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LS:ZHOU Peng

published: 2015-12-10 10:07:13       hits: 

name : ZHOU Peng Gender: male phone: 028-83202351
email: p_zhou@uestc.edu.cn office-address: Yifu Building 341, ShaHe Campus
PH.D  Supervisor: No Master Supervisor Yes
major: Bioinformatics
research interst: Structurual Bioinformatics, Computational Biology, and Computer-Aided Drug Design
Biography: Dr. ZHOU received his Ph.D. degree from the Zhejiang University in 2011. He joined the Center of Bioinformatics (COBI), UESTC, after graduation. During the 2012-2013, he performed postdoctoral research in the National Center for Toxicological Research (NCTR), U.S. Food and Drug Administration (FDA). Dr. ZHOU is the co-author of more than 50 peer-review papers.
Teaching Schedule: Bioinformatics (Spring)
Computer-Aided Drug Design (Spring & Fall)
Biophysics (Fall)
Selected Publications: [1] Wang, Q.; Chen, S.; Feng, X.; Cao, H.; Zhou, P.* 2D depiction of biological interactions and its applications in drug design. Curr. Med. Imaging Rev. 2013, 9, 18–24.
[2] Ren, Y.; Chen, X.; Li, X.; Lai, H.; Wang, Q.; Zhou, P.*; Chen, G.. Quantitative prediction of the thermal motion and intrinsic disorder of protein cofactors in crystalline state: a case study on halide anions. J. Theor. Biol. 2010, 266, 291–298.
[3] Ren, Y.; Chen, X.; Li, X.; Zhou, P.* Gaussian Process: A Promising Approach for the Modeling and Prediction of Peptide Binding Affinity to MHC Proteins. Protein Pept. Lett. 2011, 18, 670-678.
[4] Ren, Y.; Tian, F.; Zhou, P.* Computational peptidology. Progress in Chemistry 2012, 9, 1674–1682.
[5] Zhou P, Wang C, Ren Y, Yang C, Tian F. Computational peptidology: a new and promising approach to therapeutic peptide design. Curr. Med. Chem. 2013, 20: 1985–1996.
[6] Zhou P, Wang C, Ren Y, Yang C, Tian F. What are the ideal properties for functional food peptides with antihypertensive effect? A computational peptidology approach. Food Chem. 2013, 141: 2967–2973.
[7] Zhou P, Wang C, Tian F, Ren Y, Yang C, Huang J. Biomacromolecular quantitative structure-activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein-protein binding affinity. J. Comput. Aided Mol. Des. 2013, 27: 67–78.
[8] Zhou, P.; Huang, J.; Tian, F. Specific noncovalent interactions at protein–ligand interface: implications for rational drug design. Curr. Med. Chem. 2012, 19, 226–238.
[9] Zhou, P.; Tian, F.; Zou, J.; Ren, Y.; Liu, X.; Shang, Z. Do halide motifs stabilize protein architecture? J. Phys. Chem. B 2010 114, 15673–15686.
[10] Zhou, P.; Ren, Y.; Tian, F.; Zou, J.; Shang, Z. Halogen-ionic bridges: do they exist in the biomolecular world? J. Chem. Theory Comput. 2010, 6, 2225–2241.
[11] Zhou, P.; Tian, F.; Ren, Y.; Shang Z. Systematic classification and analysis of themes in protein–DNA recognition. J. Chem. Inf. Model. 2010, 50, 1476–1488.
[12] Zhou, P.; Shang, Z. 2D molecular graphics: a flattened world of chemistry and biology. Brief. Bioinform. 2009, 10, 247–258.
[13] Zhou, P.; Zou, J. Tian, F.; Shang Z. Fluorine bonding –– how does it work in protein–ligand interactions? J. Chem. Inf. Model. 2009, 49, 2344–2355.
[14] Zhou, P.; Tian, F.; Lv, F.; Shang Z. Comprehensive comparison of eight statistical modelling methods used in quantitative structure–retention relationship studies for liquid chromatographic retention times of peptides generated by protease digestion of the Escherichia coli proteome. J. Chromatogr. A 2009, 1216, 3107–3116.
[15] Zhou, P.; Lv, J.; Zou, J.; Tian, F.; Shang,Z. Halogen–water–hydrogen bridges in biomolecules. J. Struct. Biol. 2010, 169, 172–182. (
[16] Zhou, P.; Chen, X.; Wu, Y.; Shang, Z. Gaussian process: an alternative approach for QSAM modeling of peptides. Amino Acids 2010, 38, 199–212.
[17] Zhou, P.; Tian, F.; Zou, J.; Z. Shang. Rediscovery of halogen bonds in protein–ligand complexes. Mini-Rev. Med. Chem. 2010, 10, 309–314. (Cover Story)
[18] Zhou, P.; Tian, F.; Shang Z. 2D depiction of nonbonding interactions for protein complexes. J. Comput. Chem. 2009, 30, 940–951. (Cover Story)
[19] Zhou, P.; Zou, J.; Tian, F.; Shang Z. Geometric similarity between protein–RNA Interfaces. J. Comput. Chem. 2009, 30, 2738–2751.
[20] Zhou, P.; Chen, X.; Shang, Z. Side-chain conformational space analysis (SCSA): a multi conformation-based QSAR approach for modeling and prediction of protein–peptide binding affinities. J. Comput. Aided Mol. Des. 2009, 23, 129–141.
[21] Zhou, P.; Tian, F.; Lv, F.; Shang, Z. Geometric characteristics of hydrogen bonds involving sulfur atoms in proteins. Proteins 2009, 76, 151–163.
[22] Zhou, P.; Tian, F,; Chen, X.; Shang, Z. Modeling and prediction of binding affinities between the human amphiphysin SH3 domain and its peptide ligands using genetic algorithm-Gaussian processes. Biopolymers (Pept. Sci.) 2008, 90, 792–802.
[23] Zhou, P.; Tian, F.; Shang, Z. LigEvolutioner, a new strategy for modification and optimization of lead compounds in receptor⁄ligand complexes. Chem. Biol. Drug Des. 2008, 72, 525–532.
[24] Zhou, P.; Tian, F.; Wu, Y.; Li, Z.; Shang, Z. Quantitative sequence–activity model (QSAM): applying QSAR strategy to model and predict bioactivity and function of peptides, proteins and nucleic acids. Curr. Comput. Aided Drug Des. 2008, 4, 311–321.
[25] Zhou, P.; Tian, F.; Li, Z.; Shang, Z. Quantitative structure–property relationship studies for collision cross sections of 579 singly protonated peptides based on a novel descriptor as molecular graph fingerprint (MoGF). Anal. Chim. Acta 2007, 597, 214–222.
[26] Zhou, P.; Zeng, H.; Tian, F.; Li B.; Li, Z. Applying novel molecular electronegativity-interaction vector (MEIV) to QSPR study on collision cross section of singly protonated peptides. QSAR Comb. Sci. 2007, 26, 1, 117–121.
[27] Zhou, P.; Tian, F.; Li, Z. Three dimensional holographic vector of atomic interaction field (3D-HoVAIF). Chemometr. Intell. Lab. 2007, 87, 114–120.
[28] Zhou, P.; Tian F.; Li Z. A structure-based, quantitative structure–activity relationship approach for predicting HLA-A*0201-restricted cytotoxic T lymphocyte epitopes. Chem. Biol. Drug Des. 2007, 69, 56–67.
Books: [1] Zhou, P.; Huang, J. Computational Peptidology, in Methods in Molecular Biology series. Springer & Humana press, 2015, Totowa, NJ, USA.