New molecular dynamics (MD) simulations and experimental data on a deep eutectic solvent, propeline, composed by choline chloride, ChCl, and propylene glycol, PG, in a molar ratio of 1:2 are reported in this work. The experimental physicochemical properties (density, viscosity and self-diffusion coefficients) were used as support in the development of a new OPLS based force field model (FFM) for propeline. Validation of the new force field was established both through measuring physicochemical properties over a range of temperatures (298.15-373.15 K) and by comparison with experimental and simulated data of ethaline (ChCl:ethylene glycol, at a molar ration of 1:2). Classical MD simulations using the new FFM led to good agreement between experimental and simulated data. Structural properties, namely radial and spatial distribution functions, coordination numbers, and hydrogen bonding were analyzed. Moreover, it was found that the interactions between the anion, Cl-, and the hydrogen bond donor (HBD) form a network that is immutable with increasing temperature. The higher prevalence of anion-HBD hydrogen bonds is likely the major reason for the relatively high viscosity of propeline.

Background: Bioremediation is a biotechnology field that uses living organisms to remove contaminants from soil and water; therefore, they could be used to treat oil spills from the environment. Methods: Herein, we present a new mechanistic approach combining Molecular Docking Simulation and Density Functional Theory to modeling the bioremediation-based nanointeractions of a heterogeneous mixture of oil-derived hydrocarbons by using pristine and oxidized graphene nanostructures and the substrate-specific transport protein (TodX) from Pseudomonas putida. Results: The theoretical evidences pointing that the binding interactions are mainly based on noncovalent bonds characteristic of physical adsorption mechanism mimicking the "Trojan-horse effect". Conclusion: These results open new horizons to improve bioremediation strategies in over-saturation conditions against oil-spills and expanding the use of nanotechnologies in the context of environmental modeling health and safety

Herein, we evaluated the interactions between the zig-zag-single-walled carbon nanotube (z-z-SWCNT (8.0)) and the ATP-entry-point of the human mitochondrial voltage-dependent anion-selective channel (hVDAC1). For this purpose, both molecular docking and molecular dynamics simulations were performed. The flexibility properties of the referred ATP-entry-point was efficiently modeled using crystallographic validation-based on Ramachandran plot. The preferred conformations obtained for this segment were able to establish very favorable interactions with the ligands (ATP and z-z-SWCNT). Next, using both molecular docking and molecular dynamics simulations, we demonstrated that z-z-SWCNT can directly prevent the ATP-transition from its first entry-point residue (MET1). We suggested that the associated z-z-SWCNT aggregation can be responsible by avoiding the natural biochemical steps for the ATP-transport, according to a nanotoxicity mechanism based on hydrophobic interactions. The docking free energy of z-z-SWCNT/hVDAC1 and ATP/hVDAC1 complexes was remarkably close, according to local perturbation maps of the catalytic residues' cluster (i.e. MET1, ARG2, GLY3, SER4,ALA5). On the other hand, the results of molecular dynamics simulations match the ones of the docking simulations, reinforcing the hVDAC1 channel nanotoxicity hypothesis. Overall, the obtained results could open new opportunities towards the rational design of new carbon nanomaterials and in silico mitotarget drug-discovery.

Functionalizing graphene with polymers is an important area of research, owing to the potential applications of graphene in biomedicine and nanotechnology. In this paper, we investigate the covalent functionalization of graphene with a G2 poly(amidoamine) (PAMAM) dendrimer using all atom molecular dynamics simulations. Specifically, we study the dependence of the grafting approach (grafting-from and grafting-to) and the binding location of the PAMAM dendrimer to graphene (top, edge, and top-edge), on the functionalization. The instantaneous snapshots and the thickness profiles of the equilibrated dendrimer-graphene complexes reveal that the thickness of the adsorbed dendrimer is more in the grafting-to case. We have also observed that the edge-binding dendrimers of grafting-from approach can coat the graphene on either of its sides, whereas the top-binding dendrimers adsorb mostly on the side of their binding. In addition to the grafting approach and the binding location, we find that the dimension of the graphene sheet also determines the extent of surface coverage by the dendrimer. From the radii of gyration analysis and the thickness profiles of the dendrimers, we illustrate that an increase in the sheet dimensions gives rise to smoother surface coverage, whereas increasing the grafting density results in rough surface coverage. We also find that the percentage of surface coverage is higher in the grafting-to approach when compared with the grafting-from method, for a given binding condition and sheet dimensions. Our results on the dispersion of the functionalized graphene in water suggest that the dispersion of graphene depends on its surface coverage and is more probable with the grafting-from approach. Furthermore, our results on the interaction of functionalized graphene with a dimyristoylphosphatidylcholine (DMPC) lipid membrane demonstrate no bilayer disruption, hence illustrating the noncytotoxicity of the graphene-dendrimer complex.

