ANTI-CORROSION COATINGS PRODUCED FROM ORGANOSILICON COMPOUNDS

Abstract

A series of tetra-alkoxy, tetra-phenoxy and tri-alkylaryl silanes compounds were prepared neatly to be tested as corrosion inhibitors for carbon-steel alloys. Following the standard procedure, specimens from the carbon-steel alloy were prepared and divided into pairs. The surface of each pair was thinly coated with one of the above organosilicon compounds. From each pair; a specimen was thermally treated at a temperature of 750°C for ten minutes, while the other was left at ambient temperature for 3 days. The physical properties such as; electrical conductivity, surface morphology, composition, structure and degree of coherence of each residual film were measured and investigated by using; digital potentiometer, SEM, EDS, X-ray diffraction and SEM edged cross-section micrograph respectively. From the outcoming data it was noticed that, the specimens coated with tetra-phenoxysilane produed (at the two extreme temperatures) needle shaped silicon dioxide films which varied in their physical properties. However, it is believed that the optimum properties could be achieved by adjusting the temperature and thermal treatment time ranges individually. Although, the occurrence percentage of silicon metal in the tetra-alkoxysilane series were higher than that in the tetra-phenoxysilane, discrete and very thin silicon dioxide films were formed. This could be attributed to the low volatile silica and boiling points of tetra-alkoxysilane.     

Determination of melagatran in rabbit plasma by high-performance liquid chromatography with automated column switching

Melagatran is an active thrombin inhibitor showing oral and parenteral bioavailability for antithrombotic therapy. A simple and convenient liquid chromatographic method has been developed and applied to the analysis of melagatran in rabbit plasma. The clean-up and separation of the sample solutions were performed by automated on-line column switching HPLC. The method validation shows the suitability of the column switching liquid chromatographic system for the quantitation of melagatran in biological fluids.     

采用超低场生物力谱技术研究核酸适配体与凝血酶蛋白的相互作用

蛋白质和核酸是构成生命体最为重要的两类生物大分子,它们之间的相互作用是分子生物学研究的中心问题之一,也是许多生命活动的重要组成部分。本文基于一种全新的超低场生物力谱技术,以凝血酶蛋白为研究对象,考察了凝血酶与其对应的核酸适配体之间的相互作用。结果表明,凝血酶蛋白与核酸适配体之间的结合力大小约为80 p N。同时,在分子水平上获得了凝血酶蛋白与核酸适配体之间的解离动力学信息。     

Unsupervised guided docking of covalently bound ligands

Summary An approach for docking covalently bound ligands in protein enzymes or receptors was implemented in MacDOCK, a similarity-driven docking program based on DOCK 4.0. This approach was tested with a small number of covalent ligand–protein structures, using both native and non-native protein structures. In all cases, MacDOCK was able to generate orientations consistent with the known covalent binding mode of these complexes, with a performance similar to that of other docking programs. This method was also applied to search for known covalent thrombin inhibitors in a medium-sized molecular database (ca. 11,000 compounds). Detection of functional groups suitable for covalent docking was carried out automatically. A significant enrichment in known active molecules in the first 5% of the database was obtained, showing that MacDOCK can be used efficiently for the virtual screening of covalently bound ligands.     

Comparison of two implementations of the incremental construction algorithm in flexible docking of thrombin inhibitors

A set of 32 known thrombin inhibitors representing different chemical classes has been used to evaluate the performance of two implementations of incremental construction algorithms for flexible molecular docking: DOCK 4.0 and FlexX 1.5. Both docking tools are able to dock 10–35% of our test set within 2 Å of their known, bound conformations using default sampling and scoring parameters. Although flexible docking with DOCK or FlexX is not able to reconstruct all native complexes, it does offer a significant improvement over rigid body docking of single, rule-based conformations, which is still often used for docking of large databases. Docking of sets of multiple conformers of each inhibitor, obtained with a novel protocol for diverse conformer generation and selection, yielded results comparable to those obtained by flexible docking. Chemical scoring, which is an empirically modified force field scoring method implemented in DOCK 4.0, outperforms both interaction energy scoring by DOCK and the Böhm scoring function used by FlexX in rigid and flexible docking of thrombin inhibitors. Our results indicate that for reliable docking of flexible ligands the selection of anchor fragments, conformational sampling and currently available scoring methods still require improvement.     

