Nucleic Acids Research Advance Access originally published online on January 26, 2007
Nucleic Acids Research 2007 35(4):1039-1047; doi:10.1093/nar/gkl1103
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Nucleic Acids Research, 2007, Vol. 35, No. 4 1039-1047
© 2007 The Author(s).
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Computational Biology |
Energetics of protein–DNA interactions
1Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford St. Cambridge, MA 02138, USA and 2Department of Biophysics, Harvard University, Cambridge, MA 02138, USA
*To whom correspondence should be addressed. Tel: +1 617 495 4130; Fax: +1 617 384 9228; Email: jdonald{at}fas.harvard.edu
Received August 15, 2006. Revised December 1, 2006. Accepted December 4, 2006.
Protein–DNA interactions are vital for many processes in living cells, especially transcriptional regulation and DNA modification. To further our understanding of these important processes on the microscopic level, it is necessary that theoretical models describe the macromolecular interaction energetics accurately. While several methods have been proposed, there has not been a careful comparison of how well the different methods are able to predict biologically important quantities such as the correct DNA binding sequence, total binding free energy and free energy changes caused by DNA mutation. In addition to carrying out the comparison, we present two important theoretical models developed initially in protein folding that have not yet been tried on protein–DNA interactions. In the process, we find that the results of these knowledge-based potentials show a strong dependence on the interaction distance and the derivation method. Finally, we present a knowledge-based potential that gives comparable or superior results to the best of the other methods, including the molecular mechanics force field AMBER99.
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