Spontaneous insertion of carbon nanotube bundles inside biomembranes: a hybrid particle-field coarse-grained molecular dynamics study

The processes of CNTs bundle formation and insertion/rearrangement inside lipid bilayers, as models of cellular membranes, is described and analyzed in details using simulations on the microsecond scale. Molecular Dynamics simulations employing hybrid particle-field models (MD–SCF) show that during the insertion process lipid molecules coat bundles surfaces. The distortions of bilayers are more pronounced for systems undergoing to insertion of bundles made of longer CNTs. In particular, when the insertion occurs in perpendicular orientation, adsorption of lipids on CNTs surfaces promotes a transient poration. This result suggests mechanism of membrane disruption operated by bundles causing the formation of solvent-rich pockets

Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis

The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors

Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis

The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors

Coating mechanisms of single-walled carbon nanotube by linear polyether surfactants: insights from computer simulations

The noncovalent coating of carbon-based nanomaterials, such as carbon nanotubes, has important applications in nanotechnology and nanomedicine. The molecular modeling of this process can clarify its mechanism and provide a tool for the design of novel materials. In this paper, the coating mechanism of single-walled carbon nanotubes (SWCNT) in aqueous solutions by 1,2-dimethoxyethane oxide (DME), 1,2-dimethoxypropane oxide (DMP), poly(ethylene oxide) (PEO), poly(propylene oxide) (PPO) pentamers, and L64 triblock copolymer chains have been studied using molecular dynamics (MD) simulations. The results suggest a preferential binding to the SWCNT surface of the DMP molecules with respect to DME mainly driven by their difference in hydrophobicity. For the longer pentamers, it depends by the chain conformation. PPO isomers with radius of gyration larger than PEO pentamers bind more tightly than those with more compact conformation. In the case of the L64 triblock copolymer, the coating of the SWCNT surface produces a shell of PPO blocks with the PEO chains protruding into bulk water as expected from the so-called nonwrapping binding mechanism of SWCNT. In addition, the polymer coating, in qualitative agreement with experimental evidence on the poor capability of the L64 to disperse SWCNT, do not prevent the formation of CNT aggregates

Rational drug design of Axl tyrosine kinase type I inhibitors as promising candidates against cancer

The high level of Axl tyrosine kinase expression in various cancer cell lines makes it an attractive target for the development of anti-cancer drugs. In this study, we carried out several sets of in silico screening for the ATP-competitive Axl kinase inhibitors based on different molecular docking protocols. The best drug-like candidates were identified, after parental structure modifications, by their highest affinity to the target protein. We found that our newly designed compound R5, a derivative of the R428 patented analog, is the most promising inhibitor of the Axl kinase according to the three molecular docking algorithms applied in the study. The molecular docking results are in agreement with the molecular dynamics simulations using the MM-PBSA/GBSA implicit solvation models, which confirm the high affinity of R5 toward the protein receptor. Additionally, the selectivity test against other kinases also reveals a high affinity of R5 toward ABL1 and Tyro3 kinases, emphasizing its promising potential for the treatment of malignant tumors

Adsorption mechanism of an antimicrobial peptide on carbonaceous surfaces: a molecular dynamics study

Peptides are versatile molecules with applications spanning from biotechnology to nanomedicine. They exhibit a good capability to unbundle carbon nanotubes (CNT) by improving their solubility in water. Furthermore, they are a powerful drug delivery system since they can easily be uptaked by living cells, and their high surface to volume ratio facilitates the adsorption of molecules of different nature. Therefore, understanding the interaction mechanism between peptides and CNT is important for designing novel therapeutically agents. In this paper, the mechanisms of the adsorption of antimicrobial peptide Cecropin A – Magainin 2 (CA-MA) on a graphene nanosheet (GNS) and on an ultra-short single-walled CNT are characterized using molecular dynamics simulations. The results show that the peptide coats both GNS and CNT surfaces through preferential contacts with aromatic side chains. The peptide packs compactly on the carbon surfaces where the polar and functionalizable Lys side chains protrude into the bulk solvent. It is shown that the adsorption is strongly correlated to a loss of the peptide helical structure. In the case of the CNT, the outer surface is significantly more accessible for adsorption. Nevertheless when the outer surface is already covered by other peptides, a spontaneous diffusion, via the amidated C-terminus, into the interior of the CNT was observed within 150 ns of simulation time. We found that this spontaneous insertion into the CNT interior can be controlled by the polarity of the entrance rim. For the positively charged CA-MA peptide studied, hydrogenated and fluorinated rims, respectively, hinder and promote the insertion

In silico designed Axl receptor blocking drug candidates against Zika virus infection

After a large outbreak in Brazil, novel drugs against Zika virus became extremely necessary. Evaluation of virus-based pharmacological strategies concerning essential host factors brought us to the idea that targeting the Axl receptor by blocking its dimerization function could be critical for virus entry. Starting from experimentally validated compounds, such as RU-301, RU-302, warfarin, and R428, we identified a novel compound 2′ (R428 derivative) to be the most potent for this task amongst a number of alternative compounds and leads. The improved affinity of compound 2′ was confirmed by molecular docking as well as molecular dynamics simulation techniques using implicit solvation models. The current study summarizes a new possibility for inhibition of the Axl function as a potential target for future antiviral therapies

In Silico Studies Reveal Peramivir and Zanamivir as an Optimal Drug Treatment Even If H7N9 Avian Type Influenza Virus Acquires Further Resistance

An epidemic of avian type H7N9 influenza virus, which took place in China in 2013, was enhanced by a naturally occurring R294K mutation resistant against Oseltamivir at the catalytic site of the neuraminidase. To cope with such drug-resistant neuraminidase mutations, we applied the molecular docking technique to evaluate the fitness of the available drugs such as Oseltamivir, Zanamivir, Peramivir, Laninamivir, L-Arginine and Benserazide hydrochloride concerning the N9 enzyme with single (R294K, R119K, R372K), double (R119_294K, R119_372K, R294_372K) and triple (R119_294_372K) mutations in the pocket. We found that the drugs Peramivir and Zanamivir score best amongst the studied compounds, demonstrating their high binding potential towards the pockets with the considered mutations. Despite the fact that mutations changed the shape of the pocket and reduced the binding strength for all drugs, Peramivir was the only drug that formed interactions with the key residues at positions 119, 294 and 372 in the pocket of the triple N9 mutant, while Zanamivir demonstrated the lowest RMSD value (0.7 Å) with respect to the reference structure

Identification of antifungal targets based on computer modeling

Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host–pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools