Binding-induced conformational changes of a protein at regions distant from the binding site may play crucial roles in protein function and regulation. The p53 tumour suppressor is an example of such an allosterically regulated protein. Little is known, however, about how DNA binding can affect distal sites for transcription factors. Furthermore, the molecular details of how a local perturbation is transmitted through a protein structure are generally elusive and occur on timescales hard to explore by simulations. Thus, we employed state-of-the-art enhanced sampling atomistic simulations to unveil DNA-induced effects on p53 structure and dynamics that modulate the recruitment of cofactors and the impact of phosphorylation at Ser215. We show that DNA interaction promotes a conformational change in a region 3 nm away from the DNA binding site. Specifically, binding to DNA increases the population of an occluded minor state at this distal site by more than 4-fold, whereas phosphorylation traps the protein in its major state. In the minor conformation, the interface of p53 that binds biological partners related to p53 transcription-independent functions is not accessible. Significantly, our study reveals a mechanism of DNA-mediated protection of p53 from interactions with partners involved in the p53 transcription-independent signalling. This also suggests that conformational dynamics is tightly related to p53 signalling.

MovieMaker is a web server that allows short ( approximately 10 s), downloadable movies of protein motions to be generated. It accepts PDB files or PDB accession numbers as input and automatically calculates, renders and merges the necessary image files to create colourful animations covering a wide range of protein motions and other dynamic processes. Users have the option of animating (i) simple rotation, (ii) morphing between two end-state conformers, (iii) short-scale, picosecond vibrations, (iv) ligand docking, (v) protein oligomerization, (vi) mid-scale nanosecond (ensemble) motions and (vii) protein folding/unfolding. MovieMaker does not perform molecular dynamics calculations. Instead it is an animation tool that uses a sophisticated superpositioning algorithm in conjunction with Cartesian coordinate interpolation to rapidly and automatically calculate the intermediate structures needed for many of its animations. Users have extensive control over the rendering style, structure colour, animation quality, background and other image features. MovieMaker is intended to be a general-purpose server that allows both experts and non-experts to easily generate useful, informative protein animations for educational and illustrative purposes. MovieMaker is accessible at http://wishart.biology.ualberta.ca/moviemaker.

Molecular dynamics simulations with coarse-grained and/or simplified Hamiltonians are an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Structure-based Hamiltonians, simplified models developed from the energy landscape theory of protein folding, have become a standard tool for investigating biomolecular dynamics. SMOG@ctbp is an effort to simplify the use of structure-based models. The purpose of the web server is two fold. First, the web tool simplifies the process of implementing a well-characterized structure-based model on a state-of-the-art, open source, molecular dynamics package, GROMACS. Second, the tutorial-like format helps speed the learning curve of those unfamiliar with molecular dynamics. A web tool user is able to upload any multi-chain biomolecular system consisting of standard RNA, DNA and amino acids in PDB format and receive as output all files necessary to implement the model in GROMACS. Both C(alpha) and all-atom versions of the model are available. SMOG@ctbp resides at http://smog.ucsd.edu.

Solution nuclear magnetic resonance (NMR) experiments allow RNA dynamics to be determined in an aqueous environment. However, when a limited number of peaks are assigned, it is difficult to obtain structural information. We here show a protocol based on the combination of experimental data (Nuclear Overhauser Effect, NOE) and molecular dynamics simulations with enhanced sampling methods. This protocol allows to (a) obtain a maximum entropy ensemble compatible with NMR restraints and (b) obtain a minimal set of metastable conformations compatible with the experimental data (maximum parsimony). The method is applied to a hairpin of 29 nt from an inverted SINEB2, which is part of the SINEUP family and has been shown to enhance protein translation. A clustering procedure is introduced where the annotation of base-base interactions and glycosidic bond angles is used as a metric. By reweighting the contributions of the clusters, minimal sets of four conformations could be found which are compatible with the experimental data. A motif search on the structural database showed that some identified low-population states are present in experimental structures of other RNA transcripts. The introduced method can be applied to characterize RNA dynamics in systems where a limited amount of NMR information is available.

