Gliding on Ice in search of accurate and cost-effective computational methods for Astrochemistry on Grains: the puzzling case of the HCN isomerization

The isomerization of hydrogen cyanide to hydrogen isocyanide on icy grain surfaces is investigated by an accurate composite method (jun-Cheap) rooted in the coupled cluster ansatz and by density functional approaches. After benchmarking density functional predictions of both geometries and reaction energies against jun-Cheap results for the relatively small model system HCN···(H2O)2, the best performing DFT methods are selected. A large cluster containing 20 water molecules is then employed within a QM/QM′ approach to include a realistic environment mimicking the surface of icy grains. Our results indicate that four water molecules are directly involved in a proton relay mechanism, which strongly reduces the activation energy with respect to the direct hydrogen transfer occurring in the isolated molecule. Further extension of the size of the cluster up to 192 water molecules in the framework of a three-layer QM/QM′/MM model has a negligible effect on the energy barrier ruling the isomerization. Computation of reaction rates by the transition state theory indicates that on icy surfaces, the isomerization of HNC to HCN could occur quite easily even at low temperatures thanks to the reduced activation energy that can be effectively overcome by tunneling

Atoms in molecules in real space: a fertile field for chemical bonding

In this perspective, we review some recent advances in the concept of atoms-in-molecules from a real space perspective. We first introduce the general formalism of atomic weight factors that allows unifying the treatment of fuzzy and non-fuzzy decompositions under a common algebraic umbrella. We then show how the use of reduced density matrices and their cumulants allows partitioning any quantum mechanical observable into atomic or group contributions. This circumstance provides access to electron counting as well as energy partitioning, on the same footing. We focus on how the fluctuations of atomic populations, as measured by the statistical cumulants of the electron distribution functions, are related to general multi-center bonding descriptors. Then we turn our attention to the interacting quantum atom energy partitioning, which is briefly reviewed since several general accounts on it have already appeared in the literature. More attention is paid to recent applications to large systems. Finally, we consider how a common formalism to extract electron counts and energies can be used to establish an algebraic justification for the extensively used bond order-bond energy relationships. We also briefly review a path to recover one-electron functions from real space partitions. Although most of the applications considered will be restricted to real space atoms taken from the quantum theory of atoms in molecules, arguably the most successful of all the atomic partitions devised so far, all the take-home messages from this perspective are generalizable to any real space decompositionsWe acknowledge the spanish MICINN, grant PID2021-122763NB-I00 and the FICyT, grant IDI/2021/000054 for financial support. TRR gratefully acknowledges DGTIC/UNAM for computer time (LANCAD-UNAM-DGTIC 250

Computational strategies for the accurate thermochemistry and kinetics of gas-phase reactions

This PhD thesis focuses on the theoretical and computational modeling of gas phase chemical reactions, with a particular emphasis on astrophysical and atmospherical ones. The ability to accurately determine the rate coefficients of key elementary reactions is deeply connected to the accurate determination of geometrical parameters, vibrational frequencies and, even more importantly, electronic energies and zeropoint energy corrections of reactants, transition states, intermediates and products involved in the chemical reaction, together with a suitable choice of the statistical approach for the rate computation (i.e. the proper transition state theory model). The main factor limiting the accuracy of this process is the computational time requested to reach meaningful results (i.e. reaching subchemical accuracy below 1 kJ mol−1), which increases dramatically with the the size of the system under investigation. For small-sized systems, several nonempirical procedures have been developed and presented in the literature. However, for larger systems the well-known model chemistries are far from being parameter-free since they include some empirical parameters and employ geometries which are not fully reliable for transition states and noncovalent complexes possibly ruling the entrance channels. Based on these premises, this dissertation has been focused on the development of new “cheap” composite schemes, entirely based on the frozen core coupled cluster ansatz including single, double, and (perturbative) triple excitation calculations in conjunction with a triple-zeta quality basis set, including the contributions due to the extrapolation to the complete basis set limit and core-valence effects using second-order Møller- Plesset perturbation theory. For the first time the “cheap” scheme has been extended to explicitly-correlated methods, which have an improved performance with respect to their conventional counterparts. Benchmarks with different sets of state of the art energy barriers, interaction energies and geometrical parameters spanning a wide range of values show that, in the absence of strong multireference contributions, the proposed models outperforms the most well-known model chemistries, reaching a subchemical accuracy without any empirical parameter and with affordable computer times. Besides the composite schemes development efforts, a robust protocol for disclosing the thermochemistry and kinetics of reactions of atmospheric and astrophysical interest, rooted in the so-called ab initio-transition-state-theory-based master equation approach have been thoroughly investigated and validated

