Information-driven protein-DNA docking using HADDOCK: it is a matter of flexibility

Modeling of Plasmodium falciparum Telomerase Reverse Transcriptase Ternary Complex: Repurposing of Nucleoside Analog Inhibitors

The Plasmodium falciparum telomerase reverse transcriptase (PfTERT) is a ribonucleoprotein that assists the maintenance of the telomeric ends of chromosomes by reverse transcription of its own RNA subunit. It represents an attractive therapeutic target for eradication of the plasmodial parasite at the asexual liver stage. Automated modeling using MUSTER and knowledge-based techniques were used to obtain a three-dimensional model of the active site of reverse transcriptase domain of PfTERT, which is responsible for catalyzing the addition of incoming dNTPs to the growing DNA strand in presence of divalent magnesium ions. Further, the ternary complex of the active site of PfTERT bound to a DNA-RNA duplex was also modeled using Haddock server and represents the functional form of the enzyme. Initially, established nucleoside analog inhibitors of PfTERT, AZTTP, and ddGTP were docked in the modeled binding site of the PfTERT ternary complex using AutoDock v4.2. Subsequently, docking studies were carried out with 14 approved nucleoside analog inhibitors. Docking studies predicted that floxuridine, gemcitabine, stavudine, and vidarabine have high affinity for the PfTERT ternary complex. Further analysis on the basis of known side effects led us to propose repositioning of vidarabine as a suitable drug candidate for inhibition of PfTERT.

Evolution of Macromolecular Docking Techniques: The Case Study of Nickel and Iron Metabolism in Pathogenic Bacteria

The interaction between macromolecules is a fundamental aspect of most biological processes. The computational techniques used to study protein-protein and protein-nucleic acid interactions have evolved in the last few years because of the development of new algorithms that allow the a priori incorporation, in the docking process, of experimentally derived information, together with the possibility of accounting for the flexibility of the interacting molecules. Here we review the results and the evolution of the techniques used to study the interaction between metallo-proteins and DNA operators, all involved in the nickel and iron metabolism of pathogenic bacteria, focusing in particular on Helicobacter pylori (Hp). In the first part of the article we discuss the methods used to calculate the structure of complexes of proteins involved in the activation of the nickel-dependent enzyme urease. In the second part of the article, we concentrate on two applications of protein-DNA docking conducted on the transcription factors HpFur (ferric uptake regulator) and HpNikR (nickel regulator). In both cases we discuss the technical expedients used to take into account the conformational variability of the multi-domain proteins involved in the calculations.

On the interaction of Helicobacter pylori NikR, a Ni(II)-responsive transcription factor, with the urease operator: in solution and in silico studies

Helicobacter pylori (Hp) is a carcinogen that relies on Ni(II) to survive in the extreme pH conditions of the human guts. The regulation of genes coding for Ni(II) enzymes and proteins is effected by the nickel-responsive transcription factor NikR, composed of a DNA-binding domain (DBD) and a metal-binding domain (MBD). The scope of this study is to obtain the molecular details of the HpNikR interaction with the urease operator OP ureA , in solution. The size of the full-length protein prevents the characterization of the HpNikR-OP ureA interaction using NMR. We thus investigated the two separate domains of HpNikR. The conservation of their oligomeric state was established by multiple-angle light scattering. Isothermal calorimetric titrations indicated that the thermodynamics of Ni(II) binding to the isolated MBD is independent of the presence of the adjacent DBDs. The NMR spectra of the isolated DBD support considerable conservation of its structural properties. The spectral perturbations induced on the DBD by OP ureA provided information useful to calculate a structural model of the HpNikR-OP ureA complex using a docking computational protocol. The NMR assignment of the residues involved in the protein-DNA interaction represents a starting point for the development of drugs potentially able to eradicate H. pylori infections. All evidences so far collected, in this and previous studies, consistently indicate that binding of Ni(II) to the MBD increases the HpNikR-DNA affinity by modulating the dynamic, and not the structural, properties of the protein, suggesting that the formation of a stable complex relies upon an induced fit mechanism.

Development of ssDNA aptamers as potent inhibitors of Mycobacterium tuberculosis acetohydroxyacid synthase

Acetohydroxyacid synthase (AHAS) from Mycobacterium tuberculosis (Mtb) is a promising potential drug target for an emerging class of new anti-tuberculosis agents. In this study, we identify short (30-mer) single-stranded DNA aptamers as a novel class of potent inhibitors of Mtb-AHAS through an in vitro DNA-SELEX method. Among all tested aptamers, two candidate aptamers (Mtb-Apt1 and Mtb-Apt6) demonstrated the greatest inhibitory potential against Mtb-AHAS activity with IC50 values in the low nanomolar range (28.94±0.002 and 22.35±0.001 nM respectively). Interestingly, inhibition kinetics analysis of these aptamers showed different modes of enzyme inhibition (competitive and mixed type of inhibition respectively). Secondary structure-guided mutational modification analysis of Mtb-Apt1 and Mtb-Apt6 identified the minimal region responsible for their inhibitory action and consequently led to 17-mer and 20-mer shortened aptamers that retained equivalent or greater inhibitory potential. Notably, a modeling and docking exercise investigated the binding site of these two potent inhibitory aptamers on the target protein and showed possible involvement of some key catalytic dimer interface residues of AHAS in the DNA-protein interactions that lead to its potent inhibition. Importantly, these two short candidate aptamers, Mtb-Apt1 (17-mer) and Mtb-Apt6 (20-mer), also demonstrated significant growth inhibition against multidrug-resistant (MDR-TB) and extensively drug-resistant (XDR-TB) strains of tuberculosis with very low MIC of 5.36 μg/ml and 6.24 μg/ml, respectively and no significant cytotoxicity against mammalian cell line. This is the first report of functional inhibitory aptamers against Mtb-AHAS and provides the basis for development of these aptamers as novel and strong anti-tuberculosis agents.

