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Protein–DNA and protein–RNA interactions are involved in many biological processes and regulate many cellular functions. Moreover, they are related to many human diseases. To understand the molecular mechanism of protein–DNA binding and protein–RNA binding, it is important to identify which residues in the protein sequence bind to DNA and RNA. At present, there are few methods for specifically identifying the binding sites of disease-related protein–DNA and protein–RNA. In this study, so we combined four machine learning algorithms into an ensemble classifier (EPDRNA) to predict DNA and RNA binding sites in disease-related proteins. The dataset used in model was collated from UniProt and PDB database, and PSSM, physicochemical properties and amino acid type were used as features. The EPDRNA adopted soft voting and achieved the best AUC value of 0.73 at the DNA binding sites, and the best AUC value of 0.71 at the RNA binding sites in 10-fold cross validation in the training sets. In order to further verify the performance of the model, we assessed EPDRNA for the prediction of DNA-binding sites and the prediction of RNA-binding sites on the independent test dataset. The EPDRNA achieved 85% recall rate and 25% precision on the protein–DNA interaction independent test set, and achieved 82% recall rate and 27% precision on the protein–RNA interaction independent test set. The online EPDRNA webserver is freely available at http://www.s-bioinformatics.cn/epdrna. [ABSTRACT FROM AUTHOR]

Protein-nucleic acid (PNA) binding plays critical roles in the transcription, translation, regulation, and three-dimensional organization of the genome. Structural models of proteins bound to nucleic acids (NA) provide insights into the chemical, electrostatic, and geometric properties of the protein structure that give rise to NA binding but are scarce relative to models of unbound proteins. We developed a deep learning approach for predicting PNA binding given the unbound structure of a protein that we call PNAbind. Our method utilizes graph neural networks to encode the spatial distribution of physicochemical and geometric properties of protein structures that are predictive of NA binding. Using global physicochemical encodings, our models predict the overall binding function of a protein, and using local encodings, they predict the location of individual NA binding residues. Our models can discriminate between specificity for DNA or RNA binding, and we show that predictions made on computationally derived protein structures can be used to gain mechanistic understanding of chemical and structural features that determine NA recognition. Binding site predictions were validated against benchmark datasets, achieving AUROC scores in the range of 0.92–0.95. We applied our models to the HIV-1 restriction factor APOBEC3G and showed that our model predictions are consistent with and help explain experimental RNA binding data. [ABSTRACT FROM AUTHOR]

Aureochromes are light-responsive transcription factors found in photosynthetic stramenopile algae, including diatoms. They contain a blue light-sensitive LOV domain and a DNA-binding bZIP domain. Aureochromes can form homo- and heterodimers, activating the expression of intermediate regulatory factors in diatoms. These photoreceptors are important for sustaining the aquatic food web and have unique properties that allow them to directly bind to target DNA upon blue light activation. The study of aureochromes in diatoms, particularly in the model organism Phaeodactylum tricornutum, has provided insights into their role in gene regulation and their interactions with other transcription factors. Further research is needed to explore the regulatory network components and the diversity of aureochromes in different stramenopile species. [Extracted from the article]

The generalized solutions of the dimensionality reduction problem in diffusion–reaction systems have been found for the first time by rigorously decoupling probability functions. Numerically exact results are obtained by straightforwardly applying the generalized solution to three models: protein‐DNA binding model (3D‐1D reduction), surface‐mediated diffusion (3D‐2D reduction), and line‐mediated diffusion cases (2D‐1D reduction). The results are confirmed by Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Bacterial NAD+-dependent DNA ligases (LigAs) are enzymes involved in replication, recombination, and DNA-repair processes by catalyzing the formation of phosphodiester bonds in the backbone of DNA. These multidomain proteins exhibit four modular domains, that are highly conserved across species, with the BRCT (breast cancer type 1 C-terminus) domain on the C-terminus of the enzyme. In this study, we expressed and purified both recombinant full-length and a C-terminally truncated LigA from Deinococcus radiodurans (DrLigA and DrLigA∆BRCT) and characterized them using biochemical and X-ray crystallography techniques. Using seeds of DrLigA spherulites, we obtained ≤ 100 µm plate crystals of DrLigA∆BRCT. The crystal structure of the truncated protein was obtained at 3.4 Å resolution, revealing DrLigA∆BRCT in a non-adenylated state. Using molecular beacon-based activity assays, we demonstrated that DNA ligation via nick sealing remains unaffected in the truncated DrLigA∆BRCT. However, DNA-binding assays revealed a reduction in the affinity of DrLigA∆BRCT for dsDNA. Thus, we conclude that the flexible BRCT domain, while not critical for DNA nick-joining, plays a role in the DNA binding process, which may be a conserved function of the BRCT domain in LigA-type DNA ligases. [ABSTRACT FROM AUTHOR]

