Journal of Molecular Modeling

, Volume 17, Issue 12, pp 3163–3172 | Cite as

Study of protein complexes via homology modeling, applied to cysteine proteases and their protein inhibitors

  • Özlem Tastan BishopEmail author
  • Matthys Kroon
Original Paper


This paper develops and evaluates large-scale calculation of 3D structures of protein complexes by homology modeling as a promising new approach for protein docking. The complexes investigated were papain-like cysteine proteases and their protein inhibitors, which play numerous roles in human and parasitic metabolisms. The structural modeling was performed in two parts. For the first part (evaluation set), nine crystal structure complexes were selected, 1325 homology models of known complexes were rebuilt by various templates including hybrids, allowing an analysis of the factors influencing the accuracy of the models. The important considerations for modeling the interface were protease coverage and inhibitor sequence identity. In the second part (study set), the findings of the evaluation set were used to select appropriate templates to model novel cysteine protease-inhibitor complexes from human and malaria parasites Plasmodium falciparum and Plasmodium vivax. The energy scores, considering the evaluation set, indicate that the models are of high accuracy.


Cathepsin Chagasin Cystatin Malaria 



MK thanks Rhodes University and National Research Foundation (NRF) for financial support. We thank Prof Anna Tramontano for comments.

Supplementary material

894_2011_990_MOESM1_ESM.pdf (267 kb)
Online Resource 1 Energy scores of models at different RMSD values for each individual target complex in the Evaluation Set (PDF 267 kb)
894_2011_990_MOESM2_ESM.pdf (116 kb)
Online Resource 2 RMSD values at different protease and inhibitor coverage levels (PDF 115 kb)
894_2011_990_MOESM3_ESM.pdf (116 kb)
Online Resource 3 Sequence Identity and Coverage values at different i-RMSD values (PDF 115 kb)


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Rhodes University Bioinformatics (RUBi), Department of Biochemistry, Microbiology and BiotechnologyRhodes UniversityGrahamstownSouth Africa

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