Challenges with Simulating Modified RNA: Insights into Role and Reciprocity of Experimental and Computational Approaches

Molecular dynamics simulations: Insights into protein and protein ligand interactions

Molecular dynamics (MD) simulations are a powerful tool for studying biomolecular systems, offering in-depth insights into the dynamic behaviors of proteins and their interactions with ligands. This chapter delves into the fundamental principles and methodologies of MD simulations, exploring how they contribute to our understanding of protein structures, conformational changes, and the mechanisms underlying protein-ligand interactions. We discuss the computational techniques, force fields, and algorithms that drive MD simulations, highlighting their applications in drug discovery and design. Through case studies and practical examples, we illustrate the capabilities and limitations of MD simulations, emphasizing their role in predicting binding affinities, elucidating binding pathways, and optimizing lead compounds. This chapter offers a thorough understanding of how MD simulations can be leveraged to advance the study of protein-ligand interactions.

mRNA vaccine sequence and structure design and optimization: Advances and challenges

Messenger RNA (mRNA) vaccines have emerged as a powerful tool against communicable diseases and cancers, as demonstrated by their huge success during the coronavirus disease 2019 (COVID-19) pandemic. Despite the outstanding achievements, mRNA vaccines still face challenges such as stringent storage requirements, insufficient antigen expression, and unexpected immune responses. Since the intrinsic properties of mRNA molecules significantly impact vaccine performance, optimizing mRNA design is crucial in preclinical development. In this review, we outline four key principles for optimal mRNA sequence design: enhancing ribosome loading and translation efficiency through untranslated region (UTR) optimization, improving translation efficiency via codon optimization, increasing structural stability by refining global RNA sequence and extending in-cell lifetime and expression fidelity by adjusting local RNA structures. We also explore recent advancements in computational models for designing and optimizing mRNA vaccine sequences following these principles. By integrating current mRNA knowledge, addressing challenges, and examining advanced computational methods, this review aims to promote the application of computational approaches in mRNA vaccine development and inspire novel solutions to existing obstacles.

Molecular Simulations to Investigate the Impact of N6-Methylation in RNA Recognition: Improving Accuracy and Precision of Binding Free Energy Prediction

N6-Methyladenosine (m6A) is a prevalent RNA post-transcriptional modification that plays crucial roles in RNA stability, structural dynamics, and interactions with proteins. The YT521-B (YTH) family of proteins, which are notable m6A readers, functions through its highly conserved YTH domain. Recent structural investigations and molecular dynamics (MD) simulations have shed light on the mechanism of recognition of m6A by the YTHDC1 protein. Despite advancements, using MD to predict the stabilization induced by m6A on the free energy of binding between RNA and YTH proteins remains challenging due to inaccuracy of the employed force field and limited sampling. For instance, simulations often fail to sufficiently capture the hydration dynamics of the binding pocket. This study addresses these challenges through an innovative methodology that integrates metadynamics, alchemical simulations, and force-field refinement. Importantly, our research identifies hydration of the binding pocket as giving only a minor contribution to the binding free energy and emphasizes the critical importance of precisely tuning force-field parameters to experimental data. By employing a fitting strategy built on alchemical calculations, we refine the m6A partial charge parameters, thereby enabling the simultaneous reproduction of N6 methylation on both the protein binding free energy and the thermodynamic stability of nine RNA duplexes. Our findings underscore the sensitivity of binding free energies to partial charges, highlighting the necessity for thorough parametrization and validation against experimental observations across a range of structural contexts.

