HMG-D is an architecture-specific protein that preferentially binds to DNA containing the dinucleotide TG.

The high mobility group (HMG) protein HMG-D from Drosophila melanogaster is a highly abundant chromosomal protein that is closely related to the vertebrate HMG domain proteins HMG1 and HMG2. In general, chromosomal HMG domain proteins lack sequence specificity. However, using both NMR spectroscopy and standard biochemical techniques we show that binding of HMG-D to a single DNA site is sequence selective. The preferred duplex DNA binding site comprises at least 5 bp and contains the deformable dinucleotide TG embedded in A/T-rich sequences. The TG motif constitutes a common core element in the binding sites of the well-characterized sequence-specific HMG domain proteins. We show that a conserved aromatic residue in helix 1 of the HMG domain may be involved in recognition of this core sequence. In common with other HMG domain proteins HMG-D binds preferentially to DNA sites that are stably bent and underwound, therefore HMG-D can be considered an architecture-specific protein. Finally, we show that HMG-D bends DNA and may confer a superhelical DNA conformation at a natural DNA binding site in the Drosophila fushi tarazu scaffold-associated region.     

HMG-D complexed to a bulge DNA: an NMR model

An NMR model is presented for the structure of HMG-D, one of the DROSOPHILA: counterparts of mammalian HMG1/2 proteins, bound to a particular distorted DNA structure, a dA(2) DNA bulge. The complex is in fast to intermediate exchange on the NMR chemical shift time scale and suffers substantial linebroadening for the majority of interfacial resonances. This essentially precludes determination of a high-resolution structure for the interface based on NMR data alone. However, by introducing a small number of additional constraints based on chemical shift and linewidth footprinting combined with analogies to known structures, an ensemble of model structures was generated using a computational strategy equivalent to that for a conventional NMR structure determination. We find that the base pair adjacent to the dA(2) bulge is not formed and that the protein recognizes this feature in forming the complex; intermolecular NOE enhancements are observed from the sidechain of Thr 33 to all four nucleotides of the DNA sequence step adjacent to the bulge. Our results form the first experimental demonstration that when binding to deformed DNA, non-sequence-specific HMG proteins recognize the junction between duplex and nonduplex DNA. Similarities and differences of the present structural model relative to other HMG-DNA complex structures are discussed.     

Multiscale simulations of large complexes in conjunction with cryo-EM analysis

The cellular environment is highly crowded with most proteins and RNA/DNA forming homomeric and heteromeric complexes. Essential questions regarding how these complexes switch between functional, rest, and abnormal states with regulators or modifications remain challenging and complicated. Here, we review the recent progress integrating cryoelectron microscopy and multiscale molecular modeling to understand the dynamics and function-related mechanism in protein–RNA/DNA complexes, protein–protein complexes/assemblies, and membrane protein complexes. One future direction of multiscale simulations will be to interpret the large complex multibody regulation in assembly-induced function enhancement in conjunction with advanced atomic resolution structural-biology techniques and specialized computing architectures.     

Integrating multi-scale data on homologous recombination into a new recognition mechanism based on simulations of the RecA-ssDNA/dsDNA structure

RecA protein is the prototypical recombinase. Members of the recombinase family can accurately repair double strand breaks in DNA. They also provide crucial links between pairs of sister chromatids in eukaryotic meiosis. A very broad outline of how these proteins align homologous sequences and promote DNA strand exchange has long been known, as are the crystal structures of the RecA-DNA pre- and postsynaptic complexes; however, little is known about the homology searching conformations and the details of how DNA in bacterial genomes is rapidly searched until homologous alignment is achieved. By integrating a physical model of recognition to new modeling work based on docking exploration and molecular dynamics simulation, we present a detailed structure/function model of homology recognition that reconciles extremely quick searching with the efficient and stringent formation of stable strand exchange products and which is consistent with a vast body of previously unexplained experimental results.     

Computer-based screening of functional conformers of proteins

A long-standing goal in biology is to establish the link between function, structure, and dynamics of proteins. Considering that protein function at the molecular level is understood by the ability of proteins to bind to other molecules, the limited structural data of proteins in association with other bio-molecules represents a major hurdle to understanding protein function at the structural level. Recent reports show that protein function can be linked to protein structure and dynamics through network centrality analysis, suggesting that the structures of proteins bound to natural ligands may be inferred computationally. In the present work, a new method is described to discriminate protein conformations relevant to the specific recognition of a ligand. The method relies on a scoring system that matches critical residues with central residues in different structures of a given protein. Central residues are the most traversed residues with the same frequency in networks derived from protein structures. We tested our method in a set of 24 different proteins and more than 260,000 structures of these in the absence of a ligand or bound to it. To illustrate the usefulness of our method in the study of the structure/dynamics/function relationship of proteins, we analyzed mutants of the yeast TATA-binding protein with impaired DNA binding. Our results indicate that critical residues for an interaction are preferentially found as central residues of protein structures in complex with a ligand. Thus, our scoring system effectively distinguishes protein conformations relevant to the function of interest.     

