Liqin Du

Multiple field three dimensional quantitative structure–activity relationship (MF-3D-QSAR)

A new drug design method, the multiple field three‐dimensional quantitative structure–activity relationship (MF‐3D‐QSAR), is proposed. It is a combination and development of classical 2D‐QSAR and traditional 3D‐QSAR. In addition to the electrostatic and van der Waals potentials, more potential fields (such as lipophilic potential, hydrogen bonding potential, and nonthermodynamic factors) are integrated in the MF‐3D‐QSAR. Meanwhile, a principal component analysis (PCA) and iterative double least square (IDLS) technique is developed for predicting the bioactivity of query drug candidates. As an example, the MF‐3D‐QSAR is applied to the design of neuraminidase inhibitor and to prove its predictive power, and some useful findings are obtained for developing drugs against influenza virus.

Fragment-based quantitative structure–activity relationship (FB-QSAR) for fragment-based drug design

In cooperation with the fragment‐based design a new drug design method, the so‐called “fragment‐based quantitative structure–activity relationship” (FB‐QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two‐dimensional quantitative structure–activity relationship (2D‐QSAR) is a special case, in the FB‐QSAR, when the whole molecule is treated as one entity. The FB‐QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB‐QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus.

Expression and characterization of a novel highly glucose-tolerant β-glucosidase from a soil metagenome

A β-glucosidase gene unbgl1A was isolated by the function-based screening of a metagenomic library and the enzyme protein was expressed in Escherichia coli, purified, and biochemically characterized. The enzyme Unbgl1A had a Km value of 2.09 ± 0.31 mM, and a Vmax value of 183.90 ± 9.61 μmol min(-1) mg(-1) under the optimal reaction conditions, which were pH 6.0 at 50°C. Unbgl1A can be activated by a variety of monosaccharides, disaccharides, and NaCl, and exhibits a high level of stability at high concentration of NaCl. Two prominent features for this enzyme are: (i) high glucose tolerance. It can be tolerant to glucose as high as 2000 mM, with Ki = 1500 mM; (ii) high NaCl tolerance. Its activity is not affected by 600 mM NaCl. The enzyme showed transglucosylation activities resulting in the formation of cellotriose from cellobiose. These properties of Unbgl1A should have important practical implication in its potential applications for better industrial production of glucose or bioethanol started from lignocellulosic biomass.

Saturation-mutagenesis in two positions distant from active site of a Klebsiella pneumoniae glycerol dehydratase identifies some highly active mutants

Synthesis of 1,3-propanediol (1,3-PD) from glycerol through the biotransformation process requires two steps, catalyzed by glycerol dehydratase (GDHt) and 1,3-PD oxidoreductase. GDHt is the rate-limiting enzyme in this process. All recombinant microorganisms for production of 1,3-PD so far utilized the natural genes that may not have been optimized. Two positions, which are 19.3A and 29.6A away from the active site in GDHt from Klebsiella pneumoniae, were subjected to saturation-mutagenesis and 38 mutants were characterized. The catalytic activity of a mutant in beta-subunit (beta-Q42F, 29.6A from the active site) was 8.3-fold higher than the wild type, and the enzyme efficiency of other two mutants beta-Q42L and beta-Q42S for substrate glycerol was 336-fold and 80-fold higher than that for 1,2-propanediol. This investigation supplied further evidence that distant mutations could be a good source of diversity and therefore, made a contribution to the toolbox of industrial enzyme improvement.

Characterization of an invertase with pH tolerance and truncation of its N-terminal to shift optimum activity toward neutral pH.

Most invertases identified to date have optimal activity at acidic pH, and are intolerant to neutral or alkaline environments. Here, an acid invertase named uninv2 is described. Uninv2 contained 586 amino acids, with a 100 amino acids N-terminal domain, a catalytic domain and a C-terminal domain. With sucrose as the substrate, uninv2 activity was optimal at pH 4.5 and at 45°C. Removal of N-terminal domain of uninv2 has shifted the optimum pH to 6.0 while retaining its optimum temperaure at 45°C. Both uninv2 and the truncated enzyme retained highly stable at neutral pH at 37°C, and they were stable at their optimum pH at 4°C for as long as 30 days. These characteristics make them far superior to invertase from Saccharomyces cerevisiae, which is mostly used as industrial enzyme.

Succinic acid production from duckweed (Landoltia punctata) hydrolysate by batch fermentation of Actinobacillus succinogenes GXAS137.

