Molecular mechanism of DNA association with single-stranded DNA binding protein

Transient interactions modulate the affinity of NF-κB transcription factors for DNA

The dimeric nuclear factor kappa B (NF-κB) transcription factors (TFs) regulate gene expression by binding to a variety of κB DNA elements with conserved G:C-rich flanking sequences enclosing a degenerate central region. Toward defining mechanistic principles of affinity regulated by degeneracy, we observed an unusual dependence of the affinity of RelA on the identity of the central base pair, which appears to be noncontacted in the complex crystal structures. The affinity of κB sites with A or T at the central position is ~10-fold higher than with G or C. The crystal structures of neither the complexes nor the free κB DNAs could explain the differences in affinity. Interestingly, differential dynamics of several residues were revealed in molecular dynamics simulation studies, where simulation replicates totaling 148 μs were performed on NF-κB:DNA complexes and free κB DNAs. Notably, Arg187 and Arg124 exhibited selectivity in transient interactions that orchestrated a complex interplay among several DNA-interacting residues in the central region. Binding and simulation studies with mutants supported these observations of transient interactions dictating specificity. In combination with published reports, this work provides insights into the nuanced mechanisms governing the discriminatory binding of NF-κB family TFs to κB DNA elements and sheds light on cancer pathogenesis of cRel, a close homolog of RelA.

Brewing COFFEE: A Sequence-Specific Coarse-Grained Energy Function for Simulations of DNA-Protein Complexes

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription and gene expression to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse-grained Force Field for Energy Estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the self-organized polymer model with side-chains for proteins and the three interaction site model for DNA in a modular fashion, without recalibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a data set of high-resolution crystal structures. The only parameter in COFFEE is the strength (λDNAPRO) of the DNA-protein contact potential. For an optimal choice of λDNAPRO, the crystallographic B-factors for DNA-protein complexes with varying sizes and topologies are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts scattering profiles that are in quantitative agreement with small-angle X-ray scattering experiments, as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which do not alter the balance of electrostatic interactions but affect chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

Single molecule technique unveils the role of electrostatic interactions in ssDNA-gp32 molecular complex stability

The exploration of single-strand DNA-binding protein (SSB)-ssDNA interactions and their crucial roles in essential biological processes lagged behind other types of protein-nucleic acid interactions, such as protein-dsDNA and protein-RNA interactions. The ssDNA binding protein gene product 32 (gp32) of the T4 bacteriophage is a central integrating component of the replication complex that must continuously bind to and unbind from transiently exposed template strands during the DNA synthesis. To gain deeper insights into the electrostatic conditions influencing the stability of the ssDNA-gp32 molecular complex, like the salt concentration or some metal ions proven to specifically bind to gp32, we employed a method that performs rapid measurements of the DNA-protein stability using an α-Hemolysin (α-HL) protein nanopore. We indirectly probed the stability of a protein-nucleic acid complex by monitoring the dissociation process between the gp32 protein and the ssDNA molecular complex in single-molecular electrophysiology experiments, but also through fluorescence spectroscopy techniques. We have shown that the complex is more stable in 0.5 M KCl solution than in 2 M KCl solution and that the presence of Zn2+ ions further increases this stability for any salt used in the present study. This method can be applied to other nucleic acid-protein molecular complexes, as well as for an accurate determination of the drug-protein carrier stability.

Three-Dimensional Modeling of CpG DNA Binding with Matrix Lumican Shows Leucine-Rich Repeat Motif Involvement as in TLR9-CpG DNA Interactions

Lumican is an extracellular matrix proteoglycan known to regulate toll-like receptor (TLR) signaling in innate immune cells. In experimental settings, lumican suppresses TLR9 signaling by binding to and sequestering its synthetic ligand, CpG-DNA, in non-signal permissive endosomes. However, the molecular details of lumican interactions with CpG-DNA are obscure. Here, the 3-D structure of the 22 base-long CpG-DNA (CpG ODN_2395) bound to lumican or TLR9 were modeled using homology modeling and docking methods. Some of the TLR9-CpG ODN_2395 features predicted by our model are consistent with the previously reported TLR9-CpG DNA crystal structure, substantiating our current analysis. Our modeling indicated a smaller buried surface area for lumican-CpG ODN_2395 (1803 Å2) compared to that of TLR9-CpG ODN_2395 (2094 Å2), implying a potentially lower binding strength for lumican and CpG-DNA than TLR9 and CpG-DNA. The docking analysis identified 32 amino acids in lumican LRR1-11 interacting with CpG ODN_2395, primarily through hydrogen bonding, salt-bridges, and hydrophobic interactions. Our study provides molecular insights into lumican and CpG-DNA interactions that may lead to molecular targets for modulating TLR9-mediated inflammation and autoimmunity.

