Structure and mechanism of a methyltransferase ribozyme

Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions

Accurate RNA structure models are crucial for designing small molecule ligands that modulate their functions. This study assesses six standalone RNA 3D structure prediction methods-DeepFoldRNA, RhoFold, BRiQ, FARFAR2, SimRNA and Vfold2, excluding web-based tools due to intellectual property concerns. We focus on reproducing the RNA structure existing in RNA-small molecule complexes, particularly on the ability to model ligand binding sites. Using a comprehensive set of RNA structures from the PDB, which includes diverse structural elements, we found that machine learning (ML)-based methods effectively predict global RNA folds but are less accurate with local interactions. Conversely, non-ML-based methods demonstrate higher precision in modeling intramolecular interactions, particularly with secondary structure restraints. Importantly, ligand-binding site accuracy can remain sufficiently high for practical use, even if the overall model quality is not optimal. With the recent release of AlphaFold 3, we included this advanced method in our tests. Benchmark subsets containing new structures, not used in the training of the tested ML methods, show that AlphaFold 3's performance was comparable to other ML-based methods, albeit with some challenges in accurately modeling ligand binding sites. This study underscores the importance of enhancing binding site prediction accuracy and the challenges in modeling RNA-ligand interactions accurately.

Software Infrastructure for Next-Generation QM/MM-ΔMLP Force Fields

We present software infrastructure for the design and testing of new quantum mechanical/molecular mechanical and machine-learning potential (QM/MM-ΔMLP) force fields for a wide range of applications. The software integrates Amber's molecular dynamics simulation capabilities with fast, approximate quantum models in the xtb package and machine-learning potential corrections in DeePMD-kit. The xtb package implements the recently developed density-functional tight-binding QM models with multipolar electrostatics and density-dependent dispersion (GFN2-xTB), and the interface with Amber enables their use in periodic boundary QM/MM simulations with linear-scaling QM/MM particle-mesh Ewald electrostatics. The accuracy of the semiempirical models is enhanced by including machine-learning correction potentials (ΔMLPs) enabled through an interface with the DeePMD-kit software. The goal of this paper is to present and validate the implementation of this software infrastructure in molecular dynamics and free energy simulations. The utility of the new infrastructure is demonstrated in proof-of-concept example applications. The software elements presented here are open source and freely available. Their interface provides a powerful enabling technology for the design of new QM/MM-ΔMLP models for studying a wide range of problems, including biomolecular reactivity and protein-ligand binding.

A folding motif formed with an expanded genetic alphabet

Adding synthetic nucleotides to DNA increases the linear information density of DNA molecules. Here we report that it also can increase the diversity of their three-dimensional folds. Specifically, an additional nucleotide (dZ, with a 5-nitro-6-aminopyridone nucleobase), placed at twelve sites in a 23-nucleotides-long DNA strand, creates a fairly stable unimolecular structure (that is, the folded Z-motif, or fZ-motif) that melts at 66.5 °C at pH 8.5. Spectroscopic, gel and two-dimensional NMR analyses show that the folded Z-motif is held together by six reverse skinny dZ-:dZ base pairs, analogous to the crystal structure of the free heterocycle. Fluorescence tagging shows that the dZ-:dZ pairs join parallel strands in a four-stranded compact down-up-down-up fold. These have two possible structures: one with intercalated dZ-:dZ base pairs, the second without intercalation. The intercalated structure would resemble the i-motif formed by dC:dC+-reversed pairing at pH ≤ 6.5. This fZ-motif may therefore help DNA form compact structures needed for binding and catalysis.

Assessment of Nucleobase Protomeric and Tautomeric States in Nucleic Acid Structures for Interaction Analysis and Structure-Based Ligand Design

With increasing interest in RNA as a therapeutic and a potential target, the role of RNA structures has become more important. Even slight changes in nucleobases, such as modifications or protomeric and tautomeric states, can have a large impact on RNA structure and function, while local environments in turn affect protonation and tautomerization. In this work, the application of empirical tools for pKa and tautomer prediction for RNA modifications was elucidated and compared with ab initio quantum mechanics (QM) methods and expanded toward macromolecular RNA structures, where QM is no longer feasible. In this regard, the Protonate3D functionality within the molecular operating environment (MOE) was expanded for nucleobase protomer and tautomer predictions and applied to reported examples of altered protonation states depending on the local environment. Overall, observations of nonstandard protomers and tautomers were well reproduced, including structural C+G:C(A) and A+GG motifs, several mismatches, and protonation of adenosine or cytidine as the general acid in nucleolytic ribozymes. Special cases, such as cobalt hexamine-soaked complexes or the deprotonation of guanosine as the general base in nucleolytic ribozymes, proved to be challenging. The collected set of examples shall serve as a starting point for the development of further RNA protonation prediction tools, while the presented Protonate3D implementation already delivers reasonable protonation predictions for RNA and DNA macromolecules. For cases where higher accuracy is needed, like following catalytic pathways of ribozymes, incorporation of QM-based methods can build upon the Protonate3D-generated starting structures. Likewise, this protonation prediction can be used for structure-based RNA-ligand design approaches.

