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

Computation and programmability at the nano-bio interface

PhD ThesisThe manipulation of physical reality on the molecular level and construction of devices operating on the nanoscale has been the focal point of nanotechnology. In particular, nanotechnology based on DNA and RNA has a potential to nd applications in the eld of Synthetic Biology thanks to the inherent compatibility of nucleic acids with biological systems. Sca olded DNA origami, proposed by P. Rothemund, is one of the leading and most successful methods in which nanostructures are realised through rational programming of short 'staple' oligomers which fold a long single-stranded DNA called the 'sca old' strand into a variety of desired shapes. DNA origami already has many applications; including intelligent drug delivery, miniaturisation of logic circuits and computation in vivo. However, one of the factors that are limiting the complexity, applicability and scalability of this approach is the source of the sca old which commonly originates from viruses or phages. Furthermore, developing a robust and orthogonal interface between DNA nanotechnology and biological parts remains a signi cant challenge. The rst part of this thesis tackles these issues by challenging the fundamental as- sumption in the eld, namely that a viral sequence is to be used as the DNA origami sca old. A method is introduced for de novo generation of long synthetic sequences based on De Bruijn sequence, which has been previously proposed in combinatorics. The thesis presents a collection of algorithms which allow the construction of custom- made sequences that are uniquely addressable and biologically orthogonal (i.e. they do not code for any known biological function). Synthetic sca olds generated by these algorithms are computationally analysed and compared with their natural counter- parts with respect to: repetition in sequence, secondary structure and thermodynamic addressability. This also aids the design of wet lab experiments pursuing justi cation and veri cation of this novel approach by empirical evidence. The second part of this thesis discusses the possibility of applying evolutionary op- timisation to synthetic DNA sequences under constraints dictated by the biological interface. A multi-strand system is introduced based on an alternative approach to DNA self-assembly, which relies on strand-displacement cascades, for molecular data storage. The thesis demonstrates how a genetic algorithm can be used to generate viable solutions to this sequence optimisation problem which favours the target self- assembly con guration. Additionally, the kinetics of strand-displacement reactions are analysed with existing coarse-grained DNA models (oxDNA). This thesis is motivated by the application of scienti c computing to problems which lie on the boundary of Computer Science and the elds of DNA Nanotechnology, DNA Computing and Synthetic Biology, and thus I endeavour to the best of my ability to establish this work within the context of these disciplines

RNA AS A UNIQUE POLYMER TO BUILD CONTROLLABLE NANOSTRUCTURES FOR NANOMEDICINE AND NANOTECHNOLOGY

RNA nanotechnology is an emerging field that involves the design, construction and functionalization of nanostructures composed mainly of RNA for applications in biomedical and material sciences. RNA is a unique polymer with structural simplicity like DNA and functional diversity like proteins. A variety of RNA nanostructures have been reported with different geometrical structures and functionalities. This dissertation describes the design and construction of novel two-dimensional and three-dimensional self-assembled RNA nanostructures with applications in therapeutics delivery, cancer targeting and immunomodulation. Firstly, by using the ultra-stable pRNA three-way junction motif with controllable angles and arm lengths, tetrahedral architectures composed purely of RNA were successfully assembled via one-pot bottom-up assembly with high efficiency and thermal stability. By introducing arm sizes of 22 bp and 55 bp, two RNA tetrahedrons with similar global contour structure but with different sizes of 8 nm and 17 nm were successfully assembled. The RNA tetrahedrons were also highly amenable to functionalization. Fluorogenic RNA aptamers, ribozyme, siRNA, and protein-binding RNA aptamers were integrated into the tetrahedrons by simply fusing the respective sequences with the tetrahedral core modules. Secondly, I reported the design and construction of molecularly defined RNA cages with cube and dodecahedron shapes based on the stable pRNA 3WJ. The RNA cages can be easily self-assembled by single-step annealing. The RNA cages were further characterized by gel electrophoresis, cryo-electron microscopy and atomic force microscopy, confirming the spontaneous formation of the RNA cages. I also demonstrated that the constructed RNA cages could be used to deliver model drugs such as immunomodulatory CpG DNA into cells and elicit enhanced immune responses. Thirdly, by using the modular multi-domain strategy, molecular defined RNA nanowires can be successfully self-assembled via a bottom-up approach. Only four different 44-nucleotide single-stranded RNAs were used to assemble the RNA nanowire. The reported RNA nanowire has the potential to be explored in the future as the carrier for drug delivery or matrix for tissue engineering. Fourthly, the construction of RNA polygons for delivering immunoactive CpG oligonucleotides will be presented. When CpG oligonucleotides were incorporated into the RNA polygons, their immunomodulation effect for cytokine TNF-α and IL-6 induction was greatly enhanced, while RNA polygon controls induced unnoticeable cytokine induction. Moreover, the RNA polygons were delivered to macrophages specifically and the degree of immunostimulation greatly depended on the size, shape, and the number of payload per RNA polygon. Collectively, these findings demonstrated RNA nanotechnology can produce controllable nanostructures with different functionalities and result in potential applications in nanomedicine and nanotechnology

