Unveil cis-acting combinatorial mRNA motifs by interpreting deep neural network.

SUMMARY: Cis-acting mRNA elements play a key role in the regulation of mRNA stability and translation efficiency. Revealing the interactions of these elements and their impact plays a crucial role in understanding the regulation of the mRNA translation process, which supports the development of mRNA-based medicine or vaccines. Deep neural networks (DNN) can learn complex cis-regulatory codes from RNA sequences. However, extracting these cis-regulatory codes efficiently from DNN remains a significant challenge. Here, we propose a method based on our toolkit NeuronMotif and motif mutagenesis, which not only enables the discovery of diverse and high-quality motifs but also efficiently reveals motif interactions. By interpreting deep-learning models, we have discovered several crucial motifs that impact mRNA translation efficiency and stability, as well as some unknown motifs or motif syntax, offering novel insights for biologists. Furthermore, we note that it is challenging to enrich motif syntax in datasets composed of randomly generated sequences, and they may not contain sufficient biological signals. AVAILABILITY AND IMPLEMENTATION: The source code and data used to produce the results and analyses presented in this manuscript are available from GitHub (https://github.com/WangLabTHU/combmotif).

Structural basis of the monkeypox virus mRNA cap N7 methyltransferase complex.

The global outbreak of Mpox, caused by the monkeypox virus (MPXV), has attracted international attention and become another major infectious disease event after COVID-19. The mRNA cap N7 methyltransferase (RNMT) of MPXV methylates the N7 position of the added guanosine to the 5'-cap structure of mRNAs and plays a vital role in evading host antiviral immunity. MPXV RNMT is composed of the large subunit E1 and the small subunit E12. How E1 and E12 of MPXV assembly remains unclear. Here, we report the crystal structures of E12, the MTase domain of E1 with E12 (E1CTD-E12) complex, and the E1CTD-E12-SAM ternary complex, revealing the detailed conformations of critical residues and the structural changes upon E12 binding to E1. Functional studies suggest that E1CTD N-terminal extension (Asp545-Arg562) and the small subunit E12 play an essential role in the binding process of SAM. Structural comparison of the AlphaFold2-predicted E1, E1CTD-E12 complex, and the homologous D1-D12 complex of vaccinia virus (VACV) indicates an allosteric activating effect of E1 in MPXV. Our findings provide the structural basis for the MTase activity stimulation of the E1-E12 complex and suggest a potential interface for screening the anti-poxvirus inhibitors.

Silk-gelatin hybrid hydrogel: a potential carrier for RNA therapeutics.

RNA-based therapeutics have exhibited remarkable potential in targeting genetic factors for disease intervention, exemplified by recent mRNA vaccines for COVID-19. Nevertheless, the intrinsic instability of RNA and challenges related to its translational efficiency remain significant obstacles to the development of RNA as therapeutics. This study introduces an innovative RNA delivery approach using a silk fibroin (SF) and positively charged gelatin (Gel) hydrogel matrix to enhance RNA stability for controlled release. As a proof of concept, whole-cell RNA was incorporated into the hydrogel to enhance interactions with RNA molecules. Additionally, molecular modeling studies were conducted to explore the interactions between SF, collagen, chitosan (Chi), and the various RNA species including ribosomal RNAs (28S, 18S, 8.5S, and 5S rRNAs), transfer RNAs (tRNA-ALA, tRNA-GLN, and tRNA-Leu), as well as messenger RNAs (mRNA-GAPDH, mRNA-ß actin, and mRNA-Nanog), shedding light on the RNA-polymer interaction and RNA stability; SF exhibits a more robust interaction with RNA compared to collagen/gel and chitosan. We confirmed the molecular interactions of SF and RNA by FTIR and Raman spectroscopy, which were further supported by AFM and contact angle measurement. This research introduces a novel RNA delivery platform and insights into biopolymer-RNA interactions, paving the way for tailored RNA delivery systems in therapeutics and biomedical applications.

Optimizing Messenger RNA Analysis Using Ultra-Wide Pore Size Exclusion Chromatography Columns.