RNA-LIM: a novel procedure for analyzing protein/single-stranded RNA propensity data with concomitant estimation of interface structure

RNA-LIM is a procedure that can analyze various pseudo-potentials describing the affinity between single-stranded RNA (ssRNA) ribonucleotides and surface amino acids to produce a coarse-grained estimate of the structure of the ssRNA at the protein interface. The search algorithm works by evolving an ssRNA chain, of known sequence, as a series of walks between fixed sites on a protein surface. Optimal routes are found by application of a set of minimal "limiting" restraints derived jointly from (i) selective sampling of the ribonucleotide amino acid affinity pseudo-potential data, (ii) limited surface path exploration by prior determination of surface arc lengths, and (iii) RNA structural specification obtained from a statistical potential gathered from a library of experimentally determined ssRNA structures. We describe the general approach using a NAST (Nucleic Acid Simulation Tool)-like approximation of the ssRNA chain and a generalized pseudo-potential reflecting the location of nucleic acid binding residues. Minimum and maximum performance indicators of the methodology are established using both synthetic data, for which the pseudo-potential defining nucleic acid binding affinity is systematically degraded, and a representative real case, where the RNA binding sites are predicted by the amplified antisense RNA (aaRNA) method. Some potential uses and extensions of the routine are discussed. RNA-LIM analysis programs along with detailed instructions for their use are available on request from the authors.

Solution structure and DNA binding of the catalytic domain of the large serine resolvase TnpX

The transfer of antibiotic resistance between bacteria is mediated by mobile genetic elements such as plasmids and transposons. TnpX is a member of the large serine recombinase subgroup of site-specific recombinases and is responsible for the excision and insertion of mobile genetic elements that encode chloramphenicol resistance in the pathogens Clostridium perfringens and Clostridium difficile. TnpX consists of three structural domains: domain I contains the catalytic site, whereas domains II and III contain DNA-binding motifs. We have solved the solution structure of residues 1-120 of the catalytic domain I of TnpX. The TnpX catalytic domain shares the same overall fold as other serine recombinases; however, differences are evident in the identity of the proposed hydrogen donor and in the size, amino acid composition, conformation, and dynamics of the TnpX active site loops. To obtain the interaction surface of TnpX1-120 , we titrated a DNA oligonucleotide containing the circular intermediate joint attCI recombination site into (15) N-labeled TnpX1-120 and observed progressive nuclear magnetic resonance chemical shift perturbations using (15) N HSQC spectra. Perturbations were largely confined to a region surrounding the catalytic serine and encompassed residues of the active site loops. Utilizing the perturbation map and the data-driven docking program, HADDOCK, we have generated a model of the DNA interaction complex for the TnpX catalytic domain.

Identification of the target DNA sequence and characterization of DNA binding features of HlyU, and suggestion of a redox switch for hlyA expression in the human pathogen Vibrio cholerae from in silico studies

HlyU, a transcriptional regulator common in many Vibrio species, activates the hemolysin gene hlyA in Vibrio cholerae, the rtxA1 operon in Vibrio vulnificus and the genes of plp-vah1 and rtxACHBDE gene clusters in Vibrio anguillarum. The protein is also proposed to be a potential global virulence regulator for V. cholerae and V. vulnificus. Mechanisms of gene control by HlyU in V. vulnificus and V. anguillarum are reported. However, detailed elucidation of the interaction of HlyU in V. cholerae with its target DNA at the molecular level is not available. Here we report a 17-bp imperfect palindrome sequence, 5′-TAATTCAGACTAAATTA-3′, 173 bp upstream of hlyA promoter, as the binding site of HlyU. This winged helix-turn-helix protein binds necessarily as a dimer with the recognition helices contacting the major grooves and the β-sheet wings, the minor grooves. Such interactions enhance hlyA promoter activity in vivo. Mutations affecting dimerization as well as those in the DNA–protein interface hamper DNA binding and transcription regulation. Molecular dynamic simulations show hydrogen bonding patterns involving residues at the mutation sites and confirmed their importance in DNA binding. On binding to HlyU, DNA deviates by ∼68º from linearity. Dynamics also suggest a possible redox control in HlyU.

NMR structure validation in relation to dynamics and structure determination

NMR spectroscopy is a key technique for understanding the behaviour of proteins, especially highly dynamic proteins that adopt multiple conformations in solution. Overall, protein structures determined from NMR spectroscopy data constitute just over 10% of the Protein Data Bank archive. This review covers the validation of these NMR protein structures, but rather than describing currently available methodology, it focuses on concepts that are important for understanding where and how validation is most relevant. First, the inherent characteristics of the protein under study have an influence on quality and quantity of the distinct types of data that can be acquired from NMR experiments. Second, these NMR data are necessarily transformed into a model for use in a structure calculation protocol, and the protein structures that result from this reflect the types of NMR data used as well as the protein characteristics. The validation of NMR protein structures should therefore take account, wherever possible, of the inherent behavioural characteristics of the protein, the types of available NMR data, and the calculation protocol. These concepts are discussed in the context of 'knowledge based' and 'model versus data' validation, with suggestions for questions to ask and different validation categories to consider. The principal aim of this review is to stimulate discussion and to help the reader understand the relationships between the above elements in order to make informed decisions on which validation approaches are the most relevant in particular cases.

NMR approaches for structural analysis of multidomain proteins and complexes in solution

NMR spectroscopy is a key method for studying the structure and dynamics of (large) multidomain proteins and complexes in solution. It plays a unique role in integrated structural biology approaches as especially information about conformational dynamics can be readily obtained at residue resolution. Here, we review NMR techniques for such studies focusing on state-of-the-art tools and practical aspects. An efficient approach for determining the quaternary structure of multidomain complexes starts from the structures of individual domains or subunits. The arrangement of the domains/subunits within the complex is then defined based on NMR measurements that provide information about the domain interfaces combined with (long-range) distance and orientational restraints. Aspects discussed include sample preparation, specific isotope labeling and spin labeling; determination of binding interfaces and domain/subunit arrangements from chemical shift perturbations (CSP), nuclear Overhauser effects (NOEs), isotope editing/filtering, cross-saturation, and differential line broadening; and based on paramagnetic relaxation enhancements (PRE) using covalent and soluble spin labels. Finally, the utility of complementary methods such as small-angle X-ray or neutron scattering (SAXS, SANS), electron paramagnetic resonance (EPR) or fluorescence spectroscopy techniques is discussed. The applications of NMR techniques are illustrated with studies of challenging (high molecular weight) protein complexes.

