Showing papers in "Journal of Computational Chemistry in 2017"

Deep learning for computational chemistry

Abstract: The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc.

CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules

Abstract: Reading ligand structures into any simulation program is often nontrivial and time consuming, especially when the force field parameters and/or structure files of the corresponding molecules are not available. To address this problem, we have developed Ligand Reader & Modeler in CHARMM-GUI. Users can upload ligand structure information in various forms (using PDB ID, ligand ID, SMILES, MOL/MOL2/SDF file, or PDB/mmCIF file), and the uploaded structure is displayed on a sketchpad for verification and further modification. Based on the displayed structure, Ligand Reader & Modeler generates the ligand force field parameters and necessary structure files by searching for the ligand in the CHARMM force field library or using the CHARMM general force field (CGenFF). In addition, users can define chemical substitution sites and draw substituents in each site on the sketchpad to generate a set of combinatorial structure files and corresponding force field parameters for throughput or alchemical free energy simulations. Finally, the output from Ligand Reader & Modeler can be used in other CHARMM-GUI modules to build a protein-ligand simulation system for all supported simulation programs, such as CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Ligand Reader & Modeler is available as a functional module of CHARMM-GUI at http://www.charmm-gui.org/input/ligandrm. © 2017 Wiley Periodicals, Inc.

Improving scoring-docking-screening powers of protein-ligand scoring functions using random forest.

Abstract: The development of new protein-ligand scoring functions using machine learning algorithms, such as random forest, has been of significant interest. By efficiently utilizing expanded feature sets and a large set of experimental data, random forest based scoring functions (RFbScore) can achieve better correlations to experimental protein-ligand binding data with known crystal structures; however, more extensive tests indicate that such enhancement in scoring power comes with significant under-performance in docking and screening power tests compared to traditional scoring functions. In this work, to improve scoring-docking-screening powers of protein-ligand docking functions simultaneously, we have introduced a Δvina RF parameterization and feature selection framework based on random forest. Our developed scoring function Δvina RF20 , which employs 20 descriptors in addition to the AutoDock Vina score, can achieve superior performance in all power tests of both CASF-2013 and CASF-2007 benchmarks compared to classical scoring functions. The Δvina RF20 scoring function and its code are freely available on the web at: https://www.nyu.edu/projects/yzhang/DeltaVina. © 2016 Wiley Periodicals, Inc.

CHARMM‐GUI 10 years for biomolecular modeling and simulation

Abstract: CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. © 2016 Wiley Periodicals, Inc.

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

Abstract: GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc.

CHARMM‐GUI Martini Maker for modeling and simulation of complex bacterial membranes with lipopolysaccharides

Abstract: A complex cell envelope, composed of a mixture of lipid types including lipopolysaccharides, protects bacteria from the external environment. Clearly, the proteins embedded within the various components of the cell envelope have an intricate relationship with their local environment. Therefore, to obtain meaningful results, molecular simulations need to mimic as far as possible this chemically heterogeneous system. However, setting up such systems for computational studies is far from trivial, and consequently the vast majority of simulations of outer membrane proteins still rely on oversimplified phospholipid membrane models. This work presents an update of CHARMM-GUI Martini Maker for coarse-grained modeling and simulation of complex bacterial membranes with lipopolysaccharides. The qualities of the outer membrane systems generated by Martini Maker are validated by simulating them in bilayer, vesicle, nanodisc, and micelle environments (with and without outer membrane proteins) using the Martini force field. We expect this new feature in Martini Maker to be a useful tool for modeling large, complicated bacterial outer membrane systems in a user-friendly manner. © 2017 Wiley Periodicals, Inc.

W4‐17: A diverse and high‐confidence dataset of atomization energies for benchmarking high‐level electronic structure methods