Site-specific detection of circulating tumor DNA methylation in biological samples utilizing phosphorothioated primer-based loop-mediated isothermal amplification

DNA methylation, a kind of epigenetic alteration, plays a vital role in tumorigenesis and offers a new class of targets for cancer treatment. DNA hypermethylation at the E-Box site (CACGTG, -288 bp) in the SLC22A2 promoter was related to multidrug resistance of renal cell carcinoma (RCC), which can provide the target for both treatment and monitoring. Herein, we developed a novel phosphorothioated primer based loop-mediated isothermal amplification (PS-LAMP) assay to detect circulating tumor DNA (ctDNA) methylation levels in E-Box sites in tumor tissue, urine, and plasma samples from patients with RCC. Bisulfite treatment converted methylated/unmethylated discrepancy to a single base discrepancy (C/U). PS-LAMP amplified the templates to a tremendous amount. One-step strand displacement (OSD) probe provided single base resolution in amplified products and finally realized the specific site methylation detection. Our proposed method provided a linear range from 0% to 100% for methylation levels and was available in samples at low concentrations (102 copies/μL). Visually observable colorimetric detection can be achieved by incorporating the OSD probe with gold nanoparticles (AuNP). Our assay performed better than traditional methods in biological samples with low ctDNA concentration. Further, we found a potential consistency of methylation levels between tumor tissue and plasma sample from the same patient (Spearman's ρ = 0.886, P = 0.019, n = 6). In general, this work provides a PS-LAMP assay combining OSD probes for site-specific methylation detection in various biological samples, offering a method for noninvasive detection.

Analysis and Prediction of Pathogen Nucleic Acid Specificity for Toll-like Receptors in Vertebrates

Identification of key sequence, expression and function related features of nucleic acid-sensing host proteins is of fundamental importance to understand the dynamics of pathogen-specific host responses. To meet this objective, we considered toll-like receptors (TLRs), a representative class of membrane-bound sensor proteins, from 17 vertebrate species covering mammals, birds, reptiles, amphibians, and fishes in this comparative study. We identified the molecular signatures of host TLRs that are responsible for sensing pathogen nucleic acids or other pathogen-associated molecular patterns (PAMPs), and potentially play important roles in host defence mechanism. Interestingly, our findings reveal that such host-specific features are directly related to the strand (single or double) specificity of nucleic acid from pathogens. However, during host-pathogen interactions, such features were unable to explain the pathogenic PAMP (i.e., DNA, RNA or other) selectivity, suggesting a more complex mechanism. Using these features, we developed a number of machine learning models, of which Random Forest achieved a high performance (94.57% accuracy) to predict strand specificity of TLRs from protein-derived features. We applied the trained model to propose strand specificity of some previously uncharacterized distinct fish-specific novel TLRs (TLR18, TLR23, TLR24, TLR25, TLR27).

Brewing COFFEE: A sequence-specific coarse-grained energy function for simulations of DNA-protein complexes

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription, gene expression, to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse grained force field for energy estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the Self-Organized Polymer model with Side Chains for proteins and the Three Interaction Site model for DNA in a modular fashion, without re-calibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a dataset of high-resolution crystal structures. The only parameter in COFFEE is the strength (λ D N A P R O ) of the DNA-protein contact potential. For an optimal choice of λ D N A P R O , the crystallographic B-factors for DNA-protein complexes, with varying sizes and topologies, are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts the scattering profiles that are in quantitative agreement with SAXS experiments as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which does not alter the balance of electrostatic interactions, but affects chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

Intricate 3D architecture of a DNA mimic of GFP

Numerous studies have shown how RNA molecules can adopt elaborate three-dimensional (3D) architectures1-3. By contrast, whether DNA can self-assemble into complex 3D folds capable of sophisticated biochemistry, independent of protein or RNA partners, has remained mysterious. Lettuce is an in vitro-evolved DNA molecule that binds and activates4 conditional fluorophores derived from GFP. To extend previous structural studies5,6 of fluorogenic RNAs, GFP and other fluorescent proteins7 to DNA, we characterize Lettuce-fluorophore complexes by X-ray crystallography and cryogenic electron microscopy. The results reveal that the 53-nucleotide DNA adopts a four-way junction (4WJ) fold. Instead of the canonical L-shaped or H-shaped structures commonly seen8 in 4WJ RNAs, the four stems of Lettuce form two coaxial stacks that pack co-linearly to form a central G-quadruplex in which the fluorophore binds. This fold is stabilized by stacking, extensive nucleobase hydrogen bonding-including through unusual diagonally stacked bases that bridge successive tiers of the main coaxial stacks of the DNA-and coordination of monovalent and divalent cations. Overall, the structure is more compact than many RNAs of comparable size. Lettuce demonstrates how DNA can form elaborate 3D structures without using RNA-like tertiary interactions and suggests that new principles of nucleic acid organization will be forthcoming from the analysis of complex DNAs.

