Structure-based prediction of DNA target sites by regulatory proteins

Regulatory proteins play a critical role in controlling complex spatial and temporal patterns of gene expression in higher organism, by recognizing multiple DNA sequences and regulating multiple target genes. Increasing amounts of structural data on the protein-DNA complex provides clues for the mechanism of target recognition by regulatory proteins. The analyses of the propensities of base-amino acid interactions observed in those structural data show that there is no one-to-one correspondence in the interaction, but clear preferences exist. On the other hand, the analysis of spatial distribution of amino acids around bases shows that even those amino acids with strong base preference such as Arg with G are distributed in a wide space around bases. Thus, amino acids with many different geometries can form a similar type of interaction with bases. The redundancy and structural flexibility in the interaction suggest that there are no simple rules in the sequence recognition, and its prediction is not straightforward. However, the spatial distributions of amino acids around bases indicate a possibility that the structural data can be used to derive empirical interaction potentials between amino acids and bases. Such information extracted from structural databases has been successfully used to predict amino acid sequences that fold into particular protein structures. We surmised that the structures of protein-DNA complexes could be used to predict DNA target sites for regulatory proteins, because determining DNA sequences that bind to a particular protein structure should be similar to finding amino acid sequences that fold into a particular structure. Here we demonstrate that the structural data can be used to predict DNA target sequences for regulatory proteins. Pairwise potentials that determine the interaction between bases and amino acids were empirically derived from the structural data. These potentials were then used to examine the compatibility between DNA sequences and the protein-DNA complex structure in a combinatorial "threading" procedure. We applied this strategy to the structures of protein-DNA complexes to predict DNA binding sites recognized by regulatory proteins. To test the applicability of this method in target-site prediction, we examined the effects of cognate and noncognate binding, cooperative binding, and DNA deformation on the binding specificity, and predicted binding sites in real promoters and compared with experimental data. These results show that target binding sites for several regulatory proteins are successfully predicted, and our data suggest that this method can serve as a powerful tool for predicting multiple target sites and target genes for regulatory proteins.     

Helicase motifs: the engine that powers DNA unwinding

Helicases play essential roles in nearly all DNA metabolic transactions and have been implicated in a variety of human genetic disorders. A hallmark of these enzymes is the existence of a set of highly conserved amino acid sequences termed the 'helicase motifs' that were hypothesized to be critical for helicase function. These motifs are shared by another group of enzymes involved in chromatin remodelling. Numerous structure-function studies, targeting highly conserved residues within the helicase motifs, have been instrumental in uncovering the functional significance of these regions. Recently, the results of these mutational studies were augmented by the solution of the three-dimensional crystal structure of three different helicases. The structural model for each helicase revealed that the conserved motifs are clustered together, forming a nucleotide-binding pocket and a portion of the nucleic acid binding site. This result is gratifying, as it is consistent with structure-function studies suggesting that all the conserved motifs are involved in the nucleotide hydrolysis reaction. Here, we review helicase structure-function studies in the light of the recent crystal structure reports. The current data support a model for helicase action in which the conserved motifs define an engine that powers the unwinding of duplex nucleic acids, using energy derived from nucleotide hydrolysis and conformational changes that allow the transduction of energy between the nucleotide and nucleic acid binding sites. In addition, this ATP-hydrolysing engine is apparently also associated with proteins involved in chromatin remodelling and provides the energy required to alter protein-DNA structure, rather than duplex DNA or RNA structure.     

A bifunctional DNA binding region in Tn5 transposase

Tn5 transposition is a complicated process that requires the formation of a highly ordered protein-DNA structure, a synaptic complex, to catalyse the movement of a sequence of DNA (transposon) into a target DNA. Much is known about the structure of the synaptic complex and the positioning of protein-DNA contacts, although many protein-DNA contacts remain largely unstudied. In particular, there is little evidence for the positioning of donor DNA and target DNA. In this communication, we describe the isolation and analysis of mutant transposases that have, for the first time, provided genetic and biochemical evidence for the stage-specific positioning of both donor and target DNAs within the synaptic complex. Furthermore, we have provided evidence that some of the amino acids that contact donor DNA also contact target DNA, and therefore suggest that these amino acids help define a bifunctional DNA binding region responsible for these two transposase-DNA binding events.     