Investigation of binding phenomenon of NSP3 and p130Cas mutants and their effect on cell signalling

Members of the novel SH2-containing protein (NSP3) and Crk-associated substrate (p130Cas) protein families form a multi-domain signalling platforms that mediate cell signalling process. We analysed the damaging consequences of three mutations, each from NSP3 (NSP3(L469R), NSP3(L623E), NSP3(R627E)) and p130Cas (p130Cas(F794R), p130Cas(L787E), p130Cas(D797R)) protein with respect to their native biological partners. Mutations depicted notable loss in interaction affinity towards their corresponding biological partners. NSP3(L469R) and p130Cas(D797R) mutations were predicted as most prominent in docking analysis. Molecular dynamics (MD) studies were conducted to evaluate structural consequences of most prominent mutation in NSP3 and p130Cas obtained from the docking analysis. MD analysis confirmed that mutation in NSP3(L469R) and p130Cas(D797R) showed significant structural deviation, changes in conformations and increased flexibility, which in turn affected the binding affinity with their biological partners. Moreover, the root mean square fluctuation has indicated a rise in fluctuation of residues involved in moderate interaction acquired between the NSP3 and p130Cas. It has significantly affected the binding interaction in mutant complexes. The results obtained in this work present a detailed overview of molecular mechanisms involved in the loss of cell signalling associated with NSP3 and p130Cas protein.

How a low-fidelity DNA polymerase chooses non-Watson-Crick from Watson-Crick incorporation

A dogma for DNA polymerase catalysis is that the enzyme binds DNA first, followed by MgdNTP. This mechanism contributes to the selection of correct dNTP by Watson-Crick base pairing, but it cannot explain how low-fidelity DNA polymerases overcome Watson-Crick base pairing to catalyze non-Watson-Crick dNTP incorporation. DNA polymerase X from the deadly African swine fever virus (Pol X) is a half-sized repair polymerase that catalyzes efficient dG:dGTP incorporation in addition to correct repair. Here we report the use of solution structures of Pol X in the free, binary (Pol X:MgdGTP), and ternary (Pol X:DNA:MgdGTP with dG:dGTP non-Watson-Crick pairing) forms, along with functional analyses, to show that Pol X uses multiple unprecedented strategies to achieve the mutagenic dG:dGTP incorporation. Unlike high fidelity polymerases, Pol X can prebind purine MgdNTP tightly and undergo a specific conformational change in the absence of DNA. The prebound MgdGTP assumes an unusual syn conformation stabilized by partial ring stacking with His115. Upon binding of a gapped DNA, also with a unique mechanism involving primarily helix αE, the prebound syn-dGTP forms a Hoogsteen base pair with the template anti-dG. Interestingly, while Pol X prebinds MgdCTP weakly, the correct dG:dCTP ternary complex is readily formed in the presence of DNA. H115A mutation disrupted MgdGTP binding and dG:dGTP ternary complex formation but not dG:dCTP ternary complex formation. The results demonstrate the first solution structural view of DNA polymerase catalysis, a unique DNA binding mode, and a novel mechanism for non-Watson-Crick incorporation by a low-fidelity DNA polymerase.

Structure of bacterial transcription factor SpoIIID and evidence for a novel mode of DNA binding

SpoIIID is evolutionarily conserved in endospore-forming bacteria, and it activates or represses many genes during sporulation of Bacillus subtilis. An SpoIIID monomer binds DNA with high affinity and moderate sequence specificity. In addition to a predicted helix-turn-helix motif, SpoIIID has a C-terminal basic region that contributes to DNA binding. The nuclear magnetic resonance (NMR) solution structure of SpoIIID in complex with DNA revealed that SpoIIID does indeed have a helix-turn-helix domain and that it has a novel C-terminal helical extension. Residues in both of these regions interact with DNA, based on the NMR data and on the effects on DNA binding in vitro of SpoIIID with single-alanine substitutions. These data, as well as sequence conservation in SpoIIID binding sites, were used for information-driven docking to model the SpoIIID-DNA complex. The modeling resulted in a single cluster of models in which the recognition helix of the helix-turn-helix domain interacts with the major groove of DNA, as expected. Interestingly, the C-terminal extension, which includes two helices connected by a kink, interacts with the adjacent minor groove of DNA in the models. This predicted novel mode of binding is proposed to explain how a monomer of SpoIIID achieves high-affinity DNA binding. Since SpoIIID is conserved only in endospore-forming bacteria, which include important pathogenic Bacilli and Clostridia, whose ability to sporulate contributes to their environmental persistence, the interaction of the C-terminal extension of SpoIIID with DNA is a potential target for development of sporulation inhibitors.

Transition model for ricin-aptamer interactions with multiple pathways and energy barriers

We develop a transition model to interpret single-molecule ricin-aptamer interactions with multiple unbinding pathways and energy barriers measured by atomic force microscopy dynamic force spectroscopy. Molecular simulations establish the relationship between binding conformations and the corresponding unbinding pathways. Each unbinding pathway follows a Bell-Evans multiple-barrier model. Markov-type transition matrices are developed to analyze the redistribution of unbinding events among the pathways under different loading rates. Our study provides detailed information about complex behaviors in ricin-aptamer unbinding events.

Structural basis for DNA-mediated allosteric regulation facilitated by the AAA+module of Lon protease

Lon belongs to a unique group of AAA+proteases that bind DNA. However, the DNA-mediated regulation of Lon remains elusive. Here, the crystal structure of the α subdomain of the Lon protease fromBrevibacillus thermoruber(Bt-Lon) is presented, together with biochemical data, and the DNA-binding mode is delineated, showing that Arg518, Arg557 and Arg566 play a crucial role in DNA binding. Electrostatic interactions contributed by arginine residues in the AAA+module are suggested to be important to DNA binding and allosteric regulation of enzymatic activities. Intriguingly, Arg557, which directly binds DNA in the α subdomain, has a dual role in the negative regulation of ATPase stimulation by DNA and in the domain–domain communication in allosteric regulation of Bt-Lon by substrate. In conclusion, structural and biochemical evidence is provided to show that electrostatic interaction in the AAA+module is important for DNA binding by Lon and allosteric regulation of its enzymatic activities by DNA and substrate.

