A new method for evaluating the specificity of indirect readout in protein-DNA recognition

Metformin and Rifampicin combination augments active to latent tuberculosis conversion: A computational study

Tuberculosis, a global threat, is a highly infectious disease intensified by the emergence of drug-resistant strains. In tuberculosis disease spectrum, a typical situation is a dormant or latent phase where a person exposed to Mycobacterium tuberculosis has the reservoir of the disease that may or may not result in an active state. Existence of the dormant state is retarding the eradication of tuberculosis. Transcription of several genes helps M. tuberculosis to survive in nonreplicative mode. DosR transcription factor is the hallmark for this genesis. Diabetes mellitus is a predisposition factor leading to the development of tuberculosis and latent tuberculosis. High plasma insulin concentrations in the prediabetic state can increase the tuberculosis bacterium. On the other hand, antidiabetic drug metformin is known to reduce active tuberculosis disease when provided in combination with antitubercular therapy. However, the effect of the same on latent tuberculosis is still unknown. In the present work using tools of computational biology, we have tried to find the consequence of adding metformin in combination with rifampicin, a well-known antitubercular drug, on molecular mechanisms of latent tuberculosis. We have investigated whether metformin and rifampicin interact with DosR machinery or not. Our results indicate that if metformin-bound DosR-DNA complex binds with rifampicin, it will result in the conversion of active tuberculosis to latent tuberculosis.

C1188D mutation abolishes specific recognition between MLL1-CXXC domain and CpG site by inducing conformational switch of flexible N-terminal

Mixed lineage leukemia protein (MLL1 protein) recognizes the CpG site via its CXXC domain and is frequently associated with leukemia. The specific recognition is abolished by C1188D mutation, which also prevents MLL-related leukemia. In this paper, multiple molecular dynamic (MD) simulations were performed to investigate the mechanism of recognition and influences of C1188D mutation. Started from fully dissociated DNA and MLL1-CXXC domain, remarkably, the center of mass (COM) of MLL1-CXXC domain quickly concentrates on the vicinity of the CpG site in all 53 short MD simulations. Extended simulations of the wild type showed that the native complex formed in 500 ns among 4 of 53 simulations. In contrast, the C1188D mutant COM distributed broadly around the DNA and the native complex was not observed in any of the extended simulations. Simulations on the apo MLL1-CXXC domain further suggest that the wild type protein remained predominantly in an open form that closely resembles its structure in the native complex whereas C1188D mutant formed predominantly compact structures in which the N- terminal bends to D1188. This conformational switch hinders the formation of encounter complex, thus abolishes the recognition. Our study also provides clues to the study mechanism of recognition, by the CXXC domain from proteins like DNA methyltransferase and ten-eleven translocation enzymes.

Heterogeneous Dynamical Environment at the Interface of a Protein-DNA Complex

Binding between protein and DNA is an essential process to regulate different biological activities. Two puzzling questions in protein-DNA recognition are (i) how the protein's binding domain identifies the DNA sequence in an aqueous solution and (ii) how the formation of the complex alters the dynamical environment around it. In this work, we present results obtained from molecular dynamics simulations of the N-terminal α-helical domain of the λ-repressor protein (in dimeric form) bound to the corresponding operator DNA. Effects of formation of the complex in modifying the microscopic dynamics of water as well as the kinetics of hydrogen bonds at the interface have been explored. Locally heterogeneous restricted water motions at the complex interface have been observed, the extent of restriction being more significant around the directly bound residues of the protein and the DNA. In particular, the calculation revealed the existence of significantly constrained motionally restricted water layer that can form either bridges around the directly bound residues of the protein and DNA or are engaged in forming water-mediated contacts between a fraction of the unbound residues. More importantly, it is observed that the restricted water motion around the complex is correlated with the hydrogen bond relaxation time scale at the interface. It is further demonstrated that the kinetics of water-water hydrogen bonds involving the bridged water are influenced more due to complex formation.

Flexibility of the Binding Regions of a Protein-DNA Complex and the Structure and Ordering of Interfacial Water

Noncovalent interactions between protein and DNA are important to comprehend different biological activities in living organisms. One important issue is how the protein identifies the target DNA and the influence of the resulting protein-DNA complex on the hydration environment around it. In this study, we have carried out atomistic molecular dynamics simulations of the protein-DNA complex formed by the dimeric form of the α-helical N-terminal domain of the λ-repressor protein with its operator DNA. Local heterogeneous flexibilities of the residues of the protein and the DNA components that are involved in binding and the microscopic structure and ordering of water around those have been investigated in detail. The calculations revealed concurrent existence of highly ordered as well as disordered water molecules at the interface. It is found that a fraction of doubly coordinated water molecules exhibit high degree of ordering at the interface, while the randomly oriented ones are coordinated with three water molecules. The effect has been found to be more around the protein and DNA residues that are in contact in the complexed state. We believe that such highly ordered two-coordinated water molecules are likely to act as an adhesive to facilitate the formation of a protein-DNA complex and maintain its structural stability.