Abstract: Atomization reactions are among the most challenging tests for electronic structure methods. We use the first-principles Weizmann-4 (W4) computational thermochemistry protocol to generate the W4-17 dataset of 200 total atomization energies (TAEs) with 3σ confidence intervals of 1 kJ mol-1 . W4-17 is an extension of the earlier W4-11 dataset; it includes first- and second-row molecules and radicals with up to eight non-hydrogen atoms. These cover a broad spectrum of bonding situations and multireference character, and as such are an excellent benchmark for the parameterization and validation of highly accurate ab initio methods (e.g., CCSD(T) composite procedures) and double-hybrid density functional theory (DHDFT) methods. The W4-17 dataset contains two subsets (i) a non-multireference subset of 183 systems characterized by dynamical or moderate nondynamical correlation effects (denoted W4-17-nonMR) and (ii) a highly multireference subset of 17 systems (W4-17-MR). We use these databases to evaluate the performance of a wide range of CCSD(T) composite procedures (e.g., G4, G4(MP2), G4(MP2)-6X, ROG4(MP2)-6X, CBS-QB3, ROCBS-QB3, CBS-APNO, ccCA-PS3, W1, W2, W1-F12, W2-F12, W1X-1, and W2X) and DHDFT methods (e.g., B2-PLYP, B2GP-PLYP, B2K-PLYP, DSD-BLYP, DSD-PBEP86, PWPB95, ωB97X-2(LP), and ωB97X-2(TQZ)). © 2017 Wiley Periodicals, Inc.

Cassandra: An open source Monte Carlo package for molecular simulation

Abstract: Cassandra is an open source atomistic Monte Carlo software package that is effective in simulating the thermodynamic properties of fluids and solids. The different features and algorithms used in Cassandra are described, along with implementation details and theoretical underpinnings to various methods used. Benchmark and example calculations are shown, and information on how users can obtain the package and contribute to it are provided. © 2017 Wiley Periodicals, Inc.

Tinker-OpenMM: Absolute and relative alchemical free energies using AMOEBA on GPUs.

Abstract: The capabilities of the polarizable force fields for alchemical free energy calculations have been limited by the high computational cost and complexity of the underlying potential energy functions. In this work, we present a GPU-based general alchemical free energy simulation platform for polarizable potential AMOEBA. Tinker-OpenMM, the OpenMM implementation of the AMOEBA simulation engine has been modified to enable both absolute and relative alchemical simulations on GPUs, which leads to a ∼200-fold improvement in simulation speed over a single CPU core. We show that free energy values calculated using this platform agree with the results of Tinker simulations for the hydration of organic compounds and binding of host–guest systems within the statistical errors. In addition to absolute binding, we designed a relative alchemical approach for computing relative binding affinities of ligands to the same host, where a special path was applied to avoid numerical instability due to polarization between the different ligands that bind to the same site. This scheme is general and does not require ligands to have similar scaffolds. We show that relative hydration and binding free energy calculated using this approach match those computed from the absolute free energy approach. © 2017 Wiley Periodicals, Inc.

A Review of Security Concerns in Internet of Things

Abstract: The Internet of Things (IoT) represents a technologically optimistic future where objects will be connected to the internet and make intelligent collaborations with other objects anywhere, anytime. Although it makes appreciable development, there are still uncertainties about security concepts of its usage that is usually considered as a major concern in the design of IoT architectures. This paper presents a general survey of all the security issues in IoT along with an analysis of IoT architectures. The study defines security requirements and challenges that are common in IoT implementations and discusses security threats and related solutions on each layer of IoT architecture to make this technology secure and more widespread accordingly.

Implementation of the Bethe-Salpeter equation in the TURBOMOLE program.

Abstract: A software update solving the Bethe-Salpeter equation (BSE) is reported for the ESCF module of the TURBOMOLE program for the theoretical description of electronically excited states of atoms and molecules. A resolution-of-the-identity (RI) approximation is used for all two-electron electron-repulsion integrals that are required for solving the equation. Symmetry is utilized for the point group D2h and its subgroups, and the BSE approach can be applied in either a spin-restricted or a spin-unrestricted Kohn-Sham formalism. Triplet as well as singlet excited states of closed-shell atoms and molecules can be treated in the spin-restricted formalism. As a side product, the present software update also allows for the application of the RI approximation to the Hartree-Fock exchange contribution that occurs when a hybrid functional is used in time-dependent density-functional theory. © 2016 Wiley Periodicals, Inc.

Standard grids for high‐precision integration of modern density functionals: SG‐2 and SG‐3

Abstract: Density-functional approximations developed in the past decade necessitate the use of quadrature grids that are far more dense than those required to integrate older generations of functionals. This category of difficult-to-integrate functionals includes meta-generalized gradient approximations, which depend on orbital gradients and/or the Laplacian of the density, as well as functionals based on B97 and the popular "Minnesota" class of functionals, each of which contain complicated and/or oscillatory expressions for the exchange inhomogeneity factor. Following a strategy introduced previously by Gill and co-workers to develop the relatively sparse "SG-0" and "SG-1" standard quadrature grids, we introduce two higher-quality grids that we designate SG-2 and SG-3, obtained by systematically "pruning" medium- and high-quality atom-centered grids. The pruning procedure affords computational speedups approaching a factor of two for hybrid functionals applied to systems of ∼100 atoms, without significant loss of accuracy. The grid dependence of several popular density functionals is characterized for various properties. © 2017 Wiley Periodicals, Inc.