Mycobacterium tuberculosis grows linearly at the single-cell level with larger variability than model organisms

The ability of bacterial pathogens to regulate growth is crucial to control homeostasis, virulence, and drug response. Yet, we do not understand the growth and cell cycle behaviors of Mycobacterium tuberculosis (Mtb), a slow-growing pathogen, at the single-cell level. Here, we use time-lapse imaging and mathematical modeling to characterize these fundamental properties of Mtb. Whereas most organisms grow exponentially at the single-cell level, we find that Mtb exhibits a unique linear growth mode. Mtb growth characteristics are highly variable from cell-to-cell, notably in their growth speeds, cell cycle timing, and cell sizes. Together, our study demonstrates that growth behavior of Mtb diverges from what we have learned from model bacteria. Instead, Mtb generates a heterogeneous population while growing slowly and linearly. Our study provides a new level of detail into how Mtb grows and creates heterogeneity, and motivates more studies of growth behaviors in bacterial pathogens.

DNA-binding mechanism and evolution of replication protein A

Replication Protein A (RPA) is a heterotrimeric single stranded DNA-binding protein with essential roles in DNA replication, recombination and repair. Little is known about the structure of RPA in Archaea, the third domain of life. By using an integrative structural, biochemical and biophysical approach, we extensively characterize RPA from Pyrococcus abyssi in the presence and absence of DNA. The obtained X-ray and cryo-EM structures reveal that the trimerization core and interactions promoting RPA clustering on ssDNA are shared between archaea and eukaryotes. However, we also identified a helical domain named AROD (Acidic Rpa1 OB-binding Domain), and showed that, in Archaea, RPA forms an unanticipated tetrameric supercomplex in the absence of DNA. The four RPA molecules clustered within the tetramer could efficiently coat and protect stretches of ssDNA created by the advancing replisome. Finally, our results provide insights into the evolution of this primordial replication factor in eukaryotes.

Competitive ligand binding kinetics to linear polymers

Different types of ligands compete in binding to polymers with different consequences for the physical and chemical properties of the resulting complex. Here, we derive a general kinetic model for the competitive binding kinetics of different types of ligands to a linear polymer, using the McGhee and von Hippel detailed binding-site counting procedure. The derived model allows the description of the competitive binding process in terms of the size of the ligand, binding, and release rates, and cooperativity parameters. We illustrate the implications of the general theory showing the equations for the competitive binding of two ligands. The size of the ligand, given by the number of monomers occluded, is shown to have a great impact on competitive binding. Ligands requiring a large available gap for binding are strongly inhibited by smaller ligands. Ligand size then has a leading role compared to binding affinity or cooperativity. For ligands that can bind in different modes (i.e., different number of monomers), this implies that they are more effective in covering or passivating the polymer in lower modes, if the different modes have similar binding energies.

Interdomain dynamics in human Replication Protein A regulates kinetics and thermodynamics of its binding to ssDNA

Human Replication Protein A (hRPA) is a multidomain protein that interacts with ssDNA intermediates to provide the latter much-needed stability during DNA metabolism and maintain genomic integrity. Although the ssDNA organization with hRPA was studied recently through experimental means, characterizing the underlying mechanism at the atomic level remains challenging because of the dynamic domain architecture of hRPA and poorly understood heterogeneity of ssDNA-protein interactions. Here, we used a computational framework, precisely tailored to capture protein-ssDNA interactions, and investigated the binding of hRPA with a 60 nt ssDNA. Two distinct binding mechanisms are realized based on the hRPA domain flexibility. For a rigid domain architecture of hRPA, ssDNA binds sequentially with hRPA domains, resulting in slow association kinetics. The binding pathway involves the formation of stable and distinct intermediate states. On contrary, for a flexible domain architecture of hRPA, ssDNA binds synergistically to the A and B domains followed by the rest of hRPA. The domain dynamics in hRPA alleviates the free energy cost of domain orientation necessary for specific binding with ssDNA, leading to fast association kinetics along a downhill binding free energy landscape. An ensemble of free energetically degenerate intermediate states is encountered that makes it arduous to characterize them structurally. An excellent match between our results with the available experimental observations provides new insights into the rich dynamics of hRPA binding to ssDNA and in general paves the way to investigate intricate details of ssDNA-protein interactions, crucial for cellular functioning.

Mutual effects between single-stranded DNA conformation and Na+-Mg2+ ion competition in mixed salt solutions

The ion-dependence of single-stranded DNA (ssDNA) conformational changes has attracted growing attention because of its biological and technological importance. Although single-species ion effects have been extensively explored, it is challenging to study the ssDNA conformational properties under mixed monovalent/divalent ion conditions due to the complications of ssDNA flexibility and ion-ion competition. In this study, we apply Langevin dynamics simulations to investigate mixed Na⁺/Mg²⁺ ion-dependent ssDNA conformations. The ssDNA structure is described using a coarse-grained model, in which the phosphate, base, and sugar of each nucleotide are represented by three different beads. A novel improvement in our simulation model is that mixed-salt-related electrostatic interactions are computed via combining Manning counterion condensation (MCC) theory with the Monte Carlo tightly bound ion (MCTBI) model. Based on this MCC-MCTBI combination, we report new empirical functions to describe the ion-concentration-dependent and ssDNA conformation/structure-dependent electrostatic effects. The calculation results relating to the ion binding properties and the simulation results relating to the ssDNA conformational properties are validated against experimental results. In addition, our simulation results suggest a quantitative relationship between the ssDNA conformation and Na⁺-Mg²⁺ competition; this in turn reveals their mutual impact in the ion atmosphere.