Identification of tyrosine 204 as the photo-cross-linking site in the DNA-EcoRI DNA methyltransferase complex by electrospray ionization mass spectrometry

We describe a highly sensitive strategy combining laser-induced photo-cross-linking and HPLC-based electrospray ionization mass spectrometry to identify amino acid residues involved in protein-DNA recognition. The photoactivatible cross-linking thymine isostere, 5-iodoracil, was incorporated at a single site within the sequence recognized by EcoRI DNA methyltransferase (GAATTC). UV irradiation of the DNA-protein complex at 313 nm results in a >60% cross-linking yield. SDS-polyacrylamide gel electrophoresis and mass spectrometry were used to analyze the covalent cross-linked complex. The total mass is consistent with covalent bond formation between one strand of DNA and the protein with 1:1 stoichiometry. Protease digestion of the cross-linked complex yields several peptide-DNA adducts that were purified by anion-exchange column chromatography. A combination of mass spectrometric analysis and amino acid sequencing revealed that tyrosine 204 was cross-linked to the DNA. Electrospray mass spectrometric analysis of the peptide-nucleoside adduct confirmed this assignment. Tyrosine 204 resides in a peptide motif previously thought to be involved in AdoMet binding and methyl transfer. Thus, amino acids within loop segments but outside of "DNA binding" motifs can be critical to DNA recognition. Our method provides an accurate characterization of picomole quantities of DNA-protein complexes.     

A simple physical model for the prediction and design of protein-DNA interactions

Protein-DNA interactions are crucial for many biological processes. Attempts to model these interactions have generally taken the form of amino acid-base recognition codes or purely sequence-based profile methods, which depend on the availability of extensive sequence and structural information for specific structural families, neglect side-chain conformational variability, and lack generality beyond the structural family used to train the model. Here, we take advantage of recent advances in rotamer-based protein design and the large number of structurally characterized protein-DNA complexes to develop and parameterize a simple physical model for protein-DNA interactions. The model shows considerable promise for redesigning amino acids at protein-DNA interfaces, as design calculations recover the amino acid residue identities and conformations at these interfaces with accuracies comparable to sequence recovery in globular proteins. The model shows promise also for predicting DNA-binding specificity for fixed protein sequences: native DNA sequences are selected correctly from pools of competing DNA substrates; however, incorporation of backbone movement will likely be required to improve performance in homology modeling applications. Interestingly, optimization of zinc finger protein amino acid sequences for high-affinity binding to specific DNA sequences results in proteins with little or no predicted specificity, suggesting that naturally occurring DNA-binding proteins are optimized for specificity rather than affinity. When combined with algorithms that optimize specificity directly, the simple computational model developed here should be useful for the engineering of proteins with novel DNA-binding specificities.     

A lipocalin sequence signature modulates cell survival

Lipocalins are β-barrel proteins, which share three conserved motifs in their amino acid sequence. In this study, we identified by a peptide mapping approach, a seven-amino acid sequence related to one of these motifs (motif 2) that modulates cell survival. A synthetic peptide based on an insect lipocalin displayed cytoprotective activity in serum-deprived endothelial cells and leucocytes. This activity was dependent on nitric oxide synthase. This sequence was found within several lipocalins, including apolipoprotein D, retinol binding protein, lipocalin-type prostaglandin D synthase, and many unknown proteins, suggesting that it is a sequence signature and a lipocalin conserved property.     

An effective approach for generating a three-Cys<Subscript>2</Subscript>His<Subscript>2</Subscript> zinc-finger-DNA complex model by docking

Background  

Determination of protein-DNA complex structures with both NMR and X-ray crystallography remains challenging in many cases. High Ambiguity-Driven DOCKing (HADDOCK) is an information-driven docking program that has been used to successfully model many protein-DNA complexes. However, a protein-DNA complex model whereby the protein wraps around DNA has not been reported. Defining the ambiguous interaction restraints for the classical three-Cys₂His₂ zinc-finger proteins that wrap around DNA is critical because of the complicated binding geometry. In this study, we generated a Zif268-DNA complex model using three different sets of ambiguous interaction restraints (AIRs) to study the effect of the geometric distribution on the docking and used this approach to generate a newly reported Sp1-DNA complex model.     

Mapping metal ions at the catalytic centres of two intron-encoded endonucleases.

