Structure and Dynamics of DNA and RNA Double Helices Obtained from the GGGGCC and CCCCGG Hexanucleotide Repeats That Are the Hallmark of C9FTD/ALS Diseases

A (GGGGCC) hexanucleotide repeat (HR) expansion in the C9ORF72 gene, and its associated antisense (CCCCGG) expansion, are considered the major cause behind frontotemporal dementia and amyotrophic lateral sclerosis. We have performed molecular dynamics simulations to characterize the conformation and dynamics of the 12 duplexes that result from the three different reading frames in sense and antisense HRs for both DNA and RNA. These duplexes display atypical structures relevant not only for a molecular level understanding of these diseases but also for enlarging the repertoire of nucleic-acid structural motifs. G-rich helices share common features. The inner G-G mismatches stay inside the helix in G_<i>syn</i>-G_<i>anti</i> conformations and form two hydrogen bonds (HBs) between the Watson–Crick edge of G_<i>anti</i> and the Hoogsteen edge of G_<i>syn</i>. In addition, G_<i>syn</i> in RNA forms a base-phosphate HB. Inner G-G mismatches cause local unwinding of the helix. G-rich double helices are more stable than C-rich helices due to better stacking and HBs of G-G mismatches. C-rich helix conformations vary wildly. C mismatches flip out of the helix in DNA but not in RNA. Least (most) stable C-rich RNA and DNA helices have single (double) mismatches separated by two (four) Watson–Crick basepairs. The most stable DNA structure displays an “e-motif” where mismatched bases flip toward the minor groove and point in the 5′ direction. There are two RNA conformations, where the orientation and HB pattern of the mismatches is coupled to bending of the helix

Structural and Dynamical Characterization of DNA and RNA Quadruplexes Obtained from the GGGGCC and GGGCCT Hexanucleotide Repeats Associated with C9FTD/ALS and SCA36 Diseases

A (GGGGCC) hexanucleotide repeat (HR) expansion in the C9ORF72 gene has been considered the major cause behind both frontotemporal dementia and amyotrophic lateral sclerosis, while a (GGGCCT) is associated with spinocerebellar ataxia 36. Recent experiments involving NMR, CD, optical melting and 1D ¹H NMR spectroscopy, suggest that the r­(GGGGCC) HR can adopt a hairpin structure with G-G mismatches in equilibrium with a G-quadruplex structure. G-Quadruplexes have also been identified for d­(GGGGCC). As these experiments lack molecular resolution, we have used molecular dynamics microsecond simulations to obtain a structural characterization of the G-quadruplexes associated with both HRs. All DNA G-quadruplexes, parallel or antiparallel, with or without loops are stable, while only parallel and one antiparallel (stabilized by diagonal loops) RNA G-quadruplexes are stable. It is known that antiparallel G-quadruplexes require alternating guanines to be in a syn conformation that is hindered by the C3′-endo pucker preferred by RNA. Initial RNA antiparallel quadruplexes built with C2′-endo sugars evolve such that the transition (C2′-endo)-to-(C3′-endo) triggers unwinding and buckling of the flat G-tetrads, resulting in the unfolding of the RNA antiparallel quadruplex. Finally, a parallel G-quadruplex stabilizes an adjacent C-tetrad in both DNA and RNA (thus effectively becoming a mixed quadruplex of 5 layers). The C-tetrad is stabilized by the stacking interactions with the preceding G-tetrad, by cyclical hydrogen bonds C­(N4)-(O2), and by an ion between the G-tetrad and the C-tetrad. In addition, antiparallel DNA G-quadruplexes also stabilize flat C-layers at the ends of the quadruplexes

Structural Determinants of Polyglutamine Protofibrils and Crystallites

Nine inherited neurodegenerative diseases are associated with the expansion of the CAG codon. Once the translated polyglutamine expansion becomes longer than ∼36 residues, it triggers the formation of intraneural protein aggregates that often display the signature of cross-β amyloid fibrils. Here, we use fully atomistic molecular dynamics simulations to probe the structural stability and conformational dynamics of both previously proposed and new polyglutamine aggregate models. We test the relative stability of parallel and antiparallel β sheets, and characterize possible steric interfaces between neighboring sheets and the effects of different alignments of the side-chain carboxamide dipoles. Results indicate that (i) different initial oligomer structures converge to crystals consistent with available diffraction data, after undergoing cooperative side-chain rotational transitions and quarter-stagger displacements on a microsecond time scale, (ii) structures previously deemed stable on a hundred nanosecond time scale are unstable over the microsecond time scale, and (iii) conversely, structures previously deemed unstable did not account for the correct side-chain packing and once the correct symmetry is considered the structures become stable for over a microsecond, due to tightly interdigitated side chains, which lock into highly regular polar zippers with inter-side-chain and backbone–side-chain hydrogen bonds. With these insights, we built Q₄₀ monomeric models with different combinations of arc and hairpin turns and tested them for stability. The stable monomers were further probed as a function of repeat length. Our results are consistent with the aggregation threshold. These results explain and reconcile previously reported experimental and model discrepancies about polyglutamine aggregate structures

