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Yang Y.-L.,Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics | Yang Y.-L.,Shandong University
Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012 | Year: 2012

It is accepted that non-coding RNAs (ncRNAs) play very important roles in the cellular process of translation and relates to Human Severe Diseases. In this work, 14 disease-related ncRNA sequences are selected from the NONCODE database. These different ncRNAs play regulator or constituent roles and relate to Cancer. In this work, we map and analyze the Z curves of the selected sequences using Z-curve method. Then we compare the curves and calculate the base content, respectively. We can see that there are almost same curves and base content for one kind of ncRNAs playing same roles. Meanwhile, there are obviously differences in some curves of ncRNA sequences having different functions and coming from different organisms. The conclusion is that the feature of Z-curves is a criterion to recognize ncRNAs and the Z-curve is connected with the function and organisms. © 2012 IEEE.


Zhang X.,Dezhou University | Zhang X.,Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics
Journal of Computational Information Systems | Year: 2014

Image recognition by matrix recovery support vector evaluation algorithm is presented in this paper. In this study, we construct an original form of support vector evaluation algorithm for multi-layer evaluation. Firstly, the evaluation factors of image recognition are analyzed. The evaluation results of image recognition by improved wavelet-matrix recovery support vector evaluation algorithm, support vector evaluation algorithm and artificial neural network are given. And the incorrect evaluation results of image recognition by improved wavelet-matrix recovery support vector evaluation algorithm, support vector evaluation algorithm and artificial neural network are given. It is obvious that the evaluation ability of image recognition by improved wavelet-matrix recovery support vector evaluation algorithm is more excellent than by support vector evaluation algorithm or artificial neural network. © 2014 Binary Information Press


Liu L.,Dezhou University | Liu L.,Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics | Cao Z.,Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics
International Journal of Molecular Sciences | Year: 2013

The transition from α-helical to β-hairpin conformations of α-syn12 peptide is characterized here using long timescale, unbiased molecular dynamics (MD) simulations in explicit solvent models at physiological and acidic pH values. Four independent normal MD trajectories, each 2500 ns, are performed at 300 K using the GROMOS 43A1 force field and SPC water model. The most clustered structures at both pH values are β-hairpin but with different turns and hydrogen bonds. Turn9-6 and four hydrogen bonds (HB9-6, HB6-9, HB11-4 and HB4-11) are formed at physiological pH; turn8-5 and five hydrogen bonds (HB8-5, HB5-8, HB10-3, HB3-10 and HB12-1) are formed at acidic pH. A common folding mechanism is observed: the formation of the turn is always before the formation of the hydrogen bonds, which means the turn is always found to be the major determinant in initiating the transition process. Furthermore, two transition paths are observed at physiological pH. One of the transition paths tends to form the most-clustered turn and improper hydrogen bonds at the beginning, and then form the most-clustered hydrogen bonds. Another transition path tends to form the most-clustered turn, and turn5-2 firstly, followed by the formation of part hydrogen bonds, then turn5-2 is extended and more hydrogen bonds are formed. The transition path at acidic pH is as the same as the first path described at physiological pH. © 2013 by the authors; licensee MDPI, Basel, Switzerland.


Wang J.,Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics | Wang J.,Dezhou University | Cao Z.,Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics | Cao Z.,Dezhou University | And 3 more authors.
International Journal of Molecular Sciences | Year: 2011

Intrinsically disordered proteins (IDPs) are proteins that usually do not adopt well-defined native structures when isolated in solution under physiological conditions. Numerous IDPs have close relationships with human diseases such as tumor, Parkinson disease, Alzheimer disease, diabetes, and so on. These disease-associated IDPs commonly play principal roles in the disease-associated protein-protein interaction networks. Most of them in the disease datasets have more interactants and hence the size of the disease-associated IDPs interaction network is simultaneously increased. For example, the tumor suppressor protein p53 is an intrinsically disordered protein and also a hub protein in the p53 interaction network; α-synuclein, an intrinsically disordered protein involved in Parkinson diseases, is also a hub of the protein network. The disease-associated IDPs may provide potential targets for drugs modulating protein-protein interaction networks. Therefore, novel strategies for drug discovery based on IDPs are in the ascendant. It is dependent on the features of IDPs to develop the novel strategies. It is found out that IDPs have unique structural features such as high flexibility and random coil-like conformations which enable them to participate in both the "one to many" and "many to one" interaction. Accordingly, in order to promote novel strategies for drug discovery, it is essential that more and more features of IDPs are revealed by experimental and computing methods. © 2011 by the authors.


Hu G.,University of Texas at San Antonio | Hu G.,Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics | Hu G.,Dezhou University | Chen L.Y.,University of Texas at San Antonio | And 2 more authors.
Journal of Molecular Modeling | Year: 2012

Aquaporin Z (AQPZ) is a tetrameric protein that forms water channels in the cell membrane of Escherichia coli. The histidine residue (residue 174) in the selectivity filter (SF) region plays an important role in the transport of water across the membrane. In this work, we perform equilibrium molecular dynamics (MD) simulations to illustrate the gating mechanism of the SF and the influences of residue 174 in two different protonation states: Hsd174 with the proton at Nδ, and Hse174 with the proton at Nε. We calculate the pore radii in the SF region versus the simulation time. We perform steered MD to compute the free-energy profile, i.e., the potential of mean force (PMF) of a water molecule through the SF region. We conduct a quantum mechanics calculation of the binding energy of one water molecule with the residues in the SF region. The hydrogen bonds formed between the side chain of Hsd174 and the side chain of residue 189 (Arg189) play important roles in the selectivity mechanism of AQPZ. The radii of the pores, the hydrogen-bond analysis, and the free energies show that it is easier for water molecules to permeate through the SF region of AQPZ with residue 174 in the Hse state than in the Hsd state. © Springer-Verlag 2012.

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