What makes ASOs so attractive compared with conventional small-molecule drugs and monoclonal antibodies is their programmability. Because they bind their targets through straightforward Watson–Crick base pairing, researchers can in principle design a molecule against almost any RNA sequence with high specificity, relatively simple synthesis, and reproducible manufacturing. Unlike small molecules, which must find a pocket on a protein surface, ASOs target RNA directly, offering a route to diseases long considered undruggable. The review emphasizes that this specificity, combined with chemical modifications that improve stability and cellular uptake, positions ASOs as a leading platform for personalized therapies, particularly for rare genetic disorders where no other treatment options exist.

At their core, ASOs are chains of nucleotides joined by phosphodiester bonds, but unmodified DNA degrades rapidly in the body. The field has therefore developed successive generations of chemical modifications. First-generation phosphorothioate backbones replace a non-bridging oxygen atom with sulfur, conferring nuclease resistance and a longer plasma half-life, though sometimes at the cost of pro-inflammatory side effects. Second-generation chemistry adds 2′-O-methyl or 2′-O-methoxyethyl sugar modifications, and chimeric gapmer designs combine a central DNA region capable of recruiting RNase H with modified flanks that resist degradation. Third-generation chemistries, including locked nucleic acids and phosphorodiamidate morpholino oligomers, push binding affinity and stability even further, though each comes with its own trade-offs in uptake and mechanism.

The review details three principal modes of action. In RNase H1-mediated silencing, the ASO forms a DNA–RNA hybrid with its target messenger RNA, and the enzyme RNase H1 recognizes that hybrid and cleaves the RNA strand, destroying the transcript and halting protein synthesis. In splice modulation, ASOs bind pre-mRNA regulatory sequences to correct abnormal exon inclusion or exclusion; the approved drug nusinersen uses this strategy in spinal muscular atrophy by promoting inclusion of exon 7 in the SMN2 transcript, while eteplirsen induces exon skipping in Duchenne muscular dystrophy to restore the dystrophin reading frame. Finally, steric block ASOs physically obstruct ribosomes or RNA-binding proteins without triggering degradation, offering a gentler way to tune gene expression. The authors contrast ASOs with small interfering RNAs, noting that siRNAs are double-stranded molecules that operate through the RNA-induced silencing complex and Argonaute cleavage, and that studies such as Bilanges and Stokoe’s comparison of PDK1 knockdown show the two platforms produce distinct transcriptional consequences.

Designing an effective ASO is a multi-parameter optimization problem, and this is where computational tools earn their keep. The review lays out the critical design variables: oligonucleotide length, typically 15 to 25 nucleotides; GC content between 40 and 60 percent to balance hybrid stability against overly tight, nonspecific binding; binding energy of roughly −8 kcal/mol or better; minimal cross-reactivity with other transcripts; and careful target-site selection that accounts for mRNA accessibility. Regions of RNA buried inside stable stems or hairpins are poor targets, whereas loops and bulges expose nucleotides for hybridization. Thermodynamic parameters such as melting temperature determine whether the ASO–mRNA duplex survives physiological conditions, and secondary structure prediction helps designers avoid oligos that fold onto themselves and lose their intended activity.

Several dedicated software platforms now support this workflow. Sfold uses statistical RNA folding to evaluate target-site accessibility, making it a workhorse for general ASO design. PFRED offers a user-friendly computational platform for both siRNA and antisense design, integrating stability and potency parameters. ASOptimizer applies deep learning to minimize off-target effects and cytotoxicity, as demonstrated in work on IDO1 gene regulation. lncASO brings machine learning to the special case of long non-coding RNA targets, while OptiRNAi and siExplorer serve the RNA interference community. High-throughput bioinformatics pipelines built around these tools can screen hundreds of candidate sequences in silico, ranking them by melting temperature, hybridization efficiency, and predicted off-target interactions, dramatically reducing the cost and labor of experimental screening.

