Until now, it has been reasonably assumed that specific base-pair recognition is the only mechanism controlling the specificity of transcription factor (TF)−DNA binding. Contrary to this assumption, here we show that nonspecific DNA sequences possessing certain repeat symmetries, when present outside of specific TF binding sites (TFBSs), statistically control TF−DNA binding preferences. We used highthroughput protein−DNA binding assays to measure the binding levels and free energies of binding for several human TFs to tens of thousands of short DNA sequences with varying repeat symmetries. Based on statistical mechanics modeling, we identify a new protein−DNA binding mechanism induced by DNA sequence symmetry in the absence of specific base-pair recognition, and experimentally demonstrate that this mechanism indeed governs protein−DNA binding preferences. protein−DNA binding is an important biophysical mechanism operating in a living cell (1). This seminal work makes it possible to interpret experiments that measured how transcription factors (TFs) search for their specific target sites flanked by nonconsensus sequence elements (1-10). A specific consensus motif is a short DNA sequence, typically 6-20 base pairs (bp), that possesses an enhanced binding affinity for a particular TF. For example, the sequence CACGTG represents the specific consensus motif for the human protein Max used in this study (Fig. 1). The process of establishing specific, consensus protein−DNA binding requires the formation of precise geometrical fit between the protein and its consensus DNA motif, accompanied by the formation of specific hydrogen and electrostatic contacts at the protein−DNA binding interface (6, 7) ( Fig. 1). In addition to binding to their consensus DNA motifs, transcription factors can also bind, albeit with lower affinity, to DNA regions lacking any consensus motifs. The term "nonspecific protein−DNA binding" (6) is typically used to describe these weaker interactions. Von Hippel and Berg suggested classifying nonspecific protein−DNA binding into two related mechanisms (6). The first mechanism includes protein binding to its mutated specific motifs that retain some residual, reduced specificity. The second mechanism is largely DNA sequence independent, and it involves electrostatic binding modulated by the overall DNA geometry (6). Despite significant experimental progress, molecular mechanisms responsible for these two types of nonspecific binding remain poorly understood, and the free energy of nonspecific protein−DNA binding has not been systematically characterized (11)(12)(13)(14). The interplay between consensus and nonconsensus DNA sequence elements emerges as a dominant factor that governs protein−DNA binding preferences. However, this interplay is also poorly understood (15, 16). Until now, it has been reasonably assumed that specific (consensus) base-pair recognition must control the genome-wide specificity of TF−DNA binding.Contrary to this assumption, here we identify a general mechanism for protein−DNA bi...
We study statistical properties of interacting protein-like surfaces and predict two strong, related effects: (i) statistically enhanced self-attraction of proteins; (ii) statistically enhanced attraction of proteins with similar structures. The effects originate in the fact that the probability to find a pattern self-match between two identical, even randomly organized interacting protein surfaces is always higher compared with the probability for a pattern match between two different, promiscuous protein surfaces. This theoretical finding explains statistical prevalence of homodimers in protein-protein interaction networks reported earlier. Further, our findings are confirmed by the analysis of curated database of protein complexes that showed highly statistically significant overrepresentation of dimers formed by structurally similar proteins with highly divergent sequences ("superfamily heterodimers"). We suggest that promiscuous homodimeric interactions pose strong competitive interactions for heterodimers evolved from homodimers. Such evolutionary bottleneck is overcome using the negative design evolutionary pressure applied against promiscuous homodimer formation. This is achieved through the formation of highly specific contacts formed by charged residues as demonstrated both in model and real superfamily heterodimers. KeywordsProtein-protein interactions; principles of biomolecular recognition; positive and negative design; protein networks; homodimers and heterodimers
Transcription factors (TFs) are regulatory proteins that bind DNA in promoter regions of the genome and either promote or repress gene expression. Here, we predict analytically that enhanced homooligonucleotide sequence correlations, such as poly(dA:dT) and poly(dC:dG) tracts, statistically enhance nonspecific TF-DNA binding affinity. This prediction is generic and qualitatively independent of microscopic parameters of the model. We show that nonspecific TF binding affinity is universally controlled by the strength and symmetry of DNA sequence correlations. We perform correlation analysis of the yeast genome and show that DNA regions highly occupied by TFs exhibit stronger homooligonucleotide sequence correlations, and thus a higher propensity for nonspecific binding, than do poorly occupied regions. We suggest that this effect plays the role of an effective localization potential that enhances quasi-one-dimensional diffusion of TFs in the vicinity of DNA, speeding up the stochastic search process for specific TF binding sites. The effect is also predicted to impose an upper bound on the size of TF-DNA binding motifs.
We propose a model that can account for the experimentally observed phase behavior of DNAnanoparticle assemblies (R. Jin et al., JACS 125, 1643; T. A. Taton et al., Science 289, 1757Science 289, (2000). The binding of DNA-coated nano-particles by dissolved DNA linker can be described by exploiting an analogy with quantum particles obeying fractional statistics. In accordance with experimental findings, we predict that the phase-separation temperature of the nano-colloids increases with the DNA coverage of the colloidal surface. Upon the addition of salt, the demixing temperature increases logarithmically with the salt concentration. Our analysis suggests an experimental strategy to map microscopic DNA sequences onto the macroscopic phase behavior of the DNA-nanoparticle solutions. Such an approach should enhance the efficiency of methods to detect (single) mutations in specific DNA sequences. PACS numbers:Colloidal particles that can be selectively linked by specific sequences single-stranded DNA, represent an entirely novel class of complex liquids. With these particles, it becomes feasible to "design" multicomponent mixtures, where the attractive interaction between every pair of species can be controlled independently.During the past few years, the unique molecular recognition properties of DNA have been exploited to create self-assembled nano-structures and nano-devices with a remarkable degree of control (see e.g. Ref.[1]). Self-assembled nanostructures based on DNA have also been utilized to detect specific DNA sequences [2,3,4,5]. In nanoparticle-based DNA detection systems, single-stranded DNA (ssDNA) "probe" molecules are chemisorbed onto the surface of gold nanoparticles (Fig. 1). These probe ssDNA's can specifically bind to a dissolved "target" ssDNA and thus detect its presence with high sensitivity and selectivity: at high enough concentration, the target ssDNA strands induces a sharp demixing transition [6] that leads to aggregation of the nanoparticles coated with the complementary "probe" strands. These aggregates can be easily detected by optical means.The sensitivity of the nanoparticle-based DNA detection method is some two orders of magnitude higher than that of the corresponding fluorophore-based DNA-array scheme [3]. But, in addition, the method can be used to distinguish different DNA sequences that differ from each other by only a single base. The reason is that a single mismatch in the DNA sequence results in a significant change in the DNA-colloid demixing temperature. The fluorophore-based systems lack this level of selectivity [3].In a recent paper, Jin et al. [4] have analyzed the dependence of the dissolution temperature (see note [6]) of DNA-linked nanoparticles on the DNA coverage density, the particle size, and the salt concentration. In the experiments [3,4] short DNA molecules (∼ 20-base oligonucleotides) and small gold colloids (∼ 10 − 50 nm) were used. The principal experimental findings are the following: (i) The higher the ssDNA coverage density on the surface of colloi...
In this work we develop a theory of interaction of randomly patterned surfaces as a
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