Dr. Wenjun Zheng

Photo of Associate Professor Wenjun Zheng  

Associate Professor, Ph.D. Stanford University (2003)

Office: 227 Fronczak Hall,  (716) 645-2947
Email: wjzheng@buffalo.edu

link to personal website for more info


  Ph.D. -- Stanford University (2003)
M.S. -- Chinese Academy of Sciences (1998)
B.S. -- Zhejiang University, China (1995)

Research Interests

  • Multiscale modeling of biomolecular conformational dynamics
  • Bioinformatics
  • Protein structural modeling

Conformational dynamics or motions hold keys to the biological functions carried out by biomolecules such as proteins and nucleic acids. Biologically relevant motions, spanning a wide range of time scales (ns ~ min), are often prohibitively expensive to simulate by standard computational techniques like molecular dynamics which is based on atomistic force fields. Alternatively, highly simplified coarse-grained models promise to efficiently probe biomolecular dynamics of large systems and long time scales. For example, the elastic network model (ENM), explored in my earlier work, represents a protein as a 3D network of beads connected by harmonic springs. The normal mode analysis of ENM yields a spectrum of normal modes that capture various protein conformational changes (such as inter-domain hinge motions) observed in structural biology.

My long-term goal is to investigate biomolecular functions through the multi-scale modeling of biomolecular dynamics at a wide range of length scales from whole molecules down to individual atoms. I will employ various structural models of biomolecules from coarse-grained to atomistic models. These complementary models will be welded coherently to achieve both efficiency and accuracy. I am interested in integrating computer modeling with experiments via collaborations so that my models are correctly parameterized by fitting experimental data, and then make informative predictions to guide future experiments. My ultimate goal is to computationally elucidate the molecular functions of various biomolecular "nanomachines" such as motor proteins (myosins, kinesins, polymerases and helicases). .

Selected Publications

Full list of publications

1. Zheng, W., Brooks, B.R., & Hummer, G. Protein conformational transitions explored by mixed elastic network models. Proteins. 69, 43-57 (2007). (pubmed) .
2. Zheng, W., Liao, J. C., Brooks, B.R. & Doniach, S. Toward the mechanism of dynamical couplings and translocation in hepatitis C virus NS3 helicase using elastic network model. Proteins. 67, 886-96 (2007). (pubmed).
3. Zheng, W. & Brooks, B.R. Modeling protein conformational changes by iterative fitting of distance constraints using reoriented normal modes. Biophys. J. 90, 4327-36 (2006). (pubmed).
4. Zheng, W., Brooks, B.R., & Thirumalai, D. Low-frequency normal modes that describe allosteric transitions in biological nanomachines are robust to sequence variations. Proc. Natl. Acad. Sci. 103, 7664-9 (2006). (pubmed).
5. Zheng, W. & Brooks, B.R. Identification of dynamical correlations within the myosin motor domain by the normal mode analysis of an elastic network model. J. Mol. Biol. 346, 745-759 (2005). (pubmed).
6. Zheng, W. & Brooks, B.R. Probing the local dynamics of nucleotide-binding pocket coupled to the global dynamics: myosin versus kinesin. Biophys. J. 89, 167-178 (2005). (pubmed).
7. Zheng, W. & Brooks, B.R. Normal modes based prediction of protein conformational changes guided by distance constraints. Biophys. J. 88, 3109-3117 (2005). (pubmed).
8. Zheng, W., Brooks, B.R., Doniach, S., & Thirumalai, D. Network of dynamically important residues in the open/closed transition in polymerases is strongly conserved. Structure 13, 565-577 (2005). (pubmed).
9. Zheng, W. & Doniach, S. A comparative study of motor-protein motions by using a simple elastic network model. Proc. Natl. Acad. Sci. 100, 13253-58 (2003). (pubmed).
10. Zheng, W., & Doniach, S. Protein structure prediction constrained by solution X-ray scattering data and structural homology identification. J. Mol. Biol. 316, 173-187 (2002). (pubmed).