In mammals, de novo methylation of cytosines in DNA CpG sites is performed by DNA methyltransferase Dnmt3a. Changes in the methylation status of CpG islands are critical for gene regulation and for the progression of some cancers. Recently, the potential involvement of DNA G-quadruplexes (G4s) in methylation control has been found. Here, we provide evidence for a link between G4 formation and the function of murine DNA methyltransferase Dnmt3a and its individual domains. As DNA models, we used (i) an isolated G4 formed by oligonucleotide capable of folding into parallel quadruplex and (ii) the same G4 inserted into a double-stranded DNA bearing several CpG sites. Using electrophoretic mobility shift and fluorescence polarization assays, we showed that the Dnmt3a catalytic domain (Dnmt3a-CD), in contrast to regulatory PWWP domain, effectively binds the G4 structure formed in both DNA models. The G4-forming oligonucleotide displaced the DNA substrate from its complex with Dnmt3a-CD, resulting in a dramatic suppression of the enzyme activity. In addition, a direct impact of G4 inserted into the DNA duplex on the methylation of a specific CpG site was revealed. Possible mechanisms of G4-mediated epigenetic regulation may include Dnmt3a sequestration at G4 and/or disruption of Dnmt3a oligomerization on the DNA surface. [ABSTRACT FROM AUTHOR]

The complexities of DNA recognition by transcription factors (TFs) with multiple Cys2-His2 zinc fingers (C2H2-ZFs) remain poorly studied. We previously reported a mutation (R1092W) in the C2H2-ZF TF Zfp335 that led to selective loss of binding at a subset of targets, although the basis for this effect was unclear. We show that Zfp335 binds DNA and drives transcription via recognition of two distinct consensus motifs by separate ZF clusters and identify the specific motif interaction disrupted by R1092W. Our work presents Zfp335 as a model for understanding how C2H2-ZF TFs may use multiple recognition motifs to control gene expression.

Base excision repair (BER) requires a tight coordination between the repair enzymes through protein-protein interactions and involves gap filling by DNA polymerase (pol) β and subsequent nick sealing by DNA ligase (LIG) 1 or LIGIIIα at the downstream steps. Apurinic/apyrimidinic-endonuclease 1 (APE1), by its exonuclease activity, proofreads 3' mismatches incorporated by polβ during BER. We previously reported that the interruptions in the functional interplay between polβ and the BER ligases result in faulty repair events. Yet, how the protein interactions of LIG1 and LIGIIIα could affect the repair pathway coordination during nick sealing at the final steps remains unknown. Here, we demonstrate that LIGIIIα interacts more tightly with polβ and APE1 than LIG1, and the N-terminal noncatalytic region of LIG1 as well as the catalytic core and BRCT domain of LIGIIIα mediate interactions with both proteins. Our results demonstrated less efficient nick sealing of polβ nucleotide insertion products in the absence of LIGIIIα zinc-finger domain and LIG1 N-terminal region. Furthermore, we showed a coordination between APE1 and LIG1/LIGIIIα during the removal of 3' mismatches from the nick repair intermediate on which both BER ligases can seal noncanonical ends or gap repair intermediate leading to products of single deletion mutagenesis. Overall results demonstrate the importance of functional coordination from gap filling by polβ coupled to nick sealing by LIG1/LIGIIIα in the presence of proofreading by APE1, which is mainly governed by protein-protein interactions and protein-DNA intermediate communications, to maintain repair efficiency at the downstream steps of the BER pathway., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

ABSTRACT Viral infections are associated with extensive remodeling of the cellular proteome. Viruses encode gene products that manipulate host proteins to redirect cellular processes or subvert antiviral immune responses. Adenovirus (AdV) encodes proteins from the early E4 region which are necessary for productive infection. Some cellular antiviral proteins are known to be targeted by AdV E4 gene products, resulting in their degradation or mislocalization. However, the full repertoire of host proteome changes induced by viral E4 proteins has not been defined. To identify cellular proteins and processes manipulated by viral products, we developed a global, unbiased proteomics approach to analyze changes to the host proteome during infection with adenovirus serotype 5 (Ad5) virus. We used whole-cell proteomics to measure total protein abundances in the proteome during Ad5 infection. Since host antiviral proteins can antagonize viral infection by associating with viral genomes and inhibiting essential viral processes, we used Isolation of Proteins on Nascent DNA (iPOND) proteomics to identify proteins associated with viral genomes during infection with wild-type Ad5 or an E4 mutant virus. By integrating these proteomics data sets, we identified cellular factors that are degraded in an E4-dependent manner or are associated with the viral genome in the absence of E4 proteins. We further show that some identified proteins exert inhibitory effects on Ad5 infection. Our systems-level analysis reveals cellular processes that are manipulated during Ad5 infection and points to host factors counteracted by early viral proteins as they remodel the host proteome to promote efficient infection. IMPORTANCE Viral infections induce myriad changes to the host cell proteome. As viruses harness cellular processes and counteract host defenses, they impact abundance, post-translational modifications, interactions, or localization of cellular proteins. Elucidating the dynamic changes to the cellular proteome during viral replication is integral to understanding how virus-host interactions influence the outcome of infection. Adenovirus encodes early gene products from the E4 genomic region that are known to alter host response pathways and promote replication, but the full extent of proteome modifications they mediate is not known. We used an integrated proteomics approach to quantitate protein abundance and protein associations with viral DNA during virus infection. Systems-level analysis identifies cellular proteins and processes impacted in an E4-dependent manner, suggesting ways that adenovirus counteracts potentially inhibitory host defenses. This study provides a global view of adenovirus-mediated proteome remodeling, which can serve as a model to investigate virus-host interactions of DNA viruses.