Biopharmaceutical products, in particular messenger ribonucleic acid (mRNA), have the potential to dramatically improve the quality of life for patients suffering from respiratory and infectious diseases, rare genetic disorders, and cancer. However, the quality and safety of such products are particularly critical for patients and require close scrutiny. Key product-related impurities, such as fragments and aggregates, among others, can significantly reduce the efficacy of mRNA therapies. In the present work, the possibilities offered by size exclusion chromatography (SEC) for the characterization of mRNA samples were explored using state-of-the-art ultra-wide pore columns with average pore diameters of 1000 and 2500 Å. Our investigation shows that a column with 1000 Å pores proved to be optimal for the analysis of mRNA products, whatever the size between 500 and 5000 nucleotides (nt). We also studied the influence of mobile phase composition and found that the addition of 10 mM magnesium chloride (MgCl2) can be beneficial in improving the resolution and recovery of large size variants for some mRNA samples. We demonstrate that caution should be exercised when increasing column length or decreasing the flow rate. While these adjustments slightly improve resolution, they also lead to an apparent increase in the amount of low-molecular-weight species (LMWS) and monomer peak tailing, which can be attributed to the prolonged residence time inside the column. Finally, our optimal SEC method has been successfully applied to a wide range of mRNA products, ranging from 1000 to 4500 nt in length, as well as mRNA from different suppliers and stressed/unstressed samples.

A bisulfite-assisted and ligation-based qPCR amplification technology for locus-specific pseudouridine detection at base resolution.

Over 150 types of chemical modifications have been identified in RNA to date, with pseudouridine (Ψ) being one of the most prevalent modifications in RNA. Ψ plays vital roles in various biological processes, and precise, base-resolution detection methods are fundamental for deep analysis of its distribution and function. In this study, we introduced a novel base-resolution Ψ detection method named pseU-TRACE. pseU-TRACE relied on the fact that RNA containing Ψ underwent a base deletion after treatment of bisulfite (BS) during reverse transcription, which enabled efficient ligation of two probes complementary to the cDNA sequence on either side of the Ψ site and successful amplification in subsequent real-time quantitative PCR (qPCR), thereby achieving selective and accurate Ψ detection. Our method accurately and sensitively detected several known Ψ sites in 28S, 18S, 5.8S, and even mRNA. Moreover, pseU-TRACE could be employed to measure the Ψ fraction in RNA and explore the Ψ metabolism of different pseudouridine synthases (PUSs), providing valuable insights into the function of Ψ. Overall, pseU-TRACE represents a reliable, time-efficient and sensitive Ψ detection method.

Deep Learning for Elucidating Modifications to RNA-Status and Challenges Ahead.

RNA-binding proteins and chemical modifications to RNA play vital roles in the co- and post-transcriptional regulation of genes. In order to fully decipher their biological roles, it is an essential task to catalogue their precise target locations along with their preferred contexts and sequence-based determinants. Recently, deep learning approaches have significantly advanced in this field. These methods can predict the presence or absence of modification at specific genomic regions based on diverse features, particularly sequence and secondary structure, allowing us to decipher the highly non-linear sequence patterns and structures that underlie site preferences. This article provides an overview of how deep learning is being applied to this area, with a particular focus on the problem of mRNA-RBP binding, while also considering other types of chemical modification to RNA. It discusses how different types of model can handle sequence-based and/or secondary-structure-based inputs, the process of model training, including choice of negative regions and separating sets for testing and training, and offers recommendations for developing biologically relevant models. Finally, it highlights four key areas that are crucial for advancing the field.

Kinetics of programmed and spontaneous ribosome sliding along the mRNA.

The ribosome can slide along mRNA without establishing codon-anticodon interactions. This movement can be regulated (programmed) by the elements encoded in the mRNA, as observed in bypassing of non-coding gap in gene 60 of bacteriophage T4, or occur spontaneously, such as during traversal by the 70S ribosome of the 3'UTRs or upon re-initiation on bacterial polycistronic genes. In this study, we investigate the kinetic mechanism underlying the programmed and spontaneous ribosome sliding. We show that the translation rate of gene 60 mRNA decreases as the ribosome approaches the take-off site, especially when the KKYK regulatory sequence in the nascent peptide reaches the constriction site in the ribosome exit tunnel. However, efficiency of bypassing increases when the ribosome traverses the gap quickly. With the non-coding gap exceeding the natural 50 nt, the processivity of sliding remains high up to 56 nt, but drops sharply beyond that due to the loss of mRNA elements support. Sliding efficiency is temperature-dependent; while temperature regulates the number of ribosomes initiating programmed bypassing, traversing the long gaps becomes increasingly unfavorable at lower temperatures. This data offers novel insights into the kinetic determinants of programmed and spontaneous ribosome sliding along the mRNA.

A new mRNA structure prediction based approach to identifying improved signal peptides for bone morphogenetic protein 2.

BACKGROUND: Signal peptide (SP) engineering has proven able to improve production of many proteins yet is a laborious process that still relies on trial and error. mRNA structure around the translational start site is important in translation initiation and has rarely been considered in this context, with recent improvements in in silico mRNA structure potentially rendering it a useful predictive tool for SP selection. Here we attempt to create a method to systematically screen candidate signal peptide sequences in silico based on both their nucleotide and amino acid sequences. Several recently released computational tools were used to predict signal peptide activity (SignalP), localization target (DeepLoc) and predicted mRNA structure (MXFold2). The method was tested with Bone Morphogenetic Protein 2 (BMP2), an osteogenic growth factor used clinically for bone regeneration. It was hoped more effective BMP2 SPs could improve BMP2-based gene therapies and reduce the cost of recombinant BMP2 production. RESULTS: Amino acid sequence analysis indicated 2,611 SPs from the TGF-ß superfamily were predicted to function when attached to BMP2. mRNA structure prediction indicated structures at the translational start site were likely highly variable. The five sequences with the most accessible translational start sites, a codon optimized BMP2 SP variant and the well-established hIL2 SP sequence were taken forward to in vitro testing. The top five candidates showed non-significant improvements in BMP2 secretion in HEK293T cells. All showed reductions in secretion versus the native sequence in C2C12 cells, with several showing large and significant decreases. None of the tested sequences were able to increase alkaline phosphatase activity above background in C2C12s. The codon optimized control sequence and hIL2 SP showed reasonable activity in HEK293T but very poor activity in C2C12. CONCLUSIONS: These results support the use of peptide sequence based in silico tools for basic predictions around signal peptide activity in a synthetic biology context. However, mRNA structure prediction requires improvement before it can produce reliable predictions for this application. The poor activity of the codon optimized BMP2 SP variant in C2C12 emphasizes the importance of codon choice, mRNA structure, and cellular context for SP activity.

The mechanical properties of lipid nanoparticles depend on the type of biomacromolecule they are loaded with.

For drug delivery systems, the mechanical properties of drug carriers are suspected to play a crucial role in the delivery process. However, there is a lack of reliable methods available to measure the mechanical properties of drug carriers, which hampers the establishment of a link between delivery efficiency and the mechanical properties of carriers. Lipid nanoparticles (LNPs) are advanced systems for delivering nucleic acids to target cell populations for vaccination purposes (mRNA) or the development of new drugs. Hence, it is crucial to develop reliable techniques to measure the mechanical properties of LNPs. In this article, we used AFM to image and probe the mechanical properties of LNPs which are loaded with two different biopolymers either pDNA or mRNA. Imaging the LNPs before and after indentation, as well as recording the retraction curve, enables us to obtain more insight into how the AFM tip penetrates into the particle and to determine whether the deformation of the LNPs is reversible. For pDNA, the indentation by the tip leads to irreversible rupture of the LNPs, while the deformation is reversible for the mRNA-loaded LNPs. Moreover, the forces reached for pDNA are higher than for mRNA. These results pave the way toward the establishment of the link between the LNP formulation and the delivery efficiency.

Organ- and Cell-Selective Delivery of mRNA In Vivo Using Guanidinylated Serinol Charge-Altering Releasable Transporters.

Selective RNA delivery is required for the broad implementation of RNA clinical applications, including prophylactic and therapeutic vaccinations, immunotherapies for cancer, and genome editing. Current polyanion delivery relies heavily on cationic amines, while cationic guanidinium systems have received limited attention due in part to their strong polyanion association, which impedes intracellular polyanion release. Here, we disclose a general solution to this problem in which cationic guanidinium groups are used to form stable RNA complexes upon formulation but at physiological pH undergo a novel charge-neutralization process, resulting in RNA release. This new delivery system consists of guanidinylated serinol moieties incorporated into a charge-altering releasable transporter (GSer-CARTs). Significantly, systematic variations in structure and formulation resulted in GSer-CARTs that exhibit highly selective mRNA delivery to the lung (∼97%) and spleen (∼98%) without targeting ligands. Illustrative of their breadth and translational potential, GSer-CARTs deliver circRNA, providing the basis for a cancer vaccination strategy, which in a murine model resulted in antigen-specific immune responses and effective suppression of established tumors.

