RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field

Structural Studies of Biomolecular Systems with Molecular Dynamics Simulations

In vorliegender Arbeit wurden computerbasierte Simulationen eingesetzt, um verschiedene strukturelle Eigenschaften und Dynamiken von Biomolekülen aufzuklären. Die bearbeiteten Themen resultieren aus Kooperationen innerhalb des Graduiertenkolleges 2039 Molekulare Architekturen für die fluoreszente Bildgebung von Zellen. Dabei wurden sowohl klassische Molekulardynamik (MD)-Simulationen verwendet als auch Simulationen mit Verwendung sogenannter coarse-grained-Ansätze, bei denen mehrere Atome zu größeren Einheiten zusammengefasst werden. Aus dem Gebiet der Peptid-Membran-Wechselwirkungen wurden in Zusammenarbeit mit dem Arbeitskreis Ulrich (KIT) zwei hydrophobe Peptide aus Typ I Toxin-Antitoxin-Systemen bearbeitet. Im Mittelpunkt von Kapitel 3 steht das stress-induzierte Peptid tisB (29 Aminosäuren) aus E. coli, welches die Formation von Biofilmen bewirkt und den elektrochemischen Gradienten an der Bakterienzellmembran stilllegen kann. Es wurden Studien der Assemblierung des Peptides tisB als paralleles Dimer und Tetramer in der Lipidmembran durchgeführt. Die anschließenden langen Simulationen ausgewählter Strukturen wurden mit experimentell gefundenen Ergebnissen verglichen, wobei das Hervortreten des charge zipper-Motivs als Interaktionsmotiv bestätigt werden konnte. Für das Dimer und das Tetramer konnten erstmals Strukturen für einen möglichen Protonentransfer über die Membran aufgespürt werden. Das Tetramer zeichnet sich durch seinen Aufbau aus zwei antiparallelen tisB-Dimeren aus, welches einen ständigen Wasserfaden über das entstandene polare Interface erlaubt, und erscheint als sehr vielversprechende Ausgangsstruktur für mögliche Protonentransferstudien. In Kapitel 4 sind erste strukturelle Studien zum Peptid bsrG (38 Aminosäuren) aus B. subtilis dargestellt. Es konnte gezeigt werden, dass bsrG als Monomer nicht in Lipidmembranen integriert, aber an die Oberfläche assoziiert ist. Die polaren Aminosäuren sind dabei zum Wasser hin ausgerichtet. Mittels Assemblierungsstudien des Peptides als Dimer in der Lipidmembran konnten stabile parallele und antiparallele Strukturen eluiert werden, die mit experimentellen Ergebnissen übereinstimmen und das Bindungsmotiv des hydrogen bond zipper zeigen. In Zusammenarbeit mit den Arbeitskreisen Wagenknecht, Nienhaus und Schepers (alle KIT) wurden MD-Simulationen zur Aufklärung des unterschiedlichen Verhaltens zweier Doppelstrang-RNA-Konstrukte mit FRET-Farbstoffen (arabino- und ribo-Konfiguration) bei der Effizienz des FRET-Transfers eingesetzt (Kapitel 5). MD-Simulationen konnten aufzeigen, dass dieser Unterschied in der Effizienz auf Grundlage der erhöhten Mobilität der arabino-konfigurierten Farbstoffe zu erklären ist, im Gegensatz zu den sehr stark wechselwirkenden und unbeweglichen ribo-konfigurierten Farbstoffen. Jene Mobilität ermöglicht einen effizienten Energietransfer zwischen den Farbstoffen, der zu FRET führt

