Sequence-dependent anisotropic flexibility of B-DNA. A conformational study

Bending flexibility of the six tetrameric duplexes was investigated d(AAAA):d(TTTT), d(AATT)2, d(TTAA)2, d(GGGG):d(CCCC), d(GGCC)2 and d(CCGG)2,. The tetramers were extended in the both directions by regular double helices. The stiffness of the B-DNA double helix when bent into the both grooves proved to be less than that in the perpendicular direction by an order of magnitude. Such an anisotropy is a property of the sugar-phosphate backbone structure. The calculated fluctuations of the DNA bending along the dyad axis, 5-7 degree, are in agreement with experimental value of the DNA persistence length. Anisotropy of the double helix is sequence-dependent: most easily bent into the minor groove are the tetramers with purine-pyrimidine dimer (RY) in the middle. In contrast, YR dinucleotides prefer bending into the major groove. Moreover, they have an equilibrium bend of 6-12 degree into this groove. The above inequality is caused by stacking interaction of the bases. The bend in the central dimer is distributed to some extent between the adjacent links, though the main fraction of the bend remains within the central link. Variation of the sugar-phosphate geometry in the bent helix is inessential, so that DNA remains within the B-family of forms: namely, when the helical axis is bent by 20 degree. the backbone dihedral angles vary by no more than 15 degree. The obtained results are in accord with x-ray structure of the B-DNA dodecamer; they further substantiate our early model of DNA wrapping in the nucleosome by means of mini-kinks separated by a half-pitch of the double helix, i.e. by 5-6 b.p. Sequence-dependent anisotropy of DNA presumably dictates the three-dimensional structure of DNA in solution as well. We have found that nonrandom allocation of YR dimers leads to the systematic bends in equilibrium structure of certain DNA fragments.     

Bending and curvature calculations in B-DNA.

A simple program, BEND, has been written to calculate the magnitude of local bending and macroscopic curvature at each point along an arbitrary B-DNA sequence, using any desired bending model that specifies values of twist, roll and tilt as a function of sequence. The program has been used to evaluate six different DNA bending models in three categories. Two are bent non-A-tract models: (a) A new model based on the nucleosome positioning data of Satchwell et al 1986 (J. Mol. Biol. 191, 659-675), (b) The model of Calladine et al 1988 (J. Mol. Biol. 201, 127-137). Three are bent A-tract models: (c) The wedge model of Bolshoy et al 1991 (Proc. Natl. Acad. Sci. USA 88, 2312-2316), (d) The model of Cacchione et al 1989 (Biochem. 28, 8706-8713), (e) A reversed version of model (b). The last is a junction model: (f) The model of Koo & Crothers 1988 (Proc. Natl. Acad. Sci. USA 85, 1763-1767). Although they have widely different assumptions and values for twist, roll and tilt, all six models correctly predict experimental A-tract curvature as measured by gel retardation and cyclization kinetics, but only the new nucleosome positioning model is successful in predicting curvature in regions containing phased GGGCCC sequences. This model--showing local bending at mixed sequence DNA, strong bends at the sequence GGC, and straight, rigid A-tracts--is the only model consistent with both solution data from gel retardation and cyclization kinetics and structural data from x-ray crystallography.     

A molecular mechanical model to predict the helix twist angles of B-DNA

We present here a model for the prediction of helix twist angles in B-DNA, a model composed of a collection of torsional springs. Statistically averaged conformational energy calculations show that, for a specified basepair step, the basepair-basepair conformational energy is quadratically dependent on the helix twist angle, so the calculations provide the spring parameters for the basepair-basepair interactions. Torsional springs can also be used to model the effects of the backbone on the helix twist, and the parameters for those springs are derived by fitting the model to experimental data. The model predicts a macroscopic torsional stiffness and a longitudinal compressibility (Young's modulus) which are both in good agreement with experiment. One biological consequence of the model is examined, the sequence specificity of the Eco RI restriction endonuclease, and it is shown that the discriminatory power of the enzyme receives a substantial contribution from the energetic cost of torsional deformations of the DNA when wrong sequences are forced into the enzyme binding site.     