FoldX accurate structural protein-DNA binding prediction using PADA1 (Protein Assisted DNA Assembly 1)

The speed at which new genomes are being sequenced highlights the need for genome-wide methods capable of predicting protein–DNA interactions. Here, we present PADA1, a generic algorithm that accurately models structural complexes and predicts the DNA-binding regions of resolved protein structures. PADA1 relies on a library of protein and double-stranded DNA fragment pairs obtained from a training set of 2103 DNA–protein complexes. It includes a fast statistical force field computed from atom-atom distances, to evaluate and filter the 3D docking models. Using published benchmark validation sets and 212 DNA–protein structures published after 2016 we predicted the DNA-binding regions with an RMSD of <1.8 Å per residue in >95% of the cases. We show that the quality of the docked templates is compatible with FoldX protein design tool suite to identify the crystallized DNA molecule sequence as the most energetically favorable in 80% of the cases. We highlighted the biological potential of PADA1 by reconstituting DNA and protein conformational changes upon protein mutagenesis of a meganuclease and its variants, and by predicting DNA-binding regions and nucleotide sequences in proteins crystallized without DNA. These results opens up new perspectives for the engineering of DNA–protein interfaces.

How proteins bind to DNA: target discrimination and dynamic sequence search by the telomeric protein TRF1

Target search as performed by DNA-binding proteins is a complex process, in which multiple factors contribute to both thermodynamic discrimination of the target sequence from overwhelmingly abundant off-target sites and kinetic acceleration of dynamic sequence interrogation. TRF1, the protein that binds to telomeric tandem repeats, faces an intriguing variant of the search problem where target sites are clustered within short fragments of chromosomal DNA. In this study, we use extensive (>0.5 ms in total) MD simulations to study the dynamical aspects of sequence-specific binding of TRF1 at both telomeric and non-cognate DNA. For the first time, we describe the spontaneous formation of a sequence-specific native protein-DNA complex in atomistic detail, and study the mechanism by which proteins avoid off-target binding while retaining high affinity for target sites. Our calculated free energy landscapes reproduce the thermodynamics of sequence-specific binding, while statistical approaches allow for a comprehensive description of intermediate stages of complex formation.

Three new active members of the I-OnuI family of homing endonucleases

In vitro characterization of 3 LAGLIDADG-type homing endonucleases (HEs) (I-CcaI, I-CcaII, and I-AstI) that belong to the I-OnuI family showed that they are functional HEs that cleave their respective cognate target sites. These endonucleases are encoded within group ID introns and appear to be orthologues that have inserted into 3 different mitochondrial genes: rns, rnl, and cox3. The endonuclease activity of I-CcaI was tested using various substrates, and its minimum DNA recognition sequence was estimated to be 26 nt. This set of HEs may provide some insight into how these types of mobile elements can migrate into new locations. This study provides additional endonucleases that can be added to the catalog of currently available HEs that may have various biotechnology applications.

The nuclear higher-order structure defined by the set of topological relationships between DNA and the nuclear matrix is species-specific in hepatocytes

During the interphase the nuclear DNA of metazoan cells is organized in supercoiled loops anchored to constituents of a nuclear substructure or compartment known as the nuclear matrix. The stable interactions between DNA and the nuclear matrix (NM) correspond to a set of topological relationships that define a nuclear higher-order structure (NHOS). Current evidence suggests that the NHOS is cell-type-specific. Biophysical evidence and theoretical models suggest that thermodynamic and structural constraints drive the actualization of DNA-NM interactions. However, if the topological relationships between DNA and the NM were the subject of any biological constraint with functional significance then they must be adaptive and thus be positively selected by natural selection and they should be reasonably conserved, at least within closely related species. We carried out a coarse-grained, comparative evaluation of the DNA-NM topological relationships in primary hepatocytes from two closely related mammals: rat and mouse, by determining the relative position to the NM of a limited set of target sequences corresponding to highly-conserved genomic regions that also represent a sample of distinct chromosome territories within the interphase nucleus. Our results indicate that the pattern of topological relationships between DNA and the NM is not conserved between the hepatocytes of the two closely related species, suggesting that the NHOS, like the karyotype, is species-specific.

Microscopic understanding of the conformational features of a protein–DNA complex

Protein–DNA interactions play crucial roles in different stages of genetic activities, such as replication of genome, initiation of transcription,etc.

Why Cortical Neurons Cannot Divide, and Why Do They Usually Die in the Attempt?

Cortical neurons are prime examples of terminally differentiated, postmitotic cells. However, under experimental or pathological conditions, they can re-enter the cell cycle and replicate DNA but are unable to divide, dying by apoptosis or becoming either polyploid or aneuploid. Any cellular state that depends on the action of genes and their products can be reverted or bypassed by spontaneous or induced mutations, yet there are currently no reports of dividing cortical neurons. Thus, it seems unlikely that the remarkably stable postmitotic condition of cortical neurons depends on specific gene functions. This Review summarizes evidence that the postmitotic state of cortical neurons depends on the high stability of its underlying nuclear structure that results from an entropy-driven process aimed at dissipating the intrinsic structural stress present in chromosomal DNA in such a way that the structural stability of the neuronal nucleus becomes an insurmountable energy barrier for karyokinesis and mitosis. From this perspective, the integral properties of the nuclear higher order structure in neurons provide an explanation not only for why cortical neurons cannot divide but also for why they usually die if they happen to replicate their DNA. © 2016 Wiley Periodicals, Inc.