FeON-FeOFF: the Helicobacter pylori Fur regulator commutates iron-responsive transcription by discriminative readout of opposed DNA grooves

Most transcriptional regulators bind nucleotide motifs in the major groove, although some are able to recognize molecular determinants conferred by the minor groove of DNA. Here we report a transcriptional commutator switch that exploits the alternative readout of grooves to mediate opposite output regulation for the same input signal. This mechanism accounts for the ability of the Helicobacter pylori Fur regulator to repress the expression of both iron-inducible and iron-repressible genes. When iron is scarce, Fur binds to DNA as a dimer, through the readout of thymine pairs in the major groove, repressing iron-inducible transcription (FeON). Conversely, on iron-repressible elements the metal ion acts as corepressor, inducing Fur multimerization with consequent minor groove readout of AT-rich inverted repeats (FeOFF). Our results provide first evidence for a novel regulatory paradigm, in which the discriminative readout of DNA grooves enables to toggle between the repression of genes in a mutually exclusive manner.

Predicting protein-DNA interactions by full search computational docking

Protein-DNA interactions are essential for many biological processes. X-ray crystallography can provide high-resolution structures, but protein-DNA complexes are difficult to crystallize and typically contain only small DNA fragments. Thus, there is a need for computational methods that can provide useful predictions to give insights into mechanisms and guide the design of new experiments. We used the program DOT, which performs an exhaustive, rigid-body search between two macromolecules, to investigate four diverse protein-DNA interactions. Here, we compare our computational results with subsequent experimental data on related systems. In all cases, the experimental data strongly supported our structural hypotheses from the docking calculations: a mechanism for weak, nonsequence-specific DNA binding by a transcription factor, a large DNA-binding footprint on the surface of the DNA-repair enzyme uracil-DNA glycosylase (UNG), viral and host DNA-binding sites on the catalytic domain of HIV integrase, and a three-DNA-contact model of the linker histone bound to the nucleosome. In the case of UNG, the experimental design was based on the DNA-binding surface found by docking, rather than the much smaller surface observed in the crystallographic structure. These comparisons demonstrate that the DOT electrostatic energy gives a good representation of the distinctive electrostatic properties of DNA and DNA-binding proteins. The large, favourably ranked clusters resulting from the dockings identify active sites, map out large DNA-binding sites, and reveal multiple DNA contacts with a protein. Thus, computational docking can not only help to identify protein-DNA interactions in the absence of a crystal structure, but also expand structural understanding beyond known crystallographic structures.

Elastic Network Models of Nucleic Acids Flexibility

Elastic network models (ENMs) are a useful tool for describing large scale motions in protein systems. While they are well validated in the context of proteins, relatively little is known about their applicability to nucleic acids, whose different architecture does not necessarily warrant comparable performance. In this study we thoroughly evaluate and optimize the efficiency of popular ENMs for capturing RNA and DNA flexibility. We also introduce two alternative models in which the strength of elastic connections at a coarse-grained level is governed by distance distribution at atomic resolution. For each of the considered ENMs we report the optimal length of spring connections as well as the scaling of elastic force constants that provides the best agreement of vibrational frequencies with normal modes based on atomic force field. In order to determine the absolute values of force constants we introduce a novel method based on the overlap of pseudoinverse of Hessian matrices.

A docking study of enhanced intracellular survival protein from Mycobacterium tuberculosis with human DUSP16/MKP-7

The intracellular pathogen Mycobacterium tuberculosis (Mtb) causes tuberculosis, and one of its secreted effector proteins, called enhanced intracellular survival (Eis) protein, enhances its survival in macrophages. Mtb Eis activates JNK-specific dual-specificity protein phosphatase 16 (DUSP16)/mitogen-activated protein kinase phosphatase-7 (MKP-7) through the acetylation on Lys55, thus inactivating JNK by dephosphorylation. Based on the recently reported crystal structure of Mtb Eis, a docking model for the binding of Mtb Eis to DUSP16/MKP-7 was generated. In the docking model, the substrate helix containing Lys55 of DUSP16/MKP-7 fits nicely into the active-site cleft of Mtb Eis; the twisted β-sheet of Eis domain II embraces the substrate helix from one side. Most importantly, the side-chain of Lys55 is inserted toward acetyl-CoA and the resulting distance is 4.6 Å between the NZ atom of Lys55 and the carbonyl carbon of the acetyl group in acetyl-CoA. The binding of Mtb Eis and DUSP16/MKP-7 is maintained by strong electrostatic interactions. The active-site cleft of Mtb Eis has a negatively charged surface formed by Asp25, Glu138, Asp286, Glu395 and the terminal carboxylic group of Phe396. In contrast, DUSP16/MKP-7 contains five basic residues, Lys52, Lys55, Arg56, Arg57 and Lys62, which point toward the negatively charged surface of the active-site pocket of Mtb Eis. Thus, the current docking model suggests that the binding of DUSP16/MKP-7 to Mtb Eis should be established by charge complementarity in addition to a very favorable geometric arrangement. The suggested mode of binding requires the dissociation of the hexameric Mtb Eis into dimers or monomers. This study may be useful for future studies aiming to develop inhibitors of Mtb Eis as a new anti-tuberculosis drug candidate.

A structural analysis of DNA binding by myelin transcription factor 1 double zinc fingers

Myelin transcription factor 1 (MyT1/NZF2), a member of the neural zinc-finger (NZF) protein family, is a transcription factor that plays a central role in the developing central nervous system. It has also recently been shown that, in combination with two other transcription factors, the highly similar paralog MyT1L is able to direct the differentiation of murine and human stem cells into functional neurons. MyT1 contains seven zinc fingers (ZFs) that are highly conserved throughout the protein and throughout the NZF family. We recently presented a model for the interaction of the fifth ZF of MyT1 with a DNA sequence derived from the promoter of the retinoic acid receptor (RARE) gene. Here, we have used NMR spectroscopy, in combination with surface plasmon resonance and data-driven molecular docking, to delineate the mechanism of DNA binding for double ZF polypeptides derived from MyT1. Our data indicate that a two-ZF unit interacts with the major groove of the entire RARE motif and that both fingers bind in an identical manner and with overall two-fold rotational symmetry, consistent with the palindromic nature of the target DNA. Several key residues located in one of the irregular loops of the ZFs are utilized to achieve specific binding. Analysis of the human and mouse genomes based on our structural data reveals three putative MyT1 target genes involved in neuronal development.