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

Abstract: In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc.

The role of the long-range exchange corrections in the description of electron delocalization in aromatic species

Abstract: In this article, we address the role of the long-range exchange corrections in description of the cyclic delocalization of electrons in aromatic systems at the density functional theory level. A test set of diversified monocyclic and polycyclic aromatics is used in benchmark calculations involving various exchange-correlation functionals. A special emphasis is given to the problem of local aromaticity in acenes, which has been a subject of long-standing debate in the literature. The presented results indicate that the noncorrected exchange-correlation functionals significantly overestimate cyclic delocalization of electrons in heteroaromatics and aromatic systems with fused rings, which in the case of acenes leads to conflicting local aromaticity predictions from different criteria. © 2017 Wiley Periodicals, Inc.

Wireless Body Area Network: An Overview and Various Applications

Abstract: Over the past years a booming interest is comprehended in the field of wireless communication for the development of a monitoring system to observe human vital organs activities remotely Wireless Body Area Network (WBAN) is such network that provides a continuous monitoring over or inside human body for a long period and can support transmission of real time traffic such as data, voice, video to observe the status of vital organs functionalities In this paper an overview of WBAN technology and its requirements has been narrated The aim of this paper was to offer a suitable and appropriate wireless technology for deploying WBAN Several suitable short range wireless communication technologies that can be adopted in WBAN have also been discussed Finally numerous applications in the field of medical and non-medical sectors using WBAN technology have been outlined

Systematic study of the effect of HSE functional internal parameters on the electronic structure and band gap of a representative set of metal oxides

Abstract: The effect of the amount of Hartree–Fock mixing parameter (α) and of the screening parameter (w) defining the range separated HSE type hybrid functional is systematically studied for a series of seven metal oxides: TiO2, ZrO2, CuO2, ZnO, MgO, SnO2, and SrTiO3. First, reliable band gap values were determined by comparing the optimal α reproducing the experiment with the inverse of the experimental dielectric constant. Then, the effect of the w in the HSE functional on the calculated band gap was explored in detail. Results evidence the existence of a virtually infinite number of combinations of the two parameters which are able to reproduce the experimental band gap, without a unique pair able to describe the full studied set of materials. Nevertheless, the results point out the possibility of describing the electronic structure of these materials through a functional including a screened HF exchange and an appropriate correlation contribution. © 2017 Wiley Periodicals, Inc.

Relevance of the DFT method to study expanded porphyrins with different topologies

Abstract: Meso-aryl expanded porphyrins present a structural versatility that allows them to achieve different topologies with distinct aromaticities. Several studies appeared in the literature studying these topological switches from an experimental and theoretical point of view. Most of these publications include density functional theory calculations, being the B3LYP the most used methodology. In this work, we show that the selection of the functional has a critical role on the geometric, energetic, and magnetic results of these expanded porphyrins, and that the use of an inadequate methodology can even generate spurious stationary points on the potential energy surface. To illustrate these aspects, in this article we have studied different molecular distortions of two expanded porphyrins, [32]-heptaphyrin and [26]-hexaphyrin using 11 DFT functionals and performing single point energy calculations at the local pair natural orbital coupled cluster DLPNO-CCSD(T) method, which have been carried out for benchmarking purposes. For some selected functionals, the dispersion effects have also been evaluated using the D3-Grimme's dispersion correction with Becke–Johnson damping. Our results let us to conclude that the CAM-B3LYP, M05-2X, and M06-2X functionals are the methodologies that provide a more consistent description of these topological switches, while other methods, such as B3LYP, BPE, and BP86, show a biased description. © 2017 Wiley Periodicals, Inc.

Agile Software Development Methodologies: Survey of Surveys

Abstract: Agile software design and development methodologies have been gaining rigorous attention in the software engineering research community since their early introduction in the mid-nineties in addition to being highly adopted by the software development industry. In the last 15 years, an excessive number of research studies have been conducted on agile methods, a great number of notable methods have been proposed and various surveys have been presented by many researchers. In this study, the authors intend to conduct a literature survey study of the surveys of the different agile methodologies ranging from January 2000 to December 2015 using an intuitive research methodology called “Compare and Review” (CR). Furthermore, these survey papers were classified into four major categories according to their area of study. Additionally, the newly proposed agile methodologies that have not been addressed yet in any other literature review were reviewed and compared in terms of where the changes that they proposed lay on the SDLC.