The interphase mammalian chromosome as a structural system based on tensegrity

Each mammalian chromosome is constituted by a DNA fiber of macroscopic length that needs to be fitted in a microscopic nucleus. The DNA fiber is subjected at physiological temperature to random thermal bending and looping that must be constrained so as achieve structural stability thus avoiding spontaneous rupturing of the fiber. Standard textbooks assume that chromatin proteins are primarily responsible for the packaging of DNA and so of its protection against spontaneous breakage. Yet the dynamic nature of the interactions between chromatin proteins and DNA is unlikely to provide the necessary long-term structural stability for the chromosomal DNA. On the other hand, longstanding evidence indicates that stable interactions between DNA and constituents of a nuclear compartment commonly known as the nuclear matrix organize the chromosomal DNA as a series of topologically constrained, supercoiled loops during interphase. This results in a primary level of DNA condensation and packaging within the nucleus, as well as in protection against spontaneous DNA breakage, independently of chromatin proteins which nevertheless increase and dynamically modulate the degree of DNA packaging and its role in the regulation of DNA function. Thus current evidence, presented hereunder, supports a model for the organization of the interphase chromosome as resilient system that satisfies the principles of structural tensegrity.

Multiscale modelling of DNA mechanics

Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed.

Reprogramming homing endonuclease specificity through computational design and directed evolution

Homing endonucleases (HEs) can be used to induce targeted genome modification to reduce the fitness of pathogen vectors such as the malaria-transmitting Anopheles gambiae and to correct deleterious mutations in genetic diseases. We describe the creation of an extensive set of HE variants with novel DNA cleavage specificities using an integrated experimental and computational approach. Using computational modeling and an improved selection strategy, which optimizes specificity in addition to activity, we engineered an endonuclease to cleave in a gene associated with Anopheles sterility and another to cleave near a mutation that causes pyruvate kinase deficiency. In the course of this work we observed unanticipated context-dependence between bases which will need to be mechanistically understood for reprogramming of specificity to succeed more generally.

Sequence-specific transitions of the torsion angle gamma change the polar-hydrophobic profile of the DNA grooves: implication for indirect protein-DNA recognition

Variations of the shape and polarity of the DNA grooves caused by changes of the DNA conformation play an important role in the DNA readout. Despite the fact that non-canonical trans and gauche- conformations of the DNA backbone angle γ (O5'-C5'-C4'-C3') are frequently found in the DNA crystal structures, their possible role in the DNA recognition has not been studied systematically. In order to fill in this gap, we analyze the available high-resolution crystal structures of the naked and complexed DNA. The analysis shows that the non-canonical γ angle conformations are present both in the naked and bound DNA, more often in the bound vs. naked DNA, and in the nucleotides with the A-like vs. the B-like sugar pucker. The alternative angle γ torsions are more frequently observed in the purines with the A-like sugar pucker and in the pyrimidines with the B-like sugar conformation. The minor groove of the nucleotides with non-canonical γ angle conformation is more polar, while the major groove is more hydrophobic than in the nucleotides with the classical γ torsions due to variations in exposure of the polar and hydrophobic groups of the DNA backbone. The propensity of the nucleotides with different γ angle conformations to participate in the protein-nucleic acid contacts in the minor and major grooves is connected with their sugar pucker and sequence-specific. Our findings imply that the angle γ transitions contribute to the process of the protein-DNA recognition due to modification of the polar/hydrophobic profile of the DNA grooves.

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

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

DNA-recognition process described by MD simulations of the lactose repressor protein on a specific and a non-specific DNA sequence

The lactose repressor protein may bind DNA in two possible configurations: a specific one, if the DNA sequence corresponds to a binding site, and a non-specific one otherwise. To find its target sequences, the lactose repressor first binds non-specifically to DNA, and subsequently, it rapidly searches for a binding site. Atomic structures of non-specific and specific complexes are available from crystallographic and nuclear magnetic resonance experiments. However, what remains unknown is a detailed description of the steps that transform the non-specific complex into the specific one. Here, how the protein first recognizes its binding site has been studied using molecular dynamics simulations. The picture that emerges is that of a protein that is as mobile when interacting with non-specific DNA sequences as when free in solution. This high degree of mobility allows the protein to rapidly sample different DNA sequences. In contrast, when the protein encounters a binding site, the configuration ensemble collapses, and the protein sliding movements along the DNA sequence become scarce. The binding energies in the specific and non-specific complexes were analysed using the Molecular Mechanics Poisson Boltzmann Surface Area approach. These results represent a first step towards a throughout characterization of the DNA-recognition process.

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

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