scale factor was calculated by optimizing atomization energies directly (instead total energies). This way the results obtained were very similar to those of the cc-pV5Z basis sets. Finally, we optimized simplified box orbital (SBO) basis sets for different methods obtaining optimal SBO basis sets for HF, DFTs, and MP2.

Pharmacophore-based virtual screening (VS) has emerged as an efficient computer-aided drug design technique when appraising multiple ligands with similar structures or targets with unknown crystal structures. Current pharmacophore modeling and analysis software suffers from inadequate integration of mainstream methods and insufficient user-friendly program interface. In this study, we propose a stand-alone, integrated, graphical software for pharmacophore-based VS, termed ePharmer. Both ligand-based and structure-based pharmacophore generation methods were integrated into a compact architecture. Fine-grained modules were carefully organized into the computing, integration, and visualization layers. Graphical design covered the global user interface and specific user operations including editing, evaluation, and task management. Metabolites prediction analysis with the chosen VS result is provided for preselection of wet experiments. Moreover, the underlying computing units largely adopted the preliminary work of our research team. The presented software is currently in client use and will be released for both professional and nonexpert users. Experimental results verified the favorable computing capability, user convenience, and case performance of the proposed software.

Regulator of G protein signaling 4 (RGS4) is an intracellular protein that binds to the Gα subunit ofheterotrimeric G proteins and aids in terminating G protein coupled receptor signaling. RGS4 has been implicated in pain, schizophrenia, and the control of cardiac contractility. Inhibitors of RGS4 have been developed but bind covalently to cysteine residues on the protein. Therefore, we sought to identify alternative druggable sites on RGS4 using mixed-solvent molecular dynamics simulations, which employ low concentrations of organic probes to identify druggable hotspots on the protein. Pseudo-ligands were placed in consensus hotspots, and perturbation with normal mode analysis led to the identification and characterization of a putative allosteric site, which would be invaluable for structure-based drug design of non-covalent, small molecule inhibitors. Future studies on the mechanism of this allostery will aid in the development of novel therapeutics targeting RGS4.

A reaction route network for the decomposition reaction of methanol on a Pt(111) surface was constructed by using the artificial force-induced reaction (AFIR) method, which can search for reaction paths automatically and systematically. Then, the network was kinetically analyzed by applying the rate constant matrix contraction (RCMC) method. Specifically, the time hierarchy of the network, the time evolution of the population initially given to CH3 OH to the other species on the network, and the most favorable route from CH3 OH to major and minor products were investigated by the RCMC method. Consistently to previous studies, the major product on the network was CO+4H, and the most favorable route proceeded through the following steps: CH3 OH → CH2 OH+H → HCOH+2H → HCO+3H → CO+4H. Furthermore, paths to byproducts found on the network and their kinetic importance were discussed. The present procedure combining AFIR and RCMC was thus successful in explaining the title reaction without using any information on its product or the reaction mechanism.

The position-dependent diffusion coefficient along with free energy profile are important parameters needed to study mass transport in heterogeneous systems such as biological and polymer membranes, and molecular dynamics (MD) calculation is a popular tool to obtain them. Among many methodologies, the Marrink-Berendsen (MB) method is often employed to calculate the position-dependent diffusion coefficient, in which the autocorrelation function of the force on a fixed molecule is related to the friction on the molecule. However, the diffusion coefficient is shown to be affected by the period of the removal of the center-of-mass velocity, τv0 , which is necessary when performing MD calculations using the Ewald method for Coulombic interaction. We have clarified theoretically in this study how this operation affects the diffusion coefficient calculated by the MB method, and the theoretical predictions are proven by MD calculations. Therefore, we succeeded in providing guidance on how to select an appropriate τv0 value in estimating the position-dependent diffusion coefficient by the MB method. This guideline is applicable also to the Woolf-Roux method.

Quantum chemical computations were used to reinvestigate the geometries, spectroscopic, and energetic properties of the gold clusters Au27 q in three charge states (q = 1, 0, -1). Density functional theory (DFT) and the domain-based local pair natural orbital modification of the coupled-cluster theory DLPNO-CCSD(T) calculations revealed that, at variance with earlier reports in the literature, while the anion Au27 - tends to exist in a tube-like form, both the lowest-energy Au27 and Au27 + isomers exhibit a pyramidal shape. However, several isomers were found to lie very close in energy, thus rendering a structural transition and their coexistence easy to occur. More specifically, the equilibrium geometry of the neutral Au27 is a core-shell pyramid-like structure with one gold atom located inside. We also identified a novel ground state for the anion Au27 - and located for the first time the global minimum of the cation Au27 + . The vertical detachment energies of the neutral and anionic states were also computed and used to assign the available experimental photoelectron spectra. Although many Au27 isomers were predicted to be energetically quasi-degenerate, the corresponding distinctive vibrational signatures can be used as fingerprints for the identification of cluster geometrical features.