Alkaline protease AprE, produced by Bacillus licheniformis 2709 is an important edible hydrolase, which has potential applications in nutrient acquisition and medicine. The expression of AprE is finely regulated by a complex transcriptional regulation system. However, there is little study on transcriptional regulation mechanism of AprE biosynthesis in Bacillus licheniformis , which limits system engineering and further enhancement of AprE. Here, the severely depressed expression of aprE in degU and degS deletion mutants illustrated that the regulator DegU and its phosphorylation played a crucial part in AprE biosynthesis. Further electrophoretic mobility shift assay (EMSA) in vitro indicated that phosphorylated DegU can directly bind to the regulatory region though the DNase I foot-printing experiments failed to observe protected region. The plasmid-mediated overexpression of degU32 (Hy) obviously improved the yield of AprE by 41.6 % compared with the control strain, which demonstrated the importance of phosphorylation state of DegU on the transcription of aprE in vivo. In this study, the putative binding sequence of aprE (5′-TAAAT......AAAAT.......AACAT...TAAAA-3′) located upstream −91 to −87 bp, −101 to −97 bp, −195 to −191 bp, −215 to −211 bp of the transcription start site (TSS) in B. licheniformis was computationally identified based on the DNA-binding sites of DegU in Bacillus subtilis. Overall, we systematically investigated the influence of the interplay between phosphorylated DegU and its cognate DNA sequence on expression of aprE , which not only contributes to the further AprE high-production in a genetically modified host in the future, but also significantly increases our understanding of the aprE transcription mechanism. [ABSTRACT FROM AUTHOR]

Abstract Background Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex structures, protein-DNA docking can be used to predict native or near-native complex models. A docking program typically generates a large number of complex conformations and predicts the complex model(s) based on interaction energies between protein and DNA. However, the prediction accuracy is hampered by current approaches to model assessment, especially when docking simulations fail to produce any near-native models. Results We present here a Support Vector Machine (SVM)-based approach for quality assessment of the predicted transcription factor (TF)-DNA complex models. Besides a knowledge-based protein-DNA interaction potential DDNA3, we applied several structural features that have been shown to play important roles in binding specificity between transcription factors and DNA molecules to quality assessment of complex models. To address the issue of unbalanced positive and negative cases in the training dataset, we applied hard-negative mining, an iterative training process that selects an initial training dataset by combining all of the positive cases and a random sample from the negative cases. Results show that the SVM model greatly improves prediction accuracy (84.2%) over two knowledge-based protein-DNA interaction potentials, orientation potential (60.8%) and DDNA3 (68.4%). The improvement is achieved through reducing the number of false positive predictions, especially for the hard docking cases, in which a docking algorithm fails to produce any near-native complex models. Conclusions A learning-based SVM scoring model with structural features for specific protein-DNA binding and an atomic-level protein-DNA interaction potential DDNA3 significantly improves prediction accuracy of complex models by successfully identifying cases without near-native structural models.

The sequence-dependent structure and deformability of DNA play a major role for binding of proteins and regulation of gene expression. So far, most efforts to model DNA flexibility are based on unimodal harmonic stiffness models at base-pair resolution. However, multimodal behavior due to distinct conformational substates also contributes significantly to the conformational flexibility of DNA. Moreover, these local substates are correlated to their nearest-neighbor substates. A description for DNA elasticity which includes both multimodality and nearestneighbor coupling has remained a challenge, which we solve by combining our multivariate harmonic approximation with an Ising model for the substates. In a series of applications to DNA fluctuations and protein-DNA complexes, we demonstrate substantial improvements over the unimodal stiffness model. Furthermore, our multivariate Ising model reveals a mechanical destabilization for adenine (A)-tracts to undergo nucleosome formation. Our approach offers a wide range of applications to determine sequence-dependent deformation energies of DNA and to investigate indirect readout contributions to protein-DNA recognition. [ABSTRACT FROM AUTHOR]

Evolution shapes protein sequences for their functions. Here, we studied the moonlighting functions of the N-linked sequon NXS/T, where X is not P, in human nucleocytosolic proteins. By comparing membrane and secreted proteins in which sequons are well known for N-glycosylation, we discovered that cyto-sequons can participate in nucleic acid binding, particularly in zinc finger proteins. Our global studies further discovered that sequon occurrence is largely proportional to protein length. The contribution of sequons to protein functions, including both N-glycosylation and nucleic acid binding, can be regulated through their density as well as the biased usage between NXS and NXT. In proteins where other PTMs or structural features are rich, such as phosphorylation, transmembrane ɑ-helices, and disulfide bridges, sequon occurrence is scarce. The information acquired here should help understand the relationship between protein sequence and function and assist future protein design and engineering., (© 2024. The Author(s).)

DNA carries important genetic instructions and plays vital roles in regulating biological activities in living cells. Proteins such as transcription factors binds to DNA to regulate the biological functions of DNA, and similarly many drug molecules also bind to DNA to modulate its functions. Due to the importance of protein-DNA and drug-DNA binding, there has been intense effort in developing novel nanosensors in the same length scale as DNA, to effectively study these binding interactions in details. In addition, aptamers can be artificially selected to detect metal ions and pathogens such as bacteria and viruses, making nucleic acid nanosensors more versatile in detecting a large variety of analytes. In this minireview, we first explained the different types and binding modes of protein-DNA and drug-DNA interactions in the biological systems, as well as aptamer-target binding. This was followed by the review of five types of nucleic acid nanosensors based on optical or electrochemical detection. The five types of nucleic acid nanosensors utilizing colorimetric, dynamic light scattering (DLS), surface-enhanced Raman spectroscopy (SERS), fluorescence and electrochemical detections have been recently developed to tackle some of the challenges in high-throughput screening technology for large scale analysis, which is especially useful for drug development and mass screening for pandemic outbreak such as SARS or COVID-19.