Solvated protein-DNA docking using HADDOCK

Interfacial water molecules play an important role in many aspects of protein-DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the docking of protein-DNA complexes and demonstrate its feasibility on a benchmark of 30 high-resolution protein-DNA complexes containing crystallographically-determined water molecules at their interfaces. Our protocol is capable of reproducing the solvation pattern at the interface and recovers hydrogen-bonded water-mediated contacts in many of the benchmark cases. Solvated docking leads to an overall improvement in the quality of the generated protein-DNA models for cases with limited conformational change of the partners upon complex formation. The applicability of this approach is demonstrated on real cases by docking a representative set of 6 complexes using unbound protein coordinates, model-built DNA and knowledge-based restraints. As HADDOCK supports the inclusion of a variety of NMR restraints, solvated docking is also applicable for NMR-based structure calculations of protein-DNA complexes.

Specificity determinants for the abscisic acid response element

Abscisic acid (ABA) response elements (ABREs) are a group of cis-acting DNA elements that have been identified from promoter analysis of many ABA-regulated genes in plants. We are interested in understanding the mechanism of binding specificity between ABREs and a class of bZIP transcription factors known as ABRE binding factors (ABFs). In this work, we have modeled the homodimeric structure of the bZIP domain of ABRE binding factor 1 from Arabidopsis thaliana (AtABF1) and studied its interaction with ACGT core motif-containing ABRE sequences. We have also examined the variation in the stability of the protein–DNA complex upon mutating ABRE sequences using the protein design algorithm FoldX. The high throughput free energy calculations successfully predicted the ability of ABF1 to bind to alternative core motifs like GCGT or AAGT and also rationalized the role of the flanking sequences in determining the specificity of the protein-DNA interaction.

Modeling the zing finger protein SmZF1 from Schistosoma mansoni: Insights into DNA binding and gene regulation

Zinc finger proteins are widely found in eukaryotes, representing an important class of DNA-binding proteins frequently involved in transcriptional regulation. Zinc finger motifs are composed by two antiparallel β-strands and one α-helix, stabilized by a zinc ion coordinated by conserved histidine and cysteine residues. In Schistosoma mansoni, these regulatory proteins are known to modulate morphological and physiological changes, having crucial roles in parasite development. A previously described C(2)H(2) zinc finger protein, SmZF1, was shown to be present in cell nuclei of different life stages of S. mansoni and to activate gene transcription in a heterologous system. A high-quality SmZF1 tridimensional structure was generated using comparative modeling. Molecular dynamics simulations of the obtained structure revealed stability of the zinc fingers motifs and high flexibility on the terminals, comparable to the profile observed on the template X-ray structure based on thermal b-factors. Based on the protein tridimensional features and amino acid composition, we were able to characterize four C(2)H(2) zinc finger motifs, the first involved in protein-protein interactions while the three others involved in DNA binding. We defined a consensus DNA binding sequence using three distinct algorithms and further carried out docking calculations, which revealed the interaction of fingers 2-4 with the predicted DNA. A search for S. mansoni genes presenting putative SmZF1 binding sites revealed 415 genes hypothetically under SmZF1 control. Using an automatic annotation and GO assignment approach, we found that the majority of those genes code for proteins involved in developmental processes. Taken together, these results present a consistent base to the structural and functional characterization of SmZF1.

Protein-DNA docking with a coarse-grained force field

Background

Protein-DNA interactions are important for many cellular processes, however structural knowledge for a large fraction of known and putative complexes is still lacking. Computational docking methods aim at the prediction of complex architecture given detailed structures of its constituents. They are becoming an increasingly important tool in the field of macromolecular assemblies, complementing particularly demanding protein-nucleic acids X ray crystallography and providing means for the refinement and integration of low resolution data coming from rapidly advancing methods such as cryoelectron microscopy.

Results

We present a new coarse-grained force field suitable for protein-DNA docking. The force field is an extension of previously developed parameter sets for protein-RNA and protein-protein interactions. The docking is based on potential energy minimization in translational and orientational degrees of freedom of the binding partners. It allows for fast and efficient systematic search for native-like complex geometry without any prior knowledge regarding binding site location.

Conclusions

We find that the force field gives very good results for bound docking. The quality of predictions in the case of unbound docking varies, depending on the level of structural deviation from bound geometries. We analyze the role of specific protein-DNA interactions on force field performance, both with respect to complex structure prediction, and the reproduction of experimental binding affinities. We find that such direct, specific interactions only partially contribute to protein-DNA recognition, indicating an important role of shape complementarity and sequence-dependent DNA internal energy, in line with the concept of indirect protein-DNA readout mechanism.

TFinDit: transcription factor-DNA interaction data depository

Background

One of the crucial steps in regulation of gene expression is the binding of transcription factor(s) to specific DNA sequences. Knowledge of the binding affinity and specificity at a structural level between transcription factors and their target sites has important implications in our understanding of the mechanism of gene regulation. Due to their unique functions and binding specificity, there is a need for a transcription factor-specific, structure-based database and corresponding web service to facilitate structural bioinformatics studies of transcription factor-DNA interactions, such as development of knowledge-based interaction potential, transcription factor-DNA docking, binding induced conformational changes, and the thermodynamics of protein-DNA interactions.

Description

TFinDit is a relational database and a web search tool for studying transcription factor-DNA interactions. The database contains annotated transcription factor-DNA complex structures and related data, such as unbound protein structures, thermodynamic data, and binding sequences for the corresponding transcription factors in the complex structures. TFinDit also provides a user-friendly interface and allows users to either query individual entries or generate datasets through culling the database based on one or more search criteria.

Conclusions

TFinDit is a specialized structural database with annotated transcription factor-DNA complex structures and other preprocessed data. We believe that this database/web service can facilitate the development and testing of TF-DNA interaction potentials and TF-DNA docking algorithms, and the study of protein-DNA recognition mechanisms.

