Selected peptide extension contacts hydrophobic patch on neighboring zinc finger and mediates dimerization on DNA.

Protein-protein interactions often play a crucial role in stabilizing protein-DNA complexes and thus facilitate site-specific DNA recognition. We have worked to incorporate such protein-protein contacts into our design and selection strategies for short peptide extensions that promote cooperative binding of zinc finger proteins to DNA. We have determined the crystal structure of one of these fusion protein-DNA complexes. The selected peptide extension was found to mediate dimerization by reaching across the dyad axis and contacting a hydrophobic patch on the surface of the zinc finger bound to the adjacent DNA site. The peptide-zinc finger protein interactions observed in this structure are similar to those of some homeodomain heterodimers. We also find that the region of the zinc finger surface contacted by the selected peptide extension corresponds to surfaces that also make key interactions in the zinc finger proteins GLI and SWI5.     

Modelling repressor proteins docking to DNA

The docking of repressor proteins to DNA starting from the unbound protein and model-built DNA coordinates is modeled computationally. The approach was evaluated on eight repressor/DNA complexes that employed different modes for protein/ DNA recognition. The global search is based on a protein-protein docking algorithm that evaluates shape and electrostatic complementarity, which was modified to consider the importance of electrostatic features in DNA-protein recognition. Complexes were then ranked by an empirical score for the observed amino acid /nucleotide pairings (i.e., protein-DNA pair potentials) derived from a database of 20 protein/DNA complexes. A good prediction had at least 65% of the correct contacts modeled. This approach was able to identify a good solution at rank four or better for three out of the eight complexes. Predicted complexes were filtered by a distance constraint based on experimental data defining the DNA footprint. This improved coverage to four out of eight complexes having a good model at rank four or better. The additional use of amino acid mutagenesis and phylogenetic data defining residues on the repressor resulted in between 2 and 27 models that would have to be examined to find a good solution for seven of the eight test systems. This study shows that starting with unbound coordinates one can predict three-dimensional models for protein/DNA complexes that do not involve gross conformational changes on association. Proteins 33:535–549, 1998. © 1998 Wiley-Liss, Inc.     

Geometric analysis and comparison of protein-DNA interfaces: why is there no simple code for recognition?

Structural studies of protein-DNA complexes have shown that there are many distinct families of DNA-binding proteins, and have shown that there is no simple "code" describing side-chain/base interactions. However, systematic analysis and comparison of protein-DNA complexes has been complicated by the diversity of observed contacts, the sheer number of complexes currently available and the absence of any consistent method of comparison that retains detailed structural information about the protein-DNA interface. To address these problems, we have developed geometric methods for characterizing the local structural environment in which particular side-chain/base interactions are observed. In particular, we develop methods for analyzing and comparing spatial relationships at the protein-DNA interface. Our method involves attaching local coordinate systems to the DNA bases and to the C(alpha) atoms of the peptide backbone (these are relatively rigid structural units). We use these tools to consider how the position and orientation of the polypeptide backbone (with respect to the DNA) helps to determine what contacts are possible at any given position in a protein-DNA complex. Here, we focus on base contacts that are made in the major groove, and we use spatial relationships in analyzing: (i) the observed patterns of side-chain/base interactions; (ii) observed helix docking orientations; (iii) family/subfamily relationships among DNA-binding proteins; and (iv) broader questions about evolution, altered specificity mutants and the limits for the design of new DNA-binding proteins. Our analysis, which highlights differences in spatial relationships in different complexes and at different positions in a complex, helps explain why there is no simple, general code for protein-DNA recognition.     

Fine structure and activity of discrete RAG-HMG complexes on V(D)J recombination signals