Single-molecule biophysics experiments in silico: Toward a physical model of a replisome

The interpretation of single-molecule experiments is frequently aided by computational modeling of biomolecular dynamics. The growth of computing power and ongoing validation of computational models suggest that it soon may be possible to replace some experiments outright with computational mimics. Here, we offer a blueprint for performing single-molecule studies in silico using a DNA-binding protein as a test bed. We demonstrate how atomistic simulations, typically limited to sub-millisecond durations and zeptoliter volumes, can guide development of a coarse-grained model for use in simulations that mimic single-molecule experiments. We apply the model to recapitulate, in silico, force-extension characterization of protein binding to single-stranded DNA and protein and DNA replacement assays, providing a detailed portrait of the underlying mechanics. Finally, we use the model to simulate the trombone loop of a replication fork, a large complex of proteins and DNA.

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Coarse-grained model derived from all-atom simulation recapitulates experiments

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Model reproduces the elastic response to force and exchange dynamics

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Model reveals structure of intermediate states usually inaccessible to experiment

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Model applied to viral replisome with trombone loop containing tens of SSB proteins

A single-molecule insight into the ionic strength dependent, cationic peptide nucleic acids - oligonucleotides interactions

To alleviate solubility-related shortcomings associated with the use of neutral peptide nucleic acids (PNA), a powerful strategy is incorporate various charged sidechains onto the PNA structure. Here we employ a single-molecule technique and prove that the ionic current blockade signature of free poly(Arg)-PNAs and their corresponding duplexes with target ssDNAs interacting with a single a-hemolysin (a-HL) nanopore is highly ionic strength dependent, with high salt-containing electrolytes facilitating both capture and isolation of such complexes. Our data illustrate the effect of low ionic strength in reducing the effective volume of free poly(Arg)-PNAs and augmentation of their electrophoretic mobility while traversing the nanopore.  We found that unlike in high salt electrolytes, the specific hybridization of cationic moiety-containing PNAs with complementary negatively charged ssDNAs in a salt concentration as low as 0.5 M is dramatically impeded. We suggest a scenario in which reduced charge screening by counterions in low salt electrolytes enables non-specific, electrostatic interactions with the anionic backbone of polynucleotides, thus reducing the ability of PNA-DNA complementary association via hydrogen bonding patterns. We applied an experimental strategy with spatially-separated poly(Arg)-PNAs and ssDNAs, and present evidence at the single-molecule level suggestive of the real-time, long-range interactions-driven formation of poly(Arg)-PNA-DNA complexes, as individual strands entering the nanopore from opposite directions collide inside a nanocavity.

DNA Polymerase-Parental DNA Interaction Is Essential for Helicase-Polymerase Coupling during Bacteriophage T7 DNA Replication

DNA helicase and polymerase work cooperatively at the replication fork to perform leading-strand DNA synthesis. It was believed that the helicase migrates to the forefront of the replication fork where it unwinds the duplex to provide templates for DNA polymerases. However, the molecular basis of the helicase-polymerase coupling is not fully understood. The recently elucidated T7 replisome structure suggests that the helicase and polymerase sandwich parental DNA and each enzyme pulls a daughter strand in opposite directions. Interestingly, the T7 polymerase, but not the helicase, carries the parental DNA with a positively charged cleft and stacks at the fork opening using a β-hairpin loop. Here, we created and characterized T7 polymerases each with a perturbed β-hairpin loop and positively charged cleft. Mutations on both structural elements significantly reduced the strand-displacement synthesis by T7 polymerase but had only a minor effect on DNA synthesis performed against a linear DNA substrate. Moreover, the aforementioned mutations eliminated synergistic helicase-polymerase binding and unwinding at the DNA fork and processive fork progressions. Thus, our data suggested that T7 polymerase plays a dominant role in helicase-polymerase coupling and replisome progression.