APOBEC3G (A3G), an enzyme expressed in primates with the potential to inhibit human immunodeficiency virus type 1 (HIV-1) infectivity, is a single-stranded DNA (ssDNA) deoxycytidine deaminase with two domains, a catalytically active, weakly ssDNA binding C-terminal domain (CTD) and a catalytically inactive, strongly ssDNA binding N-terminal domain (NTD). Using optical tweezers, we measure A3G binding a single, long ssDNA substrate under various applied forces to characterize the binding interaction. A3G binds ssDNA in multiple steps and in two distinct conformations, distinguished by degree of ssDNA contraction. A3G stabilizes formation of ssDNA loops, an ability inhibited by A3G oligomerization. Our data suggests A3G securely binds ssDNA through the NTD, while the CTD samples and potentially deaminates the substrate. Oligomerization of A3G stabilizes ssDNA binding but inhibits the CTD’s search function. These processes explain A3G’s ability to efficiently deaminate numerous sites across a 10,000 base viral genome during the reverse transcription process.

Every method used to quantify biomolecular interactions has its own strengths and limitations. To quantify protein‐DNA binding affinities, nitrocellulose filter binding assays with 32P‐labeled DNA quantify Kd values from 10−12 to 10−8 M but have several technical limitations. Here, we considered the suitability of biolayer interferometry (BLI), which monitors association and dissociation of a soluble macromolecule to an immobilized species; the ratio koff/kon determines Kd. However, for lactose repressor protein (LacI) and an engineered repressor protein ("LLhF") binding immobilized DNA, complicated kinetic curves precluded this analysis. Thus, we determined whether the amplitude of the BLI signal at equilibrium related linearly to the fraction of protein bound to DNA. A key question was the effective concentration of immobilized DNA. Equilibrium titration experiments with DNA concentrations below Kd (equilibrium binding regime) must be analyzed differently than those with DNA near or above Kd (stoichiometric binding regime). For ForteBio streptavidin tips, the most frequent effective DNA concentration was ~2 × 10−9 M. Although variation occurred among different lots of sensor tips, binding events with Kd ≥ 10−8 M should reliably be in the equilibrium binding regime. We also observed effects from multi‐valent interactions: Tetrameric LacI bound two immobilized DNAs whereas dimeric LLhF did not. We next used BLI to quantify the amount of inducer sugars required to allosterically diminish protein‐DNA binding and to assess the affinity of fructose‐1‐kinase for the DNA‐LLhF complex. Overall, when experimental design corresponded with appropriate data interpretation, BLI was convenient and reliable for monitoring equilibrium titrations and thereby quantifying a variety of binding interactions. [ABSTRACT FROM AUTHOR]

The nuclear receptor NR4A subfamily (NR4A1/NGFI-B, NR4A2/Nurr1 and NR4A3/NOR-1) can recognize different classes of DNA response elements either as a monomer, homodimer, or heterodimer. In this study, we determined the structure of the NR4A1 DNA-binding domain (NR4A1-DBD) bound to natural Nur-responsive elements (NurREs) in the promoter region of the pituitary proopiomelanocortin (POMC) gene (NurRE POMC) at 3.12 Å resolution. The NR4A1-DBD molecules bound independently to this element in our structure. The N-terminal helix H1 forms specific contacts with major groove, and C-terminal extension interact extensively with minor groove. Moreover our modelling structure of NR4A1 large fragment complexed with NurRE POMC indicated that ligand binding domain of NR4A might form dimer interactions to help recognize DNA. Overall, our analyses provide a molecular basis for DNA binding of NR4A proteins as a homodimer and novel insight into the molecular functions of NR4A modulation of gene expression. • A crystal structure of NR4A1/DNA complexes was solved. • The DNA element is a natural sequence located in the promoter of pituitary proopiomelanocortin (POMC) gene. • A structure of full length NR4A1/DNA complexes was modeled based on our crystal structure. • A dimerization interface might exist in the ligand binding domain in the modeled structure. [ABSTRACT FROM AUTHOR]

The results obtained in this study demonstrate H-NS oligomerization in solution is not sufficient in forming large structures of H-NS-DNA assemblies indicating oligomerization along bacterial DNA is crucial. We present a comprehensive and novel multi-scale modeling scheme to study protein-protein and protein-DNA interactions, with the focus on population balance modeling of assemblies formed by the H-NS protein and bacterial DNA. The model helps understanding how the concentration of H-NS influences the formation of H-NS-DNA assemblies. The presented model covers the two underlying molecular mechanisms involved in assembly formation, H-NS oligomerization in solution and H-NS-DNA binding. Within protein oligomerization interactions, protein molecules are entitled to dimerize, propagate, recombine and deform (break). In addition, DNA binding and unbinding interactions are included to account for formation of filaments along DNA. All mechanisms have been modeled with their associated forward (formation) and backward (deformation) interactions. The results obtained agree well with former experimental studies. [ABSTRACT FROM AUTHOR]