Distilling the essential features of a protein surface for improving protein-ligand docking,scoring, and virtual screening

For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand candidate, it is important to place these points where the best interactions can be made between the protein and the ligand. This definition of favorable points of interaction can also guide protein structure-based ligand design, which typically focuses on which chemical groups provide the most energetically favorable contacts. In this paper, we present an alternative method of protein template and ligand interaction point design that identifies the most favorable points for making hydrophobic and hydrogen–bond interactions by using a knowledge base. The knowledge-based protein and ligand representations have been incorporated in version 2.0 of SLIDE and resulted in dockings closer to the crystal structure orientations when screening a set of 57 known thrombin and glutathione S–transferase (GST) ligands against the apo structures of these proteins. There was also improved scoring enrichment of the dockings, meaning better differentiation between the chemically diverse known ligands and a 15,000-molecule dataset of randomly-chosen small organic molecules. This approach for identifying the most important points of interaction between proteins and their ligands can equally well be used in other docking and design techniques. While much recent effort has focused on improving scoring functions for protein-ligand docking, our results indicate that improving the representation of the chemistry of proteins and their ligands is another avenue that can lead to significant improvements in the identification, docking, and scoring of ligands.(These authors contributed equally to this work)     

Ensembling machine learning models to boost molecular affinity prediction

This study unites six popular machine learning approaches to enhance the prediction of a molecular binding affinity between receptors (large protein molecules) and ligands (small organic molecules). Here we examine a scheme where affinity of ligands is predicted against a single receptor – human thrombin, thus, the models consider ligand features only. However, the suggested approach can be repurposed for other receptors. The methods include Support Vector Machine, Random Forest, CatBoost, feed-forward neural network, graph neural network, and Bidirectional Encoder Representations from Transformers. The first five methods use input features based on physico-chemical properties of molecules, while the last one is based on textual molecular representations. All approaches do not rely on atomic spatial coordinates, avoiding a potential bias from known structures, and are capable of generalizing for compounds with unknown conformations. Within each of the methods, we have trained two models that solve classification and regression tasks. Then, all models are grouped into a pipeline of two subsequent ensembles. The first ensemble aggregates six classification models which vote whether a ligand binds to a receptor or not. If a ligand is classified as active (i.e., binds), the second ensemble predicts its binding affinity in terms of the inhibition constant K_i.     

Immobilized enzymes and cells in poly(N-vinyl caprolactam)-based hydrogels

A one-step mild method for entrapping animal cells and enzymes in macroporous composite poly (N-vinyl caprolactam)-calcium alginate (PVCL-CaAlg) hydrogels is described. Some properties of immobilized enzymes, such as thermal and storage stabilities and stability in water/organic media were investigated. Composite PVCL-CaAlg gels were successfully applied to immobilize a number of proteases, namely, trypsin, α-chymotrypsin, carboxypeptidase B, and thrombin. Thermal stability of the immobilized preparations obtained by entrapment in hydrogel beads allowed us to use them at 65–80†C, while the native enzymes were completely inactivated at 50–55°C. Various applications of enzymes and cells immobilized in beads weredemonstrated. Immobilized trypsin and carboxypeptidase B were applied to prepare human insulin from recombinant proinsulin. The hydrogel beads with entrapped α-chymotrypsin were used in enantioselective hydrolysis of Shiff's base of D,L-phenylalanine ethyl ester (SBPH) in acetonitrile/water medium. Thrombin immobilized in PVCL-based hydrogel films was shown to be a promising compound for wound treatment. To prepare pure preparations of monoclonal antibodies (MAb) several hybridoma cell lines, including hybridoma cell lines producing MAb to interleukin-2, were successfully cultivated in the hydrogel beads.     

The Potency of Seaweed Sulfated Polysaccharides for the Correction of Hemostasis Disorders in COVID-19

Hemostasis disorders play an important role in the pathogenesis, clinical manifestations, and outcome of COVID-19. First of all, the hemostasis system suffers due to a complicated and severe course of COVID-19. A significant number of COVID-19 patients develop signs of hypercoagulability, thrombocytopenia, and hyperfibrinolysis. Patients with severe COVID-19 have a tendency toward thrombotic complications in the venous and arterial systems, which is the leading cause of death in this disease. Despite the success achieved in the treatment of SARS-CoV-2, the search for new effective anticoagulants, thrombolytics, and fibrinolytics, as well as their optimal dose strategies, continues to be relevant. The wide therapeutic potential of seaweed sulfated polysaccharides (PSs), including anticoagulant, thrombolytic, and fibrinolytic activities, opens up new possibilities for their study in experimental and clinical trials. These natural compounds can be important complementary drugs for the recovery from hemostasis disorders due to their natural origin, safety, and low cost compared to synthetic drugs. In this review, the authors analyze possible pathophysiological mechanisms involved in the hemostasis disorders observed in the pathological progression of COVID-19, and also focus the attention of researchers on seaweed PSs as potential drugs aimed to correction these disorders in COVID-19 patients. Modern literature data on the anticoagulant, antithrombotic, and fibrinolytic activities of seaweed PSs are presented, depending on their structural features (content and position of sulfate groups on the main chain of PSs, molecular weight, monosaccharide composition and type of glycosidic bonds, the degree of PS chain branching, etc.). The mechanisms of PS action on the hemostasis system and the issues of oral bioavailability of PSs, important for their clinical use as oral anticoagulant and antithrombotic agents, are considered. The combination of the anticoagulant, thrombolytic, and fibrinolytic properties, along with low toxicity and relative cheapness of production, open up prospects for the clinical use of PSs as alternative sources of new anticoagulant and antithrombotic compounds. However, further investigation and clinical trials are needed to confirm their efficacy.