Surface-Accelerated String Method for Locating Minimum Free Energy Paths

We present a surface-accelerated string method (SASM) to efficiently optimize low-dimensional reaction pathways from the sampling performed with expensive quantum mechanical/molecular mechanical (QM/MM) Hamiltonians. The SASM accelerates the convergence of the path using the aggregate sampling obtained from the current and previous string iterations, whereas approaches like the string method in collective variables (SMCV) or the modified string method in collective variables (MSMCV) update the path only from the sampling obtained from the current iteration. Furthermore, the SASM decouples the number of images used to perform sampling from the number of synthetic images used to represent the path. The path is optimized on the current best estimate of the free energy surface obtained from all available sampling, and the proposed set of new simulations is not restricted to being located along the optimized path. Instead, the umbrella potential placement is chosen to extend the range of the free energy surface and improve the quality of the free energy estimates near the path. In this manner, the SASM is shown to improve the exploration for a minimum free energy pathway in regions where the free energy surface is relatively flat. Furthermore, it improves the quality of the free energy profile when the string is discretized with too few images. We compare the SASM, SMCV, and MSMCV using 3 QM/MM applications: a ribozyme methyltransferase reaction using 2 reaction coordinates, the 2'-O-transphosphorylation reaction of Hammerhead ribozyme using 3 reaction coordinates, and a tautomeric reaction in B-DNA using 5 reaction coordinates. We show that SASM converges the paths using roughly 3 times less sampling than the SMCV and MSMCV methods. All three algorithms have been implemented in the FE-ToolKit package made freely available.

A comparative survey of the influence of small self-cleaving ribozymes on gene expression in human cell culture

Self-cleaving ribozymes are versatile tools for synthetic biologists when it comes to controlling gene expression. Up to date, 12 different classes are known, and over the past decades more and more details about their structure, cleavage mechanisms and natural environments have been uncovered. However, when these motifs are applied to mammalian gene expression constructs, the outcome can often be unexpected. A variety of factors, such as surrounding sequences and positioning of the ribozyme influences the activity and hence performance of catalytic RNAs. While some information about the efficiency of individual ribozymes (each tested in specific contexts) is known, general trends obtained from standardized, comparable experiments are lacking, complicating decisions such as which ribozyme to choose and where to insert it into the target mRNA. In many cases, application-specific optimization is required, which can be very laborious. Here, we systematically compared different classes of ribozymes within the 3'-UTR of a given reporter gene. We then examined position-dependent effects of the best-performing ribozymes. Moreover, we tested additional variants of already widely used hammerhead ribozymes originating from various organisms. We were able to identify functional structures suited for aptazyme design and generated highly efficient hammerhead ribozyme variants originating from the human genome. The present dataset will aide decisions about how to apply ribozymes for affecting gene expression as well as for developing ribozyme-based switches for controlling gene expression in human cells.

RNA-Guided RNA Modifications: Biogenesis, Functions, and Applications

Post-transcriptional modifications are ubiquitous in both protein-coding and noncoding RNAs (ncRNAs), playing crucial functional roles in diverse biological processes across all kingdoms of life. These RNA modifications can be achieved through two distinct mechanisms: RNA-independent and RNA-guided (also known as RNA-dependent). In the RNA-independent mechanism, modifications are directly introduced onto RNA molecules by enzymes without the involvement of other RNA molecules, while the cellular RNA-guided RNA modification system exists in the form of RNA-protein complexes, wherein one guide RNA collaborates with a set of proteins, including the modifying enzyme. The primary function of guide RNAs lies in their ability to bind to complementary regions within the target RNAs, orchestrating the installation of specific modifications. Both mechanisms offer unique advantages and are critical to the diverse and dynamic landscape of RNA modifications. RNA-independent modifications provide rapid and direct modification of RNA molecules, while RNA-guided mechanisms offer precise and programmable means to introduce modifications at specific RNA sites. Recently, emerging evidence has shed light on RNA-guided RNA modifications as a captivating area of research, providing precise and programmable control over RNA sequences and functions.In this Account, we focus on RNA modifications synthesized in an RNA-guided manner, including 2'-O-methylated nucleotides (Nm), pseudouridine (Ψ), N4-acetylcytidine (ac4C), and inosine (I). This Account sheds light on the intricate processes of biogenesis and elucidates the regulatory roles of these modifications in RNA metabolism. These roles include pivotal functions such as RNA stability, translation, and splicing, where each modification contributes to the diverse and finely tuned regulatory landscape of RNA biology. In addition to elucidating the biogenesis and functions of these modifications, we also provide an overview of high-throughput methods and their underlying biochemical principles used for the transcriptome-wide investigation of these modifications and their fundamental interactions in RNA-guided systems. This includes exploring RNA-protein interactions and RNA-RNA interactions, which play crucial roles in the dynamic regulatory networks of RNA-guided modifications. The ever-advancing methodologies have greatly enhanced our understanding of the dynamic and widespread nature of RNA-guided RNA modifications and their regulatory functions. Furthermore, the applications of RNA-guided RNA modifications are discussed, illuminating their potential in diverse fields. From basic research to gene therapy, the programmable nature of RNA-guided modifications presents exciting opportunities for manipulating gene expression and developing innovative therapeutic strategies.

Ghost authors revealed: The structure and function of human N6 -methyladenosine RNA methyltransferases

Despite the discovery of modified nucleic acids nearly 75 years ago, their biological functions are still being elucidated. N6 -methyladenosine (m6 A) is the most abundant modification in eukaryotic messenger RNA (mRNA) and has also been detected in non-coding RNAs, including long non-coding RNA, ribosomal RNA, and small nuclear RNA. In general, m6 A marks can alter RNA secondary structure and initiate unique RNA-protein interactions that can alter splicing, mRNA turnover, and translation, just to name a few. Although m6 A marks in human RNAs have been known to exist since 1974, the structures and functions of methyltransferases responsible for writing m6 A marks have been established only recently. Thus far, there are four confirmed human methyltransferases that catalyze the transfer of a methyl group from S-adenosylmethionine (SAM) to the N6 position of adenosine, producing m6 A: methyltransferase-like protein (METTL) 3/METTL14 complex, METTL16, METTL5, and zinc-finger CCHC-domain-containing protein 4. Though the methyltransferases have unique RNA targets, all human m6 A RNA methyltransferases contain a Rossmann fold with a conserved SAM-binding pocket, suggesting that they utilize a similar catalytic mechanism for methyl transfer. For each of the human m6 A RNA methyltransferases, we present the biological functions and links to human disease, RNA targets, catalytic and kinetic mechanisms, and macromolecular structures. We also discuss m6 A marks in human viruses and parasites, assigning m6 A marks in the transcriptome to specific methyltransferases, small molecules targeting m6 A methyltransferases, and the enzymes responsible for hypermodified m6 A marks and their biological functions in humans. Understanding m6 A methyltransferases is a critical steppingstone toward establishing the m6 A epitranscriptome and more broadly the RNome. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

RNA structure determination: From 2D to 3D

RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.

Catalytic mechanism and pH dependence of a methyltransferase ribozyme (MTR1) from computational enzymology

A methyltransferase ribozyme (MTR1) was selected in vitro to catalyze alkyl transfer from exogenous O6-methylguanine (O6mG) to a target adenine N1, and recently, high-resolution crystal structures have become available. We use a combination of classical molecular dynamics, ab initio quantum mechanical/molecular mechanical (QM/MM) and alchemical free energy (AFE) simulations to elucidate the atomic-level solution mechanism of MTR1. Simulations identify an active reactant state involving protonation of C10 that hydrogen bonds with O6mG:N1. The deduced mechanism involves a stepwise mechanism with two transition states corresponding to proton transfer from C10:N3 to O6mG:N1 and rate-controlling methyl transfer (19.4  kcal·mol-1 barrier). AFE simulations predict the pKa for C10 to be 6.3, close to the experimental apparent pKa of 6.2, further implicating it as a critical general acid. The intrinsic rate derived from QM/MM simulations, together with pKa calculations, enables us to predict an activity-pH profile that agrees well with experiment. The insights gained provide further support for a putative RNA world and establish new design principles for RNA-based biochemical tools.