Programmable RNA Loading of Extracellular Vesicles with Toehold-Release Purification.

Synthetic nanoparticles as lipid nanoparticles (LNPs) are widely used as drug delivery vesicles. However, they hold several drawbacks, including low biocompatibility and unfavorable immune responses. Naturally occurring extracellular vesicles (EVs) hold the potential as native, safe, and multifunctional nanovesicle carriers. However, loading of EVs with large biomolecules remains a challenge. Here, we present a controlled loading methodology using DNA-mediated and programmed fusion between EVs and messenger RNA (mRNA)-loaded liposomes. The fusion efficiency is characterized at the single-particle level by real-time microscopy through EV surface immobilization via lipidated biotin-DNA handles. Subsequently, fused EV-liposome particles (EVLs) can be collected by employing a DNA strand-replacement reaction. Transferring the fusion reaction to magnetic beads enables us to scale up the production of EVLs one million times. Finally, we demonstrated encapsulation of mCherry mRNA, transfection, and improved translation using the EVLs compared to liposomes or LNPs in HEK293-H cells. We envision this as an important tool for the EV-mediated delivery of RNA therapeutics.

Data-balanced transformer for accelerated ionizable lipid nanoparticles screening in mRNA delivery.

Despite the widespread use of ionizable lipid nanoparticles (LNPs) in clinical applications for messenger RNA (mRNA) delivery, the mRNA drug delivery system faces an efficient challenge in the screening of LNPs. Traditional screening methods often require a substantial amount of experimental time and incur high research and development costs. To accelerate the early development stage of LNPs, we propose TransLNP, a transformer-based transfection prediction model designed to aid in the selection of LNPs for mRNA drug delivery systems. TransLNP uses two types of molecular information to perceive the relationship between structure and transfection efficiency: coarse-grained atomic sequence information and fine-grained atomic spatial relationship information. Due to the scarcity of existing LNPs experimental data, we find that pretraining the molecular model is crucial for better understanding the task of predicting LNPs properties, which is achieved through reconstructing atomic 3D coordinates and masking atom predictions. In addition, the issue of data imbalance is particularly prominent in the real-world exploration of LNPs. We introduce the BalMol block to solve this problem by smoothing the distribution of labels and molecular features. Our approach outperforms state-of-the-art works in transfection property prediction under both random and scaffold data splitting. Additionally, we establish a relationship between molecular structural similarity and transfection differences, selecting 4267 pairs of molecular transfection cliffs, which are pairs of molecules that exhibit high structural similarity but significant differences in transfection efficiency, thereby revealing the primary source of prediction errors. The code, model and data are made publicly available at https://github.com/wklix/TransLNP.

Silicon Ether Ionizable Lipids Enable Potent mRNA Lipid Nanoparticles with Rapid Tissue Clearance.

The advent of mRNA for nucleic acid (NA) therapeutics has unlocked many diverse areas of research and clinical investigation. However, the shorter intracellular half-life of mRNA compared with other NAs may necessitate more frequent dosing regimens. Because lipid nanoparticles (LNPs) are the principal delivery system used for mRNA, this could lead to tolerability challenges associated with an accumulated lipid burden. This can be addressed by introducing enzymatically cleaved carboxylic esters into the hydrophobic domains of lipid components, notably, the ionizable lipid. However, enzymatic activity can vary significantly with age, disease state, and species, potentially limiting the application in humans. Here we report an alternative approach to ionizable lipid degradability that relies on nonenzymatic hydrolysis, leading to a controlled and highly efficient lipid clearance profile. We identify highly potent examples and demonstrate their exceptional tolerability in multiple preclinical species, including multidosing in nonhuman primates (NHP).

Elucidating Structural Configuration of Lipid Assemblies for mRNA Delivery Systems.

The development of mRNA delivery systems utilizing lipid-based assemblies holds immense potential for precise control of gene expression and targeted therapeutic interventions. Despite advancements in lipid-based gene delivery systems, a critical knowledge gap remains in understanding how the biophysical characteristics of lipid assemblies and mRNA complexes influence these systems. Herein, we investigate the biophysical properties of cationic liposomes and their role in shaping mRNA lipoplexes by comparing various fabrication methods. Notably, an innovative fabrication technique called the liposome under cryo-assembly (LUCA) cycle, involving a precisely controlled freeze-thaw-vortex process, produces distinctive onion-like concentric multilamellar structures in cationic DOTAP/DOPE liposomes, in contrast to a conventional extrusion method that yields unilamellar liposomes. The inclusion of short-chain DHPC lipids further modulates the structure of cationic liposomes, transforming them from multilamellar to unilamellar structures during the LUCA cycle. Furthermore, the biophysical and biological evaluations of mRNA lipoplexes unveil that the optimal N/P charge ratio in the lipoplex can vary depending on the structure of initial cationic liposomes. Cryo-EM structural analysis demonstrates that multilamellar cationic liposomes induce two distinct interlamellar spacings in cationic lipoplexes, emphasizing the significant impact of the liposome structures on the final structure of mRNA lipoplexes. Taken together, our results provide an intriguing insight into the relationship between lipid assembly structures and the biophysical characteristics of the resulting lipoplexes. These relationships may open the door for advancing lipid-based mRNA delivery systems through more streamlined manufacturing processes.

Unearthing a novel function of SRSF1 in binding and unfolding of RNA G-quadruplexes.

SRSF1 governs splicing of over 1500 mRNA transcripts. SRSF1 contains two RNA-recognition motifs (RRMs) and a C-terminal Arg/Ser-rich region (RS). It has been thought that SRSF1 RRMs exclusively recognize single-stranded exonic splicing enhancers, while RS lacks RNA-binding specificity. With our success in solving the insolubility problem of SRSF1, we can explore the unknown RNA-binding landscape of SRSF1. We find that SRSF1 RS prefers purine over pyrimidine. Moreover, SRSF1 binds to the G-quadruplex (GQ) from the ARPC2 mRNA, with both RRMs and RS being crucial. Our binding assays show that the traditional RNA-binding sites on the RRM tandem and the Arg in RS are responsible for GQ binding. Interestingly, our FRET and circular dichroism data reveal that SRSF1 unfolds the ARPC2 GQ, with RS leading unfolding and RRMs aiding. Our saturation transfer difference NMR results discover that Arg residues in SRSF1 RS interact with the guanine base but not other nucleobases, underscoring the uniqueness of the Arg/guanine interaction. Our luciferase assays confirm that SRSF1 can alleviate the inhibitory effect of GQ on gene expression in the cell. Given the prevalence of RNA GQ and SR proteins, our findings unveil unexplored SR protein functions with broad implications in RNA splicing and translation.

Protein G-quadruplex interactions and their effects on phase transitions and protein aggregation.

The SERF family of proteins were originally discovered for their ability to accelerate amyloid formation. Znf706 is an uncharacterized protein whose N-terminus is homologous to SERF proteins. We show here that human Znf706 can promote protein aggregation and amyloid formation. Unexpectedly, Znf706 specifically interacts with stable, non-canonical nucleic acid structures known as G-quadruplexes. G-quadruplexes can affect gene regulation and suppress protein aggregation; however, it is unknown if and how these two activities are linked. We find Znf706 binds preferentially to parallel G-quadruplexes with low micromolar affinity, primarily using its N-terminus, and upon interaction, its dynamics are constrained. G-quadruplex binding suppresses Znf706's ability to promote protein aggregation. Znf706 in conjunction with G-quadruplexes therefore may play a role in regulating protein folding. RNAseq analysis shows that Znf706 depletion specifically impacts the mRNA abundance of genes that are predicted to contain high G-quadruplex density. Our studies give insight into how proteins and G-quadruplexes interact, and how these interactions affect both partners and lead to the modulation of protein aggregation and cellular mRNA levels. These observations suggest that the SERF family of proteins, in conjunction with G-quadruplexes, may have a broader role in regulating protein folding and gene expression than previously appreciated.

G-Clamp Heterocycle Modification Containing Interstrand Photo-Cross-Linker to Capture Intracellular MicroRNA Targets.