DBD2BS: connecting a DNA-binding protein with its binding sites

By binding to short and highly conserved DNA sequences in genomes, DNA-binding proteins initiate, enhance or repress biological processes. Accurately identifying such binding sites, often represented by position weight matrices (PWMs), is an important step in understanding the control mechanisms of cells. When given coordinates of a DNA-binding domain (DBD) bound with DNA, a potential function can be used to estimate the change of binding affinity after base substitutions, where the changes can be summarized as a PWM. This technique provides an effective alternative when the chromatin immunoprecipitation data are unavailable for PWM inference. To facilitate the procedure of predicting PWMs based on protein-DNA complexes or even structures of the unbound state, the web server, DBD2BS, is presented in this study. The DBD2BS uses an atom-level knowledge-based potential function to predict PWMs characterizing the sequences to which the query DBD structure can bind. For unbound queries, a list of 1066 DBD-DNA complexes (including 1813 protein chains) is compiled for use as templates for synthesizing bound structures. The DBD2BS provides users with an easy-to-use interface for visualizing the PWMs predicted based on different templates and the spatial relationships of the query protein, the DBDs and the DNAs. The DBD2BS is the first attempt to predict PWMs of DBDs from unbound structures rather than from bound ones. This approach increases the number of existing protein structures that can be exploited when analyzing protein-DNA interactions. In a recent study, the authors showed that the kernel adopted by the DBD2BS can generate PWMs consistent with those obtained from the experimental data. The use of DBD2BS to predict PWMs can be incorporated with sequence-based methods to discover binding sites in genome-wide studies. Available at: http://dbd2bs.csie.ntu.edu.tw/, http://dbd2bs.csbb.ntu.edu.tw/, and http://dbd2bs.ee.ncku.edu.tw.

Flexible protein docking refinement using pose-dependent normal mode analysis

Modeling conformational changes in protein docking calculations is challenging. To make the calculations tractable, most current docking algorithms typically treat proteins as rigid bodies and use soft scoring functions that implicitly accommodate some degree of flexibility. Alternatively, ensembles of structures generated from molecular dynamics (MD) may be cross-docked. However, such combinatorial approaches can produce many thousands or even millions of docking poses, and require fast and sensitive scoring functions to distinguish them. Here, we present a novel approach called "EigenHex," which is based on normal mode analyses (NMAs) of a simple elastic network model of protein flexibility. We initially assume that the proteins to be docked are rigid, and we begin by performing conventional soft docking using the Hex polar Fourier correlation algorithm. We then apply a pose-dependent NMA to each of the top 1000 rigid body docking solutions, and we sample and re-score multiple perturbed docking conformations generated from linear combinations of up to 20 eigenvectors using a multi-threaded particle swarm optimization algorithm. When applied to the 63 "rigid body" targets of the Protein Docking Benchmark version 2.0, our results show that sampling and re-scoring from just one to three eigenvectors gives a modest but consistent improvement for these targets. Thus, pose-dependent NMA avoids the need to sample multiple eigenvectors and it offers a promising alternative to combinatorial cross-docking.

Spectroscopic, molecular modeling, and NMR-spectroscopic investigation of the binding mode of the natural alkaloids berberine and sanguinarine to human telomeric G-quadruplex DNA

G-quadruplex structures can be formed at the single-stranded overhang of telomeric DNA, and ligands able to stabilize this structure have recently been identified as potential anticancer drugs. Among the potential G-quadruplex binders, we have studied the binding ability of berberine and sanguinarine, two members of the alkaloid family, an important class of natural products long known for medicinal purpose. Our spectroscopic (CD, NMR, and fluorescence) studies and molecular modeling approaches revealed binding modes at ligand-complex stoichiometries >1:1 and ligand self-association induced by DNA for the interactions of the natural alkaloids berberine and sanguinarine with the human telomeric G-quadruplex DNA.

Structural models of protein-DNA complexes based on interface prediction and docking

Protein-DNA interactions are the physical basis of gene expression and DNA modification. Structural models that reveal these interactions are essential for their understanding. As only a limited number of structures for protein-DNA complexes have been determined by experimental methods, computation methods provide a potential way to fill the need. We have developed the DISPLAR method to predict DNA binding sites on proteins. Predicted binding sites have been used to assist the building of structural models by docking, either by guiding the docking or by selecting near-native candidates from the docked poses. Here we applied the DISPLAR method to predict the DNA binding sites for 20 DNA-binding proteins, which have had their DNA binding sites characterized by NMR chemical shift perturbation. For two of these proteins, the structures of their complexes with DNA have also been determined. With the help of the DISPLAR predictions, we built structural models for these two complexes. Evaluations of both the DNA binding sites for 20 proteins and the structural models of the two protein-DNA complexes against experimental results demonstrate the significant promise of our model-building approach.

High-resolution single-molecule recognition imaging of the molecular details of ricin-aptamer interaction

We studied the molecular details of DNA aptamer-ricin interactions. The toxic protein ricin molecules were immobilized on a Au(111) surface using a N-hydroxysuccinimide (NHS) ester to specifically react with lysine residues located on the ricin B chains. A single ricin molecule was visualized in situ using the AFM tip modified with an antiricin aptamer. Computer simulation was used to illustrate the protein and aptamer structures, the single-molecule ricin images on a Au(111) surface, and the binding conformations of ricin-aptamer and ricin-antibody complexes. The various ricin conformations on a Au(111) surface were caused by the different lysine residues reacting with the NHS ester. It was also observed that most of the binding sites for aptamer and antibody on the A chains of ricin molecules were not interfered by the immobilization reaction. The different locations of the ricin binding sites to aptamer and antibody were also distinguished by AFM recognition images and interpreted by simulations.