Utilizing extracellular vesicles as a drug delivery system in glaucoma and RGC degeneration

Retinal diseases are the leading cause of blindness, resulting in irreversible degeneration and death of retinal neurons. One such cell type, the retinal ganglion cell (RGC), is responsible for connecting the retina to the rest of the brain through its axons that make up the optic nerve and is the primary cell lost in glaucoma and traumatic optic neuropathy. To date, different therapeutic strategies have been investigated to protect RGCs from death and preserve vision, yet currently available strategies are restricted to treating neuron loss by reducing intraocular pressure. A major barrier identified by these studies is drug delivery to RGCs, which is in large part due to drug stability, short duration time at target, low delivery efficiency, and undesired off-target effects. Therefore, a delivery system to deal with these problems is needed to ensure maximum benefit from the candidate therapeutic material. Extracellular vesicles (EV), nanocarriers released by all cells, are lipid membranes encapsulating RNAs, proteins, and lipids. As they naturally shuttle these encapsulated compounds between cells for communicative purposes, they may be exploitable and offer opportunities to overcome hurdles in retinal drug delivery, including drug stability, drug molecular weight, barriers in the retina, and drug adverse effects. Here, we summarize the potential of an EV drug delivery system, discussing their superiorities and potential application to target RGCs.

Structural dynamics of therapeutic nucleic acids with phosphorothioate backbone modifications

Antisense oligonucleotides (ASOs) offer ground-breaking possibilities for selective pharmacological intervention for any gene product-related disease. Therapeutic ASOs contain extensive chemical modifications that improve stability to enzymatic cleavage and modulate binding affinity relative to natural RNA/DNA. Molecular dynamics (MD) simulation can provide valuable insights into how such modifications affect ASO conformational sampling and target binding. However, force field parameters for chemically modified nucleic acids (NAs) are still underdeveloped. To bridge this gap, we developed parameters to allow simulations of ASOs with the widely applied phosphorothioate (PS) backbone modification, and validated these in extensive all-atom MD simulations of relevant PS-modified NA systems representing B-DNA, RNA, and DNA/RNA hybrid duplex structures. Compared to the corresponding natural NAs, single PS substitutions had marginal effects on the ordered DNA/RNA duplex, whereas substantial effects of phosphorothioation were observed in single-stranded RNA and B-DNA, corroborated by the experimentally derived structure data. We find that PS-modified NAs shift between high and low twist states, which could affect target recognition and protein interactions for phosphorothioated oligonucleotides. Furthermore, conformational sampling was markedly altered in the PS-modified ssRNA system compared to that of the natural oligonucleotide, indicating sequence-dependent effects on conformational preference that may in turn influence duplex formation.

Adenine Methylation Enhances the Conformational Flexibility of an RNA Hairpin Tetraloop

The N6-methyladenosine modification is one of the most abundant post-transcriptional modifications in ribonucleic acid (RNA) molecules. Using molecular dynamics simulations and alchemical free-energy calculations, we studied the structural and energetic implications of incorporating this modification in an adenine mononucleotide and an RNA hairpin structure. At the mononucleotide level, we found that the syn configuration is more favorable than the anti configuration by 2.05 ± 0.15 kcal/mol. The unfavorable effect of methylation was due to the steric overlap between the methyl group and a nitrogen atom in the purine ring. We then probed the effect of methylation in an RNA hairpin structure containing an AUCG tetraloop, which is recognized by a "reader" protein (YTHDC1) to promote transcriptional silencing of long noncoding RNAs. While methylation had no significant conformational effect on the hairpin stem, the methylated tetraloop showed enhanced conformational flexibility compared to the unmethylated tetraloop. The increased flexibility was associated with the outward flipping of two bases (A6 and U7) which formed stacking interactions with each other and with the C8 and G9 bases in the tetraloop, leading to a conformation similar to that in the RNA/reader protein complex. Therefore, methylation-induced conformational flexibility likely facilitates RNA recognition by the reader protein.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Tailor made: the art of therapeutic mRNA design

mRNA medicine is a new and rapidly developing field in which the delivery of genetic information in the form of mRNA is used to direct therapeutic protein production in humans. This approach, which allows for the quick and efficient identification and optimization of drug candidates for both large populations and individual patients, has the potential to revolutionize the way we prevent and treat disease. A key feature of mRNA medicines is their high degree of designability, although the design choices involved are complex. Maximizing the production of therapeutic proteins from mRNA medicines requires a thorough understanding of how nucleotide sequence, nucleotide modification and RNA structure interplay to affect translational efficiency and mRNA stability. In this Review, we describe the principles that underlie the physical stability and biological activity of mRNA and emphasize their relevance to the myriad considerations that factor into therapeutic mRNA design.