(a) Schematic of amino acid backbone dihedrals

<p><b> and </b><b>, and (b) a corresponding Ramachandran plot.</b> In a typical Ramachandran plot of a glutamine residue, each pixel represents a bin, whose intensity represents its relative population, ranging from 1,2,,9, and 10 or more conformations, sampled in our simulations. Blue, yellow, grey, and pink clusters identify PPII, , , and regions, respectively.</p

Sample conformations of

<p><b> and </b><b>.</b> Cartoon representation of sample conformations of (a) and (b) . Purple, blue, cyan, and orange represent -helix, -helix, turn, and coil secondary structural motifs, respectively. The licorice-like representation of the proline segment of is given in (b). These structures are plotted by VMD <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Humphrey1" target="_blank">[61]</a> using STRIDE <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Frishman1" target="_blank">[60]</a> for secondary structure prediction.</p

Correlation analysis results for selected polyQ peptides.

<p>Here is given the (a) odds ratio based between any two glutamine residues ( and ) of [red] and [blue] in terms of (). From each side of the peptide ending residues are omitted in the calculations to reduce the end effects. (b) Similar to (a) for [red], [blue], and [black]. Here residues from each end are omitted. (c,d) Correlation coefficient between dihedral angles of any two glutamine residues ( and ) in terms of () for (c) [red], [blue] and (d) [red], [blue], and [black]. The end residues were omitted according to the same protocol used for odds ratio analysis. (e,f) Similar to (a,b) but with the odds ratio calculated using the probabilities that residues belong or not to an repeat region.</p

Helix and turn populations of the polyQ peptides.

<p>The helical content is partitioned into - and -helix populations. The structures are also categorized based on the number of their helical segments. The population of each category (0,1,2,) is given if greater than %. The turn content is partitioned based on both the hydrogen-bonding and turn types. For the secondary structure prediction, the DSSP analysis code <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Kabsch1" target="_blank">[58]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Joosten1" target="_blank">[59]</a> was used along with the protocols discussed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#s2" target="_blank"><i>Methods</i></a>.</p

Distribution of radius of gyration of polyQ peptides.

<p>(a) The estimated distribution for [red] and [blue]. (b) The estimated distribution for [red] and [blue]. The blue curve can be estimated as the sum [black] of three Gaussian distributions [dotted]. (c) The estimated distribution for , considering only the structures with an all-trans proline segment [green]. Similarly the green curve can be estimated as the sum [black] of four Gaussian distributions [dotted]. Considering only the structures that at least have one cis-proline results in the magenta curve for the distribution. All the histograms are obtained using a window of width . (d) The exponent in relation estimated from select pairs of (x axis) and ( for blue circles and for yellow squares). Inset: The average (in ) of Q peptides for .</p

Secondary structure analysis of the polyQ peptides.

<p>Here, we give the (a) population (as a percentage) of the residues in the different Ramachandran regions (, , PPII, and ), as well as the population of residues involved in repeats; (b) the population (as a percentage) of residues in different secondary structures (helix, turn, and other secondary structures); (c) the percentage of <i>conformations</i> having at least one PPII, , or extended secondary structures including isolated strands and hairpins. The isolated , , or (, , or ) strands – identified in the table as PPII-s, -s, -s – are defined based on at least three (four) adjacent residues with the backbone dihedral angles falling into the region associated with these structures; and not involved in any inter-residual hydrogen bonding. Similarly a hairpin – identified in the table as PPII-h, -h, -h – is defined based on two adjacent strands of at least three residues with one or more hydrogen bonds between the two strands and a turn in between. For more details of this analysis, that is based on both DSSP <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Kabsch1" target="_blank">[58]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Joosten1" target="_blank">[59]</a> and dihedral-based clustering, see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#s2" target="_blank"><i>Methods</i></a>.</p

Helical, turn and coil content of selected polyQ peptides.

<p>Here, given are the contents (as a percentage) of individual glutamine residues found in the following conformations: (a,b) helical (,) (c,d) turn (H-bonded,bend) (e,f) coil. These percentages are plotted against the Glu residue numbers for (a,c,e) [red],[blue] and (b,d,f) [red], [blue]. These percentages are obtained from the DSSP <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Kabsch1" target="_blank">[58]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002501#pcbi.1002501-Joosten1" target="_blank">[59]</a> analysis code.</p