A Gaussian statistical mechanical model for the equilibrium thermodynamics of barnase folding

Given an all non-hydrogen-atom potential function that implicitly includes solvation effects, it is possible to adjust its parameters to favor the correct native structure for several proteins over decoys produced by ungapped threading. It is also possible to further train it to reproduce the experimental free energy of unfolding in aqueous solution at 298 K for wild-type barnase and 66 mutants. For this, the native state is represented by the crystal structure at a single energy level with a calculated low degeneracy; the denatured state is represented by the extended conformation and a high calculated degeneracy. The same two-state model can be extended to account for the stability of all 67 sequences toward urea denaturation at 298 K by building in a solvation term that depends on urea concentration. With the addition of one more parameter set to give the correct heat capacity of unfolded barnase in solution, it is possible to approximate the experimental thermodynamics of barnase thermal denaturation: melting temperature, width of thermal transition, deltaG, deltaH, deltaS, and deltaCp. This requires a novel sort of statistical mechanical model where the two states each have a Gaussian density of microscopic state distribution as a function of energy.     

A statistical mechanical model of the pre- and subtransitions of lecithin membranes

A statistical mechanical model with experimentally proved facts as starting points is presented. This model explains on molecular level, the pre- and subtransitions appearing in lipid membranes. The model describes the main features of the transitions, the hysteresis of the subtransition and the mobility changes of the heads and chains at these transitions. The model was expanded for phosphatidylcholine homologues with arbitrary chain lengths, and a qualitative agreement in the case of pretransition as far as a quantitative one for the subtransition were found.     

Molecular mechanical studies on left- and right-handed B-DNA

Molecular mechanical simulations on base-paired deoxyhexanucleoside phosphates, (dAdT)₃ · (dAdT)₃, (dTdA)₃ · (dTdA)₃, (dGdC)₃ · (dGdC)₃, and (dCdG)₃ · (dCdG)₃, have been carried out to assess their energetic stabilities in left- and right-handed forms. These hexamers have also been simulated with alternating sugar-puckering profiles with the combinations (purine : C2′-endo–pyrimidine : C3′-endo) and (purine : C3′-endo–pyrimidine C2′-endo). The right-handed models have been found to be the energetically most stable structures and the left-handed structures are significantly destabilized. This instability has been rationalized in terms of competition between stabilizing stacking interactions on one hand, and distortions in the bond angles and torsion angles in the sugar-phosphate backbone on the other.     

Conformational flexibility of B-DNA at 0.74 A resolution: d(CCAGTACTGG)(2)

The affinity and specificity of a ligand for its DNA site is a function of the conformational changes between the isolated and complexed states. Although the structures of a hydroxypyrrole-imidazole-pyrrole polyamide dimer with 5'-CCAGTACTGG-3' and the trp repressor recognizing the sequence 5'-GTACT-3' are known, the baseline conformation of the DNA site would contribute to our understanding of DNA recognition by these ligands. The 0.74 A resolution structure of a B-DNA double helix, 5'-CCAGTACTGG-3', has been determined by X-ray crystallography. Six of the nine phosphates, two of four bound calcium ions and networks of water molecules hydrating the oligonucleotide have alternate conformations. By contrast, nine of the ten bases have a single, unique conformation with hydrogen atoms visible in most cases. The polyamide molecules alter the geometry of the phosphodiester backbone, and the water molecules mediating contacts in the trp repressor/operator complex are conserved in the unliganded DNA. Furthermore, the multiple conformational states, ions and hydration revealed by this ultrahigh resolution structure of a B-form oligonucleotide are potentially general considerations for understanding DNA-binding affinity and specificity by ligands.     

A statistical method for predicting classical HLA alleles from SNP data

Genetic variation at classical HLA alleles is a crucial determinant of transplant success and susceptibility to a large number of infectious and autoimmune diseases. However, large-scale studies involving classical type I and type II HLA alleles might be limited by the cost of allele-typing technologies. Although recent studies have shown that some common HLA alleles can be tagged with small numbers of markers, SNP-based tagging does not offer a complete solution to predicting HLA alleles. We have developed a new statistical methodology to use SNP variation within the region to predict alleles at key class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1, HLA-DQA1, and HLA-DQB1) loci. Our results indicate that a single panel of approximately 100 SNPs typed across the region is sufficient for predicting both rare and common HLA alleles with up to 95% accuracy in both African and non-African populations. Furthermore, we show that HLA alleles can be successfully predicted by using previously genotyped SNPs that are within the MHC and that had not been chosen for their ability to predict HLA alleles, such as those included on genome-wide products. These results indicate that our methodology, combined with an extended database of reference haplotypes, will facilitate large-scale experiments, including disease-association studies and vaccine trials, in which detailed information about HLA type is valuable.     