Two lymphoid cell-specific proteins, RAG-1 and RAG-2, initiate V(D)J recombination by introducing DNA breaks at recombination signal sequences (RSSs). Although the RAG proteins themselves bind and cleave DNA substrates containing either a 12-RSS or a 23-RSS, DNA-bending proteins HMG-1 and HMG-2 are known to promote these processes, particularly with 23-RSS substrates. Using in-gel cleavage assays and DNA footprinting techniques, I analyzed the catalytic activity and protein-DNA contacts in discrete 12-RSS and 23-RSS complexes containing the RAG proteins and either HMG-1 or HMG-2. I found that both the cleavage activity and the pattern of protein-DNA contacts in RAG-HMG complexes assembled on 12-RSS substrates closely resembled those obtained from analogous 12-RSS complexes lacking HMG protein. In contrast, 23-RSS complexes containing both RAG proteins and either HMG-1 or HMG-2 exhibited enhanced cleavage activity and displayed an altered distribution of cleavage products compared to 23-RSS complexes containing only RAG-1 and RAG-2. Moreover, HMG-dependent heptamer contacts in 23-RSS complexes were observed. The protein-DNA contacts in RAG-RSS-HMG complexes assembled on 12-RSS or 23-RSS substrates were strikingly similar at comparable positions, suggesting that the RAG proteins mediate HMG-dependent heptamer contacts in 23-RSS complexes. Results of ethylation interference experiments suggest that the HMG protein is positioned 5' of the nonamer in 23-RSS complexes, interacting largely with the side of the duplex opposite the one contacting the RAG proteins. Thus, HMG protein plays the dual role of bringing critical elements of the 23-RSS heptamer into the same phase as the 12-RSS to promote RAG binding and assisting in the catalysis of 23-RSS cleavage.     

Structure-based prediction of DNA-binding sites on proteins using the empirical preference of electrostatic potential and the shape of molecular surfaces

Protein-DNA interactions play an essential role in the genetic activities of life. Many structures of protein-DNA complexes are already known, but the common rules on how and where proteins bind to DNA have not emerged. Many attempts have been made to predict protein-DNA interactions using structural information, but the success rate is still about 80%. We analyzed 63 protein-DNA complexes by focusing our attention on the shape of the molecular surface of the protein and DNA, along with the electrostatic potential on the surface, and constructed a new statistical evaluation function to make predictions of DNA interaction sites on protein molecular surfaces. The shape of the molecular surface was described by a combination of local and global average curvature, which are intended to describe the small convex and concave and the large-scale concave curvatures of the protein surface preferentially appearing at DNA-binding sites. Using these structural features, along with the electrostatic potential obtained by solving the Poisson-Boltzmann equation numerically, we have developed prediction schemes with 86% and 96% accuracy for DNA-binding and non-DNA-binding proteins, respectively.     

Pre- and post-docking sampling of conformational changes using ClustENM and HADDOCK for protein-protein and protein-DNA systems

Incorporating the dynamic nature of biomolecules in the modeling of their complexes is a challenge, especially when the extent and direction of the conformational changes taking place upon binding is unknown. Estimating whether the binding of a biomolecule to its partner(s) occurs in a conformational state accessible to its unbound form (“conformational selection”) and/or the binding process induces conformational changes (“induced-fit”) is another challenge. We propose here a method combining conformational sampling using ClustENM—an elastic network-based modeling procedure—with docking using HADDOCK, in a framework that incorporates conformational selection and induced-fit effects upon binding. The extent of the applied deformation is estimated from its energetical costs, inspired from mechanical tensile testing on materials. We applied our pre- and post-docking sampling of conformational changes to the flexible multidomain protein-protein docking benchmark and a subset of the protein-DNA docking benchmark. Our ClustENM-HADDOCK approach produced acceptable to medium quality models in 7/11 and 5/6 cases for the protein-protein and protein-DNA complexes, respectively. The conformational selection (sampling prior to docking) has the highest impact on the quality of the docked models for the protein-protein complexes. The induced-fit stage of the pipeline (post-sampling), however, improved the quality of the final models for the protein-DNA complexes. Compared to previously described strategies to handle conformational changes, ClustENM-HADDOCK performs better than two-body docking in protein-protein cases but worse than a flexible multidomain docking approach. However, it does show a better or similar performance compared to previous protein-DNA docking approaches, which makes it a suitable alternative.     