Cleavage Under Targets and Tagmentation (CUT&Tag) provides high-resolution sequencing libraries for profiling diverse chromatin components. This protocol details the steps to generate CUT&Tag libraries from fresh or frozen tissues. This CUT&Tag workflow has nine main steps: isolation of nuclei from tissues, binding of nuclei to Concanavalin A-coated beads, binding of the primary antibody, binding of the secondary antibody, binding pA-Tn5 adapter complex, tagmentation, DNA extraction, PCR, and post-PCR cleanup and size selection. This protocol enabled us to generate and sequence CUT&Tag libraries across a broad range of fresh and frozen tissue types., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Electrophoretic mobility shift assays (EMSAs) of DNA-binding proteins and labeled DNA allow the qualitative and quantitative characterization of protein-DNA complex formation using native (nondenaturing) polyacrylamide or agarose gel electrophoresis. By varying the incubation temperature of the protein-DNA binding reaction and maintaining this temperature during electrophoresis, temperature-dependent protein-DNA interactions can be investigated. Here, we provide examples of the binding of a transcriptional repressor complex called the Evening Complex, comprising the DNA-binding protein LUX ARRYTHMO (LUX), the scaffold protein EARLY FLOWERING 3 (ELF3), and the adapter protein ELF4, to its cognate DNA and demonstrate direct detection and visualization of thermoresponsive binding in vitro. As negative controls we use the LUX DNA-binding domain and LUX full length protein, which do not exhibit temperature-dependent DNA binding., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Epigenetic regulation is essential to various biological phenomena such as cell differentiation and cancer. DNA methylation is one of the most important epigenetic signals, as it is directly involved in gene silencing of transposable elements, genomic imprinting, and chromosome X inactivation. To mediate these processes, methyl-CpG-binding domain (MBD) proteins recognize specific signals encoded in the form of DNA methylation patterns. AtMBD6, one of the 12 MBD proteins in Arabidopsis thaliana, shares a high sequential homology in the MBD domain with mammalian MBD proteins, but a detailed characterization of its structural and functional properties remains elusive. Here, we report the 1H, 13C, and 15N resonance assignments of the isolated MBD domain of AtMBD6. Analysis of the chemical shift data implied that the MBD domain of AtMBD6 has a secondary structure similar to that of mammalian MeCP2, while the β-strands β1 and β3 of AtMBD6 were found to be longer than those of MeCP2. The structural differences provide insight into the different recognition mechanisms of methylated DNA by plant and mammalian MBDs. The assignments reported here will aid further analyses such as titration experiments and three-dimensional structure determination using NMR to yield a detailed characterization of the interaction between AtMBD6 and methylated DNAs. [ABSTRACT FROM AUTHOR]

Background: Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex structures, protein-DNA docking can be used to predict native or near-native complex models. A docking program typically generates a large number of complex conformations and predicts the complex model(s) based on interaction energies between protein and DNA. However, the prediction accuracy is hampered by current approaches to model assessment, especially when docking simulations fail to produce any near-native models. Results: We present here a Support Vector Machine (SVM)-based approach for quality assessment of the predicted transcription factor (TF)-DNA complex models. Besides a knowledge-based protein-DNA interaction potential DDNA3, we applied several structural features that have been shown to play important roles in binding specificity between transcription factors and DNA molecules to quality assessment of complex models. To address the issue of unbalanced positive and negative cases in the training dataset, we applied hard-negative mining, an iterative training process that selects an initial training dataset by combining all of the positive cases and a random sample from the negative cases. Results show that the SVM model greatly improves prediction accuracy (84.2%) over two knowledge-based protein-DNA interaction potentials, orientation potential (60.8%) and DDNA3 (68.4%). The improvement is achieved through reducing the number of false positive predictions, especially for the hard docking cases, in which a docking algorithm fails to produce any near-native complex models. Conclusions: A learning-based SVM scoring model with structural features for specific protein-DNA binding and an atomic-level protein-DNA interaction potential DDNA3 significantly improves prediction accuracy of complex models by successfully identifying cases without near-native structural models. [ABSTRACT FROM AUTHOR]

Transcription factors (TFs) are primary regulators of gene expression in cells, where they bind specific genomic target sites to control transcription. Quantitative measurements of TF-DNA binding energies can improve the accuracy of predictions of TF occupancy and downstream gene expression in vivo and shed light on how transcriptional networks are rewired throughout evolution. Here, we present a sequencing-based TF binding assay and analysis pipeline (BET-seq, for Binding Energy Topography by sequencing) capable of providing quantitative estimates of binding energies for more than one million DNA sequences in parallel at high energetic resolution. Using this platform, we measured the binding energies associated with all possible combinations of 10 nucleotides flanking the known consensus DNA target interacting with two model yeast TFs, Pho4 and Cbf1. A large fraction of these flanking mutations change overall binding energies by an amount equal to or greater than consensus site mutations, suggesting that current definitions of TF binding sites may be too restrictive. By systematically comparing estimates of binding energies output by deep neural networks (NNs) and biophysical models trained on these data, we establish that dinucleotide (DN) specificities are sufficient to explain essentially all variance in observed binding behavior, with Cbf1 binding exhibiting significantly more nonadditivity than Pho4. NN-derived binding energies agree with orthogonal biochemical measurements and reveal that dynamically occupied sites in vivo are both energetically and mutationally distant from the highest affinity sites. [ABSTRACT FROM AUTHOR]

Protein-DNA binding plays a central role in gene regulation and by that in all processes in the living cell. Novel experimental and computational approaches facilitate better understanding of protein-DNA binding preferences via high-throughput measurement of protein binding to a large number of DNA sequences and inference of binding models from them. Here we review the state of the art in measuring protein-DNA binding in vitro, emphasizing the advantages and limitations of different technologies. In addition, we describe models for representing protein-DNA binding preferences and key computational approaches to learn those from high-throughput data. Using large experimental data sets, we test the performance of different models based on different measuring techniques. We conclude with pertinent open problems. [ABSTRACT FROM AUTHOR]