A statistical model for interpreting the antibiogram

Up to now, to interpret antibiotic susceptibility tests, the common practice has been to use: first, breakpoints without any quantitative justification, secondly, concordance curves between the different measurement techniques; these are not well adapted to the heterogeneous character of bacterial populations. We hereby propose another method: it is based on a global data analysis for each bacterial species, each antibiotic family and each measurement technique. So, we have drawn up a new model for the interpretation, both global and data-processed; it is based on qualifying classes, which are obtained and interpreted by hierarchical ascendent classification, principal components analysis, and comparison with pharmacological data. It can be used by any biologist. What is more, justified breakpoints with a numerical risk and quality control are defined. There are also some additional uses: evaluation of the effect of new antibiotics, standardization of new measurement techniques, detection of the emergence of new bacterial resistance in patients, guidance for research into unknown resistance mechanisms and characters.     

A statistical model for iTRAQ data analysis

We describe biological and experimental factors that induce variability in reporter ion peak areas obtained from iTRAQ experiments. We demonstrate how these factors can be incorporated into a statistical model for use in evaluating differential protein expression and highlight the benefits of using analysis of variance to quantify fold change. We demonstrate the model's utility based on an analysis of iTRAQ data derived from a spike-in study.     

A statistical model for mapping morphological shape

Background  

Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine.     

A spatial statistical model for landscape genetics

Landscape genetics is a new discipline that aims to provide information on how landscape and environmental features influence population genetic structure. The first key step of landscape genetics is the spatial detection and location of genetic discontinuities between populations. However, efficient methods for achieving this task are lacking. In this article, we first clarify what is conceptually involved in the spatial modeling of genetic data. Then we describe a Bayesian model implemented in a Markov chain Monte Carlo scheme that allows inference of the location of such genetic discontinuities from individual geo-referenced multilocus genotypes, without a priori knowledge on populational units and limits. In this method, the global set of sampled individuals is modeled as a spatial mixture of panmictic populations, and the spatial organization of populations is modeled through the colored Voronoi tessellation. In addition to spatially locating genetic discontinuities, the method quantifies the amount of spatial dependence in the data set, estimates the number of populations in the studied area, assigns individuals to their population of origin, and detects individual migrants between populations, while taking into account uncertainty on the location of sampled individuals. The performance of the method is evaluated through the analysis of simulated data sets. Results show good performances for standard data sets (e.g., 100 individuals genotyped at 10 loci with 10 alleles per locus), with high but also low levels of population differentiation (e.g., F_ST < 0.05). The method is then applied to a set of 88 individuals of wolverines (Gulo gulo) sampled in the northwestern United States and genotyped at 10 microsatellites.     

A theoretical model of DNA curvature

Distortions from the uniform idealized B-DNA structure are investigated in terms of differential interactions between adjacent nucleotide pairs on the basis of conformational energy calculations. A theoretical model of DNA curvature is proposed based on the evaluation of the curvature vector defined in the complex plane and the corresponding variance. The model appears to contain the basic physical features for translating the deterministic fluctuations of DNA sequences in superstructure elements. It allows the quantitative reproduction of all the available gel electrophoresis experiments on both periodical polynucleotides and tracts of DNAs as well as the theoretical prediction of the sequence dependent DNA writhing in good agreement with the experimental data. The general pattern of agreement between the theoretical and experimental data and the biological significance of the results obtained allow an extensive application of the model for the screening of DNA regions which are possible candidates for protein recognition.     

