Relationship Between Curved DNA Conformations and Slow Gel Migration

Abstract

We propose some specific DNA conformations that explain, in terms of molecular conformations, the anomalous gel electrophoretic behavior of the sequences (VA₄T₄X)₁, and (V₂A₃X₂)₁ where V and X are either G or C. Previously (J. Biomole. Struct. Dyn. 4, 41, 1986) we considered hydrophobic interactions a mong aliphatic hydrocarbon groups in A/T sequences. In the sequences (T)_n · (A)_n, the T's are slightly bent to yield structures with tightly stacked methyl groups along one side of the major groove. By folding together the two pairs of stacked methyls on the opposite sides of the major groove, TTAA might yield a relatively sharp bend. On this basis, we show below that the sequences (VT₄A₄X)₁ might form a very tightly coiled super-helix whereas the sequences (VA₄T₄X)₁ form a broad super-helix of radius ~ 120 A for i = 25. The sequence (V₂A₃T₃X₂)₁ forms a slightly smaller radius super-helix. The time of passage through the gel has been taken to be inversely proportional to the smallesuiimension of the molecule. Specifically we are taking the ratio of the apparent molecular weight to the actual molecular weight to be related to the moment of inertia I₁ about the smallest principal axis of the molecular conformation. We find a good fit to the experimental gel mobility data of Hagerman (2) if we assume this ratio to be proportional to (I₁)^1/5.     

Myosin flexibility: structural domains and collective vibrations

The movement of the myosin motor along an actin filament involves a directed conformational change within the cross-bridge formed between the protein and the filament. Despite the structural data that has been obtained on this system, little is known of the mechanics of this conformational change. We have used existing crystallographic structures of three conformations of the myosin head, containing the motor domain and the lever arm, for structural comparisons and mechanical studies with a coarse-grained elastic network model. The results enable us to define structurally conserved domains within the protein and to better understand myosin flexibility. Notably they point to the role of the light chains in rigidifying the lever arm and to changes in flexibility as a consequence of nucleotide binding.     

Sequence dependence of DNA conformational flexibility

By using conformational free energy calculations, we have studied the sequence dependence of flexibility and its anisotropy along various conformational variables of DNA base pairs. The results show the AT base step to be very flexible along the twist coordinate. On the other hand, homonucleotide steps, GG(CC) and AA(TT), are among the most rigid sequences. For the roll motion that would correspond to a bend, the TA step is most flexible, while the GG(CC) step is least flexible. The flexibility of roll is quite anisotropic; the ratio of fluctuations toward the major and minor grooves is the largest for the GC step and the smallest for the AA(TT) and CG steps. Propeller twisting of base pairs is quite flexible, especially of A.T base pairs; propeller twist can reach 19 degrees by thermal fluctuation. We discuss the effect of electrostatic parameters, comparison with available experimental results, and biological relevance of these results.     

Predicting binding sites of hydrolase-inhibitor complexes by combining several methods

Background

Protein-protein interactions play a critical role in protein function. Completion of many genomes is being followed rapidly by major efforts to identify interacting protein pairs experimentally in order to decipher the networks of interacting, coordinated-in-action proteins. Identification of protein-protein interaction sites and detection of specific amino acids that contribute to the specificity and the strength of protein interactions is an important problem with broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks.

Results

In order to increase the power of predictive methods for protein-protein interaction sites, we have developed a consensus methodology for combining four different methods. These approaches include: data mining using Support Vector Machines, threading through protein structures, prediction of conserved residues on the protein surface by analysis of phylogenetic trees, and the Conservatism of Conservatism method of Mirny and Shakhnovich. Results obtained on a dataset of hydrolase-inhibitor complexes demonstrate that the combination of all four methods yield improved predictions over the individual methods.

Conclusions

We developed a consensus method for predicting protein-protein interface residues by combining sequence and structure-based methods. The success of our consensus approach suggests that similar methodologies can be developed to improve prediction accuracies for other bioinformatic problems.     

Equilibrium folding and unfolding pathways for a model protein

The folding–unfolding process of reduced bovine pancreatic trypsin inhibitor was investigated with an idealized model employing approximate free energies. The protein is regarded to consist of only C^α and C^β atoms. The backbone dihedral angles are the only conformational variables and are permitted to take discrete values at every 10°. Intraresidue energies consist of two terms: an empirical part taken from the observed frequency distributions of (?,ψ) and an additional favorable energy assigned to the native conformation of each residue. Interresidue interactions are simplified by assuming that there is an attractive energy operative only between residue pairs in close contact in the native structure. A total of 230,000 molecular conformations, with no atomic overlaps, ranging from the native state to the denatured state, are randomly generated by changing the sampling bias. Each conformation is classified according to its conformational energy, F; a conformational entropy, S(F) is estimated for each value of F from the number of samples. The dependence of S(F) on energy reveals that the folding–unfolding transition for this idealized model is an “all-or-none” type; this is attributable to the specific long-range interactions. Interresidue contact probabilities, averaged over samples representing various stages of folding, serve to characterize folding intermediates. Most probable equilibrium pathways for the folding–unfolding transition are constructed by connecting conformationally similar intermediates. The specific details obtained for bovine pancreatic trypsin inhibitor are as follows: (1) Folding begins with the appearance of nativelike medium-range contacts at a β-turn and at the α-helix. (2) These grow to include the native pair of interacting β-strands. This state includes intact regular secondary conformations, as well as the interstrand sheet contacts, and corresponds to an activated state with the highest free energy on the pathway. (3) Additional native long-range contacts are completely formed either toward the amino terminus or toward the carboxyl terminus. (4) In a final step, the missing contacts appear. Although these folding pathways for this model are not consistent with experimental reports, it does indicate multiple folding pathways. The method is general and can be applied to any set of calculated conformational energies and furthermore permits investigation of gross folding features.     