Proposal of a simple and effective local reactivity descriptor through a topological analysis of an orbital-weighted fukui function.

Abstract: The prediction of reactivity is one of the long-standing objectives of chemistry, contributing to enforce the link between theory and experiment. In particular, the regioselectivity of aromatic molecules has motivated the proposal of different reactivity descriptors based on foundational theories, like Frontier Molecular Orbital (FMO) theory and density functional theory, to predict and rationalize such regioselectivity. This article examines cases where reactivity descriptors, based on FMO theories, are known to have failed, specifically on electrophilic aromatic substitution reactions, through a simple but effective new reactivity model: the Orbital-weighted Fukui function ( fw-(r)) and its topological analysis. Interestingly, this descriptor proves to be effective in adequately predicting regioselectivities where other approximations failed. © 2017 Wiley Periodicals, Inc.

BayesWHAM: A Bayesian approach for free energy estimation, reweighting, and uncertainty quantification in the weighted histogram analysis method.

Abstract: The weighted histogram analysis method (WHAM) is a powerful approach to estimate molecular free energy surfaces (FES) from biased simulation data. Bayesian reformulations of WHAM are valuable in proving statistically optimal use of the data and providing a transparent means to incorporate regularizing priors and estimate statistical uncertainties. In this work, we develop a fully Bayesian treatment of WHAM to generate statistically optimal FES estimates in any number of biasing dimensions under arbitrary choices of the Bayes prior. Rigorous uncertainty estimates are generated by Metropolis-Hastings sampling from the Bayes posterior. We also report a means to project the FES and its uncertainties into arbitrary auxiliary order parameters beyond those in which biased sampling was conducted. We demonstrate the approaches in applications of alanine dipeptide and the unthreading of a synthetic mimic of the astexin-3 lasso peptide. Open-source MATLAB and Python implementations of our codes are available for free public download. © 2017 Wiley Periodicals, Inc.

Predicting core level binding energies shifts: Suitability of the projector augmented wave approach as implemented in VASP.

Abstract: Here, we assess the accuracy of various approaches implemented in Vienna ab initio simulation package code to estimate core-level binding energy shifts (ΔBEs) using a projector augmented wave method to treat core electrons. The performance of the Perdew-Burke-Ernzerhof (PBE) and the Tao-Perdew-Staroverov-Scuseria (TPSS) exchange-correlation density functionals is examined on a dataset of 68 molecules containing B→F atoms in diverse chemical environments, accounting for 185 different 1s core level binding energy shifts, for which both experimental gas-phase X-ray photoemission (XPS) data and accurate all electron ΔBEs are available. Four procedures to calculate core-level shifts are investigated. Janak-Slater transition state approach yields mean absolute errors of 0.37 (0.21) eV at PBE (TPSS) level, similar to highly accurate all electron ΔSCF approaches using same functionals, and close to XPS experimental accuracy of 0.1 eV. The study supports the use of these procedures to assign ΔBEs of molecular moieties on material surfaces of interest in surface science, nanotechnology, and heterogeneous catalysis. © 2017 Wiley Periodicals, Inc.

New algorithm for tensor contractions on multi-core CPUs, GPUs, and accelerators enables CCSD and EOM-CCSD calculations with over 1000 basis functions on a single compute node.

Abstract: A new hardware-agnostic contraction algorithm for tensors of arbitrary symmetry and sparsity is presented. The algorithm is implemented as a stand-alone open-source code libxm. This code is also integrated with general tensor library libtensor and with the Q-Chem quantum-chemistry package. An overview of the algorithm, its implementation, and benchmarks are presented. Similarly to other tensor software, the algorithm exploits efficient matrix multiplication libraries and assumes that tensors are stored in a block-tensor form. The distinguishing features of the algorithm are: (i) efficient repackaging of the individual blocks into large matrices and back, which affords efficient graphics processing unit (GPU)-enabled calculations without modifications of higher-level codes; (ii) fully asynchronous data transfer between disk storage and fast memory. The algorithm enables canonical all-electron coupled-cluster and equation-of-motion coupled-cluster calculations with single and double substitutions (CCSD and EOM-CCSD) with over 1000 basis functions on a single quad-GPU machine. We show that the algorithm exhibits predicted theoretical scaling for canonical CCSD calculations, O(N6 ), irrespective of the data size on disk. © 2017 Wiley Periodicals, Inc.