Understanding binding cores is of fundamental importance in deciphering Protein-DNA (TF-TFBS) binding and gene regulation. Limited by expensive experiments, it is promising to discover them with variations directly from sequence data. Although existing computational methods have produced satisfactory results, they are one-to-one mappings with no site-specific information on residue/nucleotide variations, where these variations in binding cores may impact binding specificity. This study presents a new representation for modeling binding cores by incorporating variations and an algorithm to discover them from only sequence data. Our algorithm takes protein and DNA sequences from TRANSFAC (a Protein-DNA Binding Database) as input; discovers from both sets of sequences conserved regions in Aligned Pattern Clusters (APCs); associates them as Protein-DNA Co-Occurring APCs; ranks the Protein-DNA Co-Occurring APCs according to their co-occurrence, and among the top ones, finds three-dimensional structures to support each binding core candidate. If successful, candidates are verified as binding cores. Otherwise, homology modeling is applied to their close matches in PDB to attain new chemically feasible binding cores. Our algorithm obtains binding cores with higher precision and much faster runtime ($\geq$ 1,600x) than that of its contemporaries, discovering candidates that do not co-occur as one-to-one associated patterns in the raw data. Availability: http://www.pami.uwaterloo.ca/~ealee/files/tcbbPnDna2015/Release.zip. [ABSTRACT FROM PUBLISHER]

Studies of protein interactions with chemically modified nucleic acids are of importance in various areas of biomolecular and biomedical research, including investigations of the binding of proteins important in medicine with DNA modified with drugs and diagnostic applications of modified DNAs in biosensing and bioanalysis. Chemical modification of DNA substrates with various species inside or outside specific protein binding sites can affect the protein-DNA recognition. In this paper we present a simple electrochemical immunoprecipitation technique designed for evaluation of the effects of antitumor drug cisplatin on the p53-DNA binding. The cisplatin-DNA adducts are utilized as electroactive labels allowing a facile determination of the p53-bound modified DNA. Effects observed using this technique accord with results of previous biochemical assays. This approach is potentially applicable in studies that deal with the influence of any electroactive DNA modifications on the protein-DNA binding. [ABSTRACT FROM AUTHOR]

G-quadruplex (G4) is a DNA/RNA conformation that consists of two or more G-tetrads resulting from four-guanine bases connected by Hoogsteen-type hydrogen bonds, which is often found in the telomeres of chromatin, as well as in the promoter regions of genes. The function of G4 in the genomic DNA is being elucidated and some G4-protein interactions have been reported; these are believed to play a role in vital cellular functions. In this study, we focused on CpG methylation, a well-known epigenetic modification of the genomic DNA, especially found in the promoter regions. Although many G4-forming sequences within the genomic DNA harbor CpG sites, the relationship between CpG methylation and the binding properties of associated proteins remains unclear. We demonstrated that the binding ability of vascular endothelial growth factor (VEGF) G4 DNA to VEGF165 protein was significantly decreased by CpG methylation. We identified the binding activity of G4 DNA oligonucleotides derived from gene promoter regions to SP1, a transcription factor that interacts with a G4-forming DNA and is also altered by CpG methylation. The effect of methylation on binding affinity was accompanied by changes in G4 structure and/or topology. Therefore, this study suggested that CpG methylation might be involved in protein binding to G4-forming DNA segments for purposes of transcriptional regulation.

Somatic mutations are highly enriched at transcription factor (TF) binding sites, with the strongest trend being observed for ultraviolet light (UV)-induced mutations in melanomas. One of the main mechanisms proposed for this hypermutation pattern is the inefficient repair of UV lesions within TF-binding sites, caused by competition between TFs bound to these lesions and the DNA repair proteins that must recognize the lesions to initiate repair. However, TF binding to UV-irradiated DNA is poorly characterized, and it is unclear whether TFs maintain specificity for their DNA sites after UV exposure. We developed UV-Bind, a high-throughput approach to investigate the impact of UV irradiation on protein-DNA binding specificity. We applied UV-Bind to ten TFs from eight structural families, and found that UV lesions significantly altered the DNA-binding preferences of all the TFs tested. The main effect was a decrease in binding specificity, but the precise effects and their magnitude differ across factors. Importantly, we found that despite the overall reduction in DNA-binding specificity in the presence of UV lesions, TFs can still compete with repair proteins for lesion recognition, in a manner consistent with their specificity for UV-irradiated DNA. In addition, for a subset of TFs, we identified a surprising but reproducible effect at certain nonconsensus DNA sequences, where UV irradiation leads to a high increase in the level of TF binding. These changes in DNA-binding specificity after UV irradiation, at both consensus and nonconsensus sites, have important implications for the regulatory and mutagenic roles of TFs in the cell.

Several DNA binding proteins exist in dimeric form when bound with DNA to be able to exhibit various biological processes such as DNA repair, DNA replication and gene expression. Various dimeric forms of Ribonuclease A (RNase A) and other members of the ribonuclease A superfamily are endowed with a multitude of biological activities such as antitumor and antiviral activity. In the present study, we have compared the DNA binding properties between the RNase A monomer and the dityrosine (DT) cross-linked RNase A dimer, and checked the inhibitory effect of DNA on the ribonucleolytic activity of the dimeric protein. An agarose gel based assay shows that like the monomer, the dimer also binds with DNA. The number of nucleotides bound per monomer unit of the dimer is higher than the number of nucleotides that bind with the each monomer. From fluorescence measurements, the association constant ( K a ) values for complexation of the monomer and the dimer with ct-DNA are (4.95 ± 0.45) × 10 4 M − 1 and (1.29 ± 0.05) × 10 6 M − 1 respectively. Binding constant ( K b ) values for the binding of the monomer and the dimer with ct-DNA were determined using UV–vis spectroscopy and were found to be (4.96 ± 1.67) × 10 4 M − 1 and (4.32 ± 0.31) × 10 5 M − 1 respectively. Circular dichroism studies shows that the dimer possesses significant effect on DNA conformation. The melting profile for the ct-DNA–dimer indicated that the melting temperature ( T m ) for the ct-DNA–dimer complex is lower compared to the ct-DNA–monomer complex. The ribonucleolytic activity of the dimer, like the monomer, diminishes upon binding with DNA. [ABSTRACT FROM AUTHOR]

The complexities of DNA recognition by transcription factors (TFs) with multiple Cys2–His2 zinc fingers (C2H2-ZFs) remain poorly studied. We previously reported a mutation (R1092W) in the C2H2-ZF TF Zfp335 that led to selective loss of binding at a subset of targets, although the basis for this effect was unclear. We show that Zfp335 binds DNA and drives transcription via recognition of two distinct consensus motifs by separate ZF clusters and identify the specific motif interaction disrupted by R1092W. Our work presents Zfp335 as a model for understanding how C2H2-ZF TFs may use multiple recognition motifs to control gene expression. [ABSTRACT FROM AUTHOR]

Motivated by the pressing need to characterize protein-DNA and protein-RNAinteractions on large scale, we review a comprehensive set of 30 computational methods for high-throughput prediction of RNA-or DNA-binding residues fromprotein sequences. Wesummarize these predictors fromseveral significant perspectives including their design, outputs and availability. Weperformempirical assessment ofmethods that offer web servers using a new benchmark data set characterized by a more complete annotation that includes binding residues transferred fromthe same or similar proteins.Weshowthat predictors of DNA-binding (RNA-binding) residues offer relatively strong predictive performance but they are unable to properly separate DNA- fromRNA-binding residues.Wedesign andempirically assess several types of consensuses and demonstrate that machine learning (ML)-based approaches provide improved predictive performancewhen compared with the individual predictors of DNA-binding residues or RNA-binding residues.Wealso formulate and execute first-of-its-kind study that targets combined prediction ofDNA- and RNA-binding residues.Wedesign and test three types of consensuses for this prediction and conclude that this novel approach that relies on ML design provides better predictive quality than individual predictors when tested on prediction ofDNA- and RNA-binding residues individually. It also substantially improves discrimination between these two types of nucleic acids. Our results suggest that development of a new generation of predictors would benefit fromusing training data sets that combine both RNA- andDNA-binding proteins, designing new inputs that specifically target either DNA- or RNA-binding residues and pursuing combined prediction of DNA- and RNA-binding residues. [ABSTRACT FROM AUTHOR]

A multitude of studies have looked at the in vivo and in vitro behavior of the lac repressor binding to DNA and effector molecules in order to study transcriptional repression, however these studies are not always reconcilable. Here we use in vitro transcription to directly mimic the in vivo system in order to build a self consistent set of experiments to directly compare in vivo and in vitro genetic repression. A thermodynamic model of the lac repressor binding to operator DNA and effector is used to link DNA occupancy to either normalized in vitro mRNA product or normalized in vivo fluorescence of a regulated gene, YFP. An accurate measurement of repressor, DNA and effector concentrations were made both in vivo and in vitro allowing for direct modeling of the entire thermodynamic equilibrium. In vivo repression profiles are accurately predicted from the given in vitro parameters when molecular crowding is considered. Interestingly, our measured repressor–operator DNA affinity differs significantly from previous in vitro measurements. The literature values are unable to replicate in vivo binding data. We therefore conclude that the repressor-DNA affinity is much weaker than previously thought. This finding would suggest that in vitro techniques that are specifically designed to mimic the in vivo process may be necessary to replicate the native system.

An n-string tangle is a three-dimensional ball with n-strings properly embedded in it. In the late 1980s, Ernst and Sumners introduced a tangle model for protein-DNA complexes. The protein is modeled by a three-dimensional ball and the protein-bound DNA is modeled by strings embedded inside the ball. Originally the tangle model was applied to proteins such as Tn3 resolvase which binds two DNA segments. This protein breaks and rejoins two DNA segments and can create knotted DNA. A 2-string tangle model can be used for this complex. More recently, Pathania, Jayaram and Harshey determined that the topological structure of DNA within a Mu protein complex consists of three DNA segments containing five crossings. Since Mu binds DNA sequences at three sites, this Mu protein-DNA complex can be modeled by a 3-string tangle. Darcy, Leucke and Vazquez analyzed Pathania et al.'s experimental results by using 3-string tangle analysis. There are protein-DNA complexes that involve four or more DNA sites. When a protein binds circular DNA at four sites, a protein-DNA complex can be modeled by a 4-string tangle with four loops outside of the tangle. We determine a biologically relevant 4-string tangle model. We also develop mathematics for solving 4-string tangle equations to determine the topology of DNA within a protein complex. [ABSTRACT FROM AUTHOR]