The structure of the XPF-ssDNA complex underscores the distinct roles of the XPF and ERCC1 helix- hairpin-helix domains in ss/ds DNA recognition

Human XPF/ERCC1 is a structure-specific DNA endonuclease that nicks the damaged DNA strand at the 5' end during nucleotide excision repair. We determined the structure of the complex of the C-terminal domain of XPF with 10 nt ssDNA. A positively charged region within the second helix of the first HhH motif contacts the ssDNA phosphate backbone. One guanine base is flipped out of register and positioned in a pocket contacting residues from both HhH motifs of XPF. Comparison to other HhH-containing proteins indicates a one-residue deletion in the second HhH motif of XPF that has altered the hairpin conformation, thereby permitting ssDNA interactions. Previous nuclear magnetic resonance studies showed that ERCC1 in the XPF-ERCC1 heterodimer can bind dsDNA. Combining the two observations gives a model that underscores the asymmetry of the human XPF/ERCC1 heterodimer in binding at an ss/ds DNA junction.

Predicting target DNA sequences of DNA-binding proteins based on unbound structures

DNA-binding proteins such as transcription factors use DNA-binding domains (DBDs) to bind to specific sequences in the genome to initiate many important biological functions. Accurate prediction of such target sequences, often represented by position weight matrices (PWMs), is an important step to understand many biological processes. Recent studies have shown that knowledge-based potential functions can be applied on protein-DNA co-crystallized structures to generate PWMs that are considerably consistent with experimental data. However, this success has not been extended to DNA-binding proteins lacking co-crystallized structures. This study aims at investigating the possibility of predicting the DNA sequences bound by DNA-binding proteins from the proteins' unbound structures (structures of the unbound state). Given an unbound query protein and a template complex, the proposed method first employs structure alignment to generate synthetic protein-DNA complexes for the query protein. Once a complex is available, an atomic-level knowledge-based potential function is employed to predict PWMs characterizing the sequences to which the query protein can bind. The evaluation of the proposed method is based on seven DNA-binding proteins, which have structures of both DNA-bound and unbound forms for prediction as well as annotated PWMs for validation. Since this work is the first attempt to predict target sequences of DNA-binding proteins from their unbound structures, three types of structural variations that presumably influence the prediction accuracy were examined and discussed. Based on the analyses conducted in this study, the conformational change of proteins upon binding DNA was shown to be the key factor. This study sheds light on the challenge of predicting the target DNA sequences of a protein lacking co-crystallized structures, which encourages more efforts on the structure alignment-based approaches in addition to docking- and homology modeling-based approaches for generating synthetic complexes.

Structural basis for Ca2+-induced activation and dimerization of estrogen receptor α by calmodulin

The estrogen receptor α (ER-α) regulates expression of target genes implicated in development, metabolism, and breast cancer. Calcium-dependent regulation of ER-α is critical for activating gene expression and is controlled by calmodulin (CaM). Here, we present the NMR structures for the two lobes of CaM each bound to a localized region of ER-α (residues 287-305). A model of the complete CaM·ER-α complex was constructed by combining these two structures with additional data. The two lobes of CaM both compete for binding at the same site on ER-α (residues 292, 296, 299, 302, and 303), which explains why full-length CaM binds two molecules of ER-α in a 1:2 complex and stabilizes ER-α dimerization. Exposed glutamate residues in CaM (Glu(11), Glu(14), Glu(84), and Glu(87)) form salt bridges with key lysine residues in ER-α (Lys(299), Lys(302), and Lys(303)), which are likely to prevent ubiquitination at these sites and inhibit degradation of ER-α. Mutants of ER-α at the CaM-binding site (W292A and K299A) weaken binding to CaM, and I298E/K299D disrupts estrogen-induced transcription. CaM facilitates dimerization of ER-α in the absence of estrogen, and stimulation of ER-α by either Ca(2+) and/or estrogen may serve to regulate transcription in a combinatorial fashion.

Exploiting a reduced set of weighted average features to improve prediction of DNA-binding residues from 3D structures

Predicting DNA-binding residues from a protein three-dimensional structure is a key task of computational structural proteomics. In the present study, based on machine learning technology, we aim to explore a reduced set of weighted average features for improving prediction of DNA-binding residues on protein surfaces. Via constructing the spatial environment around a DNA-binding residue, a novel weighting factor is first proposed to quantify the distance-dependent contribution of each neighboring residue in determining the location of a binding residue. Then, a weighted average scheme is introduced to represent the surface patch of the considering residue. Finally, the classifier is trained on the reduced set of these weighted average features, consisting of evolutionary profile, interface propensity, betweenness centrality and solvent surface area of side chain. Experimental results on 5-fold cross validation and independent tests indicate that the new feature set are effective to describe DNA-binding residues and our approach has significantly better performance than two previous methods. Furthermore, a brief case study suggests that the weighted average features are powerful for identifying DNA-binding residues and are promising for further study of protein structure-function relationship. The source code and datasets are available upon request.

Following aptamer-ricin specific binding by single molecule recognition and force spectroscopy measurements

Single molecule recognition imaging and dynamic force spectroscopy (DFS) analysis showed strong binding affinity between an aptamer and ricin, which was comparable with antibody-ricin interaction. Molecular simulation showed a ricin binding conformation with aptamers and gave different ricin conformations immobilizing on substrates that were consistent with AFM images.

Benchmarks for flexible and rigid transcription factor-DNA docking

BACKGROUND

Structural insight from transcription factor-DNA (TF-DNA) complexes is of paramount importance to our understanding of the affinity and specificity of TF-DNA interaction, and to the development of structure-based prediction of TF binding sites. Yet the majority of the TF-DNA complexes remain unsolved despite the considerable experimental efforts being made. Computational docking represents a promising alternative to bridge the gap. To facilitate the study of TF-DNA docking, carefully designed benchmarks are needed for performance evaluation and identification of the strengths and weaknesses of docking algorithms.

RESULTS

We constructed two benchmarks for flexible and rigid TF-DNA docking respectively using a unified non-redundant set of 38 test cases. The test cases encompass diverse fold families and are classified into easy and hard groups with respect to the degrees of difficulty in TF-DNA docking. The major parameters used to classify expected docking difficulty in flexible docking are the conformational differences between bound and unbound TFs and the interaction strength between TFs and DNA. For rigid docking in which the starting structure is a bound TF conformation, only interaction strength is considered.

CONCLUSIONS

We believe these benchmarks are important for the development of better interaction potentials and TF-DNA docking algorithms, which bears important implications to structure-based prediction of transcription factor binding sites and drug design.