Description of non‐covalent interactions in SCC‐DFTB methods

Abstract: We have analyzed the description of non-covalent interactions in multiple variants of the self-consistent charges density functional tight binding (SCC-DFTB) method. While the description of London dispersion can be easily improved by empirical correction, hydrogen bonding poses a much more difficult problem. We have implemented an interaction energy decomposition scheme that allowed us to quantify the error at the level of first-order electrostatic and polarization terms. Both are underestimated because of the monopole approximation used in SCC-DFTB, with the latter being affected also by the use of minimal basis set. Among the methods tested, SCC-DFTB with the empirical D3H4 corrections worked best. To make this correction compatible with the latest development in SCC-DFTB, we have reparameterized it for use with third-order SCC-DFTB with the 3OB parameter set. © 2017 Wiley Periodicals, Inc.

Automated and efficient quantum chemical determination and energetic ranking of molecular protonation sites.

Abstract: We present an automated quantum chemical protocol for the determination of preferred protonation sites in organic and organometallic molecules containing up to a few hundred atoms. It is based on the Foster–Boys orbital localization method, whereby we automatically identify lone pairs and π orbitals as possible protonation sites. The method becomes efficient in conjunction with the robust and fast GFN-xTB semiempirical method proposed recently (Grimme et al., J. Chem. Theory Comput. 2017, 13, 1989). The protonated isomers that are found within a few seconds to minutes of computational wall-time on a standard desktop computer are then energetically refined using density functional theory (DFT), where we use a high-level double-hybrid reference method to benchmark GFN-xTB and low-cost DFT approaches. The proposed DFT/GFN-xTB/LMO composite protocol is generally applicable to almost arbitrary molecules including transition metal complexes. Importantly it is found that even in electronically complicated cases, the GFN-xTB optimized protomer structures are reasonable and can safely be used in single-point DFT calculations. Corrections from energy to free energy mostly have a small effect on computed protomer populations. The resulting protomer equilibrium is valuable, for example, in the context of electrospray ionization mass spectrometry where it may help identify the ionized species and assist the interpretation of the experiment. © 2017 Wiley Periodicals, Inc.

Nitrogen-doped C60 as a robust catalyst for CO oxidation.

Abstract: The O2 activation and CO oxidation on nitrogen-doped C59 N fullerene are investigated using first-principles calculations. The calculations indicate that the C59 N fullerene is able to activate O2 molecules resulting in the formation of superoxide species ( O2-) both kinetically and thermodynamically. The active superoxide can further react with CO to form CO2 via the Eley-Rideal mechanism by passing a stepwise reaction barrier of only 0.20 eV. Ab initio molecular dynamics (AIMD) simulation is carried out to evidence the feasibility of the Eley-Rideal mechanism. In addition, the second CO oxidation takes place with the remaining atomic O without any activation energy barrier. The full catalytic reaction cycles can occur energetically favorable and suggest a two-step Eley-Rideal mechanism for CO oxidation with O2 catalyzed by the C59 N fullerene. The catalytic properties of high percentage nitrogen-doped fullerene (C48 N12 ) is also examined. This work contributes to designing higher effective carbon-based materials catalysts by a dependable theoretical insight into the catalytic properties of the nitrogen-doped fullerene. © 2017 Wiley Periodicals, Inc.

Rapid and Accurate Assessment of GPCR-Ligand Interactions Using the Fragment Molecular Orbital-Based Density-Functional Tight-Binding Method

Abstract: The reliable and precise evaluation of receptor–ligand interactions and pair-interaction energy is an essential element of rational drug design. While quantum mechanical (QM) methods have been a promising means by which to achieve this, traditional QM is not applicable for large biological systems due to its high computational cost. Here, the fragment molecular orbital (FMO) method has been used to accelerate QM calculations, and by combining FMO with the density-functional tight-binding (DFTB) method we are able to decrease computational cost 1000 times, achieving results in seconds, instead of hours. We have applied FMO-DFTB to three different GPCR–ligand systems. Our results correlate well with site directed mutagenesis data and findings presented in the published literature, demonstrating that FMO-DFTB is a rapid and accurate means of GPCR–ligand interactions. © 2017 Authors Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Residue‐centric modeling and design of saccharide and glycoconjugate structures