Recent advances in experimental and computational methodologies are enabling ultra-high resolution genome-wide profiles of protein–DNA binding events. For example, the ChIP-exo protocol precisely characterizes protein–DNA cross-linking patterns by combining chromatin immunoprecipitation (ChIP) with 5′ → 3′ exonuclease digestion. Similarly, deeply sequenced chromatin accessibility assays (e.g. DNase-seq and ATAC-seq) enable the detection of protected footprints at protein–DNA binding sites. With these techniques and others, we have the potential to characterize the individual nucleotides that interact with transcription factors, nucleosomes, RNA polymerases and other regulatory proteins in a particular cellular context. In this review, we explain the experimental assays and computational analysis methods that enable high-resolution profiling of protein–DNA binding events. We discuss the challenges and opportunities associated with such approaches. [ABSTRACT FROM AUTHOR]

A study of the effects of salt conditions on the association and dissociation of wild type p53 with different ~3 kbp long plasmid DNA substrates (supercoiled, relaxed circular and linear, containing or lacking a specific p53 binding site, p53CON) using immunoprecipitation at magnetic beads is presented. Salt concentrations above 200 mM strongly affected association of the p53 protein to any plasmid DNA substrate. Strikingly different behavior was observed when dissociation of pre-formed p53-DNA complexes in increased salt concentrations was studied. While contribution from the p53CON to the stability of the p53-DNA complexes was detected between 100 and 170 mM KCl, p53 complexes with circular DNAs (but not linear) exhibited considerable resistance towards salt treatment for KCl concentrations as high as 2 M provided that the p53 basic C-terminal DNA binding site (CTDBS) was available for DNA binding. On the contrary, when the CTDBS was blocked by antibody used for immunoprecipitation, all p53-DNA complexes were completely dissociated from the p53 protein in KCl concentrations ≥200 mM under the same conditions. These observations suggest: (a) different ways for association and dissociation of the p53-DNA complexes in the presence of the CTDBS; and (b) a critical role for a sliding mechanism, mediated by the C-terminal domain, in the dissociation process. [ABSTRACT FROM AUTHOR]

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 high-throughput 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. [ABSTRACT FROM AUTHOR]

Four-stranded DNA structures were structurally characterized in vitro by NMR, X-ray and Circular Dichroism spectroscopy in detail. Among the different types of quadruplexes (i-Motifs, minor groove quadruplexes, G-quadruplexes, etc.), the best described are G-quadruplexes which are featured by Hoogsteen base-paring. Sequences with the potential to form quadruplexes are widely present in genome of all organisms. They are found often in repetitive sequences such as telomeric ones, and also in promoter regions and 5' non-coding sequences. Recently, many proteins with binding affinity to G-quadruplexes have been identified. One of the initially portrayed G-rich regions, the human telomeric sequence (TTAGGG)n, is recognized by many proteins which can modulate telomerase activity. Sequences with the potential to form G-quadruplexes are often located in promoter regions of various oncogenes. The NHE III1 region of the c-MYC promoter has been shown to interact with nucleolin protein as well as other G-quadruplex-binding proteins. A number of G-rich sequences are also present in promoter region of estrogen receptor alpha. In addition to DNA quadruplexes, RNA quadruplexes, which are critical in translational regulation, have also been predicted and observed. For example, the RNA quadruplex formation in telomere-repeat-containing RNA is involved in interaction with TRF2 (telomere repeat binding factor 2) and plays key role in telomere regulation. All these fundamental examples suggest the importance of quadruplex structures in cell processes and their understanding may provide better insight into aging and disease development. [ABSTRACT FROM AUTHOR]

Redundancy and competition between R2R3-MYB activators and repressors on common target genes has been proposed as a fine-tuning mechanism for the regulation of plant secondary metabolism. This hypothesis was tested in white spruce [Picea glauca (Moench) Voss] by investigating the effects of R2R3-MYBs from different subgroups on common targets from distinct metabolic pathways. Comparative analysis of transcript profiling data in spruces overexpressing R2R3-MYBs from loblolly pine (Pinus taeda L.), PtMYB1, PtMYB8, and PtMYB14, defined a set of common genes that display opposite regulation effects. The relationship between the closest MYB homologues and 33 putative target genes was explored by quantitative PCR expression profiling in wild-type P. glauca plants during the diurnal cycle. Significant Spearman’s correlation estimates were consistent with the proposed opposite effect of different R2R3-MYBs on several putative target genes in a time-related and tissue-preferential manner. Expression of sequences coding for 4CL, DHS2, COMT1, SHM4, and a lipase thio/esterase positively correlated with that of PgMYB1 and PgMYB8, but negatively with that of PgMYB14 and PgMYB15. Complementary electrophoretic mobility shift assay (EMSA) and transactivation assay provided experimental evidence that these different R2R3-MYBs are able to bind similar AC cis-elements in the promoter region of Pg4CL and PgDHS2 genes but have opposite effects on their expression. Competitive binding EMSA experiments showed that PgMYB8 competes more strongly than PgMYB15 for the AC-I MYB binding site in the Pg4CL promoter. Together, the results bring a new perspective to the action of R2R3-MYB proteins in the regulation of distinct but interconnecting metabolism pathways. [ABSTRACT FROM PUBLISHER]