Natural Fragment Bond Orbital Method for Inter-Fragment Bonding Interaction Analysis

A complex chemical system is often examined based on their fragments, so fragment-based analysis is the key to chemical understanding. We report the natural fragment bond orbital (NFBO) method for inter-fragment bonding interaction analysis, as an extension to the well-known natural bond orbital method. NFBOs together with their corresponding natural fragment hybrid orbitals (NFHOs) allow us to derive local bonding and anti-bonding orbitals among fragments from the delocalized canonical molecular orbitals. In this paper, we provide the algorithm for finding NFBOs and showcase its application to several chemically interesting systems featuring significant inter-fragment bonding interactions. Through these examples, the NFBO method is shown to be a powerful tool for molecules possessing strong inter-fragment bonding interactions

DFT Studies on Copper-Catalyzed Hydrocarboxylation of Alkynes Using CO2 and Hydrosilanes

In this paper, DFT calculations have been carried out to study the reaction mechanism of copper-catalyzed hydrocarboxylation of alkynes using CO 2 and hydrosilanes. In addition to hydrocarboxylation of alkynes, possible competitive reactions such as hydrosilylation of alkynes, hydrosilylation of CO2, and silacarboxylation of alkynes have also been investigated and compared. Through these DFT calculations, we are able to understand the reason only hydrocarboxylation of alkynes has been observed experimentally. © 2013 American Chemical Society

On the alternating structure of cyclo[18]carbon

Cyclo[18]carbon, has been recently characterized by high-resolution atomic force microscopy which revealed a polyynic structure with alternating single and triple bonds. It is natural to ask why it does not exhibit bond equalization and adopt a cumulenic structure. This paper, on the other hand, begins with the opposite question: why we expect it to exhibit bond equalization in the first place. We then reexamine whether these intuitive arguments are theoretically sound. Hückel model, which was often attributed as the underlying reason for the famous 4N+2 electron-counting rule for aromatics, was reviewed with minimal structural flexibility introduced, which surprisingly revealed that even benzene would undergo bond alternation under the Hückel framework. This analysis is confirmed by extended Hückel calculations. DFT and semi-empirical calculations revealed that internuclear repulsion would be necessary for a model to correctly predict the D6h structure of benzene. Similar scenario was observed for C18, except that a greater fraction of exact exchange may result in a small energy gain when molecule distorts from D18h to D9h geometry. HOMO energy lowering and LUMO energy rising were found in the symmetry-lowering distortion of both benzene and C18, thus disqualifying the usual explanation of the bond alternating structure of C18 based on second-order Jahn-Teller effect. Finally, a hydrogen-ring model was presented as a toy model to investigate the origin of bond equalization of so-called aromatic systems, which clearly revealed the role of nuclear repulsion in favoring high-symmetry structure while electronic energy monotonically decreases in symmetry-lowering process

Principal Interacting Spin Orbital: Understanding the Fragment Interactions in Open-Shell Systems

Due to the recent rise in the interests and research effort on first-row transition metal catalysis and other radical-related reactions, open-shell system is playing a much more important role in modern chemistry. However, the development of bonding analysis tools for open-shell system is still lagging behinid. In this work, we will present the principal interacting spin orbital (PISO) analysis, which is an analysis framework developed based on our previous principal interacting orbital (PIO) analysis. We will demonstrate the power of our framework to analyze different kinds of open-shell systems, ranging from simple organic radicals to much more complicated coordination complexes, from which we can see how different kinds of odd electron bonds could be identified. We will also illustrate its ability to be used in the analysis of chemical reaction, through which we can observe subtle patterns that could be helpful for tuning or rational design of related reactions.<br /

DFT Studies on Copper-Catalyzed Hydrocarboxylation of Alkynes Using CO₂ and Hydrosilanes

In this paper, DFT calculations have been carried out to study the reaction mechanism of copper-catalyzed hydrocarboxylation of alkynes using CO₂ and hydrosilanes. In addition to hydrocarboxylation of alkynes, possible competitive reactions such as hydrosilylation of alkynes, hydrosilylation of CO₂, and silacarboxylation of alkynes have also been investigated and compared. Through these DFT calculations, we are able to understand the reason only hydrocarboxylation of alkynes has been observed experimentally