Folding and Assembly of Multimeric Proteins: Dimeric HIV-1 Protease and a Trimeric Coiled Coil Component of a Complex Hemoglobin Scaffold: A Dissertation

Knowledge of how a polypeptide folds from a space-filling random coil into a biologically-functional, three-dimensional structure has been the essence of the protein folding problem. Though mechanistic details of DNA transcription and RNA translation are well understood, a specific code by which the primary structure dictates the acquisition of secondary, tertiary, and quarternary structure remains unknown. However, the demonstrated reversibility of in vitroprotein folding allows for a thermodynamic analysis of the folding reaction. By probing both the equilibrium and kinetics of protein folding, a protein folding mechanism can be postulated. Over the past 40 years, folding mechanisms have been determined for many proteins; however, a generalized folding code is far from clear. Furthermore, most protein folding studies have focused on monomeric proteins even though a majority of biological processes function via the association of multiple subunits. Consequently, a complete understanding of the acquisition of quarternary protein structure is essential for applying the basic principles of protein folding to biology. The studies presented in this dissertation examined the folding and assembly of two very different multimeric proteins. Underlying both of these investigations is the need for a combined analysis of a repertoire of approaches to dissect the folding mechanism for multimeric proteins. Chapter II elucidates the detailed folding energy landscape of HIV-1 protease, a dimeric protein containing β-barrel subunits. The folding of this viral enzyme exhibited a sequential three-step pathway, involving the rate-limiting formation of a monomeric intermediate. The energetics determined from this analysis and their applications to HIV-1 function are discussed. In contrast, Chapter III illustrates the association of a coiled coil component of L. terrestriserythrocruorin. This extracellular hemoglobin consists of a complex scaffold of linker chains with a central ring of interdigitating coiled coils. Allostery is maintained by twelve dodecameric hemoglobin subunits that dock upon this scaffold. Modest association was observed for this coiled coil, and the implications of this fragment to linker assembly are addressed. These studies depict the complexity of multimeric folding reactions. Chapter II demonstrates that a detailed energy landscape of a dimeric protein can be determined by combining traditional equilibrium and kinetic approaches with information from a global analysis of kinetics and a monomer construct. Chapter III indicates that fragmentation of large complexes can show the contributions of separate domains to hierarchical organization. As a whole, this dissertation highlights the importance of pursuing mulitmeric protein folding studies and the implications of these folding mechanisms to biological function

The Fuzziness in Molecular, Supramolecular, and Systems Chemistry

Fuzzy Logic is a good model for the human ability to compute words. It is based on the theory of fuzzy set. A fuzzy set is different from a classical set because it breaks the Law of the Excluded Middle. In fact, an item may belong to a fuzzy set and its complement at the same time and with the same or different degree of membership. The degree of membership of an item in a fuzzy set can be any real number included between 0 and 1. This property enables us to deal with all those statements of which truths are a matter of degree. Fuzzy logic plays a relevant role in the field of Artificial Intelligence because it enables decision-making in complex situations, where there are many intertwined variables involved. Traditionally, fuzzy logic is implemented through software on a computer or, even better, through analog electronic circuits. Recently, the idea of using molecules and chemical reactions to process fuzzy logic has been promoted. In fact, the molecular word is fuzzy in its essence. The overlapping of quantum states, on the one hand, and the conformational heterogeneity of large molecules, on the other, enable context-specific functions to emerge in response to changing environmental conditions. Moreover, analog input–output relationships, involving not only electrical but also other physical and chemical variables can be exploited to build fuzzy logic systems. The development of “fuzzy chemical systems” is tracing a new path in the field of artificial intelligence. This new path shows that artificially intelligent systems can be implemented not only through software and electronic circuits but also through solutions of properly chosen chemical compounds. The design of chemical artificial intelligent systems and chemical robots promises to have a significant impact on science, medicine, economy, security, and wellbeing. Therefore, it is my great pleasure to announce a Special Issue of Molecules entitled “The Fuzziness in Molecular, Supramolecular, and Systems Chemistry.” All researchers who experience the Fuzziness of the molecular world or use Fuzzy logic to understand Chemical Complex Systems will be interested in this book

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here