Density functional theory

Density functional theory (DFT) finds increasing use in applications related to biological systems. Advancements in methodology and implementations have reached a point where predicted properties of reasonable to high quality can be obtained. Thus, DFT studies can complement experimental investigations, or even venture with some confidence into experimentally unexplored territory. In the present contribution, we provide an overview of the properties that can be calculated with DFT, such as geometries, energies, reaction mechanisms, and spectroscopic properties. A wide range of spectroscopic parameters is nowadays accessible with DFT, including quantities related to infrared and optical spectra, X-ray absorption and Mössbauer, as well as all of the magnetic properties connected with electron paramagnetic resonance spectroscopy except relaxation times. We highlight each of these fields of application with selected examples from the recent literature and comment on the capabilities and limitations of current methods

QM/MM molecular dynamics studies of metal binding proteins

Mixed quantum-classical (quantum mechanical/molecular mechanical (QM/MM)) simulations have strongly contributed to providing insights into the understanding of several structural and mechanistic aspects of biological molecules. They played a particularly important role in metal binding proteins, where the electronic effects of transition metals have to be explicitly taken into account for the correct representation of the underlying biochemical process. In this review, after a brief description of the basic concepts of the QM/MM method, we provide an overview of its capabilities using selected examples taken from our work. Specifically, we will focus on heme peroxidases, metallo-\u3b2-lactamases, a-synuclein and ligase ribozymes to show how this approach is capable of describing the catalytic and/or structural role played by transition (Fe, Zn or Cu) and main group (Mg) metals. Applications will reveal how metal ions influence the formation and reduction of high redox intermediates in catalytic cycles and enhance drug metabolism, amyloidogenic aggregate formation and nucleic acid synthesis. In turn, it will become manifest that the protein frame directs and modulates the properties and reactivity of the metalions

Exploring bonding interactions of biochemical relevance in silicon, platinum(II) and iron(III) positively charged species

Elements playing a biological role that are present in nature or in synthetic drugs, such as silicon, platinum(II) and iron(III) usually appear coordinated to ligands in more or less composite molecular architectures. This notion is particularly true when a metal ion is placed in the active center of an enzyme or otherwise integrated into simple biomolecules and proteins. Whereas multifaceted factors affect a charged (metal) centre in a biological environment, the gas-phase provides an interesting medium for elucidating intrinsic interactions between metal ions and biological targets. The idea underlying this doctoral thesis is to highlight how state of the art techniques combining mass spectrometry, IR spectroscopy and computational chemistry can be applied to the study of ionic complexes in an isolated state. In a first section the reactivity behavior of gaseous complexes from the (CH3)3Si+ addition to acetylene has been fully explored by FT-ICR mass spectrometry and ab initio calculations. In this way the C5H11Si+ potential energy surface has been elucidated and the computational results nicely account for the experimental evidence showing an isomerization process from a primarily formed complex (a β-silyl-substituted vinyl cation acquiring an asymmetric cyclic geometry) to CH2=C(CH3)-Si(CH3)2+ silyl cation. The computational methods tested in dealing with the C5H11Si+ ion problem have been further applied to more challenging systems. In a second and third section a comprehensive investigation of the structural features of the key intermediates which are formed from cisplatin by replacement of chloro ligands by water or methionine is described. Here the experimental approach has involved vibrational spectroscopy carried out with a recently designed and assembled apparatus. The NH/OH stretching region has been found highly structurally diagnostic in the aqua complexes where hydrogen bonding interactions are crucial in determining relative conformer stability. The infrared characterization of the monofunctional adducts of platinum(II) drugs with methionine has led to identify distinct modes of interaction with cisplatin and transplatin derived species. In fact, the preferred ligand atom (S or N) seems to be depending on the specific isomer (cis- or trans-) that is reacting with the metal. Cisplatin and transplatin derived species have been sampled both experimentally and computationally, taking into account relativistic effects in the heavy metal. In a fourth task the binding properties of azole ligands toward ferric heme have been examined. Starting from simple ligands such as pyridine, 1-methylimidazole and 1H-1,2,4-triazole, the focus was then directed to imidazole- and triazole-based antifungal drugs. These drugs are known to act as inhibitors of CYP51enzyme, through binding to the heme prosthetic group. Relative binding energies were determined experimentally by energy variable collision induced dissociation experiments performed on the selected ionic complexes and evaluated theoretically by Car-Parrinello molecular dynamics calculations. To this end, theoretical investigations were carried out during a training period spent at the “Parc Cientific de Barcelona”, under the supervision of Research Professor Carme Rovira. Imidazole-based drugs consistently display higher dissociation energies when compared to triazole-based drugs