Abstract: The RosettaCarbohydrate framework is a new tool for modeling a wide variety of saccharide and glycoconjugate structures. This report describes the development of the framework and highlights its applications. The framework integrates with established protocols within the Rosetta modeling and design suite, and it handles the vast complexity and variety of carbohydrate molecules, including branching and sugar modifications. To address challenges of sampling and scoring, RosettaCarbohydrate can sample glycosidic bonds, side-chain conformations, and ring forms, and it utilizes a glycan-specific term within its scoring function. Rosetta can work with standard PDB, GLYCAM, and GlycoWorkbench (.gws) file formats. Saccharide residue-specific chemical information is stored internally, permitting glycoengineering and design. Carbohydrate-specific applications described herein include virtual glycosylation, loop-modeling of carbohydrates, and docking of glyco-ligands to antibodies. Benchmarking data are presented and compared to other studies, demonstrating Rosetta's ability to predict glyco-ligand binding. The framework expands the tools available to glycoscientists and engineers. © 2016 Wiley Periodicals, Inc.

Flexible fitting to cryo-EM density map using ensemble molecular dynamics simulations.

Abstract: Flexible fitting is a computational algorithm to derive a new conformational model that conforms to low-resolution experimental data by transforming a known structure. A common application is against data from cryo-electron microscopy to obtain conformational models in new functional states. The conventional flexible fitting algorithms cannot derive correct structures in some cases due to the complexity of conformational transitions. In this study, we show the importance of conformational ensemble in the refinement process by performing multiple fittings trials using a variety of different force constants. Application to simulated maps of Ca2+ ATPase and diphtheria toxin as well as experimental data of release factor 2 revealed that for these systems, multiple conformations with similar agreement with the density map exist and a large number of fitting trials are necessary to generate good models. Clustering analysis can be an effective approach to avoid over-fitting models. In addition, we show that an automatic adjustment of the biasing force constants during the fitting process, implemented as replica-exchange scheme, can improve the success rate. © 2017 Wiley Periodicals, Inc.

Benchmarking density functional tight binding models for barrier heights and reaction energetics of organic molecules.

Abstract: Density Functional Tight Binding (DFTB) models are two to three orders of magnitude faster than ab initio and Density Functional Theory (DFT) methods and therefore are particularly attractive in applications to large molecules and condensed phase systems. To establish the applicability of DFTB models to general chemical reactions, we conduct benchmark calculations for barrier heights and reaction energetics of organic molecules using existing databases and several new ones compiled in this study. Structures for the transition states and stable species have been fully optimized at the DFTB level, making it possible to characterize the reliability of DFTB models in a more thorough fashion compared to conducting single point energy calculations as done in previous benchmark studies. The encouraging results for the diverse sets of reactions studied here suggest that DFTB models, especially the most recent third-order version (DFTB3/3OB augmented with dispersion correction), in most cases provide satisfactory description of organic chemical reactions with accuracy almost comparable to popular DFT methods with large basis sets, although larger errors are also seen for certain cases. Therefore, DFTB models can be effective for mechanistic analysis (e.g., transition state search) of large (bio)molecules, especially when coupled with single point energy calculations at higher levels of theory. © 2017 Wiley Periodicals, Inc.

A theoretical investigation on doping superalkali for triggering considerable nonlinear optical properties of Si 12 C 12 nanostructure

Abstract: In this work, we designed a series of superalkali-doped Si12 C12 nanocage M3 O@Si12 C12 (M = Li, Na, K) with donor-acceptor framework. Density functional theory calculations demonstrated that the HOMO-LUMO gap of the complexes conspicuously narrowed with increase of atomic number of the alkali metal, the value decreased from 5.452 eV of pure Si12 C12 nanocage to 3.750, 2.984, and 2.634 eV of Li3 O@Si12 C12 , Na3 O@Si12 C12 , and K3 O@Si12 C12 , respectively. This finding shows that the pristine Si12 C12 cluster could be transformed to n-type semiconductor by introduction of the superalkali M3 O. We also showed that the superalkali doping remarkably enhanced the first hyperpolarizability of Si12 C12 . Among the studied systems, K3 O@Si12 C12 not only has the narrowest gap but also has the strongest nonlinear optical (NLO) properties, its first hyperpolarizability reached as high as 21695 a.u. The striking results presented in this work will be beneficial for potential applications of the Si12 C12 -based nanostructure in the electronic nanodevices and high-performance NLO materials. © 2017 Wiley Periodicals, Inc.