Free energy landscape of siRNA-polycation complexation: Elucidating the effect of molecular geometry, polymer flexibility, and charge neutralization

The success of medical threatments with DNA and silencing interference RNA is strongly related to the design of efficient delivery technologies. Cationic polymers represent an attractive strategy to serve as nucleic-acid carriers with the envisioned advantages of efficient complexation, low cost, ease of production, well-defined size, and low polydispersity index. However, the balance between efficacy and toxicity (safety) of these polymers is a challenge and in need of improvement. With the aim of designing more effective polycationic-based gene carriers, many parameters such as carrier morphology, size, molecular weight, surface chemistry, and flexibility/rigidity ratio need to be taken into consideration. In the present work, the binding mechanism of three cationic polymers (polyarginine, polylysine and polyethyleneimine) to a model siRNA target is computationally investigated at the atomistic level. In order to better understand the polycationic carrier-siRNA interactions, replica exchange molecular dynamic simulations were carried out to provide an exhaustive exploration of all the possible binding sites, taking fully into account the siRNA flexibility together with the presence of explicit solvent and ions. Moreover, well-tempered metadynamics simulations were employed to elucidate how molecular geometry, polycation flexibility, and charge neutralization affect the siRNA-polycations free energy landscape in term of low-energy binding modes and unbinding free energy barriers. Significant differences among polymer binding modes have been detected, revealing the advantageous binding properties of polyarginine and polylysine compared to polyethyleneimine

Role of the Genetic Study in the Management of Carotid Body Tumor in Paraganglioma Syndrome

AbstractDiagnosis of carotid body tumor (CBT) was made in a 36 years old woman. The pre-operative examination included genetic analysis of the succinate dehydrogenase that showed a mutation in his subunit D responsible of multiple paraganglioma at slow growth. Subsequently a thoraco-abdominal CT and indium111 octreotide body scan were performed and another paraganglioma was detected in the anterior mediastinum. CBT was surgically removed; differently the thoracic lesion due to his benign genetic profile was not treated. During a 3-years follow-up the thoracic paraganglioma as expected, didn't increase. Genetic analysis of succinate dehydrogenase, should be performed in the management of CBT

Aminoacid substitutions in the glycine zipper affect the conformational stability of amyloid beta fibrils

The aggregation of amyloid-beta peptides is associated with the pathogenesis of Alzheimer’s disease. The hydrophobic core of the amyloid beta sequence contains a GxxxG repeated motif, called glycine zipper, which involves crucial residues for assuring stability and promoting the process of fibril formation. Mutations in this motif lead to a completely different oligomerization pathway and rate of fibril formation. In this work, we have tested G33L and G37L residue substitutions by molecular dynamics simulations. We found that both protein mutations may lead to remarkable changes in the fibril conformational stability. Results suggest the disruption of the glycine zipper as a possible strategy to reduce the aggregation propensity of amyloid beta peptides. On the basis of our data, further investigations may consider this key region as a binding site to design/discover novel effective inhibitors. Communicated by Ramaswamy H. Sarma

The role of structural polymorphism in driving the mechanical performance of the alzheimer's beta amyloid fibrils

Alzheimer's Disease (AD) is related with the abnormal aggregation of amyloid β-peptides Aβ1-40 and Aβ1-42, the latter having a polymorphic character which gives rise to U- or S-shaped fibrils. Elucidating the role played by the nanoscale-material architecture on the amyloid fibril stability is a crucial breakthrough to better understand the pathological nature of amyloid structures and to support the rational design of bio-inspired materials. The computational study here presented highlights the superior mechanical behavior of the S-architecture, characterized by a Young's modulus markedly higher than the U-shaped architecture. The S-architecture showed a higher mechanical resistance to the enforced deformation along the fibril axis, consequence of a better interchain hydrogen bonds' distribution. In conclusion, this study, focusing the attention on the pivotal multiscale relationship between molecular phenomena and material properties, suggests the S-shaped Aβ1-42 species as a target of election in computational screen/design/optimization of effective aggregation modulators

The impact of natural compounds on s-shaped aβ42 fibril: From molecular docking to biophysical characterization

The pursuit for effective strategies inhibiting the amyloidogenic process in neurodegenerative disorders, such as Alzheimer’s disease (AD), remains one of the main unsolved issues, and only a few drugs have demonstrated to delay the degeneration of the cognitive system. Moreover, most therapies induce severe side effects and are not effective at all stages of the illness. The need to find novel and reliable drugs appears therefore of primary importance. In this context, natural compounds have shown interesting beneficial effects on the onset and progression of neurodegenerative diseases, exhibiting a great inhibitory activity on the formation of amyloid aggregates and proving to be effective in many preclinical and clinical studies. However, their inhibitory mechanism is still unclear. In this work, ensemble docking and molecular dynamics simulations on S-shaped Aβ42 fibrils have been carried out to evaluate the influence of several natural compounds on amyloid conformational behaviour. A deep understanding of the interaction mechanisms between natural compounds and Aβ aggregates may play a key role to pave the way for design, discovery and optimization strategies toward an efficient destabilization of toxic amyloid assemblies

Protein environment: A crucial triggering factor in josephin domain aggregation: The role of 2,2,2-trifluoroethanol

The protein ataxin-3 contains a polyglutamine stretch that triggers amyloid aggregation when it is expanded beyond a critical threshold. This results in the onset of the spinocerebellar ataxia type 3. The protein consists of the globular N-terminal Josephin domain and a disordered C-terminal tail where the polyglutamine stretch is located. Expanded ataxin-3 aggregates via a two-stage mechanism: first, Josephin domain self-association, then polyQ fibrillation. This highlights the intrinsic amyloidogenic potential of Josephin domain. Therefore, much effort has been put into investigating its aggregation mechanism(s). A key issue regards the conformational requirements for triggering amyloid aggregation, as it is believed that, generally, misfolding should precede aggregation. Here, we have assayed the effect of 2,2,2-trifluoroethanol, a co-solvent capable of stabilizing secondary structures, especially α-helices. By combining biophysical methods and molecular dynamics, we demonstrated that both secondary and tertiary JD structures are virtually unchanged in the presence of up to 5% 2,2,2-trifluoroethanol. Despite the preservation of JD structure, 1% of 2,2,2-trifluoroethanol suffices to exacerbate the intrinsic aggregation propensity of this domain, by slightly decreasing its conformational stability. These results indicate that in the case of JD, conformational fluctuations might suffice to promote a transition towards an aggregated state without the need for extensive unfolding, and highlights the important role played by the environment on the aggregation of this globular domain

In silico Investigations of the Mode of Action of Novel Colchicine Derivatives Targeting β-Tubulin Isotypes: A Search for a Selective and Specific β-III Tubulin Ligand

The cardinal role of microtubules in cell mitosis makes them interesting drug targets for many pharmacological treatments, including those against cancer. Moreover, different expression patterns between cell types for several tubulin isotypes represent a great opportunity to improve the selectivity and specificity of the employed drugs and to design novel compounds with higher activity only on cells of interest. In this context, tubulin isotype βIII represents an excellent target for anti-tumoral therapies since it is overexpressed in most cancer cells and correlated with drug resistance. Colchicine is a well-known antimitotic agent, which is able to bind the tubulin dimer and to halt the mitotic process. However, it shows high toxicity also on normal cells and it is not specific for isotype βIII. In this context, the search for colchicine derivatives is a matter of great importance in cancer research. In this study, homology modeling techniques, molecular docking, and molecular dynamics simulations have been employed to characterize the interaction between 55 new promising colchicine derivatives and tubulin isotype βIII. These compounds were screened and ranked based on their binding affinity and conformational stability in the colchicine binding site of tubulin βIII. Results from this study point the attention on an amide of 4-chlorine thiocolchicine. This colchicine-derivative is characterized by a unique mode of interaction with tubulin, compared to all other compounds considered, which is primarily characterized by the involvement of the α-T5 loop, a key player in the colchicine binding site. Information provided by the present study may be particularly important in the rational design of colchicine-derivatives targeting drug resistant cancer phenotypes

