DOPC versus DOPE as a helper lipid for gene-therapies: molecular dynamics simulations with DLin-MC3-DMA

Ionizable lipids are important compounds of modern therapeutic lipid nano-particles (LNPs). One of the most promising ionizable lipids (or amine lipids) is DLin-MC3-DMA. Depending on their pharmaceutical application these LNPs can also contain various helper lipids, such as phospho- and pegylated lipids, cholesterol and nucleic acids as a cargo. Due to their complex compositions the structures of these therapeutics have not been refined properly. Therefore, the role of each lipid in the pharmacological properties of LNPs has not been determined. In this work an atomistic model for the neutral form of DLin-MC3-DMA was derived and all-atom molecular dynamics (MD) simulations were carried out in order to investigate the effect of the phospholipid headgroup on the possible properties of the shell-membranes of LNPs. Bilayers containing either DOPC or DOPE lipids at two different ratios of DLin-MC3-DMA (5 mol% and 15 mol%) were constructed and simulated at neutral pH 7.4. The results from the analysis of MD trajectories revealed that DOPE lipid headgroups associated strongly with lipid tails and carbonyl oxygens of DLin-MC3-DMA, while for DOPC lipid headgroups no significant associations were observed. Furthermore, the strong associations between DOPE and DLin-MC3-DMA result in the positioning of DLin-MC3-DMA at the surface of the membrane. Such an interplay between the lipids slows down the lateral diffusion of all simulated bilayers, where a more dramatic decrease of the diffusion rate is observed in membranes with DOPE. This can explain the low water penetration of lipid bilayers with phosphatidylethanolamines and, probably, can relate to the bad transfection properties of LNPs with DOPE and DLin-MC3-DMA

Ionizable lipids penetrate phospholipid bilayers with high phase transition temperatures: perspectives from free energy calculations

The efficacies of modern gene-therapies strongly depend on their contents. At the same time the most potent formulations might not contain the best compounds. In this work we investigated the effect of phospholipids and their saturation on the binding ability of (6Z,9Z,28Z,31Z)-heptatriacont-6,9,28,31-tetraene-19-yl 4-(dimethylamino) butanoate (DLin-MC3-DMA) to model membranes at the neutral pH. We discovered that DLin-MC3-DMA has affinity to the most saturated monocomponent lipid bilayer 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and an aversion to the unsaturated one 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC). The preference to a certain membrane was also well-correlated to the phase transition temperatures of phospholipid bilayers, and to their structural and dynamical properties. Additionally, in the case of the presence of DLin-MC3-DMA in the membrane with DOPC the ionizable lipid penetrated it, which indicates possible synergistic effects. Comparisons with other ionizable lipids were performed using a model lipid bilayer of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC). Particularly, the lipids heptadecan-9-yl 8-[2-hydroxyethyl-(6-oxo-6-undecoxyhexyl)amino]octanoate (SM-102) and [(4-hydroxybutyl) azanediyl] di(hexane-6,1-diyl) bis(2-hexyldecanoate) (ALC-0315) from modern mRNA-vaccines against COVID-19 were investigated and force fields parameters were derived for those new lipids. It was discovered that ALC-0315 binds strongest to the membrane, while DLin-MC3-DMA is not able to reside in the bilayer center. The ability to penetrate the membrane POPC by SM-102 and ALC-0315 can be related to their saturation, comparing to DLin-MC3-DMA

Matter Enhanced Neutrino Oscillations with a Realistic Earth Density Profile

We have investigated matter enhanced neutrino oscillations with a mantle-core-mantle step function and a realistic Earth matter density profile in both a two and a three neutrino scenario. We found that the realistic Earth matter density profile can be well approximated with the mantle-core-mantle step function and that there could be an influence on the oscillation channel $\nu_\mu \to \nu_\tau$ due to resonant enhancement of one of the mixing angles.Comment: 8 pages, 5 figures (PostScript), MPLA LaTe

Reconstruction of the Earth's matter density profile using a single neutrino baseline

In this paper, we show numerically that a symmetric Earth matter density profile can, in principle, be reconstructed from a single baseline energy spectrum up to a certain precision. For the numerical evaluations in the high dimensional parameter space we use a genetic algorithm.Comment: 8 pages, 3 figures, LaTe

Atomistic molecular dynamics simulations of tubulin heterodimers explain the motion of a microtubule

Microtubules are essential parts of the cytoskeleton that are built by polymerization of tubulin heterodimers into a hollow tube. Regardless that their structures and functions have been comprehensively investigated in a modern soft matter, it is unclear how properties of tubulin heterodimer influence and promote the self-assembly. A detailed knowledge of such structural mechanisms would be helpful in drug design against neurodegenerative diseases, cancer, diabetes etc. In this work atomistic molecular dynamics simulations were used to investigate the fundamental dynamics of tubulin heterodimers in a sheet and a short microtubule utilizing well-equilibrated structures. The breathing motions of the tubulin heterodimers during assembly show that the movement at the lateral interface between heterodimers (wobbling) dominates in the lattice. The simulations of the protofilament curvature agrees well with recently published experimental data, showing curved protofilaments at polymerization of the microtubule plus end. The tubulin heterodimers exposed at the microtubule minus end were less curved and displayed altered interactions at the site of sheet closure around the outmost heterodimers, which may slow heterodimer binding and polymerization, providing a potential explanation for the limited dynamics observed at the minus end

Economic Growth Stability Under National Markets Integration: Mercantilism Striking Back

Sustainable economic growth as an overall positive dynamics of macroeconomic indicators without any serious fluctuations in values during a relative long term belongs to the most persuasive evidence of the internal efficiency of national economic system and also of global competitiveness under all uncertainties of the world market environment. In this article, we analyze the macroeconomic indicators of the contemporary economies so that to determine the level of impact from their involvement in the world trade on the stability of their economic development. A new, author’s method is offered here to determine the index of economic growth stability for the economies of the 21st century. A correlation is revealed being between economic growth stability and external trade activeness of the today’s economies. Countries are classified here depending on the dynamics of their trade balance. Contemporary factors of national economic growth stabilization are outlined being in direct dependence with the dynamics of external trade

Hiding Backdoors within Event Sequence Data via Poisoning Attacks

The financial industry relies on deep learning models for making important decisions. This adoption brings new danger, as deep black-box models are known to be vulnerable to adversarial attacks. In computer vision, one can shape the output during inference by performing an adversarial attack called poisoning via introducing a backdoor into the model during training. For sequences of financial transactions of a customer, insertion of a backdoor is harder to perform, as models operate over a more complex discrete space of sequences, and systematic checks for insecurities occur. We provide a method to introduce concealed backdoors, creating vulnerabilities without altering their functionality for uncontaminated data. To achieve this, we replace a clean model with a poisoned one that is aware of the availability of a backdoor and utilize this knowledge. Our most difficult for uncovering attacks include either additional supervised detection step of poisoned data activated during the test or well-hidden model weight modifications. The experimental study provides insights into how these effects vary across different datasets, architectures, and model components. Alternative methods and baselines, such as distillation-type regularization, are also explored but found to be less efficient. Conducted on three open transaction datasets and architectures, including LSTM, CNN, and Transformer, our findings not only illuminate the vulnerabilities in contemporary models but also can drive the construction of more robust systems