Kvantově chemické pojetí návrhu léčiv

Výpočetní metody jsou nedílnou součástí moderního farmaceutického výzkumu. Počítačový návrh léčiv si klade za cíl snížit čas a náklady spjaté s vývojem léčiva a také detailněji porozumět vazbě inhibitoru k danému biologickému cíli. Kvůli komplikovanosti biologických systémů a potřebě správného popisu nekovalentních interakcí nutných k molekulárnímu rozpoznávání je přesnost běžně používaných molekulově mechanických (MM) metod na hraně spolehlivosti. Na druhou stranu zde vzrůstá tendence používání kvantově mechanických (QM) metod v různých fázích vývoje léčiv díky rostoucím výpočetním možnostem. Tato disertační práce se zabývá aplikací kvantově mechanických metod pro věrný popis mezimolekulových komplexů a jejich interakcí. Tato práce zahrnuje osm původních publikací rozdělených do tří témat a doprovodný text, jenž si klade za cíl zdůraznit některé závěry plynoucí z této práce. V první řadě je vysoce přesnými kvantově mechanickými metodami studována povaha neklasických nekovalentních interakcí, tzv. vazebné interakce pomocí sigma díry. Síla a původ halogenové, chalkogenové a pniktogenové vazby v modelových systémech z rozšířených databází molekul jsou zkoumány přesnou metodou vázaných klastrů (CCSD(T)/CBS) a symetricky adaptovanou poruchovou teorií (SAPT). Druhá část se věnuje třem farmaceuticky...Computational approaches have become an established and valuable component of pharmaceutical research. Computer-aided drug design aims to reduce the time and cost of the drug development and also to bring deeper insight into the inhibitor binding to its target. The complexity of biological systems together with a need of proper description of non-covalent interactions involved in molecular recognition challenges the accuracy of commonly used molecular mechanical methods (MM). There is on the other side a growing interest of utilizing quantum mechanical (QM) methods in several stages of drug design thanks to increased computational resources. This doctoral thesis's topic is the QM-based methodology for the reliable treatement of intermolecular interactions. It consists of eight original publications devided into three topics and an accompanying text that aims to emphasize selected outcomes of the work. Firstly, the nature of nonclassical non-covalent interactions - so called σ-hole bonding - is studied by high-level QM methods. The strength and origin of halogen-, chalcogen- and pnicogen bonded model systems in extended datasets are accurately explored by coupled cluster QM method (CCSD(T)/CBS) and symmetry adapted perturbation theory (SAPT). The second part is devoted to three pharmaceutically...Katedra fyzikální a makromol. chemieDepartment of Physical and Macromolecular ChemistryFaculty of SciencePřírodovědecká fakult

NEW COMPUTATIONAL METHODS AND ALGORITHMS FOR SEMICONDUCTOR SCIENCE AND NANOTECHNOLOGY

Thesis (Ph.D.) - Indiana University, Chemistry, 2015The design and implementation of sophisticated computational methods and algorithms are critical to solve problems in nanotechnology and semiconductor science. Two key methods will be described to overcome challenges in contemporary surface science. The first method will focus on accurately cancelling interactions in a molecular system, such as modeling adsorbates on periodic surfaces at low coverages, a problem for which current methodologies are computationally inefficient. The second method pertains to the accurate calculation of core-ionization energies through X-ray photoelectron spectroscopy. The development can provide assignment of peaks in X-ray photoelectron spectra, which can determine the chemical composition and bonding environment of surface species. Finally, illustrative surface-adsorbate and gas-phase studies using the developed methods will also be featured

Formulation, Structure, and Applications of Therapeutic, Amino Acid, and Water-Based Deep Eutectic Solvents

