Complexation of single stranded RNA with an ionizable lipid: an all-atom molecular dynamics simulation study

Sucrose ester embedded lipid carrier for DNA delivery

Sucrose esters (SEs) have great potential in the field of nucleic acid delivery due to their unique physical and chemical properties and good biosafety. However, the mechanism of the effect of SEs structure on delivery efficiency has not been studied. The liposomes containing peptide lipids and SEs were constructed, and the effects of SEs on the interaction between the liposomes and DNA were studied. The addition of SEs affects the binding rate of liposomes to DNA, and the binding rate gradually decreases with the increase of SEs' carbon chain length. SEs also affect the binding site and affinity of liposomes to DNA, promoting the aggregation of lipids to form liposomes, where DNA wraps around or compresses inside the liposomes, allowing it to compress DNA without damaging the DNA structure. COL-6, which is composed of sucrose laurate, exhibits the optimal affinity for DNA, and SE promotes the formation of ordered membrane structure and enhances membrane stability, so that COL-6 exhibits a balance between rigidity and flexibility, and thus exhibits the highest delivery efficiency of DNA among these formulations. This work provides theoretical foundations for the application of SE in gene delivery and guides for the rational design of delivery systems.

mRNA-LNP COVID-19 Vaccine Lipids Induce Complement Activation and Production of Proinflammatory Cytokines: Mechanisms, Effects of Complement Inhibitors, and Relevance to Adverse Reactions

A small fraction of people vaccinated with mRNA-lipid nanoparticle (mRNA-LNP)-based COVID-19 vaccines display acute or subacute inflammatory symptoms whose mechanism has not been clarified to date. To better understand the molecular mechanism of these adverse events (AEs), here, we analyzed in vitro the vaccine-induced induction and interrelations of the following two major inflammatory processes: complement (C) activation and release of proinflammatory cytokines. Incubation of Pfizer-BioNTech's Comirnaty and Moderna's Spikevax with 75% human serum led to significant increases in C5a, sC5b-9, and Bb but not C4d, indicating C activation mainly via the alternative pathway. Control PEGylated liposomes (Doxebo) also induced C activation, but, on a weight basis, it was ~5 times less effective than that of Comirnaty. Viral or synthetic naked mRNAs had no C-activating effects. In peripheral blood mononuclear cell (PBMC) cultures supplemented with 20% autologous serum, besides C activation, Comirnaty induced the secretion of proinflammatory cytokines in the following order: IL-1α < IFN-γ < IL-1β < TNF-α < IL-6 < IL-8. Heat-inactivation of C in serum prevented a rise in IL-1α, IL-1β, and TNF-α, suggesting C-dependence of these cytokines' induction, although the C5 blocker Soliris and C1 inhibitor Berinert, which effectively inhibited C activation in both systems, did not suppress the release of any cytokines. These findings suggest that the inflammatory AEs of mRNA-LNP vaccines are due, at least in part, to stimulation of both arms of the innate immune system, whereupon C activation may be causally involved in the induction of some, but not all, inflammatory cytokines. Thus, the pharmacological attenuation of inflammatory AEs may not be achieved via monotherapy with the tested C inhibitors; efficacy may require combination therapy with different C inhibitors and/or other anti-inflammatory agents.

Lipid shape and packing are key for optimal design of pH-sensitive mRNA lipid nanoparticles

The ionizable-lipid component of RNA-containing nanoparticles controls the pH-dependent behavior necessary for an efficient delivery of the cargo-the so-called endosomal escape. However, it is still an empirical exercise to identify optimally performing lipids. Here, we study two well-known ionizable lipids, DLin-MC3-DMA and DLin-DMA using a combination of experiments, multiscale computer simulations, and electrostatic theory. All-atom molecular dynamics simulations, and experimentally measured polar headgroup pKa values, are used to develop a coarse-grained representation of the lipids, which enables the investigation of the pH-dependent behavior of lipid nanoparticles (LNPs) through Monte Carlo simulations, in the absence and presence of RNA molecules. Our results show that the charge state of the lipids is determined by the interplay between lipid shape and headgroup chemistry, providing an explanation for the similar pH-dependent ionization state observed for lipids with headgroup pKa values about one-pH-unit apart. The pH dependence of lipid ionization is significantly influenced by the presence of RNA, whereby charge neutrality is achieved by imparting a finite and constant charge per lipid at intermediate pH values. The simulation results are experimentally supported by measurements of α-carbon 13C-NMR chemical shifts for eGFP mRNA LNPs of both DLin-MC3-DMA and DLin-DMA at various pH conditions. Further, we evaluate the applicability of a mean-field Poisson-Boltzmann theory to capture these phenomena.

Computational approaches to lipid-based nucleic acid delivery systems

Nucleic acid-based therapies have shown enormous effectiveness as vaccines against the recent COVID19 pandemics and hold great promises in the fight of a broad spectrum of diseases ranging from viral infections to cancer up to genetically transmitted pathologies. Due to their highly degradable polyanionic nature, nucleic acids need to be packed in sophisticate delivery vehicles which compact them up, protect them from early degradation and help delivery them to the right tissue/cells. Lipid-based nanoparticles (LNP) represent, at present, the main solution for nucleic acid delivery. They are made of a mixture of lipids whose key ingredient is an ionizable cationic lipid. Indeed, the interactions between the polyanionic nucleic acids and the ionizable cationic lipids, and their pH-dependent regulation in the life cycle of the nanoparticle, from production to cargo delivery, mostly determine the effectiveness of the therapeutic approach. Notwithstanding the large improvements in the delivery efficiency of LNPs in the last two decades, it is estimated that only a small fraction of the cargo is actually delivered, stimulating further research for the design of more effective LNP formulations. A rationally driven design would profit from the knowledge of the precise molecular structure of these materials, which is however still either missing or characterized by poor spatial resolution. Computational approaches have often been used as a molecular microscope either to enrich the available experimental data and provide a molecular-level picture of the LNPs or even simulate specific processes involving the formation and/or the molecular mechanisms of action of the LNP. Here, I review the recent literature in the field.

Intricate subcellular journey of nanoparticles to the enigmatic domains of endoplasmic reticulum

It is evident that site-specific systemic drug delivery can reduce side effects, systemic toxicity, and minimal dosage requirements predominantly by delivering drugs to particular pathological sites, cells, and even subcellular structures. The endoplasmic reticulum (ER) and associated cell organelles play a vital role in several essential cellular functions and activities, such as the synthesis of lipids, steroids, membrane-associated proteins along with intracellular transport, signaling of Ca2+, and specific response to stress. Therefore, the dysfunction of ER is correlated with numerous diseases where cancer, neurodegenerative disorders, diabetes mellitus, hepatic disorder, etc., are very common. To achieve satisfactory therapeutic results in certain diseases, it is essential to engineer delivery systems that can effectively enter the cells and target ER. Nanoparticles are highly biocompatible, contain a variety of cargos or payloads, and can be modified in a pliable manner to achieve therapeutic effectiveness at the subcellular level when delivered to specific organelles. Passive targeting drug delivery vehicles, or active targeting drug delivery systems, reduce the nonselective accumulation of drugs while reducing side effects by modifying them with small molecular compounds, antibodies, polypeptides, or isolated bio-membranes. The targeting of ER and closely associated organelles in cells using nanoparticles, however, is still unsymmetrically understood. Therefore, here we summarized the pathophysiological prospect of ER stress, involvement of ER and mitochondrial response, disease related to ER dysfunctions, essential therapeutics, and nanoenabled modulation of their delivery to optimize therapy.