Fluctuation solution theory

Doctor of PhilosophyDepartment of ChemistryPaul E. SmithThe Kirkwood-Buff (KB) theory of solutions, published in 1951, established a route from integrals over radial (pair) distribution functions (RDFs) in the grand canonical ensemble to a set of thermodynamic quantities in an equivalent closed ensemble. These “KB integrals” (KBIs) can also be expressed in terms of the particle-particle (i.e., concentration or density) fluctuations within grand canonical ensemble regions. Contributions by Ben-Naim in 1977 provided the means to obtain the KBIs if one already knew the set of thermodynamic quantities for the mixture of interest; that is, he provided the inversion procedure. Thus, KB theory provides a two-way bridge between local (microscopic) and global (bulk/thermodynamic) properties. Due to its lack of approximations, its wide ranging applicability, and the absence of a competitive theory for rigorously understanding liquid mixtures, it has been used to understand solution microheterogeneity, solute solubility, cosolvent effects on biomolecules, preferential solvation, etc. Here, after using KB theory to test the accuracy of pair potentials, we present and illustrate two extensions of the theory, resulting in a general Fluctuation Solution Theory (FST). First, we generalize KB theory to include two-way relationships between the grand canonical ensemble’s particle-energy and energy-energy fluctuations and additional thermodynamic quantities. This extension allows for non-isothermal conditions to be considered, unlike traditional KB theory. We illustrate these new relationships using analyses of experimental data and molecular dynamics (MD) simulations for pure liquids and binary mixtures. Furthermore, we use it to obtain conformation-specific infinitely dilute partial molar volumes and compressibilities for proteins (other properties will follow) from MD simulations and compare the method to a non-FST method for obtaining the same properties. The second extension of KB theory involves moving beyond doublet particle fluctuations to additionally consider triplet and quadruplet particle fluctuations, which are related to derivatives of the thermodynamic properties involved in regular KB theory. We present these higher order fluctuations obtained from experiment and simulation for pure liquids and binary mixtures. Using the newfound experimental third and fourth cumulants of the distribution of particles in solution, which can be extracted from bulk thermodynamic data using this extension, we also probe particle distributions’ non-Gaussian nature

The interaction of materials and biology: simulations of peptides, surfaces, and biomaterials

Biomaterials were originally designed to augment or replace damaged tissue in the body, but now encompass a wider range of applications including drug delivery, cancer vaccines, electronic sensor devices, and non-fouling coatings for ship hulls. At the heart of all of these applications is the interface between synthetic materials and biology. Modern techniques for studying this interface are limited to the macro and micro scales. With the advent of high performance computing clusters, molecular simulation is now capable of simulating the interface at the nano-scale. This thesis demonstrates how simulation adds important insights to the understanding of biomaterials. It begins with a comprehensive outline of the theoretical aspects of simulating the interface between water and solid surfaces. After this, small surface-bound biological molecules are modelled to explain experiments showing that they can capture cells on the surface. Finally, a new and practical, scalable technique for controlling biological molecules at the surface is developed. This work advances the field of biomaterials by explaining important processes that occur at the interface of biology and technology

Modeling and Molecular Dynamics Simulations on the in situ Murine Cytochrome P450 4F System

Cytochrome P450s are major participants in the maintenance and well-being of cellular function and have important roles in the health and disease of living creatures. The ω-hydroxylation, catalyzed by CYP4 family members, has been observed to be an important metabolic pathway for the homeostasis of mammalian cells as it regulates inflammatory processes with the eicosanoid cascade of metabolites of the ω-6 polyunsaturated fatty acid, arachidonic acid. Many human CYP4F and murine Cyp4f subfamily members have recently gained interest for their usage as potential cancer biomarkers as the expression of these proteins are modified in tumor cells. 20-HETE, the ω-hydroxylated product of arachidonic acid, has gained attention for being the chief metabolic product of interest in vascular function, tumor progression and propagation. Whether or not individual Cyp4f isoforms are responsible for the production of this metabolite is of great interest to medicine as such insight could provide researchers with new avenues of study in the fight against cancer. One particular Cyp4f isozyme, Cyp4f13, has received relatively little study until only very recently and is the focus of the work presented in this thesis, as it has not fully had its role in eicosanoid metabolism understood. Using a combination of computational chemistry approaches, this study focuses on exploring the murine cytochrome P450 4f13 system and its active site using all-atomistic Molecular Dynamics Simulation of a homology model. With the embedded protein solvated and in situ environment replicated, the resting state of the substrate-free Cyp4f13 system was generated. Solvation of the active site was performed to explore the inner active cavity of the P450 system, with subsequent molecular docking and mutation of active site residues performed in order to gain insight into the interactions present in the protein-substrate complex. Protonation state changes were observed to have significant effects on both protein structure and arachidonate binding through electrostatic interactions. Leu137, Arg237, and Gly327 were modified and displayed drastic effects on predicted regiospecificity on the P450 substrate. With the insights obtained, we hope to further the understanding of murine Cyp4f13-catalyzed ω-hydroxylation of arachidonic acid

