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Structure selection for protein kinase docking and virtual screening: homology models or crystal structures?
William M Rockey1, Adrian H Elcock
1Department of Biochemistry, University of Iowa, Iowa City, IA, USA. william-rockey@uiowa.edu
Current Protein & Peptide Science
|November 1, 2006
Summary
Protein kinase homology models can be effective for virtual screening, even outperforming crystal structures in some docking studies. Choosing templates crystallized with relevant ligands improves model accuracy for inhibitor design.
Area of Science:
- Biochemistry
- Structural Biology
- Computational Chemistry
Background:
- Limited protein structures necessitate reliable homology models for drug discovery.
- Protein kinase homology models are valuable for virtual screening when experimental structures are unavailable.
Purpose of the Study:
- To evaluate the efficacy of protein kinase homology models in virtual screening.
- To investigate optimal template selection strategies for homology modeling in inhibitor design.
Main Methods:
- Docking studies using AutoDock to compare ligand binding.
- Homology models were generated from templates co-crystallized with ligands.
- Performance was assessed against crystal structures of unliganded or differently liganded targets.
Main Results:
- Homology models performed comparably to or better than crystal structures in docking simulations.
- Models built from templates bound to relevant ligands showed high accuracy.
- This suggests a potential advantage of using ligand-bound templates for homology modeling.
Conclusions:
- Protein kinase homology models are a viable alternative to crystal structures for virtual screening.
- Template selection is critical; using structures co-crystallized with similar ligands can enhance model performance.
- This approach may be particularly beneficial for virtual screening focused on specific inhibitor classes.
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