Structure based modeling of small molecules binding to the TLR7 by atomistic level simulations

Toll-Like Receptors (TLR) are a large family of proteins involved in the immune system response. Both the activation and the inhibition of these receptors can have positive effects on several diseases, including viral pathologies and cancer, therefore prompting the development of new compounds. In order to provide new indications for the design of Toll-Like Receptor 7 (TLR7)-targeting drugs, the mechanism of interaction between the TLR7 and two important classes of agonists (imidazoquinoline and adenine derivatives) was investigated through docking and Molecular Dynamics simulations. To perform the computational analysis, a new model for the dimeric form of the receptors was necessary and therefore created. Qualitative and quantitative differences between agonists and inactive compounds were determined. The in silico results were compared with previous experimental observations and employed to define the ligand binding mechanism of TLR7

Chronic Intermittent Ethanol Regulates Hippocampal GABA(A) Receptor Delta Subunit Gene Expression.

Chronic ethanol consumption causes structural and functional reorganization in the hippocampus and induces alterations in the gene expression of gamma-aminobutyric acid type A receptors (GABAARs). Distinct forced intermittent exposure models have been used previously to investigate changes in GABAAR expression, with contrasting results. Here, we used repeated cycles of a Chronic Intermittent Ethanol paradigm to examine the relationship between voluntary, dependence-associated ethanol consumption, and GABAAR gene expression in mouse hippocampus. Adult male C57BL/6J mice were exposed to four 16-h ethanol vapor (or air) cycles in inhalation chambers alternated with limited-access two-bottle choice between ethanol (15%) and water consumption. The mice exposed to ethanol vapor showed significant increases in ethanol consumption compared to their air-matched controls. GABAAR alpha4 and delta subunit gene expression were measured by qRT-PCR at different stages. There were significant changes in GABAAR delta subunit transcript levels at different time points in ethanol-vapor exposed mice, while the alpha4 subunit levels remained unchanged. Correlated concurrent blood ethanol concentrations suggested that GABAAR delta subunit mRNA levels fluctuate depending on ethanol intoxication, dependence, and withdrawal state. Using a vapor-based Chronic Intermittent Ethanol procedure with combined two-bottle choice consumption, we corroborated previous evidences showing that discontinuous ethanol exposure affects GABAAR delta subunit expression but we did not observe changes in alpha4 subunit. These findings indicate that hippocampal GABAAR delta subunit expression changes transiently over the course of a Chronic Intermittent Ethanol paradigm associated with voluntary intake, in response to ethanol-mediated disturbance of GABAergic neurotransmission

Neuraghe: Exploiting CPU-FPGA synergies for efficient and flexible CNN inference acceleration on zynQ SoCs

Deep convolutional neural networks (CNNs) obtain outstanding results in tasks that require human-level understanding of data, like image or speech recognition. However, their computational load is significant, motivating the development of CNN-specialized accelerators. This work presents NEURAghe, a flexible and efficient hardware/software solution for the acceleration of CNNs on Zynq SoCs. NEURAghe leverages the synergistic usage of Zynq ARM cores and of a powerful and flexible Convolution-Specific Processor deployed on the reconfigurable logic. The Convolution-Specific Processor embeds both a convolution engine and a programmable soft core, releasing the ARM processors from most of the supervision duties and allowing the accelerator to be controlled by software at an ultra-fine granularity. This methodology opens the way for cooperative heterogeneous computing: While the accelerator takes care of the bulk of the CNN workload, the ARM cores can seamlessly execute hard-to-accelerate parts of the computational graph, taking advantage of the NEON vector engines to further speed up computation. Through the companion NeuDNN SW stack, NEURAghe supports end-to-end CNN-based classification with a peak performance of 169GOps/s and an energy efficiency of 17GOps/W. Thanks to our heterogeneous computing model, our platform improves upon the state-of-the-art, achieving a frame rate of 5.5 frames per second (fps) on the end-to-end execution of VGG-16 and 6.6fps on ResNet-18