RNA bulge entropies in the unbound state correlate with peptide binding strengths for HIV-1 and BIV TAR RNA because of improved conformational access.

For the binding of peptides to wild-type HIV-1 and BIV TAR RNA and to mutants with bulges of various sizes, changes in the DeltaDelta G values of binding were determined from experimental K d values. The corresponding entropies of these bulges are estimated by enumerating all possible RNA bulge conformations on a lattice and then applying the Boltzmann relationship. Independent calculations of entropies from fluctuations are also carried out using the Gaussian network model (GNM) recently introduced for analyzing folded structures. Strong correlations are seen between the changes in free energy determined for binding and the two different unbound entropy calculations. The fact that the calculated entropy increase with larger bulge size is correlated with the enhanced experimental binding free energy is unusual. This system exhibits a dependence on the entropy of the unbound form that is opposite to usual binding models. Instead of a large initial entropy being unfavorable since it would be reduced upon binding, here the larger entropies actually favor binding. Several interpretations are possible: (i) the higher conformational freedom implies a higher competence for binding with a minimal strain, by suitable selection amongst the set of already accessible conformations; (ii) larger bulge entropies enhance the probability of the specific favorable conformation of the bound state; (iii) the increased freedom of the larger bulges contri-butes more to the bound state than to the unbound state; (iv) indirectly the large entropy of the bound state might have an unfavorable effect on the solvent structure. Nonetheless, this unusual effect is interesting.     

Strong Patterns in Homooligomer Tracts Occurrences in Non-Coding and in Potential Regulatory Sites in Eukaryotic Genomes

Abstract

Previous studies of the dinucleotides flanking both the 5′ and 3′ ends of homooligomer tracts have shown that some flanks are consistently preferred over others (1,2). In the first preferred group, the homooligomer tracts are flanked by the same nucleotide and/or the complementary nucleotides, e.g., ATA_n, TTA_n, CCG_n, where n=2–5. Runs flanked by nucleotides with which they cannot base pair are distinctly disfavored. (In this group A/T_n are flanked by C and/or G; G_n/C_n are flanked by A/T, e.g., CGA_n, T_nGG, G., AT). The frequencies of runs flanked by AorT, and G or C (“mixed” group) are as expected. Here we seek the origin of this effect and its relevance to protein-DNA interactions. Surprisingly, within the first group, runs flanked by their complements with a pyrimidine-purine junction (e.g., TTA_n, C_nGG) are greatly preferred. The frequencies of their purine-pyrimidine junction mirror-images is just as expected. This effect, as well as additional ones enumerated below, is seen universally in eukaryotes and in prokaryotes, although it is stronger in the former. Detailed analysis of regulatory regions shows these strong trends, particularly in GC sequences. The potential relationship to DNA conformation and DNA-protein interaction is discussed.     

Elastic network models capture the motions apparent within ensembles of RNA structures

The role of structure and dynamics in mechanisms for RNA becomes increasingly important. Computational approaches using simple dynamics models have been successful at predicting the motions of proteins and are often applied to ribonucleo-protein complexes but have not been thoroughly tested for well-packed nucleic acid structures. In order to characterize a true set of motions, we investigate the apparent motions from 16 ensembles of experimentally determined RNA structures. These indicate a relatively limited set of motions that are captured by a small set of principal components (PCs). These limited motions closely resemble the motions computed from low frequency normal modes from elastic network models (ENMs), either at atomic or coarse-grained resolution. Various ENM model types, parameters, and structure representations are tested here against the experimental RNA structural ensembles, exposing differences between models for proteins and for folded RNAs. Differences in performance are seen, depending on the structure alignment algorithm used to generate PCs, modulating the apparent utility of ENMs but not significantly impacting their ability to generate functional motions. The loss of dynamical information upon coarse-graining is somewhat larger for RNAs than for globular proteins, indicating, perhaps, the lower cooperativity of the less densely packed RNA. However, the RNA structures show less sensitivity to the elastic network model parameters than do proteins. These findings further demonstrate the utility of ENMs and the appropriateness of their application to well-packed RNA-only structures, justifying their use for studying the dynamics of ribonucleo-proteins, such as the ribosome and regulatory RNAs.     

Genomic variation in cline shape across a hybrid zone

Hybrid zones are unique biological interfaces that reveal both population level and species level evolutionary processes. A genome‐scale approach to assess gene flow across hybrid zones is vital, and now possible. In Mexican towhees (genus Pipilo), several morphological hybrid gradients exist. We completed a genome survey across one such gradient (9 populations, 140 birds) using mitochondrial DNA, 28 isozyme, and 377 AFLP markers. To assess variation in introgression among loci, cline parameters (i.e., width, center) for the 61 clinally varying loci were estimated and compiled into genomic distributions for tests against three empirical models spanning the range of observed cline shape. No single model accounts for observed variation in cline shape among loci. Numerous backcross individuals near the gradient center confirm a hybrid origin for these populations, contrary to a previous hypothesis based on social mimicry and character displacement. In addition, the observed variation does not bin into well‐defined categories of locus types (e.g., neutral vs. highly selected). Our multi‐locus analysis reveals cross‐genomic variation in selective constraints on gene flow and locus‐specific flexibility in the permeability of the interspecies membrane.