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Xiaoqin Zou, PhD

Professor, Department of Physics and Department of Biochemistry
Office Location: 222D DCRC
Office Phone: 573-882-6045

Research Interests

Protein-ligand interactions, protein-protein interactions, computer-aided drug design and modeling of quantitative structure-function relationships of membrane proteins.

Research Description

The molecular interactions that drive ligand-protein binding are a key to quantitatively understanding the basis of molecular recognition and to designing therapeutic interventions through rational drug design. Drug molecules usually act by binding to specific target proteins. Drug candidates that have high binding affinities can be identified by their geometric and chemical complementarity to the target in a process analogous to solving a "jigsaw puzzle, " if the target structure is known. An energy model that can give rapid and accurate evaluation of the molecular interaction strength is thus essential for selecting plausible candidate compounds from a chemical database consisting of hundreds of thousands of molecules.

Zou is developing novel and efficient algorithms to calculate binding free energies for ligand-receptor complexes. The derived energy models will be applied to protein-substrate interactions, protein-protein interactions, and structure-based drug design. Zou is also developing new docking algorithms to account for protein flexibility. Methods used in the laboratory include computer modeling, simulation and graphics display.

A second line of research in the laboratory is quantitative studies on structure-function relationship of membrane proteins. Structures of membrane proteins will be predicted using homology modeling and structure alignment techniques. Structural information often suggests mechanisms of protein function, which will be experimentally tested in collaboration with other Dalton investigators.

Professional Background

  • Obtained BS in physics, Wuhan University, China.
  • Obtained PhD in physics and biophysics, University of California-San Diego.

Selected Publications

Sam G. Grinter, Xiaoqin Zou*. A Bayesian statistical approach of improving knowledge-based scoring functions for protein-ligand~interactions. Journal of Computational Chemistry, to be accepted after minor revision.

Sheng-You Huang, Xiaoqin Zou*. A knowledge-based scoring function for protein-RNA interactions derived from a statistical mechanics-based iterative method. Nucleic Acids Research, accepted.

Sheng-You Huang, Chengfei Yan, Sam G. Grinter, Shan Chang, Lin Jiang, Xiaoqin Zou*. Inclusion of the orientational entropic effect and low-resolution experimental information for protein-protein docking in CAPRI. Proteins: Structure, Function and Bioinformatics, Special Issue on 5th CAPRI Evaluations (highly competitive selection), 81: 2183–2191, 2013.

Sam G. Grinter, Chengfei Yan, Sheng-You Huang, Lin Jiang, Xiaoqin Zou*. Automated large-scale file preparation, docking, and scoring: Evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource Benchmark. Journal of Chemical Information and Modeling, Special Issue on CSAR 2012 Scoring Exercise (invited), 53: 1905−1914, 2013.

Sheng-You Huang, Xiaoqin Zou*. A non-redundant structure dataset for benchmarking protein-RNA computational docking. Journal of Computational Chemistry 34: 311-318, 2013. (Selected as the front cover of the issue.)

Juan Xu, Xie Jie, Chengfei Yan, Xiaoqin Zou, Dongtao Ren, and Shuqun Zhang. A chemical genetic approach demonstrates that MPK3/MPK6 activation and NADPH oxidase-mediated oxidative burst are two independent signaling events in plant immunity. The Plant Journal, doi: 10.1111/tpj.12382 [Epub ahead of print].

Min Li, Shan Chang, Jingyi Shi, Kelli McFarland, Longlin Yang, Xiao Yang, Alyssa Moller, Chunguang Wang, Xiaoqin Zou, Chengwu Chi, Jianmin Cui. Conopeptide Vt3.1_1 preferentially inhibits BK channels containing b4 subunits via electrostatic interactions. Journal of Biological Chemistry, accepted.

Marc F. Lensink, et al. Blind Prediction of Interfacial Water Positions in CAPRI. Proteins: Structure, Function and Bioinformatics, Special Issue on 5th CAPRI Evaluations, DOI: 10.1002/prot.24439. [Epub ahead of print].

Rocco Moretti et al. Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions. Proteins: Structure, Function and Bioinformatics, 81:1980-1987, 2013.

Tao Yu, Xiao-Qing Wang, Jian-Ping Sang, Chun-Xu Pan, Xian-Wu Zou, Tsung-Yu Chen, Xiaoqin Zou*. Influences of mutations on the electrostatic binding free energies of chloride ions in Escherichia coli ClC. Journal of Physical Chemistry B, 116, 6431-6438, 2012.

Sheng-You Huang, Xiaoqin Zou*. Construction and test of ligand decoy sets using MDock: Community Structure-Activity Resource benchmarks for binding mode prediction. Journal of Chemical Information and Modeling, Special Issue on CSAR 2010 Scoring Exercise (invited). 51:2107-2114, 2011. (The 6th most-viewed paper in the Journal from June 2011- June 2012.)

Huang SY, Zou X., Scoring and Lessons Learned with the CSAR Benchmark Using an Improved Iterative Knowledge-Based Scoring Function., J Chem Inf Model. 2011 Sep 26;51(9):2097-106. Epub 2011 Aug 31.PMID: 21830787

Huang SY, Zou X., Construction and Test of Ligand Decoy Sets Using MDock: Community Structure-Activity Resource Benchmarks for Binding Mode Prediction., J Chem Inf Model. 2011 Sep 26;51(9):2107-14. Epub 2011 Aug 3.PMID: 21755952

Huang SY, Zou X., Statistical mechanics-based method to extract atomic distance-dependent potentials from protein structures., Proteins. 2011 Sep;79(9):2648-61. doi: 10.1002/prot.23086. Epub 2011 Jul 5.PMID:21732421

Grinter SZ, Liang Y, Huang SY, Hyder SM, Zou X., An inverse docking approach for identifying new potential anti-cancer targets., J Mol Graph Model. 2011 Apr;29(6):795-9. Epub 2011 Jan 19.PMID: 21315634

Huang SY, Zou X., Advances and challenges in protein-ligand docking., Int J Mol Sci. 2010 Aug 18;11(8):3016-34.PMID:21152288

Published by Dalton Cardiovascular Research Center, 1500 Research Park Drive, Columbia, MO 65211
Phone: 573-882-7588 Email: