Predicting transcription factor specificity with all-atom models

The binding of a transcription factor (TF) to a DNA operator site can initiate or repress the expression of a gene. Computational prediction of sites recognized by a TF has traditionally relied upon knowledge of several cognate sites, rather than an ab initio approach. Here, we examine the possibili...

Full description

Bibliographic Details
Main Authors: Virnau, Peter (Author), Rahi, Sahand Jamal (Contributor), Mirny, Leonid A. (Contributor), Kardar, Mehran (Contributor)
Other Authors: Harvard University- (Contributor), Massachusetts Institute of Technology. Department of Physics (Contributor)
Format: Article
Language:English
Published: Oxford University Press (OUP), 2012-05-25T19:57:05Z.
Subjects:
Online Access:Get fulltext
LEADER 02332 am a22003133u 4500
001 70954
042 |a dc 
100 1 0 |a Virnau, Peter  |e author 
100 1 0 |a Harvard University-  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Department of Physics  |e contributor 
100 1 0 |a Kardar, Mehran  |e contributor 
100 1 0 |a Rahi, Sahand Jamal  |e contributor 
100 1 0 |a Mirny, Leonid A.  |e contributor 
100 1 0 |a Kardar, Mehran  |e contributor 
700 1 0 |a Rahi, Sahand Jamal  |e author 
700 1 0 |a Mirny, Leonid A.  |e author 
700 1 0 |a Kardar, Mehran  |e author 
245 0 0 |a Predicting transcription factor specificity with all-atom models 
260 |b Oxford University Press (OUP),   |c 2012-05-25T19:57:05Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/70954 
520 |a The binding of a transcription factor (TF) to a DNA operator site can initiate or repress the expression of a gene. Computational prediction of sites recognized by a TF has traditionally relied upon knowledge of several cognate sites, rather than an ab initio approach. Here, we examine the possibility of using structure-based energy calculations that require no knowledge of bound sites but rather start with the structure of a protein-DNA complex. We study the PurR Escherichia coli TF, and explore to which extent atomistic models of protein-DNA complexes can be used to distinguish between cognate and noncognate DNA sites. Particular emphasis is placed on systematic evaluation of this approach by comparing its performance with bioinformatic methods, by testing it against random decoys and sites of homologous TFs. We also examine a set of experimental mutations in both DNA and the protein. Using our explicit estimates of energy, we show that the specificity for PurR is dominated by direct protein-DNA interactions, and weakly influenced by bending of DNA. 
520 |a National Science Foundation (U.S.) (Grant DMR-08- 03315) 
520 |a Deutsche Forschungsgemeinschaft (DFG) (Grant VI237/1) 
520 |a NEC Research Support Fund 
520 |a National Institutes of Health. National Centers for Biomedical Computing (Informatics for Integrating Biology and the Bedside) 
520 |a National Institutes of Health (U.S.) (3U54LM008748-04S1) 
546 |a en_US 
655 7 |a Article 
773 |t Nucleic Acids Research