Structural prediction remains the hardest computational problem. Unlike proteins, where decades of experimental data have enabled powerful folding models, single-stranded DNA adopts a bewildering variety of conformations, including hairpins, bulges, and G-quadruplexes, and its polyanionic character is strongly influenced by metal ions. The review highlights a workflow proposed by Jeddi and Saiz that repurposes RNA 3D prediction tools for ssDNA: predict the DNA secondary structure, model the corresponding ssRNA tertiary structure, then convert ribose to deoxyribose and uracil to thymine. Tools such as Mfold, RNAfold from the Vienna RNA WebSuite, CentroidFold, RNAstructure, and KineFold handle secondary structure prediction with complementary thermodynamic and centroid-based approaches, while RNA Composer builds large RNA 3D models from secondary structure information. Conversion utilities like PyMOL, ChimeraX, 3DNA, and the authors’ own RNA2DNA script then translate RNA structures into their DNA counterparts.

Downstream, molecular docking platforms such as HADDOCK, HDOCK, and HNADOCK can generate structural hypotheses for ASO–protein interactions, and molecular dynamics engines like Schrödinger’s DESMOND and GROMACS simulate how ASO–target complexes behave over time under biological conditions. The review is careful to note the caveats: docking scores for flexible, chemically modified single-stranded oligonucleotides should be treated as hypothesis-generating rather than definitive, and experimental validation through biochemical binding assays, crosslinking–mass spectrometry, or high-resolution structural methods remains essential. Current in silico models also struggle with non-canonical base pairing such as pseudoknots and G-quadruplexes, with the dynamic role of RNA-binding proteins, and with cellular environmental factors like ionic conditions and competing endogenous RNAs, all of which can shift ASO behavior away from computational predictions.

The clinical track record justifies the investment. Fomivirsen (Vitravene) became the first FDA-approved ASO in 1998 for cytomegalovirus retinitis, followed by mipomersen (Kynamro) for homozygous familial hypercholesterolemia in 2013. Nusinersen (Spinraza) transformed the outlook for spinal muscular atrophy, inotersen (Tegsedi) treats hereditary transthyretin-mediated amyloidosis, and the exon-skipping drugs eteplirsen and golodirsen address Duchenne muscular dystrophy. Each success rests on the same triad of rational sequence design, protective chemical modification, and delivery engineering, whether through lipid nanoparticles, polymeric carriers, cell-penetrating peptides, or GalNAc conjugates that home in on hepatocytes. The review argues that integrating computational screening with cell-based assays, exon-skipping experiments, high-throughput sequencing, and RNA immunoprecipitation creates a hybrid pipeline that narrows the design space before any expensive laboratory work begins.

The authors conclude that in silico approaches are now unavoidable in ASO development, offering speed, cost savings, and accuracy that no purely experimental campaign can match, while cautioning that computational predictions will never fully capture biological complexity on their own. Future progress, they suggest, depends on feeding high-resolution experimental data from cryo-electron microscopy, X-ray crystallography, and small-angle X-ray scattering back into predictive models, and on developing algorithms that handle non-canonical structures and dynamic protein–RNA interactions. As ASO platforms expand beyond rare genetic diseases into oncology, infectious disease, and neurodegeneration, the fusion of next-generation computational design with rigorous experimental validation is expected to accelerate the arrival of safer, more specific, and more personalized gene-silencing medicines.

Subject of Research: Computational design and engineering of antisense oligonucleotide therapeutics

Article Title: Silencing with precision: In silico strategies for antisense oligonucleotide engineering

Article References: Nagaraj, A., Kavana, C. P., Harendra, B., Srinivasa, S., Dharmashekara, C., Kollur, S. P., Shreevatsa, B., & Shivamallu, C. (2026). Silencing with precision: In silico strategies for antisense oligonucleotide engineering. Molecular Biology Reports, 53(1), Article 1639. https://doi.org/10.1007/s11033-026-12635-8

Image Credits: AI Generated

DOI: 10.1007/s11033-026-12635-8

Keywords: antisense oligonucleotides, gene silencing, in silico drug design, RNase H1, splice modulation, molecular docking, molecular dynamics, RNA secondary structure, nucleic acid therapeutics, nusinersen, personalized medicine, machine learning

The stakes of this delivery problem are easy to appreciate when one considers the enzymes involved. Adenine base editors, first described by Gaudelli and colleagues in 2017, are programmable molecular machines that convert A•T base pairs to G•C in genomic DNA without making a double-strand break. Their precision and safety profile have made them attractive candidates for treating genetic disease, but they are encoded by messenger RNAs that are substantially longer than those used in early LNP applications. Cas9 messenger RNA itself already stretches the formulation envelope, and base editors push it further. When a delivery vehicle is asked to carry a transcript several kilobases long, the physics and chemistry of how lipids and RNA organize into a nanoparticle change in ways that conventional screening pipelines, which typically rely on short reporter RNAs, never register.

The clinical context sharpens the urgency. The pivotal trial by Frangoul and colleagues that produced the first approved CRISPR therapy for sickle cell disease and beta-thalassemia relied on ex vivo editing of harvested cells, sidestepping the delivery challenge entirely. In vivo editing is a different proposition. Gillmore and colleagues showed in a first-in-human trial that lipid nanoparticle-delivered CRISPR-Cas9 can edit the liver to treat transthyretin amyloidosis, and Rothgangl and colleagues demonstrated in macaques that LNP-based adenine base editing of PCSK9 can durably reduce LDL cholesterol. These landmark results prove that LNP-mediated in vivo editing works, but they also reveal how much of the therapeutic potential remains locked behind the efficiency ceiling of current formulations. Every incremental improvement in delivery translates into lower doses, reduced off-target exposure, and access to tissues beyond the liver.

Dong and colleagues approached the problem by asking a deceptively simple question: what happens to a lipid nanoparticle when the RNA inside it is the size of a gene editor’s transcript? The answer, revealed through structural characterization, is that the cargo is not a passive passenger. Large messenger RNAs alter how ionizable lipids and nucleic acids pack together, producing nanoparticles whose internal organization differs from those formed with short RNAs. Because the structure of an LNP governs its behavior in the body, particularly its ability to escape the endosome, the membrane-bound compartment that engulfs incoming particles after cellular uptake, a structurally compromised particle is a poorly functional one. Endosomal escape is widely regarded as the critical bottleneck in RNA delivery; only a small fraction of nanoparticles that enter a cell ever release their payload into the cytoplasm, where translation can begin.

Armed with this structural insight, the team built their screening strategy around the principle that the assay should match the application. Instead of evaluating candidate ionizable lipids with compact reporter RNAs, they screened formulations using a gene-editor-sized RNA, ensuring that the structural and functional properties being measured were those that would actually matter in a therapeutic context. This cargo-matched screening identified a lead ionizable lipid, designated LC-1, that had presumably been overlooked or underappreciated in conventional screens because its advantages only manifest when the RNA cargo is large.

The mechanistic payoff of LC-1 lies in endosomal escape. Structural analysis showed that LC-1-containing nanoparticles form an internal arrangement that enhances the release of large RNA payloads from endosomes, directly attacking the step that limits cytoplasmic delivery. This is a notable example of structure-guided formulation design: rather than treating the ionizable lipid as a tunable parameter optimized through iterative empirical variation, the study connects a specific lipid-dependent structural feature to a specific biological bottleneck, and then exploits that connection to select a superior candidate. The finding suggests that the field’s extensive libraries of ionizable lipids may contain many molecules whose true strengths and weaknesses are invisible unless they are tested with realistic cargo.

The functional consequences were validated across three tissues in mice. LC-1-based nanoparticles enabled efficient genome editing in the liver, the traditional stronghold of LNP delivery, but also in the lung and the brain, tissues that have historically been far more difficult targets for intravenously or systemically administered lipid nanoparticles. Achieving robust editing in the lung and brain hints at therapeutic applications that extend well beyond hepatology, from respiratory genetic diseases to central nervous system disorders, although the authors’ mouse data represent an early step on a long translational road. Tissue tropism in LNP delivery is governed by a complex interplay of particle properties, route of administration, and interactions with serum proteins, and the study’s title, which references both large RNA cargo optimization and tissue targeting, indicates that the formulation work was designed with this broader targeting problem in mind.

