Research Article
The energy profiles of atomic conformational transition intermediates of adenylate kinase
Article first published online: 28 APR 2009
DOI: 10.1002/prot.22467
Copyright © 2009 Wiley-Liss, Inc.
Issue

Proteins: Structure, Function, and Bioinformatics
Volume 77, Issue 3, pages 551–558, 15 November 2009
Additional Information
How to Cite
Feng, Y., Yang, L., Kloczkowski, A. and Jernigan, R. L. (2009), The energy profiles of atomic conformational transition intermediates of adenylate kinase. Proteins: Structure, Function, and Bioinformatics, 77: 551–558. doi: 10.1002/prot.22467
Publication History
- Issue published online: 14 SEP 2009
- Article first published online: 28 APR 2009
- Accepted manuscript online: 28 APR 2009 12:00AM EST
- Manuscript Accepted: 22 APR 2009
- Manuscript Revised: 8 APR 2009
- Manuscript Received: 9 FEB 2009
Funded by
- National Institutes of Health. Grant Numbers: 1R01GM081680, 1R01GM072014, 1R01GM073095
Keywords:
- adenylate kinase;
- CHARMM force-field;
- elastic networks;
- conformational transitions;
- transition intermediates;
- coarse-grained models;
- transition pathways;
- combinatorial extension
Abstract
The elastic network interpolation (ENI) (Kim et al., Biophys J 2002;83:1620–1630) is a computationally efficient and physically realistic method to generate conformational transition intermediates between two forms of a given protein. However it can be asked whether these calculated conformations provide good representatives for these intermediates. In this study, we use ENI to generate conformational transition intermediates between the open form and the closed form of adenylate kinase (AK). Based on Cα-only intermediates, we construct atomic intermediates by grafting all the atoms of known AK structures onto the Cα atoms and then perform CHARMM energy minimization to remove steric conflicts and optimize these intermediate structures. We compare the energy profiles for all intermediates from both the CHARMM force-field and from knowledge-based energy functions. We find that the CHARMM energies can successfully capture the two energy minima representing the open AK and closed AK forms, while the energies computed from the knowledge-based energy functions can detect the local energy minimum representing the closed AK form and show some general features of the transition pathway with a somewhat similar energy profile as the CHARMM energies. The combinatorial extension structural alignment (Shindyalov et al., 1998;11:739–747) and the k-means clustering algorithm are then used to show that known PDB structures closely resemble computed intermediates along the transition pathway. Proteins 2009. © 2009 Wiley-Liss, Inc.

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