DNA predominantly contains Watson-Crick (WC) base pairs, but a non-negligible fraction of base pairs are in the Hoogsteen (HG) hydrogen bonding motif at any time. In HG, the purine is rotated ∼180° relative to the WC motif. The transitions between WC and HG may play a role in recognition and replication, but are difficult to investigate experimentally because they occur quickly, but only rarely. To gain insight into the mechanisms for this process, we performed transition path sampling simulations on a model nucleotide sequence in which an AT pair changes from WC to HG. This transition can occur in two ways, both starting with loss of hydrogen bonds in the base pair, followed by rotation around the glycosidic bond. In one route the adenine base converts from WC to HG geometry while remaining entirely within the double helix. The other route involves the adenine leaving the confines of the double helix and interacting with water. Our results indicate that this outside route is more probable. We used transition interface sampling to compute rate constants and relative free energies for the transitions between WC and HG. Our results agree with experiments, and provide highly detailed insights into the mechanisms of this important process.

Thymine DNA glycosylase (TDG), as a repair enzyme, plays essential roles in maintaining the genome integrity by correcting several mismatched/damaged nucleobases. TDG acquires an efficient strategy to search for the lesions among a vast number of cognate base pairs. Currently, atomic-level details of how TDG translocates along DNA as it approaches the lesion site and the molecular mechanisms of the interplay between TDG and DNA are still elusive. Here, by constructing the Markov state model based on hundreds of molecular dynamics simulations with an integrated simulation time of ∼25 μs, we reveal the rotation-coupled sliding dynamics of TDG along a 9 bp DNA segment containing one G·T mispair. We find that TDG translocates along DNA at a relatively faster rate when distant from the lesion site, but slows down as it approaches the target, accompanied by deeply penetrating into the minor-groove, opening up the mismatched base pair and significantly sculpturing the DNA shape. Moreover, the electrostatic interactions between TDG and DNA are found to be critical for mediating the TDG translocation. Notably, several uncharacterized TDG residues are identified to take part in regulating the conformational switches of TDG occurred in the site-transfer process, which warrants further experimental validations.

The kinetics of folding is crucial for the function of many regulatory RNAs including RNA G-quadruplexes (rG4s). Here, we characterize the folding pathways of a G-quadruplex from the telomeric repeat-containing RNA by combining all-atom molecular dynamics and coarse-grained simulations with circular dichroism experiments. The quadruplex fold is stabilized by cations and thus, the ion atmosphere forming a double layer surrounding the highly charged quadruplex guides the folding process. To capture the ionic double layer in implicit solvent coarse-grained simulations correctly, we develop a matching procedure based on all-atom simulations in explicit water. The procedure yields quantitative agreement between simulations and experiments as judged by the populations of folded and unfolded states at different salt concentrations and temperatures. Subsequently, we show that coarse-grained simulations with a resolution of three interaction sites per nucleotide are well suited to resolve the folding pathways and their intermediate states. The results reveal that the folding progresses from unpaired chain via hairpin, triplex and double-hairpin constellations to the final folded structure. The two- and three-strand intermediates are stabilized by transient Hoogsteen interactions. Each pathway passes through two on-pathway intermediates. We hypothesize that conformational entropy is a hallmark of rG4 folding. Conformational entropy leads to the observed branched multi-pathway folding process for TERRA25. We corroborate this hypothesis by presenting the free energy landscapes and folding pathways of four rG4 systems with varying loop length.

Elastic network models (ENMs) are valuable and efficient tools for characterizing the collective internal dynamics of proteins based on the knowledge of their native structures. The increasing evidence that the biological functionality of RNAs is often linked to their innate internal motions poses the question of whether ENM approaches can be successfully extended to this class of biomolecules. This issue is tackled here by considering various families of elastic networks of increasing complexity applied to a representative set of RNAs. The fluctuations predicted by the alternative ENMs are stringently validated by comparison against extensive molecular dynamics simulations and SHAPE experiments. We find that simulations and experimental data are systematically best reproduced by either an all-atom or a three-beads-per-nucleotide representation (sugar-base-phosphate), with the latter arguably providing the best balance of accuracy and computational complexity.

Protein-DNA interactions play a central role in transcriptional regulation and other biological processes. Investigating the mechanism of binding affinity and specificity in protein-DNA complexes is thus an important goal. Here we develop a simple physical energy function, which uses electrostatics, solvation, hydrogen bonds and atom-packing terms to model direct readout and sequence-specific DNA conformational energy to model indirect readout of DNA sequence by the bound protein. The predictive capability of the model is tested against another model based only on the knowledge of the consensus sequence and the number of contacts between amino acids and DNA bases. Both models are used to carry out predictions of protein-DNA binding affinities which are then compared with experimental measurements. The nearly additive nature of protein-DNA interaction energies in our model allows us to construct position-specific weight matrices by computing base pair probabilities independently for each position in the binding site. Our approach is less data intensive than knowledge-based models of protein-DNA interactions, and is not limited to any specific family of transcription factors. However, native structures of protein-DNA complexes or their close homologs are required as input to the model. Use of homology modeling can significantly increase the extent of our approach, making it a useful tool for studying regulatory pathways in many organisms and cell types.

