, Volume 21, Issue 2, pp 951–971 | Cite as

Simulation analysis of the cellulase Cel7A carbohydrate binding module on the surface of the cellulose Iβ

  • Emal M. Alekozai
  • Pavan K. GhattyVenkataKrishna
  • Edward C. Uberbacher
  • Michael F. Crowley
  • Jeremy C. Smith
  • Xiaolin ChengEmail author
Original Paper


The Family 7 cellobiohydrolase (Cel7A) from Trichoderma reesei consists of a carbohydrate-binding module (CBM) joined by a linker to a catalytic domain. Cellulose hydrolysis is limited by the accessibility of Cel7A to crystalline substrates, which is perceived to be primarily mediated by the CBM. Here, the binding of CBM to the cellulose Iβ fiber is characterized by combined Brownian dynamics (BD) and molecular dynamics (MD) simulations. The results confirm that CBM prefers to dock to the hydrophobic than to the hydrophilic fiber faces. Both electrostatic (ES) and van der Waals (VDW) interactions are required for achieving the observed binding preference. The VDW interactions play a more important role in stabilizing the CBM-fiber binding, whereas the ES interactions contribute through the formation of a number of hydrogen bonds between the CBM and the fiber. At long distances, an ES steering effect is also observed that tends to align the CBM in an antiparallel manner relative to the fiber axis. Furthermore, the MD results reveal hindered diffusion of the CBM on all fiber surfaces. The binding of the CBM to the hydrophobic surfaces is found to involve partial dewetting at the CBM-fiber interface coupled with local structural arrangements of the protein. The present simulation results complement and rationalize a large body of previous work and provide detailed insights into the mechanism of the CBM-cellulose fiber interactions.


Cellulose Cellulase Brownian dynamics Molecular dynamics Carbohydrate binding Surface diffusion 



E.A. thanks Razif R. Gabdoulline, Lipi Thukral, Ricky B. Nellas, Tomasz Bereźniak and Mithun Biswas for useful discussions. This work was supported by the Genomic Science Program, Office of Biological and Environmental Research, US Department of Energy, under Contract FWP ERKP752. E.A. was supported by the HGS MathComp, University of Heidelberg. For computational resources we acknowledge the bwGRiD (, the National Science Foundation through TeraGrid resources provided by NISC under grant number TG-MCA08X032, and the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231.

Supplementary material

10570_2013_26_MOESM1_ESM.doc (9.6 mb)
Supplementary material 1 (DOC 9830 kb)


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Copyright information

© Springer Science+Business Media Dordrecht (outside the USA)  2013

Authors and Affiliations

  • Emal M. Alekozai
    • 1
    • 2
  • Pavan K. GhattyVenkataKrishna
    • 3
    • 5
  • Edward C. Uberbacher
    • 3
    • 5
  • Michael F. Crowley
    • 4
    • 5
  • Jeremy C. Smith
    • 2
    • 5
  • Xiaolin Cheng
    • 2
    • 5
    Email author
  1. 1.Interdisciplinary Center for Scientific ComputingUniversity of HeidelbergHeidelbergGermany
  2. 2.Center for Molecular BiophysicsUniversity of Tennessee/Oak Ridge National LaboratoryOak RidgeUSA
  3. 3.Computational Biology and Bioinformatics GroupOak Ridge National LaboratoryOak RidgeUSA
  4. 4.Renewable and Sustainable Energy InstituteNational Renewable Energy LaboratoryGoldenUSA
  5. 5.BioEnergy Science CenterOak Ridge National LaboratoryOak RidgeUSA

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