Research in the Field of Drug Design and Development

The processes used by academic and industrial scientists to discover new drugs have recently experienced a true renaissance, with many new and exciting techniques being developed over the past 5-10 years alone. Drug design and discovery, and the search for new safe and well-tolerated compounds, as well as the ineffectiveness of existing therapies, and society's insufficient knowledge concerning the prophylactics and pharmacotherapy of the most common diseases today, comprise a serious challenge. This can influence not only the quality of human life, but also the health of whole societies, which became evident during the COVID-19 pandemic. In general, the process of drug development consists of three main stages: drug discovery, preclinical development using cell-based and animal models/tests, clinical trials on humans and, finally, forward moving toward the step of obtaining regulatory approval, in order to market the potential drug. In this review, we will attempt to outline the first three most important consecutive phases in drug design and development, based on the experience of three cooperating and complementary academic centers of the Visegrád group; i.e., Medical University of Lublin, Poland, Masaryk University of Brno, Czech Republic, and Comenius University Bratislava, Slovak Republic.

The Effect of Ethanol on Lipid Nanoparticle Stabilization from a Molecular Dynamics Simulation Perspective

Lipid nanoparticles (LNPs) have emerged as a promising delivery system, particularly for genetic therapies and vaccines. LNP formation requires a specific mixture of nucleic acid in a buffered solution and lipid components in ethanol. Ethanol acts as a lipid solvent, aiding the formation of the nanoparticle's core, but its presence can also affect LNP stability. In this study, we used molecular dynamics (MD) simulations to investigate the physicochemical effect of ethanol on LNPs and gain a dynamic understanding of its impact on the overall structure and stability of LNPs. Our results demonstrate that ethanol destabilizes LNP structure over time, indicated by increased root mean square deviation (RMSD) values. Changes in the solvent-accessible surface area (SASA), electron density, and radial distribution function (RDF) also suggest that ethanol affects LNP stability. Furthermore, our H-bond profile analysis shows that ethanol penetrates the LNP earlier than water. These findings emphasize the importance of immediate ethanol removal in lipid-based systems during LNP production to ensure stability.

Atomistic Insights into Organization of RNA-Loaded Lipid Nanoparticles

RNA-based therapies have shown promise in a wide range of applications, from cancer therapy, treatment of inherited diseases to vaccination. Encapsulation of RNA into ionizable lipid (IL) containing lipid nanoparticles (LNPs) has enabled its safe and targeted delivery. We present here the simulations of the self-assembly process of pH-sensitive RNA-carrying LNPs and their internal morphology. At low pH, the simulations confirm a lipid core encapsulating RNA in the hexagonal phase. Our all-atom and coarse-grained simulations show that an RNA molecule inside an LNP is protected from interactions with ions by being enveloped in the charged ILs. At neutral pH, representing the environment after LNP administration into human tissues, LNPs expelled most of the encapsulated RNA and water and formed separate bulk IL-rich and ordered the helper-lipid-rich phase. Helper lipids arranged themselves to be in contact with RNA or water. The presented models provide atomistic understanding of the LNP structure and open a way to investigate them in silico, varying the LNP composition or interacting with other biostructures aiming at increasing the efficiency of RNA-based medicine.

Messenger RNA in lipid nanoparticles rescues HEK 293 cells from lipid-induced mitochondrial dysfunction as studied by real time pulse chase NMR, RTPC-NMR, spectroscopy

Analytical tools to study cell physiology are critical for optimizing drug-host interactions. Real time pulse chase NMR spectroscopy, RTPC-NMR, was introduced to monitor the kinetics of metabolite production in HEK 293T cells treated with COVID-19 vaccine-like lipid nanoparticles, LNPs, with and without mRNA. Kinetic flux parameters were resolved for the incorporation of isotopic label into metabolites and clearance of labeled metabolites from the cells. Changes in the characteristic times for alanine production implicated mitochondrial dysfunction as a consequence of treating the cells with lipid nanoparticles, LNPs. Mitochondrial dysfunction was largely abated by inclusion of mRNA in the LNPs, the presence of which increased the size and uniformity of the LNPs. The methodology is applicable to all cultured cells.

Effects of the structure of lipid-based agents in their complexation with a single stranded mRNA fragment: a computational study

In this work we employed fully atomistic molecular dynamics simulations, aiming towards a better understanding of the mechanisms associated with the formation and the stability of lipid-based RNA nanoassemblies, in an aqueous environment. We examined two groups of lipid-based complexation agents, differing in the degree of hydrophobicity and in the overall charge. The first group was comprised of cationic ionizable agents while the second included electrically neutral amphoteric phosphatidylcholine lipids. It was found that the overall charge of the complexation agents played the most decisive role in the energetics of the lipid/RNA association, while their degree of hydrophobicity affected their self-assembly and their complexation kinetics. The latter also affected the structural stability of the formed complexes since the water entrapped within the clusters of the less hydrophobic agents appeared to reduce the coherence of the lipid-RNA nanoassemblies. The combined effects of the aforementioned attributes dictated also the RNA conformation after complexation. The results from the present study provide thus new insight towards controlling the morphology, the energetic stability and the structural integrity of the formed complexes.

Decoding the Kinetic Pathways toward a Lipid/DNA Complex of Alkyl Alcohol Cationic Lipids Formed in a Microfluidic Channel

Complexes of cationic liposomes with DNA have emerged as promising nonviral vectors for delivering genetic information into cells for gene therapy. Kinetics of the liposome/DNA complex (lipoplex) formation on a millisecond time scale are studied by monitoring time evolution of fluorescence of 8-anilino-1-naphthalene sulfonic acid (ANS) and ethidium bromide (EtBr) in a continuous flow microfluidic channel coupled to a fluorescence microscope. The formation of lipoplexes between calf thymus DNA and liposomes based on two novel cationic lipids (Lip1810 and Lip1814) are found to follow a two-step process with kinetic constants for the Lip1814/DNA complex (k₁ = 1120-1383 s^-1, k₂ = 0.227-1.45 s^-1) being significantly different from those (k₁ = 68.53-98.5 s^-1, k₂ = 32.3-60.19 s^-1) corresponding to formation of the Lip1810/DNA complex. The kinetic pathway leading to the formation of Lip1814/DNA complex is diffusion-controlled whereas the formation of Lip1810/DNA complex occurs by a conformational rearrangement-controlled pathway. The observed difference in the kinetics of lipoplex formation likely originates from different structures of the lipid/DNA complexes.

pH-Dependent Behavior of Ionizable Cationic Lipids in mRNA-Carrying Lipoplexes Investigated by Molecular Dynamics Simulations

Lipid-based nanoparticles and lipoplexes containing ionizable lipids are among the most successful nanocarriers for mRNA-based therapies. The molecular structure of these assemblies is still not fully understood, as well as the role played by the ionizable lipids. SAXS experiments have shown that lipoplexes including the ionizable lipid 2-dioleyloxy-N,N-dimethyl-3-aminopropane (DODMA), under specific conditions, have a lamellar structure, where lipid bilayers are separated by mRNA-rich layers, with an overall spacing between 6.5 and 8.0 nm and a complex pH-dependence. Here, the structure and dynamics of these lipoplexes are investigated at varying pH and mRNA concentration using multiscale molecular dynamics simulations. It is observed that the interaction between DODMA and RNA is slightly attractive only at low pH levels, while it becomes effectively repulsive at high and intermediate pH. This results into a pH-dependent relocation of the RNA inside the multilayers, from the lipid head groups at low pH to a more uniform distribution inside the hydrophilic slabs of the multilayers at high pH. It is also observed that at high pH, DODMA lipids shift toward the hydrophobic part of the bilayer, consequently increasing their leaflet-flipping rate, a phenomenon which may ultimately affect the fusion process of the lipoplex with the endosomal membrane.

Prediction of lipid nanoparticles for mRNA vaccines by the machine learning algorithm

Lipid nanoparticle (LNP) is commonly used to deliver mRNA vaccines. Currently, LNP optimization primarily relies on screening ionizable lipids by traditional experiments which consumes intensive cost and time. Current study attempts to apply computational methods to accelerate the LNP development for mRNA vaccines. Firstly, 325 data samples of mRNA vaccine LNP formulations with IgG titer were collected. The machine learning algorithm, lightGBM, was used to build a prediction model with good performance (R² > 0.87). More importantly, the critical substructures of ionizable lipids in LNPs were identified by the algorithm, which well agreed with published results. The animal experimental results showed that LNP using DLin-MC3-DMA (MC3) as ionizable lipid with an N/P ratio at 6:1 induced higher efficiency in mice than LNP with SM-102, which was consistent with the model prediction. Molecular dynamic modeling further investigated the molecular mechanism of LNPs used in the experiment. The result showed that the lipid molecules aggregated to form LNPs, and mRNA molecules twined around the LNPs. In summary, the machine learning predictive model for LNP-based mRNA vaccines was first developed, validated by experiments, and further integrated with molecular modeling. The prediction model can be used for virtual screening of LNP formulations in the future.

Role of Ionizable Lipids in SARS-CoV-2 Vaccines As Revealed by Molecular Dynamics Simulations: From Membrane Structure to Interaction with mRNA Fragments

Recent advances in RNA-based medicine have provided new opportunities for the global current challenge, i.e., the COVID-19 pandemic. Novel vaccines are based on a messenger RNA (mRNA) motif with a lipid nanoparticle (LNP) vector, consisting of high content of unique pH-sensitive ionizable lipids (ILs). Here we provide molecular insights into the role of the ILs and lipid mixtures used in current mRNA vaccines. We observed that the lipid mixtures adopted a nonlamellar organization, with ILs separating into a very disordered, pH-sensitive phase. We describe structural differences of the two ILs leading to their different congregation, with implications for the vaccine stability. Finally, as RNA interacts preferentially with IL-rich phases located at the regions with high curvature of lipid phase, local changes in RNA flexibility and base pairing are induced by lipids. A proper atomistic understanding of RNA-lipid interactions may enable rational tailoring of LNP composition for efficient RNA delivery.

Pharma 4.0 Continuous mRNA Drug Products Manufacturing

Continuous mRNA drugs manufacturing is perceived to nurture flow processes featuring quality by design, controlled automation, real time validation, robustness, and reproducibility, pertaining to regulatory harmonization. However, the actual adaptation of the latter remains elusive, hence batch-to-continuous transition would a priori necessitate holistic process understanding. In addition, the cost related to experimental, pilot manufacturing lines development and operations thereof renders such venture prohibitive. Systems-based Pharmaceutics 4.0 digital design enabling tools, i.e., converging mass and energy balance simulations, Monte-Carlo machine learning iterations, and spatial arrangement analysis were recruited herein to overcome the aforementioned barriers. The primary objective of this work is to hierarchically design the related bioprocesses, embedded in scalable devices, compatible with continuous operation. Our secondary objective is to harvest the obtained technological data and conduct resource commitment analysis. We herein demonstrate for first time the feasibility of the continuous, end-to-end production of sterile mRNA formulated into lipid nanocarriers, defining the equipment specifications and the desired operational space. Moreover, we find that the cell lysis modules and the linearization enzymes ascend as the principal resource-intensive model factors, accounting for 40% and 42% of the equipment and raw material, respectively. We calculate MSPD 1.30–1.45 €, demonstrating low margin lifecycle fluctuation.