Introduction: Monoamine oxidase inhibitors (MAOIs) are compounds largely used in the treatment of Parkinson's disease (PD), Alzheimer's disease and other neuropsychiatric disorders since they are closely related to the MAO enzymes activity. The two isoforms of the MAO enzymes, MAO-A and MAO-B, are responsible for the degradation of monoamine neurotransmitters and due to this, relevant efforts have been devoted to finding new compounds with more selectivity and less side effects. One of the most used approaches is based on the use of computational approaches since they are time and money-saving and may allow us to find a more relevant structure-activity relationship. Objective: In this manuscript, we will review the most relevant computational approaches aimed at the prediction and development of new MAO inhibitors. Subsequently, we will also introduce a new multitask model aimed at predicting MAO-A and MAO-B inhibitors. Methods: The QSAR multi-task model herein developed was based on the use of the linear discriminant analysis. This model was developed gathering 5,759 compounds from the public dataset Chembl. The molecular descriptors used was calculated using the Dragon software. Classical statistical tests were performed to check the validity and robustness of the model. Results: The herein proposed model is able to correctly classify all the 5,759 compounds. All the statistical performed tests indicated that this model is robust and reproducible. Conclusion: MAOIs are compounds of large interest since they are largely used in the treatment of very serious illness. These inhibitors may lose efficacy and produce severe side effects. Due to this, the development of selective MAO-A or MAO-B inhibitors is crucial for the treatment of these diseases and their effects. The herein proposed multi-target QSAR model may be a relevant tool in the development of new and more selective MAO inhibitors.

Higher Education Student burnout is an increasingly educational and social concern. The problem is complex and multilayered, demanding new approaches in predicting hazardous situations that can lead to the demise of the mental and physical well-being of the students. This work proposes a new model that can be used to predict and prevent such educational and/or social scenarios, resourcing to new tools, as the Reductio ad dystopia and speculative data. It departs from recent social quantum-based models and selected speculative literature works while introducing the use of social network theory to add the time variable to the model. The results clearly indicate that speculative and real scenarios can be juxtaposed in such a model, and concludes that a time interval for predicting the occurrence of the problem can be one of its advantages. © This work is licensed under a Creative Commons License CC BY-NC-ND 4.0

Though in the past online learning was considered of poorer professional quality than classroom learning, it has become a useful and, in some cases, vital tool for promoting the inclusivity of education. Some of its benefits include allowing greater accessibility to educational resources previously unattainable by those in rural areas, and in current times, it has proven to be a critical asset as universities shut down due to natural disasters and pandemics. Examining the current state of distance learning and determining online assessment tools and processes that can enhance the online learning experience are clearly crucial for the advancement of modern education. The Handbook of Research on Determining the Reliability of Online Assessment and Distance Learning is a collection of pioneering investigations on the methods and applications of digital technologies in the realm of education. It provides a clear and extensive analysis of issues regarding online learning while also offering frameworks to solve these addressed problems. Moreover, the book reviews and evaluates the present and intended future of distance learning, focusing on the societal and employer perspective versus the academic proposals. While highlighting topics including hybrid teaching, blended learning, and telelearning, this book is ideally designed for teachers, academicians, researchers, educational administrators, and students. © 2021 by IGI Global. All rights reserved.