MicroRNAs (miRNAs) play indispensable roles in post-transcriptional gene regulation. The identification of target mRNAs is essential for dissecting the recognition basis, dynamics, and regulatory mechanism of miRNA-mRNA interactions. However, the lack of an unbiased method for detecting weak miRNA-mRNA interactions remains a long-standing obstacle for miRNA research. Here, we develop and provide proof-of-concept evidence demonstrating a chemical G-clamp-enhanced photo-cross-linking strategy for covalent capture of intracellular miRNA targets in different cell lines. This approach relies on an aryl-diazirine-G-clamp-modified-nucleoside (ARAGON) miRNA probe containing an alkynyl group that improves the thermal stability of miRNA-target mRNA duplex molecules and can rapidly cross-link with the complementary strand upon UV 365 nm activation, enhancing the transient capture of mRNA targets. After validating the accuracy and binding properties of ARAGON-based miRNA probes through the successful enrichment for the known targets of miR-106a, miR-21, and miR-101, we then extend ARAGON's application to screen for previously unknown targets of different miRNAs in various cell lines. Ultimately, results in this study uncover GAB1 as a target of miR-101 in H1299 lung cancer cells and show that miR-101 silencing of GAB1 can promote apoptosis in H1299 cells, suggesting an oncogenic mechanism of GAB1. This study thus provides a powerful and versatile tool for enhanced screening of global miRNA targets in cells to facilitate investigations of miRNA functions in fundamental cellular processes and disease pathogenesis.

Supramolecular Lipid Nanoparticles Based on Host-Guest Recognition: A New Generation Delivery System of mRNA Vaccines For Cancer Immunotherapy.

Dendritic cell (DC) maturation is a crucial process for antigen presentation and the initiation of T cell-mediated immune responses. Toll-like receptors play pivotal roles in stimulating DC maturation and promoting antigen presentation. Here, a novel message RNA (mRNA) cancer vaccine is reported that boosts antitumor efficacy by codelivering an mRNA encoding tumor antigen and a TLR7/8 agonist (R848) to DC using supramolecular lipid nanoparticles (SMLNP) as a delivery platform, in which a new ionizable lipid (N2-3L) remarkably enhances the translation efficiency of mRNA and a ß-cyclodextrin (ß-CD)-modified ionizable lipid (Lip-CD) encapsulates R848. The incorporation of R848 adjuvant into the mRNA vaccine through noncovalent host-guest complexation significantly promotes DC maturation and antigen presentation after vaccination, thus resulting in superior antitumor efficacy in vivo. Moreover, the antitumor efficacy is further boosted synergized with immune checkpoint blockade by potentiating the anticancer capability of cytotoxic T lymphocytes infiltrated in tumor sites. This work indicates that SMLNP shows brilliant potential as next-generation delivery system in the development of mRNA vaccines with high efficacy.

Despite the odds: formation of the SARS-CoV-2 methylation complex.

Coronaviruses modify their single-stranded RNA genome with a methylated cap during replication to mimic the eukaryotic mRNAs. The capping process is initiated by several nonstructural proteins (nsp) encoded in the viral genome. The methylation is performed by two methyltransferases, nsp14 and nsp16, while nsp10 acts as a co-factor to both. Additionally, nsp14 carries an exonuclease domain which operates in the proofreading system during RNA replication of the viral genome. Both nsp14 and nsp16 were reported to independently bind nsp10, but the available structural information suggests that the concomitant interaction between these three proteins would be impossible due to steric clashes. Here, we show that nsp14, nsp10, and nsp16 can form a heterotrimer complex upon significant allosteric change. This interaction is expected to encourage the formation of mature capped viral mRNA, modulating nsp14's exonuclease activity, and protecting the viral RNA. Our findings show that nsp14 is amenable to allosteric regulation and may serve as a novel target for therapeutic approaches.

The RNA secondary structure of androgen receptor-FL and V7 transcripts reveals novel regulatory regions.

The androgen receptor (AR) is a ligand-dependent nuclear transcription factor belonging to the steroid hormone nuclear receptor family. Due to its roles in regulating cell proliferation and differentiation, AR is tightly regulated to maintain proper levels of itself and the many genes it controls. AR dysregulation is a driver of many human diseases including prostate cancer. Though this dysregulation often occurs at the RNA level, there are many unknowns surrounding post-transcriptional regulation of AR mRNA, particularly the role that RNA secondary structure plays. Thus, a comprehensive analysis of AR transcript secondary structure is needed. We address this through the computational and experimental analyses of two key isoforms, full length (AR-FL) and truncated (AR-V7). Here, a combination of in-cell RNA secondary structure probing experiments (targeted DMS-MaPseq) and computational predictions were used to characterize the static structural landscape and conformational dynamics of both isoforms. Additionally, in-cell assays were used to identify functionally relevant structures in the 5' and 3' UTRs of AR-FL. A notable example is a conserved stem loop structure in the 5'UTR of AR-FL that can bind to Poly(RC) Binding Protein 2 (PCBP2). Taken together, our results reveal novel features that regulate AR expression.