PSSM-based prediction of DNA binding sites in proteins

Background  

Detection of DNA-binding sites in proteins is of enormous interest for technologies targeting gene regulation and manipulation. We have previously shown that a residue and its sequence neighbor information can be used to predict DNA-binding candidates in a protein sequence. This sequence-based prediction method is applicable even if no sequence homology with a previously known DNA-binding protein is observed. Here we implement a neural network based algorithm to utilize evolutionary information of amino acid sequences in terms of their position specific scoring matrices (PSSMs) for a better prediction of DNA-binding sites.     

Predicting DNA-binding sites of proteins based on sequential and 3D structural information

Protein–DNA interactions play important roles in many biological processes. To understand the molecular mechanisms of protein–DNA interaction, it is necessary to identify the DNA-binding sites in DNA-binding proteins. In the last decade, computational approaches have been developed to predict protein–DNA-binding sites based solely on protein sequences. In this study, we developed a novel predictor based on support vector machine algorithm coupled with the maximum relevance minimum redundancy method followed by incremental feature selection. We incorporated not only features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure, solvent accessibility, but also five three-dimensional (3D) structural features calculated from PDB data to predict the protein–DNA interaction sites. Feature analysis showed that 3D structural features indeed contributed to the prediction of DNA-binding site and it was demonstrated that the prediction performance was better with 3D structural features than without them. It was also shown via analysis of features from each site that the features of DNA-binding site itself contribute the most to the prediction. Our prediction method may become a useful tool for identifying the DNA-binding sites and the feature analysis described in this paper may provide useful insights for in-depth investigations into the mechanisms of protein–DNA interaction.     

Protein-DNA interactions: structural, thermodynamic and clustering patterns of conserved residues in DNA-binding proteins

Amino acid residues, which play important roles in protein function, are often conserved. Here, we analyze thermodynamic and structural data of protein-DNA interactions to explore a relationship between free energy, sequence conservation and structural cooperativity. We observe that the most stabilizing residues or putative hotspots are those which occur as clusters of conserved residues. The higher packing density of the clusters and available experimental thermodynamic data of mutations suggest cooperativity between conserved residues in the clusters. Conserved singlets contribute to the stability of protein-DNA complexes to a lesser extent. We also analyze structural features of conserved residues and their clusters and examine their role in identifying DNA-binding sites. We show that about half of the observed conserved residue clusters are in the interface with the DNA, which could be identified from their amino acid composition; whereas the remaining clusters are at the protein-protein or protein-ligand interface, or embedded in the structural scaffolds. In protein-protein interfaces, conserved residues are highly correlated with experimental residue hotspots, contributing dominantly and often cooperatively to the stability of protein-protein complexes. Overall, the conservation patterns of the stabilizing residues in DNA-binding proteins also highlight the significance of clustering as compared to single residue conservation.     

Incorporation of 5-bromodeoxycytidine in the adenovirus 2 replication origin interferes with nuclear factor 1 binding.

We have studied the binding of nuclear factor 1 (NFI), a human sequence-specific DNA-binding protein, to a DNA fragment substituted in vitro with 5-bromodeoxycytidine (5-BrdC). Even at low substitution grades binding of NFI to its recognition sequence was considerably lower than with the unsubstituted control fragment. We developed a procedure to cleave substituted DNA specifically at a BrdC residue and searched for contacts between NFI and 5-BrdC residues by an interference assay. Surprisingly, no specific contacts were found in or near the recognition sequence. It appeared instead that interference was inversely related to the distance of a 5-BrdC residue from the NFI binding site. Models to explain these results, including a possible sliding mechanism, are discussed.     

Substituting an alpha-helix switches the sequence-specific DNA interactions of a repressor

It has been suggested that many DNA-binding proteins use an alpha-helix for specific sequence recognition. We have used amino acid sequence homologies to identify the presumptive DNA-recognition helices in two related proteins whose structures are unknown--the repressor and cro protein of bacteriophage 434. The 434 repressor and cro protein each bind to three similar sites in the rightward phage 434 operator, OR, and they make different contacts in each binding site, as revealed by the chemical probe dimethyl sulfate. We substituted the putative recognition alpha-helix of 434 repressor with the putative recognition alpha-helix of 434 cro protein to create a hybrid protein named repressor*. The specific DNA contacts made by repressor* are like those of 434 cro protein.     

Altering the DNA-binding specificity of the yeast Matalpha 2 homeodomain protein.

Homeodomain proteins are a highly conserved class of DNA-binding proteins that are found in virtually every eukaryotic organism. The conserved mechanism that these proteins use to bind DNA suggests that there may be at least a partial DNA recognition code for this class of proteins. To test this idea, we have investigated the sequence-specific requirements for DNA binding and repression by the yeast alpha2 homeodomain protein in association with its cofactors, Mcm1 and Mata1. We have determined the contribution for each residue in the alpha2 homeodomain that contacts the DNA in the co-crystal structures of the protein. We have also engineered mutants in the alpha2 homeodomain to alter the DNA-binding specificity of the protein. Although we were unable to change the specificity of alpha2 by making substitutions at residues 47, 54, and 55, we were able to alter the DNA-binding specificity by making substitutions at residue 50 in the homeodomain. Since other homeodomain proteins show similar changes in specificity with substitutions at residue 50, this suggests that there is at least a partial DNA recognition code at this position.     

Flexible DNA target site recognition by divergent homing endonuclease isoschizomers I-CreI and I-MsoI

Homing endonucleases are highly specific catalysts of DNA strand breaks that induce the transposition of mobile intervening sequences containing the endonuclease open reading frame. These enzymes recognize long DNA targets while tolerating individual sequence polymorphisms within those sites. Sequences of the homing endonucleases themselves diversify to a great extent after founding intron invasion events, generating highly divergent enzymes that recognize similar target sequences. Here, we visualize the mechanism of flexible DNA recognition and the pattern of structural divergence displayed by two homing endonuclease isoschizomers. We determined structures of I-CreI bound to two DNA target sites that differ at eight of 22 base-pairs, and the structure of an isoschizomer, I-MsoI, bound to a nearly identical DNA target site. This study illustrates several principles governing promiscuous base-pair recognition by DNA-binding proteins, and demonstrates that the isoschizomers display strikingly different protein/DNA contacts. The structures allow us to determine the information content at individual positions in the binding site as a function of the distribution of direct and water-mediated contacts to nucleotide bases, and provide an evolutionary snapshot of endonucleases at an early stage of divergence in their target specificity.     

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.

     

Mutations altering the cleavage specificity of a homing endonuclease

The homing endonuclease I-CreI recognizes and cleaves a particular 22 bp DNA sequence. The crystal structure of I-CreI bound to homing site DNA has previously been determined, leading to a number of predictions about specific protein–DNA contacts. We test these predictions by analyzing a set of endonuclease mutants and a complementary set of homing site mutants. We find evidence that all structurally predicted I-CreI/DNA contacts contribute to DNA recognition and show that these contacts differ greatly in terms of their relative importance. We also describe the isolation of a collection of altered specificity I-CreI derivatives. The in vitro DNA-binding and cleavage properties of two such endonucleases demonstrate that our genetic approach is effective in identifying homing endonucleases that recognize and cleave novel target sequences.     

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.     

Thermodynamics of DNA target site recognition by homing endonucleases

The thermodynamic profiles of target site recognition have been surveyed for homing endonucleases from various structural families. Similar to DNA-binding proteins that recognize shorter target sites, homing endonucleases display a narrow range of binding free energies and affinities, mediated by structural interactions that balance the magnitude of enthalpic and entropic forces. While the balance of ΔH and TΔS are not strongly correlated with the overall extent of DNA bending, unfavorable ΔH_binding is associated with unstacking of individual base steps in the target site. The effects of deleterious basepair substitutions in the optimal target sites of two LAGLIDADG homing endonucleases, and the subsequent effect of redesigning one of those endonucleases to accommodate that DNA sequence change, were also measured. The substitution of base-specific hydrogen bonds in a wild-type endonuclease/DNA complex with hydrophobic van der Waals contacts in a redesigned complex reduced the ability to discriminate between sites, due to nonspecific ΔS_binding.     

The DNA-binding domain in the Bacillus subtilis transition-state regulator AbrB employs significant motion for promiscuous DNA recognition

AbrB is a Bacillus subtilis protein responsible for regulating a diverse array of unrelated genes during periods of sub-optimal growth conditions. DNA binding by AbrB is unique in that sequence recognition is specific, yet no obvious consensus sequence of bound promoter regions is apparent. The N-terminal domain is a recently characterized representative of a novel class of DNA-binding proteins that possess a looped-hinge helix DNA-binding topology. Although the structural characterization of this DNA-binding topology contributed to an understanding of the architectural basis for recognition of DNA target sequences, specific mechanisms responsible for promiscuity in DNA sequence recognition still were not apparent. Analysis of (15)N backbone relaxation parameters shows that dynamic motion of regions directly linked to DNA binding show concerted motion on the microsecond-millisecond timescale. Furthermore, dynamic motion of the hinge region suggests that the DNA-binding region is capable of conformational orientations that allow it to accommodate DNA sequence variability in the cognate binding sites.