Vesicle encapsulation stabilizes intermolecular association and structure formation of functional RNA and DNA

During the origin of life, encapsulation of RNA inside vesicles is believed to have been a defining feature of the earliest cells (protocells). The confined biophysical environment provided by membrane encapsulation differs from that of bulk solution and has been shown to increase activity as well as evolutionary rate for functional RNA. However, the structural basis of the effect on RNA has not been clear. Here, we studied how encapsulation of the hairpin ribozyme inside model protocells affects ribozyme kinetics, ribozyme folding into the active conformation, and cleavage and ligation activities. We further examined the effect of encapsulation on the folding of a stem-loop RNA structure and on the formation of a triplex structure in a pH-sensitive DNA switch. The results indicate that encapsulation promotes RNA-RNA association, both intermolecular and intramolecular, and also stabilizes tertiary folding, including the docked conformation characteristic of the active hairpin ribozyme and the triplex structure. The effects of encapsulation were sufficient to rescue the activity of folding-deficient mutants of the hairpin ribozyme. Stabilization of multiple modes of nucleic acid folding and interaction thus enhanced the activity of encapsulated nucleic acids. Increased association between RNA molecules may facilitate the formation of more complex structures and cooperative interactions. These effects could promote the emergence of biological functions in an "RNA world" and may have utility in the construction of minimal synthetic cells.

Cooperative kinetics of ligand binding to linear polymers

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Cooperative kinetic equation for large ligands binding to long polymers.

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Cooperativity in general affects binding and release rates.

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Appropriate counting of the available binding sites for a ligand to a linear polymer.

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Positive cooperativity increases polymer coverage by the ligand.

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Large ligand size reduces cooperativity effects.

Ligands change the chemical and mechanical properties of polymers. In particular, single strand binding protein (SSB) non-specifically bounds to single-stranded DNA (ssDNA), modifying the ssDNA stiffness and the DNA replication rate, as recently measured with single-molecule techniques. SSB is a large ligand presenting cooperativity in some of its binding modes. We aim to develop an accurate kinetic model for the cooperative binding kinetics of large ligands. Cooperativity accounts for the changes in the affinity of a ligand to the polymer due to the presence of another bound ligand. Large ligands, attaching to several binding sites, require a detailed counting of the available binding possibilities. This counting has been done by McGhee and von Hippel to obtain the equilibrium state of the ligands-polymer complex. The same procedure allows to obtain the kinetic equations for the cooperative binding of ligands to long polymers, for all ligand sizes. Here, we also derive approximate cooperative kinetic equations in the large ligand limit, at the leading and next-to-leading orders. We found cooperativity is negligible at the leading-order, and appears at the next-to-leading order. Positive cooperativity (increased affinity) can be originated by increased binding affinity or by decreased release affinity, implying different kinetics. Nevertheless, the equilibrium state is independent of the origin of cooperativity and only depends on the overall increase in affinity. Next-to-leading approximation is found to be accurate, particularly for small cooperativity. These results allow to understand and characterize relevant ligand binding processes, as the binding kinetics of SSB to ssDNA, which has been reported to affect the DNA replication rate for several SSB-polymerase pairs.

Mechanisms of SSBP1 variants in mitochondrial disease: Molecular dynamics simulations reveal stable tetramers with altered DNA binding surfaces

Several mutations in the gene for the mitochondrial single stranded DNA binding protein (SSBP1) have recently been implicated in human disease, but initial reports are insufficient to explain the molecular mechanism of disease, including the possible role of SSBP1 heterotetramers in heterozygous patients. Here we employed molecular simulations to model the dynamics of wild type and 31 variant SSBP1 tetramer systems, including 7 variant homotetramer and 24 representative heterotetramer systems. Our simulations indicate that all variants are stable and most have stronger intermonomer interactions, reduced solvent accessible surface areas, and a net loss of positive surface charge. We then used structural alignments and phosphate binding simulations to predict DNA binding surfaces on SSBP1. Our models suggest that nearly the entire surface of SSBP1, excluding flexible loops and protruding helices, is available for DNA binding, and we observed several potential DNA binding hotspots. Changes to the protein surface in variant SSBP1 tetramers potentially alter anchor points or wrapping paths, rather than abolishing binding altogether. Overall, our findings disqualify tetramer destabilization or gross disruption of DNA binding as mechanisms of disease. Instead, they are consistent with subtle changes to DNA binding, wrapping, or release that cause rare but consequential failures of mtDNA maintenance, which, in turn, are consistent with the late onset of disease in most of the reported SSBP1 cases.

Revealing atomic-scale molecular diffusion of a plant-transcription factor WRKY domain protein along DNA

In transcription factors’ search for target genes, one-dimensional diffusion of the protein along DNA is essential. Experimentally, it remains challenging to resolve the individual diffusional steps of protein on DNA. Here, we report mainly all-atom equilibrium simulations of a WRKY domain protein in association with and diffusion along DNA. We demonstrate a complete stepping cycle of the protein for one base pair on DNA within microseconds, along with stochastic motions. Processive protein diffusions on DNA have been further sampled in a coarse-grained model. We have also found preferential DNA-strand association of the domain protein, which becomes most prominent at specific DNA binding, and it can be common for small-domain proteins to balance movements on the DNA with the sequence recognition.

