Nanoparticles encapsulation

The small size along with the novel optical, electronic, and structural properties of nanoparticles that are not obtainable in discrete molecules or bulk solids, can be exploited to design customizable, targeted drug delivery systems capable of carrying different doses of drugs to the desired destination. Certain drugs can be carried as prodrugs or inactive drugs, which on reaching the target, can be converted to become active. Alternatively, the drugs in the nanoparticle form can be conjugated with the targeting moiety, leading to the accumulation of conjugated nanoparticles in the target site. As a result the concentration of the drug at the target can reach 10 to 100 times more than dosage obtained by the direct administration of the drug. Spurred by the launch of Abraxane as the first nanoparticle drug delivery system, researchers worldwide have put tremendous efforts into the development of nanoparticle-based drug carriers resulting in an exponential accumulation of novel nanoparticle systems and related research data. By the year 2014, there are 43 approved drug formulations which are marketed as nanopharmaceuticals. Many more nanotechnology-based systems are rapidly advancing towards preclinical and clinical trials for diagnosis and therapy. However, before propelling a new nanoparticle formulation from the bench to the bedside several challenges must first be addressed. Ideally, while in circulation, nanoparticle formulations should be stable and inert towards blood components. The carrier should protect the drug from systemic degradation while promoting controlled release properties at the target site. Additionally, the translation of promising nanodrug delivery systems can be accelerated with an improved understanding of various kinds of targeting moieties and biomarkers. The present lecture will focus on the recent advancements in nanoparticle-based drug delivery technology towards various target sites

Homology modeling of pyranose 2-oxidase from phanerochaete chrysosporium

Currently, most of the demand for energy relies on petroleum products. Nevertheless, the issues of energy security, economics and environment has led to the breakthrough of biofuel cells (BFCs) technology as one of the promising solution to the problems. However, the performance of BFCs need to be improved in order to compete with the existing technologies. One way to improve the efficiency of BFCs is to ensure that the enzyme used as the catalyst in BFCs, in this case, pyranose 2-oxidase (P2Ox) has better binding characteristic and more reactive. For this purpose, studies on three-dimensional (3-D) structure of P2Ox enzyme can offer insights on the structure-function correlations. Unfortunately, at present there is no available crystal structure of P2Ox from Phanerochaete chrysosporium (PcP2Ox). Thus, in this study homology modelling was used as the reliable alternative method to predict the 3-D structure of PcP2Ox enzyme and thus provide necessary information to improve the efficiency of the enzyme

Molecular dynamics approach in designing Thermostable Bacillus circulans Xylanase

We have applied molecular dynamics methods as a tool in designing thermostable Bacillus circulans Xylanase, by examining Root Mean Square Deviation (RMSD) of enzymes structure at its optimum temperature and compare with its high temperature behavior. As RMSD represents structural fluctuation at a particular temperature, a better understanding of this factor will suggest approaches to bioengineer these enzymes to enhance their thermostability. In this work molecular dynamic simulations of Bacillus circulans xylanase (BcX) have been carried at 318K (optimum catalytic temperature) and 343K (BcX reported inactive temperature). Structural analysis revealed that the fluctuations of the β-sheet regions are larger at higher temperatures compared to the fluctuations at optimum temperature

NGS-data analysis for netagenome cellulose- and Xylan- degrading enzymes finding

Abstract. For the aim of finding cellulose- and xylan-degrading enzymes needed in green industry to produce biofuel from plant biomass, a metagenomic DNA library from palm oil mill effluent (POME) was constructed and high-throughputly screened. The positive clones’ DNA were sequenced with next generation sequencing and raw data (short insert-paired) was analyzed with bioinformatic tools. First, the quality of 64.821.599 reverse and forward sequences of 101bp length raw data was identified using Fastqc. Then, raw data filtering was done by trimming low quality values and short reads and the vector sequences were removed and again the output was checked and the trimming was repeated until a high quality read sets was obtained. The second step was the de novo assembly of sequences to reconstruct 2900 contigs following de bruijn graph algorithm. Pre-assembled contigs were arranged in order, the distances between contigs were identified and oriented with SSPACE, where 2139 scaffolds have been reconstructed. 16386 genes have been identified after gene prediction using Prodigal and putative ID assignment with Blastp Vs NR protein. In these results, 17 cellulose-degrading enzymes and 2 xylan-degrading enzymes have been found. The genes encoding these enzymes will be recombinant to pBAD TOPO vector and cloned into TOP10 E. coli to express and characterize the enzymes for downstream processes. Key words: metagenomics, contig, scaffold, de novo assembly, de Bruijn, SSPACE, Prodigal, Blastp