Modelling molecule-surface interactions-an automated quantum-classical approach using a genetic algorithm

We present an automated and efficient method to develop force fields for molecule-surface interactions. A genetic algorithm (GA) is used to parameterise a classical force field so that the classical adsorption energy landscape of a molecule on a surface matches the corresponding landscape from density functional theory (DFT) calculations. The procedure performs a sophisticated search in the parameter phase space and converges very quickly. The method is capable of fitting a significant number of structures and corresponding adsorption energies. Water on a ZnO(0001) surface was chosen as a benchmark system but the method is implemented in a flexible way and can be applied to any system of interest. In the present case, pairwise Lennard Jones (LJ) and Coulomb potentials are used to describe the molecule-surface interactions. In the course of the fitting procedure, the LJ parameters are refined in order to reproduce the adsorption energy landscape. The classical model is capable of describing a wide range of energies, which is essential for a realistic description of a fluid-solid interface

Insights into enzymatic halogenation from computational studies

The halogenases are a group of enzymes that have only come to the fore over the last 10 years thanks to the discovery and characterization of several novel representatives. They have revealed the fascinating variety of distinct chemical mechanisms that nature utilizes to activate halogens and introduce them into organic substrates. Computational studies using a range of approaches have already elucidated many details of the mechanisms of these enzymes, often in synergistic combination with experiment. This Review summarizes the main insights gained from these studies. It also seeks to identify open questions that are amenable to computational investigations. The studies discussed herein serve to illustrate some of the limitations of the current computational approaches and the challenges encountered in computational mechanistic enzymology

Bioinorganic Chemistry

This book covers material that could be included in a one-quarter or one-semester course in bioinorganic chemistry for graduate students and advanced undergraduate students in chemistry or biochemistry. We believe that such a course should provide students with the background required to follow the research literature in the field. The topics were chosen to represent those areas of bioinorganic chemistry that are mature enough for textbook presentation. Although each chapter presents material at a more advanced level than that of bioinorganic textbooks published previously, the chapters are not specialized review articles. What we have attempted to do in each chapter is to teach the underlying principles of bioinorganic chemistry as well as outlining the state of knowledge in selected areas. We have chosen not to include abbreviated summaries of the inorganic chemistry, biochemistry, and spectroscopy that students may need as background in order to master the material presented. We instead assume that the instructor using this book will assign reading from relevant sources that is appropriate to the background of the students taking the course. For the convenience of the instructors, students, and other readers of this book, we have included an appendix that lists references to reviews of the research literature that we have found to be particularly useful in our courses on bioinorganic chemistry

Embedded Mean-Field Theory

We introduce embedded mean-field theory (EMFT), an approach that flexibly allows for the embedding of one mean-field theory in another without the need to specify or fix the number of particles in each subsystem. EMFT is simple, is well-defined without recourse to parameters, and inherits the simple gradient theory of the parent mean-field theories. In this paper, we report extensive benchmarking of EMFT for the case where the subsystems are treated using different levels of Kohn–Sham theory, using PBE or B3LYP/6-31G* in the high-level subsystem and LDA/STO-3G in the low-level subsystem; we also investigate different levels of density fitting in the two subsystems. Over a wide range of chemical problems, we find EMFT to perform accurately and stably, smoothly converging to the high-level of theory as the active subsystem becomes larger. In most cases, the performance is at least as good as that of ONIOM, but the advantages of EMFT are highlighted by examples that involve partitions across multiple bonds or through aromatic systems and by examples that involve more complicated electronic structure. EMFT is simple and parameter free, and based on the tests provided here, it offers an appealing new approach to a multiscale electronic structure

Novel algorithms and high-performance cloud computing enable efficient fully quantum mechanical protein-ligand scoring

Ranking the binding of small molecules to protein receptors through physics-based computation remains challenging. Though inroads have been made using free energy methods, these fail when the underlying classical mechanical force fields are insufficient. In principle, a more accurate approach is provided by quantum mechanical density functional theory (DFT) scoring, but even with approximations, this has yet to become practical on drug discovery-relevant timescales and resources. Here, we describe how to overcome this barrier using algorithms for DFT calculations that scale on widely available cloud architectures, enabling full density functional theory, without approximations, to be applied to protein-ligand complexes with approximately 2500 atoms in tens of minutes. Applying this to a realistic example of 22 ligands binding to MCL1 reveals that density functional scoring outperforms classical free energy perturbation theory for this system. This raises the possibility of broadly applying fully quantum mechanical scoring to real-world drug discovery pipelines.Comment: 15 pages, 5 figures, 1 tabl