In the design of greener chemicals, deep eutectic solvents (DESs) are considered as one of the most versatile alternative solvents with widespread applications. DESs have the advantages of being nonflammable with negligible vapor pressure compared to traditional solvents. They share many characteristics of ionic liquids, but DESs are cheaper to formulate, typically nontoxic, recyclable, biodegradable, and are suitable for use with biological systems. In my Ph.D. research, three types of emerging and unconventional types of DESs, namely therapeutic DES (THEDES), amino acid-based DES (AADES), and water-based DES (WDES), have been investigated. To formulate these DES easily available and cheaper chemicals, such as water, choline chloride, menthol, aspirin, glutamic acid, arginine, and glycerol, were used. Besides formulation, experimental structural characterization, and rigorous computational studies, some of their preliminary applications have been explored to understand their potential area of applications. Formulation for poorly soluble drugs as THEDESs could enhance their solubility significantly and AADES were used to selectively depolymerize lignin. A complete characterization of WDES and solubility of salt or drug was explored. The structures and structural properties of the DES studied were explored rigorously, as these insights can help to make them more effective. The major aim of the research projects was to find out the gaps of the DES research and provide a solid background for future research. Combining the molecular dynamics (MD), density functional theory (DFT), spectroscopic (Raman, IR, and VCD) techniques, solvatochormism, cheminformatics, and chromatographic techniques helped to understand the behavior and potential of the studied formulations. For example, atom-atom radial distribution functions (RDFs) based on MD simulation reveal that hydrogen bonds are formed between Cl-…HOCh+ and Cl- …HOCOOH of the THEDES, where Cl- works as a bridge between ASA and Ch+. Cationanion electrostatic attractions are disrupted by highly interconnected hydrogen bonds. Nonsalt HBA-HBD THEDES (1:1 L-Menthol: acetic acid) is also explored and found that their depression of melting point is mainly because of long network of hydrogen bond. Since menthol is a chiral molecular, VCD was found as a good tool to understand the behavior of chiral molecule-based DES. Melting points of WDESs (1:3 and 1:4 choline chloride: H2O) were found significantly low, -79.21 and -79.25 °C, respectively. TGA study proved that water could be relatively stable at a higher temperature when it forms the DESs. Solvent selectivity triangle (SST) of Kamlet-Taft parameters proved that the DESs possess similar solvatochromic properties to ionic liquids. A simple analytical method was developed employing ion chromatography and atomic absorption spectroscopy to investigate the solubility of sodium halides, alkali chlorides, and cobalt chloride in the studied water-based DESs. Solubility trends of the metal halides in both DESs were found same, NaCl \u3e NaBr \u3e NaI \u3e NaF for sodium halides and LiCl \u3e NaCl \u3e KCl for alkali metal chlorides. Solubilities of the studied drug molecules such as aspirin were found to be 1.3 to 6.7 times higher in the solvents than their solubilities in water. Cell viability assay of the WDES1 (1:3 ChCl:H2O) compared to dimethyl sulfoxide (DMSO) against HEK293 cell line proved that the solvent is applicable to the biological system. The eutectic points of the formulated AADESs were -0.14°C for Glu-Gly and -1.36°C for Arg-Gly. FT-IR, 1HNMR spectroscopy, and mass spectrometry studies found that Glu-Gly formed ester impurities. However, mass spectrometry showed that the impurities are negligible. TGA revealed that both DESs could be applied up to 150-160°C without losing weight, while Glu-Gly could be used up to 200°C. AADESs are excellent pretreatment media for biomass, lignin was treated as a model biomass in this study with the formulated AADESs to determine their reaction products. It was found that Arg-Gly can isolate only one monomeric compound (4-methyl benzaldehyde), while Glu-Gly can isolate three monomeric compounds. Oxidative depolymerization of the lignin residues validated the outcomes obtained from the AADES-lignin reactions. Overall, this work helped to understand how to formulate novel DESs, their wide variety of characterizations, and possible application

How Water's Properties Are Encoded in Its Molecular Structure and Energies.

How are water's material properties encoded within the structure of the water molecule? This is pertinent to understanding Earth's living systems, its materials, its geochemistry and geophysics, and a broad spectrum of its industrial chemistry. Water has distinctive liquid and solid properties: It is highly cohesive. It has volumetric anomalies-water's solid (ice) floats on its liquid; pressure can melt the solid rather than freezing the liquid; heating can shrink the liquid. It has more solid phases than other materials. Its supercooled liquid has divergent thermodynamic response functions. Its glassy state is neither fragile nor strong. Its component ions-hydroxide and protons-diffuse much faster than other ions. Aqueous solvation of ions or oils entails large entropies and heat capacities. We review how these properties are encoded within water's molecular structure and energies, as understood from theories, simulations, and experiments. Like simpler liquids, water molecules are nearly spherical and interact with each other through van der Waals forces. Unlike simpler liquids, water's orientation-dependent hydrogen bonding leads to open tetrahedral cage-like structuring that contributes to its remarkable volumetric and thermal properties

Applications and Improvements in the Molecular Modeling of Protein and Ligand Interactions

Understanding protein and ligand interactions is fundamental to treat disease and avoid toxicity in biological organisms. Molecular modeling is a helpful but imperfect tool used in computer-aided toxicology and drug discovery. In this work, molecular docking and structural informatics have been integrated with other modeling methods and physical experiments to better understand and improve predictions for protein and ligand interactions. Results presented as part of this research include: 1.) an application of single-protein docking for an intermediate state structure, specifically, modeling an intermediate state structure of alpha-1-antitrypsin and using the resulting model to virtually screen for chemical inhibitors that can treat alpha-1-antitrypsin deficiency, 2.) an application of multi-protein docking and metabolism prediction, specifically, modeling the cytochrome P450 metabolism and estrogen receptor activity of an environmental pollutant (PCB-30), and 3.) providing evidence to support the inclusion of anion-pi interactions in molecular modeling by demonstrating the biological roles of anion-pi interactions in stabilizing protein and protein-ligand structures. This work has direct applications for mitigating disease and toxicity, but it also demonstrates useful ways of integrating computational and experimental data to improve upon modeling protein and ligand interactions