Divalent metal ions play a crucial role in forming the catalytic centres of DNA endonucleases. Substitution of Mg2+ ions by Fe2+ ions in two archaeal intron-encoded homing endonucleases, I-DmoI and I-PorI, yielded functional enzymes and enabled the generation of reactive hydroxyl radicals within the metal ion binding sites. Specific hydroxyl radical-induced cleavage was observed within, and immediately after, two conserved LAGLIDADG motifs in both proteins and at sites at, and near, the scissile phosphates of the corresponding DNA substrates. Titration of Fe2+-containing protein-DNA complexes with Ca2+ ions, which are unable to support endonucleolytic activity, was performed to distinguish between the individual metal ions in the complex. Mutations of single amino acids in this region impaired catalytic activity and caused the preferential loss of a subset of hydroxyl radical cleavages in both the protein and the DNA substrate, suggesting an active role in metal ion coordination for these amino acids. The data indicate that the endonucleases cleave their DNA substrates as monomeric enzymes, and contain a minimum of four divalent metal ions located at or near the catalytic centres of each endonuclease. The metal ions involved in cleaving the coding and the non-coding strand are positioned immediately after the N- and C-terminally located LAGLIDADG motifs, respectively. The dual protein/nucleic acid footprinting approach described here is generally applicable to other protein-nucleic acid complexes when the natural metal ion can be replaced by Fe2+.     

Improved modeling of side-chain--base interactions and plasticity in protein--DNA interface design

Combinatorial sequence optimization for protein design requires libraries of discrete side-chain conformations. The discreteness of these libraries is problematic, particularly for long, polar side chains, since favorable interactions can be missed. Previously, an approach to loop remodeling where protein backbone movement is directed by side-chain rotamers predicted to form interactions previously observed in native complexes (termed "motifs") was described. Here, we show how such motif libraries can be incorporated into combinatorial sequence optimization protocols and improve native complex recapitulation. Guided by the motif rotamer searches, we made improvements to the underlying energy function, increasing recapitulation of native interactions. To further test the methods, we carried out a comprehensive experimental scan of amino acid preferences in the I-AniI protein-DNA interface and found that many positions tolerated multiple amino acids. This sequence plasticity is not observed in the computational results because of the fixed-backbone approximation of the model. We improved modeling of this diversity by introducing DNA flexibility and reducing the convergence of the simulated annealing algorithm that drives the design process. In addition to serving as a benchmark, this extensive experimental data set provides insight into the types of interactions essential to maintain the function of this potential gene therapy reagent.     

Quantitative parameters for amino acid-base interaction: implications for prediction of protein-DNA binding sites.

Inspection of the amino acid-base interactions in protein-DNA complexes is essential to the understanding of specific recognition of DNA target sites by regulatory proteins. The accumulation of information on protein-DNA co-crystals challenges the derivation of quantitative parameters for amino acid-base interaction based on these data. Here we use the coordinates of 53 solved protein-DNA complexes to extract all non-homologous pairs of amino acid-base that are in close contact, including hydrogen bonds and hydrophobic interactions. By comparing the frequency distribution of the different pairs to a theoretical distribution and calculating the log odds, a quantitative measure that expresses the likelihood of interaction for each pair of amino acid-base could be extracted. A score that reflects the compatibility between a protein and its DNA target can be calculated by summing up the individual measures of the pairs of amino acid-base involved in the complex, assuming additivity in their contributions to binding. This score enables ranking of different DNA binding sites given a protein binding site and vice versa and can be used in molecular design protocols. We demonstrate its validity by comparing the predictions using this score with experimental binding results of sequence variants of zif268 zinc fingers and their DNA binding sites.     

Searching for protein signatures using a multilevel alphabet

Short motifs are known to play diverse roles in proteins, such as in mediating the interactions with other molecules, binding to membranes, or conducting a specific biological function. Standard approaches currently employed to detect short motifs in proteins search for enrichment of amino acid motifs considering mostly the sequence information. Here, we presented a new approach to search for common motifs (protein signatures) which share both physicochemical and structural properties, looking simultaneously at different features. Our method takes as an input an amino acid sequence and translates it to a new alphabet that reflects its intrinsic structural and chemical properties. Using the MEME search algorithm, we identified the proteins signatures within subsets of protein which encompass common sequence and structural information. We demonstrated that we can detect enriched structural motifs, such as the amphipathic helix, from large datasets of linear sequences, as well as predicting common structural properties (such as disorder, surface accessibility, or secondary structures) of known functional‐motifs. Finally, we applied the method to the yeast protein interactome and identified novel putative interacting motifs. We propose that our approach can be applied for de novo protein function prediction given either sequence or structural information. Proteins 2013; © 2012 Wiley Periodicals, Inc.