Base sequence, local helix structure, and macroscopic curvature of A-DNA and B-DNA

Given a specified DNA sequence and starting with an idealized conformation for the double helix (A-DNA or B-DNA), the dependence of conformational energy on variations in the local geometry of the double helix can be examined by computer modeling. By averaging over all thermally accessible states, it is possible to determine 1) how the optimum local structure differs from the initial idealized conformation and 2) the energetic costs of small structural deformations. This paper describes such a study. Tables are presented for the prediction of helix twist angles and base pair roll angles for both A-DNA and B-DNA when the sequence has been specified. Local deviations of helix parameters from their average values can accumulate to produce a net curvature of the molecule, a curvature that can be sharp enough to be experimentally detectable. As an independent check on the method, the calculations provide predictions for the longitudinal compressibility (Young's modulus) and the average torsional stiffness, both of which are in good agreement with experimental values. In examining the role of sequence-dependent variations in helix structure for the recognition of specific sequences by proteins, we have calculated the energy needed to deform the self-complementary hexanucleotide d(CAATTG) to match the local geometry of d(GAATTC), which is the sequence recognized by the EcoRI restriction endonuclease. That energy would be sufficient to reduce the binding of the incorrect sequence to the protein by over 2 orders of magnitude relative to the correct sequence.     

Sequence-dependent DNA curvature and flexibility from scanning force microscopy images

This paper reports a study of the sequence-dependent DNA curvature and flexibility based on scanning force microscopy (SFM) images. We used a palindromic dimer of a 1878-bp pBR322 fragment and collected a large pool of SFM images. The curvature of each imaged chain was measured in modulus and direction. It was found that the ensemble curvature modulus does not allow the separation of static and dynamic contributions to the curvature, whereas the curvature, when its direction in the two dimensions is taken into account, permits the direct separation of the intrinsic curvature contributions static and dynamic contributions. The palindromic symmetry also acted as an internal gauge of the validity of the SFM images statistical analysis. DNA static curvature resulted in good agreement with the predicted sequence-dependent intrinsic curvature. Furthermore, DNA sequence-dependent flexibility was found to correlate with the occurrence of A.T-rich dinucleotide steps along the chain and, in general, with the normalized basepair stacking energy distribution.     

A biological marker model for predicting disease transitions

For patients with chronic myelogenous leukemia (CML), the effect of elevated blood levels of adenosine deaminase (ADA) is studied as a marker for transitions from stable disease to blast crisis and then to death. Data in the form of snapshots over time, with day, state of disease, and ADA level, are analyzed for 55 patients. A simple three-state Markov model with one-way transition probabilities dependent on ADA is used to determine if the marker has a significant effect on the prediction of changes from stable disease to blast crisis.     

Chain flexibility and configurational dimensions of left handed Z- DNA and right handed B-DNA helices

The configurational behaviour of flexible helices of right handed B- and left handed Z-types have been analysed using statistical mechanical procedures. The configuration-dependent parameter, most importantly, the persistence length has been computed, using the heminucleotide scheme of treating polynucleotide chains under the approximation that perturbations in the backbone torsions produce sufficient flexibility in these helices. The values of persistence lengths obtained for Z-helices are very much higher than that of B-helices indicating that former is less flexible compared to the latter. These are in accordance with the results obtained recently on B- and Z-forms of poly(dG-dC). (dG-dC) using light scattering studies. Also the persistence lengths of B_II-DNA helices characterised by a skew 3'-hemiucleotide (ε-270°), and also when they coexist with B-DNA have been computed and the values lie within the range of experimentally reported values on B-helices. It is argued that the decrease in the persistence length values of B-DNA at higher salt concentration is due to additional small fluctuations in sugar residue torsions induced due to neutralisation of electrostatic repulsions between adjacent phosphates of the nucleotide. Noteworthy is that these are correlated to winding angle variations and the consequent bending of the helix. Contribution No. 659.     

A statistical model for red blood cell survival

A statistical model for the survival time of red blood cells (RBCs) with a continuous distribution of cell lifespans is presented. The underlying distribution of RBC lifespans is derived from a probability density function with a bathtub-shaped hazard curve, and accounts for death of RBCs due to senescence (age-dependent increasing hazard rate) and random destruction (constant hazard), as well as for death due to initial or delayed failures and neocytolysis (equivalent to early red cell mortality). The model yields survival times similar to those of previously published studies of RBC survival and is easily amenable to inclusion of drug effects and haemolytic disorders.