Structure model of a complex between the factor for inversion stimulation (FIS) and DNA: Modeling protein-DNA complexes with dyad symmetry and known protein structures

A method is presented to predict overall conformations of protein-DNA complexes on the basis of the known three-dimensional structures of the proteins. The method is restricted to proteins with a common twofold symmetry axis, which show only minor conformational changes upon binding to DNA. The method uses a numerical finite difference solution of the linearized Poisson-Boltzmann equation and subsequent energy minimization cycles. Structural parameters—the rotation angle of the DNA relative to the protein around the common symmetry axis, the protein-DNA distance, and intermolecular hydrogen-bonding contacts—are presented for two test cases, DNA bound to CAP (catabolite gene activator protein) and to the Cro-repressor of bacteriophage 434. The DNA curvature in the starting model of the docking procedure was chosen as a smoothed approximation of the conformation found in the X-ray structures of these complexes. The method is further used to predict the unknown structure of the complex between the factor for inversion stimulation (FIS) and DNA, which is bent upon binding to FIS. In contrast to the test cases, the unknown curvature of the starting model is derived from a calibration of electrostatic precalculations for different proteins according to crystallographically observed DNA bending. The results of the modeling are in good accordance with the experimentally observed overall structure of protein-DNA complexes for the two test cases; for FIS, they correspond to several of the experimentally proposed protein-DNA contacts. © 1996 Wiley-Liss, Inc.     

Domain-Based Protein Docking with Extremely Large Conformational Changes

Proteins are key components in many processes in living cells, and physical interactions with other proteins and nucleic acids often form key parts of their functions. In many cases, large flexibility of proteins as they interact is key to their function. To understand the mechanisms of these processes, it is necessary to consider the 3D structures of such protein complexes. When such structures are not yet experimentally determined, protein docking has long been present to computationally generate useful structure models. However, protein docking has long had the limitation that the consideration of flexibility is usually limited to very small movements or very small structures. Methods have been developed which handle minor flexibility via normal mode or other structure sampling, but new methods are required to model ordered proteins which undergo large-scale conformational changes to elucidate their function at the molecular level. Here, we present Flex-LZerD, a framework for docking such complexes. Via partial assembly multidomain docking and an iterative normal mode analysis admitting curvilinear motions, we demonstrate the ability to model the assembly of a variety of protein–protein and protein-nucleic acid complexes.     

The DNA-binding domain of human c-Abl tyrosine kinase promotes the interaction of a HMG chromosomal protein with DNA.

The biological activity of the c-Abl protein is linked to its tyrosine kinase and DNA-binding activities. The protein, which plays a major role in the cell cycle response to DNA damage, interacts preferentially with sequences containing an AAC motif and exhibits a higher affinity for bent or bendable DNA, as is the case with high mobility group (HMG) proteins. We have compared the DNA-binding characteristics of the DNA-binding domain of human c-Abl and the HMG-D protein from Drosophila melanogaster. c-Abl binds tightly to circular DNA molecules and potentiates the interaction of DNA with HMG-D. In addition, we used a series of DNA molecules containing modified bases to determine how the exocyclic groups of DNA influence the binding of the two proteins. Interfering with the 2-amino group of purines affects the binding of the two proteins similarly. Adding a 2-amino group to adenines restricts the access of the proteins to the minor groove, whereas deleting this bulky substituent from guanines facilitates the protein-DNA interaction. In contrast, c-Abl and HMG-D respond very differently to deletion or addition of the 5-methyl group of pyrimidine bases in the major groove. Adding a methyl group to cytosines favours the binding of c-Abl to DNA but inhibits the binding of HMG-D. Conversely, deleting the methyl group from thymines promotes the interaction of the DNA with HMG-D but diminishes its interaction with c-Abl. The enhanced binding of c-Abl to DNA containing 5-methylcytosine residues may result from an increased propensity of the double helix to denature locally coupled with a protein-induced reduction in the base stacking interaction. The results show that c-Abl has unique DNA-binding properties, quite different from those of HMG-D, and suggest an additional role for the protein kinase.     

Structural study of homeodomain protein-DNA complexes using a homology modeling approach

The homeodomain is a conserved protein motif that binds to DNA and plays a central role in gene regulation. We use homeodomain as a model system to study the specific interactions between protein and DNA in a complex. Following the fundamental concept of homology modeling, we have developed an algorithm for predicting structures of both protein and DNA using the known structure of a similar complex as the template. The accuracies of the algorithm in predicting the complex structures are evaluated when two of the homeodomain protein-DNA complexes with known structures (antennapedia and MATalpha2) are selected as test systems. This algorithm allows structural studies of homeodomain binds to DNA with different sequences.