Deciphering effectual binding potential of xylo-substrates towards xylose isomerase and xylokinase through molecular docking and molecular dynamic simulation

Xylooligosaccharide interferes with the cell cycle and reduces the antibiotic tolerance of avian pathogenic Escherichia coli by associating with its potential antimetabolic actions

This study aimed to probe if xylooligosaccharide (XOS) could act as an antimetabolite to impact the cell cycle and antibiotic tolerance of avian pathogenic Escherichia coli (APEC). We firstly measured the bacteriostasis of XOS against APEC O78 and its effect on the growth of APEC O78 growing on different medium. Afterwards, the effects of XOS on xylose operon activation along with the cell cycle and antibiotic tolerance of APEC O78 were analyzed. The results showed that XOS caused no inhibitory circle against APEC O78 and did not affect (P > 0.05) the growth of APEC O78 growing on LB medium. Besides, APEC O78 was unable to grow on M9 medium (carbon-free) added with XOS. However, XOS exerted a similar role as xylose in increasing (P < 0.05) the expression of certain xylose operon genes including xylose isomerase (XylA)-encoding gene (xylA) and xylose-binding periplasmic protein (XylF)-encoding gene (xylF) in APEC O78. The molecular docking simulation revealed that the major monomer components (xylobiose, xylotriose and xylotetraose) of XOS had stable binding potentials to both XylA and XylF proteins of E. coli, as supported by the low binding free energy and the formation of considerable hydrogen bonds between them. The subsequent analysis showed that XOS altered certain cell cycle-related genes expression, especially elevated (P < 0.05) nrdB expression and decreased ihfB expression to a degree. Moreover, XOS played a similar role as 2-deoxy-glucose (a glucose analogue serving as a typical antimetabolite) in lowering (P < 0.05) the number of ampicillin-tolerant APEC O78. Collectively, XOS had no direct bacteriostasis against APEC and could not be metabolized/utilized by APEC O78. However, it might become an analogue of xylose and then activate xylose transport- and metabolism-related proteins in APEC O78, thus functioning as a potential antimetabolite and exerting antimetabolic actions. This could at least partially interpret the observed roles of XOS in interfering with the cell cycle and diminishing the antibiotic tolerance of APEC O78. The above findings expand the knowledges about the functions of XOS and provide a basis for exploring novel strategies to reduce the antibiotic tolerance of APEC.

Study on the structure-activity relationship of rice immunopeptides based on molecular docking

Research on food-derived immunoregulatory peptides has attracted increasing attention of scientists worldwide. However, the structure-activity relationship of rice immunopeptides was not clearly. Herein, 114 rice immunopeptides were obtained by simulating the enzymatic hydrolysis of rice proteins and were further analyzed by NetMHCIipan-4.0. Subsequently, the molecular docking was used to simulate the binding of immunoreactive peptides to major histocompatibility complex class II (MHC-II) molecules. Results show that S, R, D, E, and T amino acid could easily form hydrogen bonds with MHC-II molecules, thus enhancing innate and adaptive immunity. Finally, glucose-modified rice immunopeptides were to investigate the binding of the peptides with MHC-II molecules after glycosylation modification; this provided a theoretical basis for the targeted modification of the generated immunopeptides. All in all, the present study provides a theoretical foundation to further utilize rice processing byproducts and other food products to enhance immunity.

Research and study of 2-((4,6 dimethyl pyrimidine-2-yle) thio)-N-phenyl acetamide derivatives as inhibitors of sirtuin 2 protein for the treatment of cancer using QSAR, molecular docking and molecular dynamic simulation

Phenyl acetamide derivatives have a wide range of biological activities, so their research and development can be useful and effective for the design production of new drugs. In this project, quantitative structure-activity relationship (QSAR) was performed. For modeling two methods of multiple linear regression (MLR) and nonlinear regression of support vector machine (SVR) were used. In the MLR stage, the best model with the values of R²_train = 0.913 and R²_test = 0.881 was selected by stepwise method. In this model, 4 descriptors of BELV2, GATS8p, GATS6e and RDF080m were included, which were used as input for the nonlinear support vector regression method. In the SVR model, the best results were obtained using the radial Gaussian kernel function (RBF) with R²_train = 0.978 and R²_test = 0.990. In the next step, using molecular docking and molecular dynamic simulation methods, the interaction between phenyl acetamide derivatives and the sirtuin 2 protein was investigated. Examining the results of molecular docking, it was observed that these derivatives formed complexes by forming hydrogen and hydrophobic bonds with the sirtuin 2 protein. Also, the results of molecular dynamic simulation show that phenyl acetamide compounds form stable complex with the sirtuin 2 protein, and it was found that the compounds with more activity have formed a number of hydrogen bonds with the protein.

Multi-Objective Optimization Through Machine Learning Modeling for Production of Xylooligosaccharides from Alkali-Pretreated Corn-Cob Xylan Via Enzymatic Hydrolysis

The hemicellulose content present in corn cobs can help in producing a high amount of xylooligosaccharides (XOS) in an eco-friendly manner. In this work, the XOS was produced from alkali pre-treated corn-cobs having a true yield of 38 ± 1.4% via enzymatic hydrolysis with the help of xylanase from T. lanuginosus VAPS-24. The production process was optimized to achieve a high concentration of XOS using innovative multi-objective optimization through machine learning modeling and finding out the most suitable parameters where xylobiose production is higher than xylose. The Multi-objective connected neural networks (MOCNN) model with tangent sigmoid activation function yielded a correlation coefficient of 96.51%; there were six optimal sets where xylobiose concentration was higher than xylose. The best-optimized conditions yielded 3.03 mg/ml of xylobiose and 1.31 mg/ml of xylose. Therefore, this novel approach of machine learning can target the increasing demand for xylooligosaccharides in the growing industrial market of prebiotics.

Understanding the Xylooligosaccharides Utilization Mechanism of Lactobacillus brevis and Bifidobacterium adolescentis: Proteins Involved and Their Conformational Stabilities for Effectual Binding

Xylooligosaccharides having various degrees of polymerization such as xylobiose, xylotriose, and xylotetraose positively affect human health by interacting with gut proteins. The present study aimed to identify proteins present in gut microflora, such as xylosidase, xylulokinase, etc., with the help of retrieved whole-genome annotations and find out the mechanistic interactions of those with the above substrates. The 3D structures of proteins, namely Endo-1,4-beta-xylanase B (XynB) from Lactobacillus brevis and beta-D-xylosidase (Xyl3) from Bifidobacterium adolescentis, were computationally predicted and validated with the help of various bioinformatics tools. Molecular docking studies identified the effectual binding of these proteins to the xylooligosaccharides, and the stabilities of the best-docked complexes were analyzed by molecular dynamic simulation. The present study demonstrated that XynB and Xyl3 showed better effectual binding toward Xylobiose with the binding energies of - 5.96 kcal/mol and - 4.2 kcal/mol, respectively. The interactions were stabilized by several hydrogen bonding having desolvation energy (- 6.59 and - 7.91). The conformational stabilities of the docked complexes were observed in the four selected complexes of XynB-xylotriose, XynB-xylotetraose, Xyl3-xylobiose, and Xyn3-xylotriose by MD simulations. This study showed that the interactions of these four complexes are stable, which means they have complex metabolic activities among each other. Extending these studies of understanding, the interaction between specific probiotics enzymes and their ligands can explore the detailed design of synbiotics in the future.