Transcription factor (TF) target search on genome is highly essential for gene expression and regulation. High-resolution determination of TF diffusion along DNA remains technically challenging. Here, we constructed a TF model system using the plant WRKY domain protein in complex with DNA from crystallography and demonstrated microsecond diffusion dynamics of WRKY on DNA by employing all-atom molecular-dynamics (MD) simulations. Notably, we found that WRKY preferentially binds to one strand of DNA with significant energetic bias compared with the other, or nonpreferred strand. The preferential DNA-strand binding becomes most prominent in the static process, from nonspecific to specific DNA binding, but less distinct during diffusive movements of the domain protein on the DNA. Remarkably, without employing acceleration forces or bias, we captured a complete one-base-pair stepping cycle of the protein tracking along major groove of DNA with a homogeneous poly-adenosine sequence, as individual hydrogen bonds break and reform at the protein–DNA binding interface. Further DNA-groove tracking motions of the protein forward or backward, with occasional sliding as well as strand crossing to minor groove of DNA, were also captured. The processive diffusion of WRKY along DNA has been further sampled via coarse-grained MD simulations. The study thus provides structural dynamics details on diffusion of a small TF domain protein, suggests how the protein approaches a specific recognition site on DNA, and supports further high-precision experimental detection. The stochastic movements revealed in the TF diffusion also provide general clues about how other protein walkers step and slide along DNA.

A comparative study of protein-ssDNA interactions

Single-stranded DNA-binding proteins (SSBs) play crucial roles in DNA replication, recombination and repair, and serve as key players in the maintenance of genomic stability. While a number of SSBs bind single-stranded DNA (ssDNA) non-specifically, the others recognize and bind specific ssDNA sequences. The mechanisms underlying this binding discrepancy, however, are largely unknown. Here, we present a comparative study of protein-ssDNA interactions by annotating specific and non-specific SSBs and comparing structural features such as DNA-binding propensities and secondary structure types of residues in SSB-ssDNA interactions, protein-ssDNA hydrogen bonding and π-π interactions between specific and non-specific SSBs. Our results suggest that protein side chain-DNA base hydrogen bonds are the major contributors to protein-ssDNA binding specificity, while π-π interactions may mainly contribute to binding affinity. We also found the enrichment of aspartate in the specific SSBs, a key feature in specific protein-double-stranded DNA (dsDNA) interactions as reported in our previous study. In addition, no significant differences between specific and non-specific groups with respect of conformational changes upon ssDNA binding were found, suggesting that the flexibility of SSBs plays a lesser role than that of dsDNA-binding proteins in conferring binding specificity.

Mechanism of Dynamic Binding of Replication Protein A to ssDNA

Replication protein A (RPA) serves as a hub protein inside eukaryotic cells, where it coordinates crucial DNA metabolic processes and activates the DNA-damage response system. A characteristic feature of its action is to associate with single-stranded DNA (ssDNA) intermediates before handing them over to downstream proteins. The length of ssDNA intermediates differs for different pathways. This means that RPA must have mechanisms for selective processing of ssDNA intermediates based on their length, the knowledge of which is fundamental to elucidate when and how DNA repair and replication processes are symphonized. By employing extensive molecular dynamics simulations, we investigated the mechanism of binding of RPA to ssDNA of different lengths. We show that the binding involves dynamic equilibrium with a stable intermediate, the population of which increases with the length of ssDNA. The vital underlying factors are decoded through collective variable principal component analysis. It suggests a differently orchestrated set of interactions that define the action of RPA based on the length of ssDNA intermediates. We further estimated the association kinetics that matches excellently well with previous experimental studies and probed the diffusion mechanism of RPA to ssDNA. RPA diffuses on short ssDNA through progressive "bulge" formation. With long ssDNA, we observed a conformational change in ssDNA coupled with its binding to RPA in a cooperative fashion. This unanticipated binding mechanism successfully explains how the "short-lived", long ssDNA intermediates are processed quickly in vivo. This study thus reveals the molecular basis of several recent experimental observations related to RPA binding to ssDNA and provides novel insights into the RPA functioning in DNA repair and replication.

Replication protein A: a multifunctional protein with roles in DNA replication, repair and beyond

Single-stranded DNA (ssDNA) forms continuously during DNA replication and is an important intermediate during recombination-mediated repair of damaged DNA. Replication protein A (RPA) is the major eukaryotic ssDNA-binding protein. As such, RPA protects the transiently formed ssDNA from nucleolytic degradation and serves as a physical platform for the recruitment of DNA damage response factors. Prominent and well-studied RPA-interacting partners are the tumor suppressor protein p53, the RAD51 recombinase and the ATR-interacting proteins ATRIP and ETAA1. RPA interactions are also documented with the helicases BLM, WRN and SMARCAL1/HARP, as well as the nucleotide excision repair proteins XPA, XPG and XPF–ERCC1. Besides its well-studied roles in DNA replication (restart) and repair, accumulating evidence shows that RPA is engaged in DNA activities in a broader biological context, including nucleosome assembly on nascent chromatin, regulation of gene expression, telomere maintenance and numerous other aspects of nucleic acid metabolism. In addition, novel RPA inhibitors show promising effects in cancer treatment, as single agents or in combination with chemotherapeutics. Since the biochemical properties of RPA and its roles in DNA repair have been extensively reviewed, here we focus on recent discoveries describing several non-canonical functions.