Biological Catalysis and Information Storage Have Relied on N-Glycosyl Derivatives of β-D-Ribofuranose since the Origins of Life

Most naturally occurring nucleotides and nucleosides are N-glycosyl derivatives of β-d-ribose. These N-ribosides are involved in most metabolic processes that occur in cells. They are essential components of nucleic acids, forming the basis for genetic information storage and flow. Moreover, these compounds are involved in numerous catalytic processes, including chemical energy production and storage, in which they serve as cofactors or coribozymes. From a chemical point of view, the overall structure of nucleotides and nucleosides is very similar and simple. However, their unique chemical and structural features render these compounds versatile building blocks that are crucial for life processes in all known organisms. Notably, the universal function of these compounds in encoding genetic information and cellular catalysis strongly suggests their essential role in the origins of life. In this review, we summarize major issues related to the role of N-ribosides in biological systems, especially in the context of the origin of life and its further evolution, through the RNA-based World(s), toward the life we observe today. We also discuss possible reasons why life has arisen from derivatives of β-d-ribofuranose instead of compounds based on other sugar moieties.

Establishment, optimization, and application of genetic technology in Aspergillus spp

Aspergillus is widely distributed in nature and occupies a crucial ecological niche, which has complex and diverse metabolic pathways and can produce a variety of metabolites. With the deepening of genomics exploration, more Aspergillus genomic informations have been elucidated, which not only help us understand the basic mechanism of various life activities, but also further realize the ideal functional transformation. Available genetic engineering tools include homologous recombinant systems, specific nuclease based systems, and RNA techniques, combined with transformation methods, and screening based on selective labeling. Precise editing of target genes can not only prevent and control the production of mycotoxin pollutants, but also realize the construction of economical and efficient fungal cell factories. This paper reviewed the establishment and optimization process of genome technologies, hoping to provide the theoretical basis of experiments, and summarized the recent progress and application in genetic technology, analyzes the challenges and the possibility of future development with regard to Aspergillus.

Regulation of Gene Expression Through Effector-dependent Conformational Switching by Cobalamin Riboswitches

Riboswitches are an outstanding example of genetic regulation mediated by RNA conformational switching. In these non-coding RNA elements, the occupancy status of a ligand-binding domain governs the mRNA's decision to form one of two mutually exclusive structures in the downstream expression platform. Temporal constraints upon the function of many riboswitches, requiring folding of complex architectures and conformational switching in a limited co-transcriptional timeframe, make them ideal model systems for studying these processes. In this review, we focus on the mechanism of ligand-directed conformational changes in one of the most widely distributed riboswitches in bacteria: the cobalamin family. We describe the architectural features of cobalamin riboswitches whose structures have been determined by x-ray crystallography, which suggest a direct physical role of cobalamin in effecting the regulatory switch. Next, we discuss a series of experimental approaches applied to several model cobalamin riboswitches that interrogate these structural models. As folding is central to riboswitch function, we consider the differences in folding landscapes experienced by RNAs that are produced in vitro and those that are allowed to fold co-transcriptionally. Finally, we highlight a set of studies that reveal the difficulties of studying cobalamin riboswitches outside the context of transcription and that co-transcriptional approaches are essential for developing a more accurate picture of their structure-function relationships in these switches. This understanding will be essential for future advancements in the use of small-molecule guided RNA switches in a range of applications such as biosensors, RNA imaging tools, and nucleic acid-based therapies.

An RNA aptamer that shifts the reduction potential of metabolic cofactors

The discovery of ribozymes has inspired exploration of RNA's potential to serve as primordial catalysts in a hypothesized RNA world. Modern oxidoreductase enzymes employ differential binding between reduced and oxidized forms of redox cofactors to alter cofactor reduction potential and enhance the enzyme's catalytic capabilities. The utility of differential affinity has been underexplored as a chemical strategy for RNA. Here we show an RNA aptamer that preferentially binds oxidized forms of flavin over reduced forms and markedly shifts flavin reduction potential by -40 mV, similar to shifts for oxidoreductases. Nuclear magnetic resonance structural analysis revealed π-π and donor atom-π interactions between the aptamer and flavin that cause unfavorable contacts with the electron-rich reduced form, suggesting a mechanism by which the local environment of the RNA-binding pocket drives the observed shift in cofactor reduction potential. It seems likely that primordial RNAs could have used similar strategies in RNA world metabolisms.