For the field, the most consequential message may be methodological. LNP development has historically been accelerated by combinatorial chemistry and high-throughput screening, approaches that generated the lipid libraries behind today’s clinical products. But if the performance of an ionizable lipid depends on the size of the RNA it carries, then screening campaigns built on small reporter RNAs may systematically misrank candidates for the applications that matter most, namely the delivery of long editor transcripts. The Dong study effectively establishes cargo-matched screening as a design principle: the RNA used in the assay should approximate the size and presumably the structural behavior of the therapeutic payload. This recalibration could redirect attention to existing lipids that were dismissed in earlier screens and could change how new libraries are evaluated.

The work also deepens a conceptual shift that has been gathering momentum in drug delivery research. Nanoparticles are increasingly understood not as inert shells but as self-assembled systems whose components, including the cargo itself, co-determine the final architecture and thus the biological performance. A several-kilobase messenger RNA is not merely a payload to be protected; it is a structural element of the particle, influencing lipid packing, internal morphology, and ultimately endosomal escape. Recognizing the cargo as a design variable opens a second axis of optimization alongside lipid chemistry: formulators can now think about matching vehicle to payload the way structural biologists think about matching ligand to binding pocket.

Cautious optimism is warranted. The reported results are preclinical, generated in mice, and the translation of LNP performance from rodents to humans has historically involved surprises in biodistribution, tolerability, and potency. Nevertheless, the study arrives at a moment when in vivo gene editing is transitioning from proof-of-concept to therapeutic platform, with liver-directed CRISPR therapies already tested in patients and base editors advancing through development for indications ranging from hypercholesterolemia to genetic blindness. Delivery efficiency is the variable that determines dose, safety margin, and tissue reach for all of these programs. By showing that cargo size matters, that structure explains why, and that a cargo-matched screen can find lipids like LC-1 that unlock efficient editing in liver, lung, and brain, the researchers have supplied the field with both a practical tool and a conceptual correction. The next generation of gene-editing medicines will likely be formulated not around generic nanoparticles, but around vehicles designed for the specific, oversized molecular machines they must deliver.

Subject of Research: Lipid nanoparticle design for delivery of large gene-editor mRNA cargo

Article Title: Cargo size matters when designing lipid nanoparticles for delivery of large gene editors

Article References: Cargo size matters when designing lipid nanoparticles for delivery of large gene editors. (2026). Nature Biotechnology. https://doi.org/10.1038/s41587-026-03297-9

Image Credits: AI Generated

DOI: 10.1038/s41587-026-03297-9

Keywords: lipid nanoparticles, gene editing, base editors, ionizable lipids, endosomal escape, mRNA delivery, LC-1, in vivo genome editing, drug delivery, nucleic acid therapeutics, tissue targeting, CRISPR

Pentavalent phosphorus (P(V)) chemistry has long been viewed as an alternative because it can, in principle, form nucleotide linkages without the repetitive oxidation routine. But earlier attempts struggled with practical chemistry: unstable intermediates, slow couplings, harsh deprotection conditions, and failures during chain elongation all prevented widespread replacement of P(III) strategies.

Now a team led by Associate Professor Noriko Saito-Tarashima at Tokushima University, working with doctoral researcher Nana Mihara, revisits the historical promise of P(V) chemistry using a modern design concept: stable nucleoside 3′-phosphorofluoridates (P(V)–F) as building blocks. Their study appears online on June 19, 2026, and is published in the Journal of the American Chemical Society (JACS), dated July 1, 2026.

The central idea is to remove oxidation from the cycle by using P(V)–F monomers that support neutral chain growth. This “oxidation-free” design targets three practical constraints at once: isolable, storage-stable monomers; coupling performance comparable to phosphoramidites; and reliable propagation of the growing oligonucleotide chain.

To make the approach work, the researchers activate the P(V)–F linkage with a silicon-based additive. By screening reaction bases and silicon-containing activators, they identify conditions that enable efficient dinucleotide formation. In a model system, the coupling yield reaches a quantitative level, indicating strong reactivity under synthetically practical conditions.

