Prediction of DNA Target Sites by Regulatory Proteins
Based on Structure-Derived Potential

Hidetoshi Kono

hkono@rtc.riken.go.jp

Akinori Saraisarai@rtc.riken.go.jp

The Institute of Physical and Chemical Research (RIKEN)
3-1-1, Koyadai, Tsukuba, Ibaraki 305-0074, Japan

1 Introduction

Gene expression in higher organisms is controlled by a variety of regulatory proteins. Structural
analysis of protein-DNA complexes has revealed that the same amino acids often interact with di erent
bases and vice versa. Thus, no general rules yet exist to explain how proteins discriminate among DNA
sequences or that predict their target sites. On the other hand, the amount of structural information
on protein-DNA recognition has been increasing rapidly. The structures of more than 200 proteinDNA complexes are now registered in the Protein Data Bank (PDB) [1], and they serve as a richsource of information about the interactions between amino acids and base pairs at the atomic level.
Statistical analysis of contact potentials between pairs of amino acids, empirically derived from protein
tertiary structures, has been used to predict amino acid sequences that fold into particular structure[2]. We applied this strategy to the structures of protein-DNA complexes in order to predict DNA
binding sites recognized by regulatory proteins.
2 Methods

The structures of 52 protein-DNA complexes were selected from the PDB making certain that redundant and low resolution data (resolution  3:2A) were excluded. A set of pairwise potentials between
DNA bases and C atoms of all amino acids was then empirically determined by statistical analysis
of known protein structures using a modi cation of the method of Sippl [3]. For a pair of base a andamino acid b at grid point s, the potential is given by the following expressions:#"ab (s)1mab w abf
f ab (s) =(1)1E ab(s) = 0RT ln f (s) ;1 + mabw f (s) + 1 + mabw g (s)where mab is the number of pairs ab observed, w is the weight given to each observation, f (s) is therelative frequency of occurrence of any amino acids at grid point s against any bases, gab(s) is theequivalent relative frequency of occurrence of amino acid a against base b. R and T are gas constantand absolute temperature, respectively.
DNA sequences were t to a template of protein-DNA geometry, and the energy potentials werecalculated. The sum of the potentials for a sequence with a given length is de ned as the energy forthe sequences. The length of DNA sequence depends on the interface size of the binding proteins. Theenergy for the sequences in the crystal structures were characterized by their Z-scores against random
sequences.
3 Results and Discussion

Our ability to predict DNA binding sequences from patterns of atomic interaction between bases andamino acids was examined by jack-knife test for 15 protein-DNA crystal structures exhibiting distinct
characteristics.
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Frequency

Glucocorticoid receptor mutant (1LAT)

Glucocorticoid receptor (1GLU)

10000

10000

8000

8000

6000

6000

4000

4000

2000

2000

0−5.0 −4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 4.0 5.0

0−5.0 −4.0 −3.0 −2.0 −1.0 0.0 1.0 2.0 3.0 4.0 5.0

Z-scoreZ-scoreFigure 1: Histograms of Z-scores for random DNA sequences 50,000 base pairs in length. In eachhistogram, the positions of the co-crystallized DNA sequence with protein are shown as lled bars.
In each case the database includes 52 complex-structures, except where the test complex was itself inthe database, in which case it has been excluded.
For the 15 protein-DNA complexes, the co-crystallized DNA sequence with protein were detectedwith average Z-score of -2.8. This means that we can nd the target DNA sequence within the top 3
among 1,000 random sequences. An interesting example for the structure-speci city relationship is thecognate and non-cognate complex structures of nuclear receptor. Gewirth and Sigler solved the crystal
structure of an estrogen receptor (ER)-like DNA-binding domain (a glucocorticoid receptor (GR)DNA-binding domain altered by mutation) bound to the wrong type of half-site (a glucocorticoid
response element; GRE) and revealed an interface resembling the speci c interfaces of the GR orER bound to their correct response elements [4]. The subtle di erence in binding speci city can betested by the present analysis. When this non-cognate complex (1LAT; Fig. 1 (left)) was used as atemplate, the GRE site was not detected (Z= 00:1). On the other hand, when a speci c complex
structure between GR and GRE (1GLU) [5] was used, a more favorable Z-score (Z= 01:9; Fig. 1(right)) was obtained. Thus, this result indicates that our method can detect a subtle di erence inbinding speci city for target sites with some sequence variations. In addition, we considered e ect ofcooperativity on binding speci city, e ect of DNA deformation and role of water molecules and theanalyses have provided some insights into these e ects.
We found that energy potentials extracted from distributions of C atoms around DNA bases of
the known protein-DNA complex structures are suciently sensitive to detect the DNA binding sitesof regulatory proteins. Moreover, this method can also be applied to proteins of unknown structure butwith homology to known proteins, from which structures can be modeled and binding sites predicted.
Increases in the amount of structural data should enable further re nement of the potential, and makethis method a powerful tool for predicting multiple target sites and genes for regulatory proteins.
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[3] Sippl, M., Calculation of Conformational Ensembles for Potentials of Mean Force An Approach to
the Knowledge-based Prediction of Local Structures in Globular Proteins,, 213:859{
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[4] Gewirth, D.T. and Sigler, P.B., The basis for half-site speci city explored through a non-cognate
steroid receptor-DNA complex,, 2:386{394, 1995.
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