Biopharmaceutics 4.0, Advanced Pre-Clinical Development of mRNA-Encoded Monoclonal Antibodies to Immunosuppressed Murine Models

Administration of mRNA against SARS-CoV-2 has demonstrated sufficient efficacy, tolerability and clinical potential to disrupt the vaccination field. A multiple-arm, cohort randomized, mixed blind, placebo-controlled study was designed to investigate the in vivo expression of mRNA antibodies to immunosuppressed murine models to conduct efficacy, safety and bioavailability evaluation. Enabling 4.0 tools we reduced animal sacrifice, while interventions were designed compliant to HARRP and SPIRIT engagement: (a) Randomization, blinding; (b) pharmaceutical grade formulation, monitoring; (c) biochemical and histological analysis; and (d) theoretic, statistical analysis. Risk assessment molded the study orientations, according to the ARRIVE guidelines. The primary target of this protocol is the validation of the research hypothesis that autologous translation of Trastuzumab by in vitro transcribed mRNA-encoded antibodies to immunosuppressed animal models, is non-inferior to classical treatments. The secondary target is the comparative pharmacokinetic assessment of the novel scheme, between immunodeficient and healthy subjects. Herein, the debut clinical protocol, investigating the pharmacokinetic/pharmacodynamic impact of mRNA vaccination to immunodeficient organisms. Our design, contributes novel methodology to guide the preclinical development of RNA antibody modalities by resolving efficacy, tolerability and dose regime adjustment for special populations that are incapable of humoral defense.

Development of a Nanocrystal Formulation of a Low Melting Point API Following a Quality by Design Approach

Preparation of nanocrystal formulations by wet media milling and spray-drying is a reliable technique to enhance dissolution and ameliorate absorption limitations of poorly soluble BCS II drugs. However, when thermosensitive compositions are dried at high temperatures, the risks of particle aggregation and thermal degradation must be considered. The present study investigates the effects of nanosuspension formulation variables when performing the spray drying process at equidistant temperatures above and below the melting point. Towards this purpose, Fenofibrate is exploited as a model drug of unfavorable pharmacokinetic profile and low melting point (79–82 °C), properties that render thermal processing a nontrivial task. Rationalizing the system’s behavior by combining molecular simulations with QbD methodology, the preparation of stable nanocrystals can be “steered” in order to avoid undesirable melting. The statistically resolved operational conditions showed that Fenofibrate Critical Quality Attribute–compliant nanosuspensions i.e., bearing hydrodynamic diameter and ζ-potential of 887 nm and −16.49 mV, respectively, were obtained by wet milling drug to Pharmacoat and mannitol weighted optimum ratios of 4.075% and 0.75%, after spray drying at the desired temperature of 77 °C. In conclusion, we present a quality assurance methodology of nano-comminution generally applicable for thermo-labile BCS II drugs.

mRNA-lipid nanoparticle COVID-19 vaccines: Structure and stability

A drawback of the current mRNA-lipid nanoparticle (LNP) COVID-19 vaccines is that they have to be stored at (ultra)low temperatures. Understanding the root cause of the instability of these vaccines may help to rationally improve mRNA-LNP product stability and thereby ease the temperature conditions for storage. In this review we discuss proposed structures of mRNA-LNPs, factors that impact mRNA-LNP stability and strategies to optimize mRNA-LNP product stability. Analysis of mRNA-LNP structures reveals that mRNA, the ionizable cationic lipid and water are present in the LNP core. The neutral helper lipids are mainly positioned in the outer, encapsulating, wall. mRNA hydrolysis is the determining factor for mRNA-LNP instability. It is currently unclear how water in the LNP core interacts with the mRNA and to what extent the degradation prone sites of mRNA are protected through a coat of ionizable cationic lipids. To improve the stability of mRNA-LNP vaccines, optimization of the mRNA nucleotide composition should be prioritized. Secondly, a better understanding of the milieu the mRNA is exposed to in the core of LNPs may help to rationalize adjustments to the LNP structure to preserve mRNA integrity. Moreover, drying techniques, such as lyophilization, are promising options still to be explored.