Speed matters as well: when benchmarked against standard P(III) phosphoramidite coupling, the P(V)–F system delivers faster assembly. That kinetic advantage suggests a path toward more efficient nucleotide cycles without sacrificing product quality.

Crucially, the method is not confined to solution-phase chemistry. The team adapts the P(V)–F coupling chemistry to automated solid-phase synthesis using a standard DNA/RNA synthesizer. Initial trials showed inconsistency, but targeted optimizations enabled successful automated oligonucleotide production—an essential step for real-world manufacturing.

Overall, the work positions P(V)–F as a complementary platform rather than a sudden replacement. By addressing oxidation overhead and improving robustness, the strategy could streamline the next generation of oligonucleotide manufacturing, accelerating research timelines and supporting future diagnostic and therapeutic pipelines.

Subject of Research: Oligonucleotide synthesis (chemical nucleic acid assembly)

Article Title: Nucleoside 3′-Phosphorofluoridates for P(V)-Based Oligonucleotide Synthesis

News Publication Date: 19-Jun-2026 (online availability); published 01-Jul-2026

Web References: https://pubs.acs.org/doi/10.1021/jacs.6c04623

References: DOI: 10.1021/jacs.6c04623

Image Credits: Credit: Associate Professor Noriko Saito-Tarashima from Tokushima University, Japan

Keywords: P(V) chemistry, oxidation-free synthesis, nucleoside 3′-phosphorofluoridates, oligonucleotides, silicon-mediated activation, automated solid-phase synthesis, phosphoramidite replacement, JACS

Rare diseases, defined by the European Medicines Agency as those affecting fewer than five in 10,000 individuals, cumulatively impact approximately 300 million people globally, with around 36 million patients in the European Union alone. Despite their widespread collective prevalence, the traditional pharmaceutical development pipeline, with its reliance on centralized production of mass-market drugs, fails to adequately serve this diverse and fragmented patient population. The immense costs and complex logistics of producing individualized gene therapies have historically restricted access, leaving a significant treatment gap. NANOSPRESSO seeks to overturn these limitations by decentralizing the production of nucleic acid nanomedicines, tailoring therapies to patients’ unique genetic aberrations within hospital settings.

At the core of NANOSPRESSO lies the fusion of two validated biomedical technologies: nucleic acid therapeutics, which leverage RNA or DNA molecules to selectively target malfunctioning genes, and lipid nanoparticles (LNPs), engineered nanocarriers optimized for delivering these fragile molecules safely into cells. By encapsulating the nucleic acids within lipid carriers, the device ensures protection from enzymatic degradation and facilitates precise biodistribution, enabling the therapeutic cargo to reach the intended cellular targets effectively. The system’s microfluidic design mimics the precision and convenience of espresso machines, employing cartridge-based inputs that hospital pharmacists can load with lipid formulations and patient-specific genetic sequences to fabricate sterile, injectable nanomedicines on site.

This paradigm-shifting technology holds particular promise for the treatment of rare genetic diseases, many of which manifest early in life and often lack approved therapies due to the prohibitive costs associated with individualized drug development. Unlike conventional manufacturing, which caters to high-volume production and fails to economically justify small-batch therapeutics, NANOSPRESSO’s compact footprint and streamlined process could enable tailored medicines to be produced at the point of care. Such democratization of gene therapy manufacturing might significantly alleviate the disparities in healthcare access, bridging the gap between advanced medical technologies and under-resourced clinics across the globe.

The biological underpinnings of nucleic acid therapies are pivotal to their versatility. These therapeutics work by modulating gene expression through specifically designed RNA or DNA sequences that can silence, correct, or replace faulty genetic instructions responsible for disease phenotypes. Moreover, by altering the nucleic acid sequence payload, this treatment modality can rapidly pivot to address a myriad of conditions, ranging from monogenic inherited disorders, various malignancies, to infectious diseases where crucial viral or bacterial proteins need to be hindered. The high specificity of these therapies reduces off-target effects and enhances patient safety profiles.

NANOSPRESSO’s development has been spearheaded by a multidisciplinary team led by Professor Raymond Schiffelers at University Medical Center Utrecht. Their work builds on the successes of nucleic acid-based medicines, such as the mRNA vaccines deployed during the COVID-19 pandemic, demonstrating that clinically relevant, gene-targeted therapeutics can be produced efficiently and at scale. What sets NANOSPRESSO apart is its ability to condense the traditionally complex and resource-intensive manufacturing process into a user-friendly device operable by hospital pharmacists without requiring extensive specialized infrastructure.

Functionally, the device utilizes pre-loaded cartridges containing bespoke formulations of lipids and nucleic acids specific to the patient’s disease-causing mutation. These components are precisely combined within a sterile, closed-system microfluidic platform that facilitates controlled mixing and nanoparticle assembly in real time. The result is a homogenized suspension of nucleic acid-carrying lipid nanoparticles, formulated with rigor to meet stringent safety, efficacy, and sterility standards. The entire procedure circumvents the logistical and regulatory delays associated with centralized drug manufacturing and distribution, offering a just-in-time pharmaceutical manufacturing model.

Nevertheless, the introduction of such disruptive technology poses significant challenges to existing healthcare and regulatory frameworks. The notion of hospital-based production of gene therapies requires a re-evaluation of quality control systems, approval pathways, and liability construct to ensure patient safety without stifling innovation. The NANOSPRESSO team has proactively initiated dialogues with regulators and industry stakeholders to delineate pathways for compliance and integration, drawing parallels to the historical practice of pharmaceutical compounding, where pharmacists formulated personalized medicines prior to the industrialization of drug production.

Ethical and economic considerations also emerge as critical discourse points. By empowering local manufacturing, NANOSPRESSO could reduce drug costs substantially, making precision nanomedicine accessible beyond affluent nations and tertiary care centers. This localization may reduce healthcare disparities, particularly in rural or low-income regions traditionally marginalized in advanced therapy availability. However, implementing such technology demands robust training programs, standardized operating protocols, and integration within hospital pharmacy workflows to safeguard against variability and ensure reproducible therapeutic quality.

Currently, NANOSPRESSO prototypes are in active development, with ongoing research addressing technological refinement, pharmacological efficacy, biosafety, and integration logistics. Investigations are underway to validate the device’s performance across a spectrum of nucleic acid sequences and lipid formulations, simulate clinical deployment scenarios, and engage with healthcare providers to tailor operational models. The overarching ambition is to establish a scalable platform that seamlessly embeds into healthcare environments, enabling clinicians to harness personalized nanomedicines for diverse rare diseases and beyond.

By seamlessly bridging the gap between cutting-edge biotechnology and practical clinical application, NANOSPRESSO represents a beacon of innovation in the realm of personalized medicine. Its potential to transform the treatment landscape for millions suffering from rare genetic diseases is unparalleled, offering a vision of healthcare where medicines are no longer mass-produced commodities but precise, patient-customized interventions fabricated at bedside. As this technology matures and regulatory frameworks evolve, the promise of democratized gene therapy production draws nearer, heralding a new era of accessible precision health.

The project NANOSPRESSO-NL, supported by the Netherlands Science Agenda and the Netherlands Organization for Scientific Research, exemplifies how collaborative, interdisciplinary efforts can enable paradigm shifts in medical technology. The convergence of molecular biology, bioengineering, and clinical pharmacy embodied in NANOSPRESSO paves the way for a future where innovation transcends traditional manufacturing bottlenecks and empowers local healthcare providers to deliver next-generation therapies to patients irrespective of geography or resource constraints.

Subject of Research: Not applicable
Article Title: NANOSPRESSO: toward personalized, locally produced nucleic acid nanomedicines
News Publication Date: 26-Jun-2025
Web References: 10.3389/fsci.2025.1458636
Keywords: Personalized medicine, gene therapy, nucleic acid therapeutics, lipid nanoparticles, rare diseases, drug delivery systems, precision medicine, microfluidics, nanomedicine, healthcare equity, gene delivery, pharmacogenetics