Structure Prediction,Evaluation, and Validation of GPR18 Lipid Receptor Using Free Programs

The GPR18 receptor, often referred to as the N-arachidonylglycine receptor, although assigned (along with GPR55 and GPR119) to the new class A GPCR subfamily-lipid receptors, officially still has the status of a class A GPCR orphan. While its signaling pathways and biological significance have not yet been fully elucidated, increasing evidence points to the therapeutic potential of GPR18 in relation to immune, neurodegenerative, and cancer processes to name a few. Therefore, it is necessary to understand the interactions of potential ligands with the receptor and the influence of particular structural elements on their activity. Thus, given the lack of an experimentally solved structure, the goal of the present study was to obtain a homology model of the GPR18 receptor in the inactive state, meeting all requirements in terms of protein structure quality and recognition of active ligands. To increase the reliability and precision of the predictions, different contemporary protein structure prediction methods and software were used and compared herein. To test the usability of the resulting models, we optimized and compared the selected structures followed by the assessment of the ability to recognize known, active ligands. The stability of the predicted poses was then evaluated by means of molecular dynamics simulations. On the other hand, most of the best-ranking contemporary CADD software/platforms for its full usability require rather expensive licenses. To overcome this down-to-earth obstacle, the overarching goal of these studies was to test whether it is possible to perform the thorough CADD experiments with high scientific confidence while using only license-free/academic software and online platforms. The obtained results indicate that a wide range of freely available software and/or academic licenses allow us to carry out meaningful molecular modelling/docking studies.     

Impact of Polypyridyl Ru Complexes on Angiogenesis—Contribution to Their Antimetastatic Activity

The use of polypyridyl Ru complexes to inhibit metastasis is a novel approach, and recent studies have shown promising results. We have reported recently that Ru (II) complexes gathering two 4,7-diphenyl-1,10-phenanthroline (dip) ligands and the one being 2,2′-bipyridine (bpy) or its derivative with a 4-[3-(2-nitro-1H-imidazol-1-yl)propyl (bpy-NitroIm) or 5-(4-{4′-methyl-[2,2′-bipyridine]-4-yl}but-1-yn-1-yl)pyridine-2-carbaldehyde semicarbazone (bpy-SC) moieties can alter the metastatic cascade, among others, by modulating cell adhesion properties. In this work, we show further studies of this group of complexes by evaluating their effect on HMEC-1 endothelial cells. While all the tested complexes significantly inhibited the endothelial cell migration, Ru-bpy additionally interrupted the pseudovessels formation. Functional changes in endothelial cells might arise from the impact of the studied compounds on cell elasticity and expression of proteins (vinculin and paxillin) involved in focal adhesions. Furthermore, molecular studies showed that complexes modulate the expression of cell adhesion molecules, which has been suggested to be one of the factors that mediate the activation of angiogenesis. Based on the performed studies, we can conclude that the investigated polypyridyl Ru (II) complexes can deregulate the functionality of endothelial cells which may lead to the inhibition of angiogenesis.     

Neural network for predicting the performance of credit card accounts

This paper reports the interim results of an experimental project using neural networks as a decision support tool for credit card risk assessment within a major bank. Two prototype neural network systems have been developed: one which emulates the decisions of the current risk assessment system, and another which attempts to predict the performance of credit card accounts based on the accounts historical data. This paper focuses on the development of the neural network model for credit card account performance prediction. The study has shown that such a tool can help in discovering the potential problems with credit card applicants at the very early stage of the credit account life cycle.     

Novel,solvent-based method for the production of polymer sheets with a superhydrophobic surface

We have introduced a novel solvent-based method to roughen polymer surfaces and characterized treated polypropylene (PP). The method consists of three main steps: solvent treatment, drying, and peeling. We investigated the effects of process parameters such as time of immersion in the solvent, solvent temperature, and drying temperature on the surface morphology created. The structure formed on the surface is mainly influenced by solvent temperature and drying temperature. We also characterized the wetting behavior of the surfaces. The patterned surfaces exhibit superhydrophobic characteristics with a high water contact angle (CA) (>155 °) and low water contact hysteresis (<5°). Adding an effective nucleating agent to PP makes it possible to generate outstanding CAs (>160°) and tailor spherulite sizes. The method is simple and scalable, therefore this superhydrophobic material is easy to mass-produce.     

Biofunctionalization of Metal–Organic Framework Nanoparticles via Combined Nitroxide-Mediated Polymerization and Nitroxide Exchange Reaction

Surface engineering of metal–organic framework nanoparticles (MOF NPs), and enabling their post-synthetic modulation that facilitates the formation of bio-interfaces has tremendous potential for diverse applications including therapeutics, imaging, biosensing, and drug-delivery systems. Despite the progress in MOF NPs synthesis, colloidal stability and homogeneous dispersity—a desirable property for biotechnological applications, stands as a critical obstacle and remains a challenging task. In this report, dynamic surfaces modification of MOF NPs with polyethylene glycol (PEG) polymer is described using grafting-from PEGylation by employing nitroxide-mediated polymerization (NMP) and inserting arginylglycylaspartic acid (RGD) peptides on the surface via a nitroxide exchange reaction (NER). The dynamic modification strategy enables tailoring PEG-grafted MOF NPs of the type UiO-66-NH₂ with improved colloidal stability, and high dispersity, while the morphology and lattice crystallinity are strictly preserved. The interaction of PEG-grafted MOF NPs with human serum albumin (HSA) protein under physiological conditions is studied. The PEG-grafted colloidal MOF NPs adsorb less HSA protein than the uncoated ones. Therefore, the described approach increases the scope of bio-relevant applications of colloidal MOF NPs by reducing nonspecific interactions using NMP based PEGylation, while preserving the possibility to introduce targeting moieties via NER for specific interactions.