Cluster-MLP: An Active Learning Genetic Algorithm Framework for Accelerated Discovery of Global Minimum Configurations of Pure and Alloyed Nanoclusters.

Structural characterization of nanoclusters is one of the major challenges in nanocluster modeling owing to the multitude of possible configurations of arrangement of cluster atoms. The genetic algorithm (GA), a class of evolutionary algorithms based on the principles of natural evolution, is a commonly employed search method for locating the global minimum configuration of nanoclusters. Although a GA search at the DFT level is required for the accurate description of a potential energy surface to arrive at the correct global minimum configuration of nanoclusters, computationally expensive DFT evaluation of the significantly larger number of cluster geometries limits its practicability.

Electrocatalytic reduction of CO on size-selected nanoclusters of first-row transition metal nanoclusters: a comprehensive mechanistic investigation.

Recycling CO back to fuels offers an ideal solution to control anthropogenic global CO emissions as well as providing a sustainable green solution to alternative energy resources from a cheap and earth-abundant carbon source. Size-selected nanoclusters open a novel area in catalysis as these atomically precise nanoclusters possess unique electronic and catalytic properties different from larger nanoparticles and traditional bulk catalysts. In this work, we have investigated the ability of first-row transition metal nanoclusters (Sc-Cu) of varying sizes (3 to 10 atoms) for CO electroreduction (CORR).

Computational investigation of cobalt and copper bis (oxothiolene) complexes as an alternative for olefin purification.

Considering that olefins present a large volume feedstock, it is reasonable to expect that their purification is industrially critical. After the discovery of the nickel bis (dithiolene) complex Ni(SC(CF)) that exhibits electro-catalytic activity with olefins but tends to decompose by a competitive reaction route, related complexes have been explored experimentally and theoretically. In this paper, a computational examination is performed on differently charged cobalt and copper bis (oxothiolene) complexes [M (OSC(CN))] to test their potential applicability as the catalysts for olefin purification, using the simplest olefin, ethylene.

Nickel Bis(diselenolene) as a Catalyst for Olefin Purification.

Nickel bis(dithiolene) reversibly binds olefins via a known interligand binding mechanism, but the complex has limited practical use, due to a competitive intraligand addition which results in decomposition. The present work examines an alternative nickel-based complex that eliminates the decomposition route. Specifically, we have examined the olefin binding processes of nickel bis(diselenolene) complexes using modern density functional theory.

Mechanism of Ethylene Addition to Nickel Bis(oxothiolene) and Nickel Bis(dioxolene) Complexes.

The electrochemically reversible binding of olefins by nickel bis(dithiolene) has been extensively studied, both theoretically and computationally. To optimize a catalyst for this process, we have investigated all possible reaction pathways of ethylene addition onto the related complex nickel bis(dioxolene), and the two isomers (cis and trans) of nickel bis(oxothiolene). Modern DFT calculations predict that the nickel bis(dioxolene) complex has limited practical use due to high barriers to binding.

A unified set of experimental organometallic data used to evaluate modern theoretical methods.

We applied a test set of ligand dissociation enthalpies derived entirely from a unified experimental approach to evaluate the efficacy of various methods for modeling organometallic chemistry. This differs from most benchmarking studies, as it is common to evaluate theoretical methods by using more computationally expensive calculations to provide the "target" values. With an aim of presenting the 'best suited functional/functionals' for calculations involving the metal-ligand bond dissociation enthalpies (BDEs) of organometallic complexes, we utilized a database of 30 experimental metal-ligand bond dissociation enthalpies, and tested for 101 density functionals and 2 ab initio methods, all with a large basis set.

Iron(0) mediated C-H activation of 1-hexyne: a mechanistic study using time-resolved infrared spectroscopy.

Photolysis of an iron tricarbonyl complex in the presence of 1-hexyne results in the activation of the terminal C-H bond to yield an iron-alkynyl species. The reaction proceeds through a single transition state with an activation enthalpy of 13.5 kcal mol(-1).

Aromatic interactions modulate the 5'-base selectivity of the DNA-binding autoantibody ED-10.

We present detailed computational analyses of the binding of four dinucleotides to a highly sequence-selective single-stranded DNA (ssDNA) binding antibody (ED-10) and selected point mutants. Anti-DNA antibodies are central to the pathogenesis of systemic lupus erythematosus (SLE), and a more complete understanding of the mode of binding of DNA and other ligands will be necessary to elucidate the role of anti-DNA antibodies in the kidney inflammation associated with SLE. Classical molecular mechanics based molecular dynamics simulations and density functional theory (DFT) computations were applied to pinpoint the origin of selectivity for the 5'-nucleotide.

Thermal and photochemical reactivity of manganese tricarbonyl and tetracarbonyl complexes with a bulky diazabutadiene ligand.

The manganese tricarbonyl complex fac-Mn(Br)(CO)3((i)Pr2Ph-DAB) (1) [(i)Pr2Ph-DAB = (N,N'-bis(2,6-di-isopropylphenyl)-1,4-diaza-1,3-butadiene)] was synthesized from the reaction of Mn(CO)5Br with the sterically encumbered DAB ligand. Compound 1 exhibits rapid CO release under low power visible light irradiation (560 nm) suggesting its possible use as a photoCORM. The reaction of compound 1 with TlPF6 in the dark afforded the manganese(I) tetracarbonyl complex, [Mn(CO)4((i)Pr2Ph-DAB)][PF6] (2).

Broad Transferability of Substituent Effects in π-Stacking Interactions Provides New Insights into Their Origin.

Substituent effects in model stacked homodimers and heterodimers of benzene, borazine, and 1,3,5-triazine have been examined computationally. We show that substituent effects in these dimers are strongly dependent on the identity of the unsubstituted ring, yet are independent of the ring bearing the substituent. This supports the local, direct interaction model [J.

Insights into the activity and specificity of Trypanosoma cruzi trans-sialidase from molecular dynamics simulations.

Trypanosoma cruzitrans-sialidase (TcTS), which catalyzes the transfer or hydrolysis of terminal sialic acid residues, is crucial to the development and proliferation of the T. cruzi parasite and thus has emerged as a potential drug target for the treatment of Chagas disease. We here probe the origin of the observed preference for the transfer reaction over hydrolysis where the substrate for TcTS is the natural sialyl donor (represented in this work by sialyllactose).

Physical Nature of Substituent Effects in XH/π Interactions.

XH/π interactions (e.g.: CH/π, OH/π, etc.

Substituent effects on non-covalent interactions with aromatic rings: insights from computational chemistry.

Non-covalent interactions with aromatic rings pervade modern chemical research. The strength and orientation of these interactions can be tuned and controlled through substituent effects. Computational studies of model complexes have provided a detailed understanding of the origin and nature of these substituent effects, and pinpointed flaws in entrenched models of these interactions in the literature.

An evaluation of the GLYCAM06 and MM3 force fields, and the PM3-D* molecular orbital method for modelling prototype carbohydrate-aromatic interactions.

The structures and interaction energies of 21 binary complexes of fucose and glucose with toluene, 3-methylindole or p-hydroxytoluene, evaluated at the DFT-D level, are used to judge the accuracy of the GLYCAM06 and MM3 force fields, and the PM3-D* molecular orbital method for modelling carbohydrate-arene interactions. The accuracy of the DFT-D method is substantiated by comparison with high level CCSD(T) calculations on a small number of representative complexes. It is found that a correct description of the intermolecular dispersive interactions is essential.

The effects of perfluorination on carbohydrate-pi interactions: computational studies of the interaction of benzene and hexafluorobenzene with fucose and cyclodextrin.

The effect of benzene fluorination on C-H...

Modelling the binding of HIV-reverse transcriptase and nevirapine: an assessment of quantum mechanical and force field approaches and predictions of the effect of mutations on binding.

The importance of the intermolecular interactions which contribute to the binding of HIV-1 RT with the NNRTI inhibitor, nevirapine (NVP), has been studied using quantum mechanical and molecular simulation methods. A range of computational methods, including density functional theory with empirical dispersion corrections, have been employed and show that although pi-pi stacking interactions are important, the combined effect of a number of C-H/pi interactions provides a significant contribution to the binding. The AMBER empirical force-field has been shown to be particularly effective to describe the interactions in this case; MM-GBSA free-energy methods were subsequently used to explore the effects on binding with several known mutations of HIV-1 RT.

Carbohydrate-aromatic pi interactions: a test of density functionals and the DFT-D method.

The performance of a number of computational approaches based upon density functional theory (DFT) for the accurate description of carbohydrate-pi interactions is described. A database containing interaction energies of a small number of representative complexes, computed at a high ab initio level, is described, and is used to judge 18 different density functionals including the M05 and M06 families as well as the DFT method augmented with empirical dispersive corrections (DFT-D). The DFT-D method and the M06 functionals are found to perform particularly well, whilst traditional functionals such as B3LYP perform poorly.

Carbohydrate-protein recognition probed by density functional theory and ab initio calculations including dispersive interactions.

Carbohydrate-protein recognition has been studied by electronic structure calculations of complexes of fucose and glucose with toluene, p-hydroxytoluene and 3-methylindole, the latter aromatic molecules being analogues of phenylalanine, tyrosine and tryptophan, respectively. We use mainly a density functional theory model with empirical corrections for the dispersion interactions (DFT-D), this method being validated by comparison with a limited number of high level ab initio calculations. We have calculated both binding energies of the complexes as well as their harmonic vibrational frequencies and proton NMR chemical shifts.

The interaction of carbohydrates and amino acids with aromatic systems studied by density functional and semi-empirical molecular orbital calculations with dispersion corrections.

Density functional theory (DFT-D) and semi-empirical (PM3-D) methods having an added dispersion correction have been used to study stabilising carbohydrate-aromatic and amino acid-aromatic interactions. The interaction energy for three simple sugars in different conformations with benzene, all give interaction energies close to 5 kcal mol(-1). Our original parameterization of PM3 (PM3-D) seriously overestimates this value, and has prompted a reparametrization which includes a modified core-core interaction term.