DNA-binding proteins are key players in the regulation of gene expression and, hence, are essential for cell function. Chimeric proteins composed of DNA-binding domains and DNA modifying domains allow for precise genome manipulation. A key prerequisite is the specific recognition of a particular nucleotide sequence. Here, we quantitatively assess the binding affinity of DNA-binding proteins by molecular dynamics-based alchemical free energy simulations. A computational framework was developed to automatically set up in silico screening assays and estimate free energy differences using two independent procedures, based on equilibrium and non-equlibrium transformation pathways. The influence of simulation times on the accuracy of both procedures is presented. The binding specificity of a zinc-finger transcription factor to several sequences is calculated, and agreement with experimental data is shown. Finally we propose an in silico screening strategy aiming at the derivation of full specificity profiles for DNA-binding proteins.

A major obstacle towards elucidating the molecular basis of transcriptional regulation is the lack of a detailed understanding of the interplay between non-specific and specific protein-DNA interactions. Based on molecular dynamics simulations of C(2)H(2) zinc fingers (ZFs) and engrailed homeodomain transcription factors (TFs), we show that each of the studied DNA-binding domains has a set of highly constrained side chains in preset configurations ready to form hydrogen bonds with the DNA backbone. Interestingly, those domains that bury their recognition helix into the major groove are found to have an electrostatic hot spot for Cl(-) ions located on the same binding cavity as the most buried DNA phosphate. The spot is characterized by three protein hydrogen bond donors, often including two basic side chains. If bound, Cl(-) ions, likely mimicking phosphates, steer side chains that end up forming specific contacts with bases into bound-like conformations. These findings are consistent with a multi-step DNA-binding mechanism in which a pre-organized set of TF side chains assist in the desolvation of phosphates into well defined sites, prompting the re-organization of specificity determining side chains into conformations suitable for the recognition of their cognate sequence.

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.

Transcription factors are involved in many cellular processes that take place remote from their cognate DNA sequences. The efficiencies of these activities are thus in principle counteracted by high binding affinities of the factors to their cognate DNAs. Models such as facilitated diffusion or dissociation address this apparent contradiction. We show that the MYC associated transcription factor X (MAX) undergoes nanoscale conformational fluctuations in the DNA-bound state, which is consistent with facilitated dissociation from or diffusion along DNA strands by transiently reducing binding energies. An integrative approach involving EPR, NMR, crystallographic and molecular dynamics analyses demonstrates that the N-terminal domain of MAX constantly opens and closes around a bound DNA ligand thereby dynamically tuning the binding epitope and the mode of interaction.

The link between genomic structure and biological function is yet to be consolidated, it is, however, clear that physical manipulation of the genome, driven by the activity of a variety of proteins, is a crucial step. To understand the consequences of the physical forces underlying genome organization, we build a coarse-grained polymer model of the genome, featuring three fundamentally distinct classes of interactions: lengthwise compaction, i.e., compaction of chromosomes along its contour, self-adhesion among epigenetically similar genomic segments, and adhesion of chromosome segments to the nuclear envelope or lamina. We postulate that these three types of interactions sufficiently represent the concerted action of the different proteins organizing the genome architecture and show that an interplay among these interactions can recapitulate the architectural variants observed across the tree of life. The model elucidates how an interplay of forces arising from the three classes of genomic interactions can drive drastic, yet predictable, changes in the global genome architecture, and makes testable predictions. We posit that precise control over these interactions in vivo is key to the regulation of genome architecture.

A combination of explicit solvent molecular dynamics simulation (30 simulations reaching 4 µs in total), hybrid quantum mechanics/molecular mechanics approach and isothermal titration calorimetry was used to investigate the atomistic picture of ion binding to 15-mer thrombin-binding quadruplex DNA (G-DNA) aptamer. Binding of ions to G-DNA is complex multiple pathway process, which is strongly affected by the type of the cation. The individual ion-binding events are substantially modulated by the connecting loops of the aptamer, which play several roles. They stabilize the molecule during time periods when the bound ions are not present, they modulate the route of the ion into the stem and they also stabilize the internal ions by closing the gates through which the ions enter the quadruplex. Using our extensive simulations, we for the first time observed full spontaneous exchange of internal cation between quadruplex molecule and bulk solvent at atomistic resolution. The simulation suggests that expulsion of the internally bound ion is correlated with initial binding of the incoming ion. The incoming ion then readily replaces the bound ion while minimizing any destabilization of the solute molecule during the exchange.

Spontaneous assembly of DNA molecules into compact structures is ubiquitous in biological systems. Experiment has shown that polycations can turn electrostatic self-repulsion of DNA into attraction, yet the physical mechanism of DNA condensation has remained elusive. Here, we report the results of atomistic molecular dynamics simulations that elucidated the microscopic structure of dense DNA assemblies and the physics of interactions that makes such assemblies possible. Reproducing the setup of the DNA condensation experiments, we measured the internal pressure of DNA arrays as a function of the DNA-DNA distance, showing a quantitative agreement between the results of our simulations and the experimental data. Analysis of the MD trajectories determined the DNA-DNA force in a DNA condensate to be pairwise, the DNA condensation to be driven by electrostatics of polycations and not hydration, and the concentration of bridging cations, not adsorbed cations, to determine the magnitude and the sign of the DNA-DNA force. Finally, our simulations quantitatively characterized the orientational correlations of DNA in DNA arrays as well as diffusive motion of DNA and cations.

A major obstacle towards understanding the molecular basis of transcriptional regulation is the lack of a recognition code for protein-DNA interactions. Using high-quality crystal structures and binding data on the promiscuous family of C(2)H(2) zinc fingers (ZF), we decode 10 fundamental specific interactions responsible for protein-DNA recognition. The interactions include five hydrogen bond types, three atomic desolvation penalties, a favorable non-polar energy, and a novel water accessibility factor. We apply this code to three large datasets containing a total of 89 C(2)H(2) transcription factor (TF) mutants on the three ZFs of EGR. Guided by molecular dynamics simulations of individual ZFs, we map the interactions into homology models that embody all feasible intra- and intermolecular bonds, selecting for each sequence the structure with the lowest free energy. These interactions reproduce the change in affinity of 35 mutants of finger I (R(2) = 0.998), 23 mutants of finger II (R(2) = 0.96) and 31 finger III human domains (R(2) = 0.94). Our findings reveal recognition rules that depend on DNA sequence/structure, molecular water at the interface and induced fit of the C(2)H(2) TFs. Collectively, our method provides the first robust framework to decode the molecular basis of TFs binding to DNA.

RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available.

Photolyases are flavoenzymes responsible for the repair of carcinogenic DNA damage caused by ultraviolet radiation. They harbor the catalytic cofactor flavin adenine dinucleotide (FAD). The light-driven electron transfer from the excited state of the fully-reduced form of FAD to the DNA lesions causes rearrangement of the covalent bonds, leading to the restoration of intact nucleobases. In addition to the catalytic chromophore, some photolyases bear a secondary chromophore with better light absorption capability than FAD, acting as a light-harvesting chromophore that harvests photons in sunlight efficiently and transfers light energy to the catalytic center, as observed in natural photoreceptor proteins. Inspired by nature, we covalently and site-specifically attached a synthetic chromophore to the surface of photolyase using oligonucleotides containing a modified nucleoside and a cyclobutane-type DNA lesion, and successfully enhanced its enzymatic activity in the light-driven DNA repair. Peptide mapping in combination with theoretical calculations identified the amino acid residue that binds to the chromophore, working as an artificial light-harvesting chromophore. Our results broaden the strategies for protein engineering and provide a guideline for tuning of the light perception abilities and enzymatic activity of the photoreceptor proteins.

The POU family transcription factor Oct4 plays pivotal roles in regulating pluripotency and somatic cell reprogramming. Previous studies have indicated an important role for major groove contacts in Oct4-DNA recognition; however, the contributions of the RK motif in the POUh domain and the linker segment joining the two DNA-binding domains remain poorly understood. Here, by combining molecular modelling and functional assays, we find that the RK motif is essential for Oct4-DNA association by recognizing the narrowed DNA minor groove. Intriguingly, computational simulations reveal that the function of the RK motif may be finely tuned by H-bond interactions with the partially disordered linker segment and that breaking these interactions significantly enhances the DNA binding and reprogramming activities of Oct4. These findings uncover a self-regulatory mechanism for specific Oct4-DNA recognition and provide insights into the functional crosstalk at the molecular level that may illuminate mechanistic studies of the Oct protein family and possibly transcription factors in the POU family. Our gain-of-function Oct4 mutants might also be useful tools for use in reprogramming and regenerative medicine.