Modification and characterization of phytases for animal feed production

Phytases catalyze the hydrolysis of inorganic phosphate from phytic acid and improve the nutritional quality of phytate rich diet. Monogastric animal such as poultry and fish do not have the ability to completely hydrolyze phytate. As a result, beneficial nutrient necessary for growth becomes unavailable and its elimination through excretions leads to land pollution, eutrophication of ground water and aquatic environment. Besides, it leads to the negative effect on vitamin utilization that lead to the emaciation, retarded growth and reproductive failure in animals. In view of these adverse effects phytases are added in animal feeds. Phytases from microbial sources are commonly used for their commercial exploitations. Waste water bacterium phytase is the subject of interest in this project. In the present study in-silico experiments are used to identify and examine active site of phytase.The factors influencing the ligand binding strength in the active site is analyzed and computational site directed mutagenesis experiments have been carried out to evaluate the effects of mutations on the binding strength. Compare to native enzyme, structural prediction suggest that single mutations at position M216R and E219R add hydrogen bonds surrounding the active site, which increases in the binding of the phytate substrate eventually leading to better degradation. Detailed results from out single and multiple mutation studies provide new direction towards design and development of new phytases with enhanced functional properties

Modeling the growth kinetics of Escherichia Coli fermentation in bioreactors

ABSTRACT The chapter focuses on the growth kinetics and modelling of recombinant Escherichia coli in fermentation processes. Experimental data for from four bioreactors were analyzed using Monod, Logistic and Contois models. A comparison between the models' predicted values of cell, substrate and product (β-glucuronidase enzyme) was done with the kinetic parameters mmax, YX/S, Ks, k1, and k2 calculated from the experimental data. Substrate used for this modelling was glucose while the independent variables were peptone soy, sodium chloride and yeast extract. The Logistic model is found to describe the growth of E. coli in the fermentation process with the limited supply of glucose and the Monod and Contois models failed to represent the cell growth profiles. Keywords: growth kinetics, modeling, recombinant E. coli, fermentation

Study of intraparticle diffusionreaction of substrate for Michaelis–Menten kinetics in a porous slab catalyst

The effect of internal diffusion on the overall reaction rate in a biocatalyst having slab geometry containing an immobilized enzyme or cells have been investigated theoretically. Zero-order, first-order and Michaelis-Menten kinetics were studied. The exact solutions for zero-order and first- order reactions were studied to verify our numerical algorithm which was later used to obtain solution for the Michaelis-Menten kinetic. The concentration profiles within the catalyst slab were obtained as a function of Thiele modulus which in turn were used to evaluate effectiveness factor. The exact solutions for zero and first order reactions can be obtained analytically. However one has to resort to numerical solution for Michaelis Menten kinetics as the resulting nonlinear differential equation cannot be solved analytically for the exact solution. Thus, for the Michaelis–Menten kinetics, the diffusion-reaction equation is solved using numerical method employing an explicit finite difference scheme which proved to be stable and accurate. A simple third order polynomial solution to the differential equation is also proposed. The approximate solution shows close agreement (error about less than 10%) with the numerical solution within the range of parameters of practical significance such as Thiele modulus values up to 8. Thus the approximate solution obtained in this work gives quite satisfactory results for a wide range of Thiele modulus compared to that reported in the literature. The nutrients diffuse deeper into the pellet with decreasing Thiele moduli for the three rate kinetics studied. The effectiveness factor decreases with increasing Thiele moduli which is in agreement with the trend in concentration profile for all the cases investigated and the range of parameters studied. Keywords: Diffusion-reaction; Michaelis–Menten kinetics; Immobilized slab biocatalyst; Finite difference method; Approximate solutio

