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Tangshan, China

Lin H.,University of Electronic Science and Technology of China | Chen W.,Hebei United University | Ding H.,University of Electronic Science and Technology of China
PLoS ONE | Year: 2013

The structure and activity of enzymes are influenced by pH value of their surroundings. Although many enzymes work well in the pH range from 6 to 8, some specific enzymes have good efficiencies only in acidic (pH<5) or alkaline (pH>9) solution. Studies have demonstrated that the activities of enzymes correlate with their primary sequences. It is crucial to judge enzyme adaptation to acidic or alkaline environment from its amino acid sequence in molecular mechanism clarification and the design of high efficient enzymes. In this study, we developed a sequence-based method to discriminate acidic enzymes from alkaline enzymes. The analysis of variance was used to choose the optimized discriminating features derived from g-gap dipeptide compositions. And support vector machine was utilized to establish the prediction model. In the rigorous jackknife cross-validation, the overall accuracy of 96.7% was achieved. The method can correctly predict 96.3% acidic and 97.1% alkaline enzymes. Through the comparison between the proposed method and previous methods, it is demonstrated that the proposed method is more accurate. On the basis of this proposed method, we have built an online web-server called AcalPred which can be freely accessed from the website (http://lin.uestc.edu.cn/server/AcalPred). We believe that the AcalPred will become a powerful tool to study enzyme adaptation to acidic or alkaline environment. © 2013 Lin et al. Source


Wang X.,University of Georgia | Wang X.,Hebei United University | Tang H.,University of Georgia | Paterson A.H.,University of Georgia
Plant Cell | Year: 2011

Whole genome duplication ~70 million years ago provided raw material for Poaceae (grass) diversification. Comparison of rice (Oryza sativa), sorghum (Sorghumbicolor), maize (Zeamays), and Brachypodium distachyon genomes revealed that one paleoduplicated chromosome pair has experienced very different evolution than all the others. For tens of millions of years, the two chromosomes have experienced illegitimate recombination that has been temporally restricted in a stepwisemanner, producing structural stratification in the chromosomes. These strata formed independently in different grass lineages,with their similarities (low sequence divergence between paleo-duplicated genes) preserved in parallel for millions of years since the divergence of these lineages. The pericentromeric region of this homeologous chromosome pair accounts for two-thirds of the gene content differences between themodern chromosomes. Both intriguing and perplexing is a distal chromosomal region with the greatest DNA similarity between surviving duplicated genes but also with the highest concentration of lineage-specific gene pairs found anywhere in these genomes and with a significantly elevated gene evolutionary rate. Intragenomic similarity near this chromosomal terminusmaybeimportant in hom(e)ologouschromosome pairing.Chromosome structural stratification, together with enrichment of autoimmune response-related (nucleotide binding site-leucine-rich repeat) genes and accelerated DNA rearrangementandgene loss,conferastrikingresemblanceof thisgrasschromosomepair tothe sexchromosomes of other taxa. © American Society of Plant Biologists. Source


Ge M.,Hebei United University
Cuihua Xuebao/Chinese Journal of Catalysis | Year: 2014

A visible-light-driven Ag3PO4 catalyst was successfully synthesized by a facile ion-exchange route. The as-synthesized Ag3PO4 was characterized by X-Ray diffraction (XRD), field-emission scanning electron microscopy, N2 adsorption-desorption, UV-Vis diffuse reflectance spectroscopy and Fourier transform infrared spectroscopy. Under visible light irradiation, the Ag3PO4 catalyst showed excellent photocatalytic activity for rhodamine (RhB) degradation, but was poor at degrading methyl orange (MO) because of lower adsorption of MO molecules onto the surface of the Ag3PO4. The photodegradation of RhB and MO was achieved by holes and O2 ·- radical attack in the Ag3PO4 suspension. The photodegradation of MO over the Ag3PO4catalyst was greatly enhanced in the presence of RhB owing to greater production of O2 ·-radicals. © 2014, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved. Source


Wang M.-M.,Nankai University | Wang M.-M.,Hebei United University | Yan X.-P.,Nankai University
Analytical Chemistry | Year: 2012

Graphene oxide (GO) has received great interest for its unique properties and potential diverse applications. Here, we show the fabrication of GO nanosheets incorporated monolithic column via one-step room temperature polymerization for capillary electrochromatography (CEC). GO is attractive as the stationary phase for CEC because it provides not only ionized oxygen-containing functional groups to modify electroendoosmotic flow (EOF) but also aromatic macromolecule to give hydrophobicity and π-π electrostatic stacking property. Incorporation of GO into monolithic column greatly increased the interactions between the tested neutral analytes (alkyl benzenes and polycyclic aromatics) and the stationary phase and significantly improved their CEC separation. Baseline separation of the tested neutral analytes on the GO incorporated monolithic column was achieved on the basis of typical reversed-phase separation mechanism. The precision (relative standard deviation (RSD), n = 3) of EOF was 0.3%, while the precision of retention time, peak area, and peak height for the tested neutral analytes were in the range of 0.4-3.0%, 0.8-4.0%, and 0.8-4.9%, respectively. In addition, a set of anilines were well separated on the GO incorporated monolith. The GO incorporated monolithic columns are promising for CEC separation. © 2011 American Chemical Society. Source


Lin H.,University of Electronic Science and Technology of China | Chen W.,Hebei United University
Journal of Microbiological Methods | Year: 2011

The thermostability of proteins is particularly relevant for enzyme engineering. Developing a computational method to identify mesophilic proteins would be helpful for protein engineering and design. In this work, we developed support vector machine based method to predict thermophilic proteins using the information of amino acid distribution and selected amino acid pairs. A reliable benchmark dataset including 915 thermophilic proteins and 793 non-thermophilic proteins was constructed for training and testing the proposed models. Results showed that 93.8% thermophilic proteins and 92.7% non-thermophilic proteins could be correctly predicted by using jackknife cross-validation. High predictive successful rate exhibits that this model can be applied for designing stable proteins. © 2010 Elsevier B.V. Source

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