Intermolecular and intramolecular readout mechanisms in protein-DNA recognition

Protein-DNA recognition plays an essential role in the regulation of gene expression. Regulatory proteins are known to recognize specific DNA sequences directly through atomic contacts (intermolecular readout) and/or indirectly through the conformational properties of the DNA (intramolecular readout). However, little is known about the respective contributions made by these so-called direct and indirect readout mechanisms. We addressed this question by making use of information extracted from a structural database containing many protein-DNA complexes. We quantified the specificity of intermolecular (direct) readout by statistical analysis of base-amino acid interactions within protein-DNA complexes. The specificity of the intramolecular (indirect) readout due to DNA was quantified by statistical analysis of the sequence-dependent DNA conformation. Systematic comparison of these specificities in a large number of protein-DNA complexes revealed that both intermolecular and intramolecular readouts contribute to the specificity of protein-DNA recognition, and that their relative contributions vary depending upon the protein-DNA complexes. We demonstrated that combination of the intermolecular and intramolecular energies derived from the statistical analyses lead to enhanced specificity, and that the combined energy could explain experimental data on binding affinity changes caused by base mutations. These results provided new insight into the relationship between specificity and structure in the process of protein-DNA recognition, which would lead to prediction of specific protein-DNA binding sites.     

Pyrimidine 5-methyl groups influence the magnitude of DNA curvature

DNA containing short sequences of the form (dA)n.(dT)n can exhibit pronounced degrees of stable curvature of the helix axis, provided that these homooligomeric stretches are approximately in phase with the helix repeat. However, the precise origin of this effect is unknown. We have observed that pyrimidine 5-methyl groups can have a significant effect on the degree of curvature, depending on their locations within the homooligomeric sequences. Such effects are observed in both (dA)n.(dT/dU)n and (dI)n.(dC/d5meC)n sequence motifs, arguing for a general structural perturbation due to the methyl group. The current observations suggest that pyrimidine methyl groups could influence protein-DNA interactions not only through direct protein-methyl group contacts but also by methyl group induced alterations in local DNA structure.     

Determination of the three-dimensional structure of the Mrf2-DNA complex using paramagnetic spin labeling

Understanding the mechanism of protein-DNA interactions at the molecular level is one of the main focuses in structural and molecular biological investigations. At present, NMR spectroscopy is the only approach that can provide atomic details of protein-DNA recognition in solution. However, determining the structures of protein-DNA complexes using NMR spectroscopy has been dependent on the observation of intermolecular nuclear Overhauser effects (NOE) and their assignments, which are difficult to obtain in many cases. In this study, we have shown that intermolecular distance constraints derived from a single spin-label in combination with docking calculations have defined many specific contacts of the complex between the AT-rich interaction domain (ARID) of Mrf2 and its target DNA. Mrf2 contacts DNA mainly using the two flexible loops, L1 and L2. While the L1 loop contacts the phosphate backbone, L2 and several residues in the adjacent helices interact with AT base pairs in the major groove of DNA. Despite the structural diversity in the ARID family of DNA-binding proteins, Mrf2 maintains contacts with DNA similar to those observed in the homologous Dri-DNA complex.     

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.     

Assembly and self-association of oxytricha telomeric nucleoprotein complexes

Two types of specific telomeric protein-DNA complex are reconstituted upon incubation of purified Oxytricha telomere protein with (T4G4)4, an oligodeoxynucleotide of telomeric sequence. The complexes differ in electrophoretic mobility, in protein-DNA contacts, and in the rate of DNA exchange. The patterns of protein-DNA interaction determined by modification interference suggest a model in which the protein can bind either to the two T4G4 repeats at the 3' end or to two internal repeats; in the latter case, it can make a different set of contacts with the terminal repeat to form the more stable complex. Native telomeric chromatin isolated from Oxytricha contains both types of complexes. The reconstituted monomeric complexes associate to give a high molecular weight form that has an altered chemical footprint. Such interactions may mediate the association of chromosomal telomeres in vivo.     

Uracil interference, a rapid and general method for defining protein-DNA interactions involving the 5-methyl group of thymines: the GCN4-DNA complex.