Computer Aided Design of Polygalacturonase II from Aspergillus niger

Pectin is a complex polysaccharide found in the cell walls of plants and consisting mainly of esterified D-galacturonic acid resides in α-(1-4) chain. In production of fruit juice, pectin contributes to fruit juice viscosity, thereby reducing the juice production and increasing the filtration time. Polygalacturonase improves the juice production process by rapid degradation of pectin. In this project we have designed a novel polygalacturonase enzyme using computer aided design approaches. The three dimension structure of polygalacturonase is first modeled on the basis of the known crystal structure. The active site in this enzyme is identified by manual and automated docking methods. Lamarckian genetic algorithm is used for automated docking andthe active site is validated by comparing with existing experimental data. This is followed by in silico mutations of the enzymes and the automated docking process is repeated using the mutant enzymes. The strength of the binding of the ligands inside the active site is evaluated by computing the binding score using Potential Mean Force (PMF) method. The mutations R256Q, K258N and E252A show improvement of the binding score while N186E reduces the binding strength. The R256Q, K258N or E252A mutant enzymes can be used in the fruit juice industry to minimize the cost of juice productio

Homology Modeling Of β-Glucuronidases From E. Coli and T. Maritima

The enzyme β-Glucuronidases (GUS) which belongs to the glycoside hydrolase family of enzymes, can hydrolyze any aglycne conjugated to D-glucuronic acid through a β-O~glycosidic linkage. It is present in almost all tissues of vertebrates and their residentinal flora, including E. coli. However, GUS enzymes obtained from different sources have different stability towards heat, resistance to detergents and varying catalytic activities. A good understanding or the reasons for this variation can lead to designing new enzymes with desired level of property. having great prospect in the industry. For this purpose, studies on the three-dimensional structure of GUS enzyme can offer insights on the structure-function correlations, and provide information on the distribution or certain residues both in E. coli and T. maritima enzymes. The structures of GUS enzymes from E. coli and T. maritima are not known experimentally. As such in the current work, homology modeling or the three-dimensional structure of both variants of the GUS enzyme was carried out based on the solved crystal structure of Human GUS enzyme. Multiple sequence alignment for both enzyme sequences was carried out in order to locate the most suitable template for homology modeling and the models thus prepared were found to cotain 32-43% sequence identity with the template. Superposition of the model obtained with the template as well as structural alignment were carried out to classify the structural differences. This paper will also present an analysis and verification studies of the model based on various criteria. The current work offers a better understanding of the structural differences between GUS enzymes from different sources, as well as suggests regions for further modification using experimental and computational methods

Molecular dynamics studies of human β-Glucuronidase

Problem statement: The enzyme β-glucuronidase is being used as a reporter molecule in the area of genetic engineering, as a component of prodrug therapy in cancer treatment and in the scouring process of cotton fabrics. However, a detailed understanding of the factors responsible for the stability and the activity of this enzyme is still not available. Molecular Dynamics (MD) simulations provide an estimate of equilibrium and dynamic properties of enzyme systems that cannot be calculated analytically. With this perspective, molecular dynamics simulations of human β- glucuronidase (GUS) have been carried out to determine the behavior of this enzyme in vacuum and solvent environments at a defined temperature. Approach: CHARMM force field along with distance dependent dielectric model was used to represent the solvent environment in the MD simulations. The parameters employed in various stages of MD simulations had been selected based on repeated trials under various conditions as a method of choosing the optimum parameters for each stage. Results: It was found that simulations in vacuum caused the backbone of GUS to have smaller fluctuations from their mean values compared with the fluctuation in implicit solvent simulations, due to the fact that vacuum environment did not provide for the electrostatic interactions affecting the backbone of GUS that may otherwise exist in a solvent environment. Conclusion: Inclusion of solvent effects in MD simulations is crucial in understanding structural flexibility and stability of β-glucuronidase. Implicit solvent method can provide a realistic inclusion of backbone flexibility and structural compactness of GUS, which will have profound influence on the stability and activity of the enzymes, with a marginal increase in computational time