MODLE REDUCTION IN BIOMECHANICS

The mechanical characteristic of the cell is primarily performed by the cytoskeleton. Microtubules, actin, and intermediate filaments are the three main cytoskeletal polymers. Of these, microtubules are the stiffest and have multiple functions within a cell that include: providing tracks for intracellular transport, transmitting the mechanical force necessary for cell division during mitosis, and providing sufficient stiffness for propulsion in flagella and cilia. Microtubule mechanics has been studied by a variety of methods: detailed molecular dynamics (MD), coarse-grained models, engineering type models, and elastic continuum models. In principle, atomistic MD simulations should be able to predict all desired mechanical properties of a single molecule, however, in practice the large computational resources are required to carry out a simulation of larger biomolecular system. Due to the limited accessibility using even the most ambitious all-atom models and the demand for the multiscale molecular modeling and simulation, the emergence of the reduced models is critically important to provide the capability for investigating the biomolecular dynamics that are critical to many biological processes. Then the coarse-grained models, such as elastic network models and anisotropic network models, have been shown to bequite accurate in predicting microtubule mechanical response, but still requires significant computational resources. On the other hand, the microtubule is treated as comprising materials with certain continuum material properties. Such continuum models, especially Euler-Bernoulli beam models, are often used to extract mechanical parameters from experimental results. The microtubule is treated as comprising materials with certain continuum material properties. Such continuum models, especially Euler-Bernoulli beam models in which the biomolecular system is assumed as homogeneous isotropic materials with solid cross-sections, are often used to extract mechanical parameters from experimental results. However, in real biological world, these homogeneous and isotropic assumptions are usually invalidate. Thus, instead of using hypothesized model, a specific continuum model at mesoscopic scale can be introduced based upon data reduction of the results from molecular simulations at atomistic level. Once a continuum model is established, it can provide details on the distribution of stresses and strains induced within the biomolecular system which is useful in determining the distribution and transmission of these forces to the cytoskeletal and sub-cellular components, and help us gain a better understanding in cell mechanics. A data-driven model reduction approach to the problem of microtubule mechanics as an application is present, a beam element is constructed for microtubules based upon data reduction of the results from molecular simulation of the carbon backbone chain of αβ-tubulin dimers. The data base of mechanical responses to various types of loads from molecular simulation is reduced to dominant modes. The dominant modes are subsequently used to construct the stiffness matrix of a beam element that captures the anisotropic behavior and deformation mode coupling that arises from a microtubule’s spiral structure. In contrast to standard Euler-Bernoulli or Timoshenko beam elements, the link between forces and node displacements results not from hypothesized deformation behavior, but directly from the data obtained by molecular scale simulation. Differences between the resulting microtubule data-driven beam model (MTDDBM) and standard beam elements are presented, with a focus on coupling of bending, stretch, shear deformations. The MTDDBM is just as economical to use as a standard beam element, and allows accurate reconstruction of the mechanical behavior of structures within a cell as exemplified in a simple model of a component element of the mitotic spindle.Doctor of Philosoph