We describe a novel uracil interference method for examining protein contacts with the 5-methyl group of thymines. The protein of interest is incubated with target DNA containing randomly distributed deoxyuracil substitutions that is generated by carrying out the polymerase chain reaction in the presence of a mixture of TTP and dUTP. After separating DNA-protein complexes away from unbound DNA, the locations of deoxyuracil residues that either do or do not interfere with DNA-binding are determined by cleavage with uracil-N-glycosylase followed by piperidine. Using this uracil interference assay, we show that the methyl groups of the four core thymines, but not the two peripheral thymines, of the optimal binding site (ATG-ACTCAT) are important for high affinity binding of GCN4. Similar, but not identical, results are obtained using KMnO4 interference, another method used for studying protein-DNA interactions involving thymine residues. These observations strongly suggest that GCN4 directly contacts the 5-methyl groups of the four core thymines that lie in the major groove of the target DNA. Besides providing specific structural information about protein-DNA complexes, uracil interference should also be useful for identifying DNA-binding proteins and their target sites in eukaryotic promoter regions.     

Predicting DNA-binding locations and orientation on proteins using knowledge-based learning of geometric properties

Background

DNA-binding proteins perform their functions through specific or non-specific sequence recognition. Although many sequence- or structure-based approaches have been proposed to identify DNA-binding residues on proteins or protein-binding sites on DNA sequences with satisfied performance, it remains a challenging task to unveil the exact mechanism of protein-DNA interactions without crystal complex structures. Without information from complexes, the linkages between DNA-binding proteins and their binding sites on DNA are still missing.

Methods

While it is still difficult to acquire co-crystallized structures in an efficient way, this study proposes a knowledge-based learning method to effectively predict DNA orientation and base locations around the protein’s DNA-binding sites when given a protein structure. First, the functionally important residues of a query protein are predicted by a sequential pattern mining tool. After that, surface residues falling in the predicted functional regions are determined based on the given structure. These residues are then clustered based on their spatial coordinates and the resultant clusters are ranked by a proposed DNA-binding propensity function. Clusters with high DNA-binding propensities are treated as DNA-binding units (DBUs) and each DBU is analyzed by principal component analysis (PCA) to predict potential orientation of DNA grooves. More specifically, the proposed method is developed to predict the direction of the tangent line to the helix curve of the DNA groove where a DBU is going to bind.

Results

This paper proposes a knowledge-based learning procedure to determine the spatial location of the DNA groove with respect to the query protein structure by considering geometric propensity between protein side chains and DNA bases. The 11 test cases used in this study reveal that the location and orientation of the DNA groove around a selected DBU can be predicted with satisfied errors.

Conclusions

This study presents a method to predict the location and orientation of DNA grooves with respect to the structure of a DNA-binding protein. The test cases shown in this study reveal the possibility of imaging protein-DNA binding conformation before co-crystallized structure can be determined. How the proposed method can be incorporated with existing protein-DNA docking tools to study protein-DNA interactions deserve further studies in the near future.

     

Influence of DNA stiffness in protein-DNA recognition

Protein-DNA recognition plays an essential role in the regulation of gene expression. The protein-DNA binding specificity is based on direct atomic contacts between protein and DNA and/or the conformational properties of DNA. In this work, we have analyzed the influence of DNA stiffness (E) to the specificity of protein-DNA complexes. The average DNA stiffness parameters for several protein-DNA complexes have been computed using the structure based sequence dependent stiffness scale. The relationship between DNA stiffness and experimental protein-DNA binding specificity has been brought out. We have investigated the importance of DNA stiffness with the aid of experimental free energy changes (DeltaDeltaG) due to binding in several protein-DNA complexes, such as, ETS proteins, 434, lambda, Mnt and trp repressors, 434 cro protein, EcoRV endonuclease V and zinc fingers. We found a correlation in the range 0.65-0.97 between DeltaDeltaG and E in these examples. Further, we have qualitatively analyzed the effect of mutations in the target sequence of lambda repressor and we observed that the DNA stiffness could correctly identify 70% of the correct bases among the considered nine positions.     

A new analytical scale DNA affinity binding assay for analyses of specific protein-DNA interactions.

We describe a rapid analytical assay for identification of proteins binding to specific DNA sequences. The DAPSTER assay (DNA affinity preincubation specificity test of recognition assay) is a DNA affinity chromatography-based microassay that can discriminate between specific and nonspecific protein-DNA interactions. The assay is sensitive and can detect protein-DNA interactions and larger multicomponent complexes that can be missed by other analytical methods. Here we describe in detail the optimization and utilization of the DAPSTER assay to isolate AP-1 complexes and associated proteins in multimeric complexes bound to the AP-1 DNA element.