Duckweed is potentially an ideal succinic acid (SA) feedstock due to its high proportion of starch and low lignin content. Pretreatment methods, substrate content and nitrogen source were investigated to enhance the bioconversion of duckweed to SA and to reduce the costs of production. Results showed that acid hydrolysis was an effective pretreatment method because of its high SA yield. The optimum substrate concentration was 140g/L. The optimum substrate concentration was 140g/L. Corn steep liquor powder could be considered a feasible and inexpensive alternative to yeast extract as a nitrogen source. Approximately 57.85g/L of SA was produced when batch fermentation was conducted in a 1.3L stirred bioreactor. Therefore, inexpensive duckweed can be a promising feedstock for the economical and efficient production of SA through fermentation by Actinobacillus succinogenes GXAS137.

Structure-Based and Multiple Potential Three-Dimensional Quantitative Structure–Activity Relationship (SB-MP-3D-QSAR) for Inhibitor Design

The inhibitions of enzymes (proteins) are determined by the binding interactions between ligands and targeting proteins. However, traditional QSAR (quantitative structure-activity relationship) is a one-side technique, only considering the structures and physicochemical properties of inhibitors. In this study, the structure-based and multiple potential three-dimensional quantitative structure-activity relationship (SB-MP-3D-QSAR) is presented, in which the structural information of host protein is involved in the QSAR calculations. The SB-MP-3D-QSAR actually is a combinational method of docking approach and QSAR technique. Multiple docking calculations are performed first between the host protein and ligand molecules in a training set. In the targeting protein, the functional residues are selected, which make the major contribution to the binding free energy. The binding free energy between ligand and targeting protein is the summation of multiple potential energies, including van der Waals energy, electrostatic energy, hydrophobic energy, and hydrogen-bond energy, and may include nonthermodynamic factors. In the foundational QSAR equation, two sets of weighting coefficients {aj} and {bp} are assigned to the potential energy terms and to the functional residues, respectively. The two coefficient sets are solved by using iterative double least-squares (IDLS) technique in the training set. Then, the two sets of weighting coefficients are used to predict the bioactivities of inquired ligands. In an application example, the new developed method obtained much better results than that of docking calculations.

Simple, fast, and efficient process for producing and purifying trehalulose

A new property of recombinant trehalose synthase (GTase) from Thermus thermophilus HB-8 (ATCC 27634) was found and described in this study. GTase can act on sucrose and catalyze trehalulose formation without isomaltose, isomaltulose, or isomelezitose, releasing small amounts of glucose and fructose as byproducts. Maximum trehalulose yield (approximately 81%) was obtained at an optimum temperature of 65°C and was independent of substrate concentration. A simple, fast, and efficient method of producing and purifying trehalulose is then described. In the first step, GTase catalyzed trehalulose formation using a 20% sucrose substrate. Miscellaneous sugars were then rapidly removed, while trehalulose was completely preserved by Saccharomyces cerevisiae cells. Finally, the cells were separated by centrifugation, and salt ions were removed by an ion-exchange resin, subsequently obtaining a high-purity trehalulose solution. A trehalulose recovery rate of over 95% was achieved using this process. This method has a simple process, fast separation efficiency, and low investment in production equipment, so greatly to improve production efficiency and reduce production costs.

Sucrose hydrolytic enzymes: old enzymes for new uses as biocatalysts for medical applications.

Sucrose hydrolytic enzymes, widely used in a variety of food industries, employ sucrose as a substrate. In addition to their hydrolysis activities, they have other recently discovered characteristics that should make them useful for medical applications. Here, the two enzymes sucrose phosphorylase and invertase are discussed. Sucrose phosphorylase glycosylates non-carbohydrate small molecules and invertase can be used in a portable and personal biosensor to quantify a variety of analytical targets.

Statistical energy potential: reduced representation of Dehouck–Gilis–Rooman function by selecting against decoy datasets

Statistical effective energy function (SEEF) is derived from the statistical analysis of the database of known protein structures. Dehouck–Gilis–Rooman (DGR) group has recently created a new generation of SEEF in which the additivity of the energy terms was manifested by decomposing the total folding free energy into a sum of lower order terms. We have tried to optimize the potential function based on their work. By using decoy datasets as screening filter, and through modification of algorithms in calculation of accessible surface area and residue–residue interaction cutoff, four new combinations of the energy terms were found to be comparable to DGR potential in performance test. Most importantly, the term number was reduced from the original 30 terms to only 5 in our results, thereby substantially decreasing the computation time while the performance was not sacrificed. Our results further proved the additivity and manipulability of the DGR original energy function, and our new combination of the energy could be used in prediction of protein structures.