Noncooperative thermodynamics and kinetic models of ligand binding to polymers: Connecting McGhee-von Hippel model with the Tonks gas model

Ligand binding to polymers modifies the physical and chemical properties of the polymers, leading to physical, chemical, and biological implications. McGhee and von Hippel obtained the equilibrium coverage as a function of the ligand affinity, through the computation of the possible binding sites for the ligand. Here, we complete this theory deriving the kinetic model for the ligand-binding dynamics and the associated equilibrium chemical potential, which turns out to be of the Tonks gas model type. At low coverage, the Tonks chemical potential becomes the Fermi chemical potential and even the ideal gas chemical potential. We also discuss kinetic models associated with these chemical potentials. These results clarify the kinetic models of ligand binding, their relations with the chemical potentials, and their range of validity. Our results highlight the inaccuracy of ideal and simplified kinetic approaches for medium and high coverages.

Molecular dynamics simulations of DNA-DNA and DNA-protein interactions

The all-atom molecular dynamics method can characterize the molecular-level interactions in DNA and DNA-protein systems with unprecedented resolution. Recent advances in computational technologies have allowed the method to reveal the unbiased behavior of such systems at the microseconds time scale, whereas enhanced sampling approaches have matured enough to characterize the interaction free energy with quantitative precision. Here, we describe recent progress toward increasing the realism of such simulations by refining the accuracy of the molecular dynamics force field, and we highlight recent application of the method to systems of outstanding biological interest.

The mechanism of Single strand binding protein-RecG binding: Implications for SSB interactome function

The Escherichia coli single-strand DNA binding protein (SSB) is essential to viability where it functions to regulate SSB interactome function. Here it binds to single-stranded DNA and to target proteins that comprise the interactome. The region of SSB that links these two essential protein functions is the intrinsically disordered linker. Key to linker function is the presence of three, conserved PXXP motifs that mediate binding to oligosaccharide-oligonucleotide binding folds (OB-fold) present in SSB and its interactome partners. Not surprisingly, partner OB-fold deletions eliminate SSB binding. Furthermore, single point mutations in either the PXXP motifs or, in the RecG OB-fold, obliterate SSB binding. The data also demonstrate that, and in contrast to the view currently held in the field, the C-terminal acidic tip of SSB is not required for interactome partner binding. Instead, we propose the tip has two roles. First, and consistent with the proposal of Dixon, to regulate the structure of the C-terminal domain in a biologically active conformation that prevents linkers from binding to SSB OB-folds until this interaction is required. Second, as a secondary binding domain. Finally, as OB-folds are present in SSB and many of its partners, we present the SSB interactome as the first family of OB-fold genome guardians identified in prokaryotes.

ssDNA diffuses along replication protein A via a reptation mechanism

Replication protein A (RPA) plays a critical role in all eukaryotic DNA processing involving single-stranded DNA (ssDNA). Contrary to the notion that RPA provides solely inert protection to transiently formed ssDNA, the RPA-ssDNA complex acts as a dynamic DNA processing unit. Here, we studied the diffusion of RPA along 60 nt ssDNA using a coarse-grained model in which the ssDNA-RPA interface was modeled by both aromatic and electrostatic interactions. Our study provides direct evidence of bulge formation during the diffusion of ssDNA along RPA. Bulges can form at a few sites along the interface and store 1-7 nt of ssDNA whose release, upon bulge dissolution, leads to propagation of ssDNA diffusion. These findings thus support the reptation mechanism, which involves bulge formation linked to the aromatic interactions, whose short range nature reduces cooperativity in ssDNA diffusion. Greater cooperativity and a larger diffusion coefficient for ssDNA diffusion along RPA are observed for RPA variants with weaker aromatic interactions and for interfaces homogenously stabilized by electrostatic interactions. ssDNA propagation in the latter instance is characterized by lower probabilities of bulge formation; thus, it may fit the sliding-without-bulge model better than the reptation model. Thus, the reptation mechanism allows ssDNA mobility despite the extensive and high affinity interface of RPA with ssDNA. The short-range aromatic interactions support bulge formation while the long-range electrostatic interactions support the release of the stored excess ssDNA in the bulge and thus the overall diffusion.