An [Au₁₃]⁵⁺ Approach to the Study of Gold Nanoclusters

Recently, many examples of gold nanoclusters have been synthesized due to their exceptional spectroscopic properties and potential applications in nanotechnology. In this work we put forward an approach based on the icosahedral [Au₁₃]⁵⁺ unit and summarize three possible extensions of the unit: wrapping, bonding, and vertex sharing. We show that the electronic structure of such clusters can be treated in a more localized manner and show how the approach could be applied to understand the structure and bonding of a large variety of gold nanoclusters

Application of Markov State Models to simulate long timescale dynamics of biological macromolecules

Conformational changes of proteins are an*Author contributed equally with all other contributors. essential part of many biological processes such as: protein folding, ligand binding, signal transduction, allostery, and enzymatic catalysis. Molecular dynamics (MD) simulations can describe the dynamics of molecules at atomic detail, therefore providing a much higher temporal and spatial resolution than most experimental techniques. Although MD simulations have been widely applied to study protein dynamics, the timescales accessible by conventional MD methods are usually limited to timescales that are orders of magnitude shorter than the conformational changes relevant for most biological functions. During the past decades great effort has been devoted to the development of theoretical methods that may enhance the conformational sampling. In recent years, it has been shown that the statistical mechanics framework provided by discrete-state and -time Markov State Models (MSMs) can predict long timescale dynamics from a pool of short MD simulations. In this chapter we provide the readers an account of the basic theory and selected applications of MSMs. We will first introduce the general concepts behind MSMs, and then describe the existing procedures for the construction of MSMs. This will be followed by the discussions of the challenges of constructing and validating MSMs, Finally, we will employ two biologically-relevant systems, the RNA polymerase and the LAO-protein, to illustrate the application of Markov State Models to elucidate the molecular mechanisms of complex conformational changes at biologically relevant timescales

Eliminating Fragment Group Orbital (eFGO) Analysis for Deciphering Chemical Bonding in Complex Systems

The delocalized nature of canonical molecular orbitals in quantum chemistry calculations is always in conflict with the localized nature of orbital interactions and derived chemical concepts. Localization of molecular orbitals has been achieved in many approaches, but sometimes they could be over-localized for complex systems, especially those with multicenter bonding. A fragment-based approach is thus proposed to eliminate the electron density contribution from substituents, ligands and other peripheral moieties such that the skeletal bonding is clearly revealed. To be specific, fragment group orbitals, as in analogy with ligand group orbitals in coordination chemistry, are eliminated from the space spanned by occupied molecular orbitals. Via this approach, the skeletal bonding orbitals of complex systems including but not limited to pi-delocalized systems and cluster compounds are recovered with a minimal contribution from surrounding moieties, making this method the ideal choice to analyze the electronic structure of complex systems and separate skeletal bonding contribution against peripheral moieties from various sum-over-orbital properties

Automatic state Partitioning for Multi-body systems (APM): An Efficient Algorithm for Constructing Markov State Models to Elucidate Conformational Dynamics of Multi-body Systems

The conformational dynamics of multibody systems plays crucial roles in many important problems. Markov state models (MSMs) are powerful kinetic network models that can predict long-time-scale dynamics using many short molecular dynamics simulations. Although MSMs have been successfully applied to conformational changes of individual proteins, the analysis of multibody systems is still a challenge because of the complexity of the dynamics that occur on a mixture of drastically different time scales. In this work, we have developed a new algorithm, automatic state partitioning for multibody systems (APM), for constructing MSMs to elucidate the conformational dynamics of multibody systems. The APM algorithm effectively addresses different time scales in the multibody systems by directly incorporating dynamics into geometric clustering when identifying the metastable conformational states. We have applied the APM algorithm to a 2D potential that can mimic a proteinligand binding system and the aggregation of two hydrophobic particles in water and have shown that it can yield tremendous enhancements in the computational efficiency of MSM construction and the accuracy of the models