The role of DNA bending in Cro protein-DNA interactions

Novel approach for selecting the best predictor for identifying the binding sites in DNA binding proteins

Protein-DNA complexes play vital roles in many cellular processes by the interactions of amino acids with DNA. Several computational methods have been developed for predicting the interacting residues in DNA-binding proteins using sequence and/or structural information. These methods showed different levels of accuracies, which may depend on the choice of data sets used in training, the feature sets selected for developing a predictive model, the ability of the models to capture information useful for prediction or a combination of these factors. In many cases, different methods are likely to produce similar results, whereas in others, the predictors may return contradictory predictions. In this situation, a priori estimates of prediction performance applicable to the system being investigated would be helpful for biologists to choose the best method for designing their experiments. In this work, we have constructed unbiased, stringent and diverse data sets for DNA-binding proteins based on various biologically relevant considerations: (i) seven structural classes, (ii) 86 folds, (iii) 106 superfamilies, (iv) 194 families, (v) 15 binding motifs, (vi) single/double-stranded DNA, (vii) DNA conformation (A, B, Z, etc.), (viii) three functions and (ix) disordered regions. These data sets were culled as non-redundant with sequence identities of 25 and 40% and used to evaluate the performance of 11 different methods in which online services or standalone programs are available. We observed that the best performing methods for each of the data sets showed significant biases toward the data sets selected for their benchmark. Our analysis revealed important data set features, which could be used to estimate these context-specific biases and hence suggest the best method to be used for a given problem. We have developed a web server, which considers these features on demand and displays the best method that the investigator should use. The web server is freely available at http://www.biotech.iitm.ac.in/DNA-protein/. Further, we have grouped the methods based on their complexity and analyzed the performance. The information gained in this work could be effectively used to select the best method for designing experiments.

Structure based sequence dependent stiffness scale for trinucleotides: a direct method

A new set of stiffness parameters for all the 32trinucleotide units has been set up directly from thethree dimensional structures of DNA molecules. It wasobserved that GAC/GTC is the stiffest trinucleotideand ACC/GGT is the most flexible one. The averagestiffness values computed for a set of operatorsequences using the new parameters correlate very wellwith the protein-DNA binding specificity and bindingfree energy change of 434 repressor and Cro repressor,respectively. The new structure based stiffness scalecan explain the protein-DNA binding specificity to thelevel of 0.92.

Computational approaches for predicting the binding sites and understanding the recognition mechanism of protein-DNA complexes

Protein-DNA recognition plays an important role in the regulation of gene expression. Understanding the influence of specific residues for protein-DNA interactions and the recognition mechanism of protein-DNA complexes is a challenging task in molecular and computational biology. Several computational approaches have been put forward to tackle these problems from different perspectives: (i) development of databases for the interactions between protein and DNA and binding specificity of protein-DNA complexes, (ii) structural analysis of protein-DNA complexes, (iii) discriminating DNA-binding proteins from amino acid sequence, (iv) prediction of DNA-binding sites and protein-DNA binding specificity using sequence and/or structural information, and (v) understanding the recognition mechanism of protein-DNA complexes. In this review, we focus on all these issues and extensively discuss the advancements on the development of comprehensive bioinformatics databases for protein-DNA interactions, efficient tools for identifying the binding sites, and plausible mechanisms for understanding the recognition of protein-DNA complexes. Further, the available online resources for understanding protein-DNA interactions are collectively listed, which will serve as ready-to-use information for the research community.

Scoring function based approach for locating binding sites and understanding recognition mechanism of protein-DNA complexes

Protein-DNA recognition plays an essential role in the regulation of gene expression. Understanding the recognition mechanism of protein-DNA complexes is a challenging task in molecular and computational biology. In this work, a scoring function based approach has been developed for identifying the binding sites and delineating the important residues for binding in protein-DNA complexes. This approach considers both the repulsive interactions and the effect of distance between atoms in protein and DNA. The results showed that positively charged, polar, and aromatic residues are important for binding. These residues influence the formation of electrostatic, hydrogen bonding, and stacking interactions. Our observation has been verified with experimental binding specificity of protein-DNA complexes and found to be in good agreement with experiments. The comparison of protein-RNA and protein-DNA complexes reveals that the contribution of phosphate atoms in DNA is twice as large as in protein-RNA complexes. Furthermore, we observed that the positively charged, polar, and aromatic residues serve as hotspot residues in protein-RNA complexes, whereas other residues also altered the binding specificity in protein-DNA complexes. Based on the results obtained in the present study and related reports, a plausible mechanism has been proposed for the recognition of protein-DNA complexes.