Replicative DNA polymerases promote active displacement of SSB proteins during lagging strand synthesis

Genome replication induces the generation of large stretches of single-stranded DNA (ssDNA) intermediates that are rapidly protected by single-stranded DNA-binding (SSB) proteins. To date, the mechanism by which tightly bound SSBs are removed from ssDNA by the lagging strand DNA polymerase without compromising the advance of the replication fork remains unresolved. Here, we aimed to address this question by measuring, with optical tweezers, the real-time replication kinetics of the human mitochondrial and bacteriophage T7 DNA polymerases on free-ssDNA, in comparison with ssDNA covered with homologous and non-homologous SSBs under mechanical tension. We find important differences between the force dependencies of the instantaneous replication rates of each polymerase on different substrates. Modeling of the data supports a mechanism in which strong, specific polymerase-SSB interactions, up to ∼12 k_BT, are required for the polymerase to dislodge SSB from the template without compromising its instantaneous replication rate, even under stress conditions that may affect SSB–DNA organization and/or polymerase–SSB communication. Upon interaction, the elimination of template secondary structure by SSB binding facilitates the maximum replication rate of the lagging strand polymerase. In contrast, in the absence of polymerase–SSB interactions, SSB poses an effective barrier for the advance of the polymerase, slowing down DNA synthesis.

Molecular Mechanisms of DNA Replication and Repair Machinery: Insights from Microscopic Simulations

Reproduction, the hallmark of biological activity, requires making an accurate copy of the genetic material to allow the progeny to inherit parental traits. In all living cells, the process of DNA replication is carried out by a concerted action of multiple protein species forming a loose protein-nucleic acid complex, the replisome. Proofreading and error correction generally accompany replication but also occur independently, safeguarding genetic information through all phases of the cell cycle. Advances in biochemical characterization of intracellular processes, proteomics and the advent of single-molecule biophysics have brought about a treasure trove of information awaiting to be assembled into an accurate mechanistic model of the DNA replication process. In this review, we describe recent efforts to model elements of DNA replication and repair processes using computer simulations, an approach that has gained immense popularity in many areas of molecular biophysics but has yet to become mainstream in the DNA metabolism community. We highlight the use of diverse computational methods to address specific problems of the fields and discuss unexplored possibilities that lie ahead for the computational approaches in these areas.

Structure, stability and specificity of the binding of ssDNA and ssRNA with proteins

Recognition of single-stranded DNA (ssDNA) or single-stranded RNA (ssRNA) is important for many fundamental cellular functions. A variety of single-stranded DNA-binding proteins (ssDBPs) and single-stranded RNA-binding proteins (ssRBPs) have evolved that bind ssDNA and ssRNA, respectively, with varying degree of affinities and specificities to form complexes. Structural studies of these complexes provide key insights into their recognition mechanism. However, computational modeling of the specific recognition process and to predict the structure of the complex is challenging, primarily due to the heterogeneity of their binding energy landscape and the greater flexibility of ssDNA or ssRNA compared with double-stranded nucleic acids. Consequently, considerably fewer computational studies have explored interactions between proteins and single-stranded nucleic acids compared with protein interactions with double-stranded nucleic acids. Here, we report a newly developed energy-based coarse-grained model to predict the structure of ssDNA–ssDBP and ssRNA–ssRBP complexes and to assess their sequence-specific interactions and stabilities. We tuned two factors that can modulate specific recognition: base–aromatic stacking strength and the flexibility of the single-stranded nucleic acid. The model was successfully applied to predict the binding conformations of 12 distinct ssDBP and ssRBP structures with their cognate ssDNA and ssRNA partners having various sequences. Estimated binding energies agreed well with the corresponding experimental binding affinities. Bound conformations from the simulation showed a funnel-shaped binding energy distribution where the native-like conformations corresponded to the energy minima. The various ssDNA–protein and ssRNA–protein complexes differed in the balance of electrostatic and aromatic energies. The lower affinity of the ssRNA–ssRBP complexes compared with the ssDNA–ssDBP complexes stems from lower flexibility of ssRNA compared to ssDNA, which results in higher rate constants for the dissociation of the complex (k_off) for complexes involving the former.

Quantifying bimolecular self-assembly is pivotal to understanding cellular function. In recent years, a large progress has been made in understanding the structure and biophysics of protein-protein interactions. Particularly, various computational tools are available for predicting these structures and to estimate their stability and the driving forces of their formation. The understating of the interactions between proteins and nucleic acids, however, is still limited, presumably due to the involvement of non-specific interactions as well as the high conformational plasticity that may demand an induced-fit mechanism. In particular, the interactions between proteins and single-stranded nucleic acids (i.e., single-stranded DNA and RNA) is very challenging due to their high flexibility. Furthermore, the interface between proteins and single-stranded nucleic acids is often chemically more heterogeneous than the interface between proteins and double-stranded DNA. In this study, we developed a coarse-grained computational model to predict the structure of complexes between proteins and single-stranded nucleic acids. The model was applied to estimate binding affinities and the estimated binding energies agreed well with the corresponding experimental binding affinities. The kinetics of association as well as the specificity of the complexes between proteins and ssDNA are different than those with ssRNA, mostly due to differences in their conformational flexibility.