Predicting DNA-binding locations and orientation on proteins using knowledge-based learning of geometric properties

BACKGROUND

DNA-binding proteins perform their functions through specific or non-specific sequence recognition. Although many sequence- or structure-based approaches have been proposed to identify DNA-binding residues on proteins or protein-binding sites on DNA sequences with satisfied performance, it remains a challenging task to unveil the exact mechanism of protein-DNA interactions without crystal complex structures. Without information from complexes, the linkages between DNA-binding proteins and their binding sites on DNA are still missing.

METHODS

While it is still difficult to acquire co-crystallized structures in an efficient way, this study proposes a knowledge-based learning method to effectively predict DNA orientation and base locations around the protein's DNA-binding sites when given a protein structure. First, the functionally important residues of a query protein are predicted by a sequential pattern mining tool. After that, surface residues falling in the predicted functional regions are determined based on the given structure. These residues are then clustered based on their spatial coordinates and the resultant clusters are ranked by a proposed DNA-binding propensity function. Clusters with high DNA-binding propensities are treated as DNA-binding units (DBUs) and each DBU is analyzed by principal component analysis (PCA) to predict potential orientation of DNA grooves. More specifically, the proposed method is developed to predict the direction of the tangent line to the helix curve of the DNA groove where a DBU is going to bind.

RESULTS

This paper proposes a knowledge-based learning procedure to determine the spatial location of the DNA groove with respect to the query protein structure by considering geometric propensity between protein side chains and DNA bases. The 11 test cases used in this study reveal that the location and orientation of the DNA groove around a selected DBU can be predicted with satisfied errors.

CONCLUSIONS

This study presents a method to predict the location and orientation of DNA grooves with respect to the structure of a DNA-binding protein. The test cases shown in this study reveal the possibility of imaging protein-DNA binding conformation before co-crystallized structure can be determined. How the proposed method can be incorporated with existing protein-DNA docking tools to study protein-DNA interactions deserve further studies in the near future.

Inverted repeats in the promoter as an autoregulatory sequence for TcrX in Mycobacterium tuberculosis

TcrY, a histidine kinase, and TcrX, a response regulator, constitute a two-component system in Mycobacterium tuberculosis. tcrX, which is expressed during iron scarcity, is instrumental in the survival of iron-dependent M. tuberculosis. However, the regulator of tcrX/Y has not been fully characterized. Crosslinking studies of TcrX reveal that it can form oligomers in vitro. Electrophoretic mobility shift assays (EMSAs) show that TcrX recognizes two regions in the promoter that are comprised of inverted repeats separated by ∼30 bp. The dimeric in silico model of TcrX predicts binding to one of these inverted repeat regions. Site-directed mutagenesis and radioactive phosphorylation indicate that D54 of TcrX is phosphorylated by H256 of TcrY. However, phosphorylated and unphosphorylated TcrX bind the regulatory sequence with equal efficiency, which was shown with an EMSA using the D54A TcrX mutant.

Putative binding modes of Ku70-SAP domain with double strand DNA: a molecular modeling study

The channel structure of the Ku protein elegantly reveals the mechanistic basis of sequence-independent DNA-end binding, which is essential to genome integrity after exposure to ionizing radiation or in V(D)J recombination. However, contradicting evidence indicates that this protein is also involved in the regulation of gene expression and in other regulatory processes with intact chromosomes. This computational study predicts that a putative DNA binding domain of this protein, the SAP domain, can form DNA-bound complexes with relatively high affinities (ΔG ≈ -20 kcal mol(-1)). The binding modes are searched by low frequency vibration modes driven by the fully flexible docking method while binding affinities are calculated by the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. We find this well defined 5 kDa domain with a helix-extended loop-helix structure is suitable to form favorable electrostatic and hydrophobic interactions with either the major groove or the minor groove of DNA. The calculation also reveals the sequence specified binding preference which may relate to the observed pause sites when Ku translocates along DNA and the perplex binding of Ku with circular DNA.

Structural basis of simultaneous recruitment of the transcriptional regulators LMO2 and FOG1/ZFPM1 by the transcription factor GATA1

The control of red blood cell and megakaryocyte development by the regulatory protein GATA1 is a paradigm for transcriptional regulation of gene expression in cell lineage differentiation and maturation. Most GATA1-regulated events require GATA1 to bind FOG1, and essentially all GATA1-activated genes are cooccupied by a TAL1/E2A/LMO2/LDB1 complex; however, it is not known whether FOG1 and TAL1/E2A/LMO2/LDB1 are simultaneously recruited by GATA1. Our structural data reveal that the FOG1-binding domain of GATA1, the N finger, can also directly contact LMO2 and show that, despite the small size (< 50 residues) of the GATA1 N finger, both FOG1 and LMO2 can simultaneously bind this domain. LMO2 in turn can simultaneously contact both GATA1 and the DNA-binding protein TAL1/E2A at bipartite E-box/WGATAR sites. Taken together, our data provide the first structural snapshot of multiprotein complex formation at GATA1-dependent genes and support a model in which FOG1 and TAL1/E2A/LMO2/LDB1 can cooccupy E-box/WGATAR sites to facilitate GATA1-mediated activation of gene activation.

ParaDock: a flexible non-specific DNA--rigid protein docking algorithm

Accurate prediction of protein–DNA complexes could provide an important stepping stone towards a thorough comprehension of vital intracellular processes. Few attempts were made to tackle this issue, focusing on binding patch prediction, protein function classification and distance constraints-based docking. We introduce ParaDock: a novel ab initio protein–DNA docking algorithm. ParaDock combines short DNA fragments, which have been rigidly docked to the protein based on geometric complementarity, to create bent planar DNA molecules of arbitrary sequence. Our algorithm was tested on the bound and unbound targets of a protein–DNA benchmark comprised of 47 complexes. With neither addressing protein flexibility, nor applying any refinement procedure, CAPRI acceptable solutions were obtained among the 10 top ranked hypotheses in 83% of the bound complexes, and 70% of the unbound. Without requiring prior knowledge of DNA length and sequence, and within <2 h per target on a standard 2.0 GHz single processor CPU, ParaDock offers a fast ab initio docking solution.