Scaling behavior of nucleotide cluster in DNA sequences

In this paper we study the scaling behavior of nucleotide cluster in 11 chromosomes of Encephalitozoon cuniculi Genome. The statistical distribution of nucleotide clusters for 11 chromosomes is characterized by the scaling behavior of P(S) proportional, variant e(-alphaS), where S represents nucleotide cluster size. The cluster-size distribution P(S(1)+S(2)) with the total size of sequential C-G cluster and A-T cluster S(1)+S(2) were also studied. P(S(1)+S(2)) follows exponential decay. There does not exist the case of large C-G cluster following large A-T cluster or large A-T cluster following large C-G cluster. We also discuss the relatively random walk length function L(n) and the local compositional complexity of nucleotide sequences based on a new model. These investigations may provide some insight into nucleotide cluster of DNA sequence.

A quantitative study of lambda-phage SWITCH and its components

We propose what we believe is a new model to quantitatively describe the lambda-phage SWITCH system. The model incorporates facilitated transfer mechanism of transcription factor, which can be simplified into a two-step reaction. We first sequentially obtain two indispensable parameters by fitting our model to experimental data of two simple systems, and then apply them to study the natural lambda-SWITCH system. By incorporating the facilitated transfer mechanism, we find that in RecA(-) host Escherichia coli, the wild-type lambda-lysogenic state is in a monostable regime rather than in a bistable regime. Furthermore, the model explains the weak role of Cro protein and probably sheds light on the evolution of lambda-Cro protein, which is known to be structurally distinct from the other Cros in lambdoid family members.

Indirect readout: detection of optimized subsequences and calculation of relative binding affinities using different DNA elastic potentials

Essential biological processes require that proteins bind to a set of specific DNA sites with tuned relative affinities. We focus on the indirect readout mechanism and discuss its theoretical description in relation to the present understanding of DNA elasticity on the rigid base pair level. Combining existing parametrizations of elastic potentials for DNA, we derive elastic free energies directly related to competitive binding experiments, and propose a computationally inexpensive local marker for elastically optimized subsequences in protein-DNA co-crystals. We test our approach in an application to the bacteriophage 434 repressor. In agreement with known results we find that indirect readout dominates at the central, non-contacted bases of the binding site. Elastic optimization involves all deformation modes and is mainly due to the adapted equilibrium structure of the operator, while sequence-dependent elasticity plays a minor role. These qualitative observations are robust with respect to current parametrization uncertainties. Predictions for relative affinities mediated by indirect readout depend sensitively on the chosen parametrization. Their quantitative comparison with experimental data allows for a critical evaluation of DNA elastic potentials and of the correspondence between crystal and solution structures. The software written for the presented analysis is included as Supplementary Data.

Role of inter and intramolecular interactions 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 between protein and DNA, and/or indirectly through the conformational properties of the DNA. In this work, we have analyzed the specificity of intermolecular interactions by statistical analysis of base-amino acid interactions within protein-DNA complexes as well as the computer simulations of base-amino acid interactions. The specificity of the intramolecular interactions was studied by statistical analysis of the sequence-dependent DNA conformational parameters and the elastic properties of DNA. Systematic comparison of these specificities in a large number of protein-DNA complexes revealed that both intermolecular and intramolecular interactions contribute to the specificity of protein-DNA recognition, and their relative contributions vary depending upon the protein-DNA complex. We demonstrated that combination of the intermolecular and intramolecular energies leads to enhanced specificity and 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.

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.

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.

Near equilibrium dynamics of nonhomogeneous Kirchhoff filaments in viscous media

We study the near equilibrium dynamics of nonhomogeneous elastic filaments in viscous media using the Kirchhoff model of rods. Viscosity is incorporated in the model as an external force, which we approximate by the resistance felt by an infinite cylinder immersed in a slowly moving fluid. We use the recently developed method of Goriely and Tabor [Phys. Rev. Lett. 77, 3537 (1996); Physica D 105, 20 (1997); 105, 45 (1997)] to study the dynamics in the vicinity of the simplest equilibrium solution for a closed rod with nonhomogeneous distribution of mass, namely, the planar ring configuration. We show that small variations of the mass density along the rod are sufficient to couple the symmetric modes of the homogeneous rod problem, producing asymmetric deformations that modify substantially the dynamical coiling, even at quite low Reynolds number. The higher-density segments of the rod tend to become more rigid and less coiled. We comment on possible applications to DNA.