A Monte Carlo method for generating structures of short single-stranded DNA sequences

Duplex DNA Retains the Conformational Features of Single Strands: Perspectives from MD Simulations and Quantum Chemical Computations

Molecular dynamics simulations and geometry optimizations carried out at the quantum level as well as by quantum mechanical/molecular mechanics methods predict that short, single-stranded DNA oligonucleotides adopt conformations very similar to those observed in crystallographic double-stranded B-DNA, with rise coordinates close to ≈3.3 Å. In agreement with the experimental evidence, the computational results show that DNA single strands rich in adjacent purine nucleobases assume more regular arrangements than poly-thymine. The preliminary results suggest that single-stranded poly-cytosine DNA should also retain a substantial helical order in solution. A comparison of the structures of single and double helices confirms that the B-DNA motif is a favorable arrangement also for single strands. Indeed, the optimal geometry of the complementary single helices is changed to a very small extent in the formation of the duplex.

Parallel poly(A) homo- and hetero-duplex formation detection with an adapted DNA nanoswitch technique

Polyriboadenylic [poly(rA)] strands of sufficient length form parallel double helices in acidic and/or ammonium-containing conditions. Poly(rA) duplexes in acidic conditions are held together by A⁺-A⁺ base-pairing also involving base interactions with the phosphate backbone. Traditional UV-melting studies of parallel poly(A) duplexes have typically examined homo-duplex formation of a single nucleic acid species in solution. We have adapted a technique utilizing a DNA nanoswitch that detects interaction of two different strands either with similar or differing lengths or modifications. Our method detected parallel duplex formation as a function of length, chemical modifications, and pH, and at a sensitivity that required over 100-fold less concentration of sample than prior UV-melting methods. While parallel polyriboadenylic acid and poly-2'-O-methyl-adenylic acid homo-duplexes formed, we did not detect homo-duplexes of polydeoxyriboadenylic acid strands or poly-locked nucleic acid (LNA)-adenylic strands. Importantly however, a poly-locked nucleic acid (LNA)-adenylic strand, as well as a poly-2'-O-methyl-adenylic strand, formed a hetero-duplex with a polyriboadenylic strand. Overall, our work validates a new tool for studying parallel duplexes and reveals fundamental properties of poly(A) parallel duplex formation. Parallel duplexes may find use in DNA nanotechnology and in molecular biology applications such as a potential poly(rA) tail capture tool as an alternative to traditional oligo(dT) based purification.

Single-Stranded DNA Oligonucleotides Retain Rise Coordinates Characteristic of Double Helices

The structures of single-stranded DNA oligonucleotides from dimeric to hexameric sequences have been thoroughly investigated. Computations performed at the density functional level of theory including dispersion forces and solvation show that single-stranded helices adopt conformations very close to crystallographic B-DNA, with rise coordinates amounting up to 3.3 Å. Previous results, suggesting that single strands should be shorter than double helices, largely originated from the incompleteness of the adopted basis set. Although sensible deviations with respect to standard B-DNA are predicted, computations indicate that sequences rich in stacked adenines are the most ordered ones, favoring the B-DNA pattern and inducing regular arrangements also on flanking nucleobases. Several structural properties of double helices rich in adenine are indeed already reflected by the corresponding single strands.

Visualizing single-stranded nucleic acids in solution

Single-stranded nucleic acids (ssNAs) are ubiquitous in many key cellular functions. Their flexibility limits both the number of high-resolution structures available, leaving only a small number of protein-ssNA crystal structures, while forcing solution investigations to report ensemble averages. A description of the conformational distributions of ssNAs is essential to more fully characterize biologically relevant interactions. We combine small angle X-ray scattering (SAXS) with ensemble-optimization methods (EOM) to dynamically build and refine sets of ssNA structures. By constructing candidate chains in representative dinucleotide steps and refining the models against SAXS data, a broad array of structures can be obtained to match varying solution conditions and strand sequences. In addition to the distribution of large scale structural parameters, this approach reveals, for the first time, intricate details of the phosphate backbone and underlying strand conformations. Such information on unperturbed strands will critically inform a detailed understanding of an array of problems including protein-ssNA binding, RNA folding and the polymer nature of NAs. In addition, this scheme, which couples EOM selection with an iteratively refining pool to give confidence in the underlying structures, is likely extendable to the study of other flexible systems.

Molecular modeling of nucleic acid structure: energy and sampling

An overview of computer simulation techniques as applied to nucleic acid systems is presented. This unit discusses methods used to treat energy and to sample representative configurations. Emphasis is placed on molecular mechanics and empirical force fields.

Molecular modeling of nucleic acid structure

This unit is the first in a series of four units covering the analysis of nucleic acid structure by molecular modeling. The unit provides an overview of the computer simulation of nucleic acids. Topics include the static structure model, computational graphics and energy models, the generation of an initial model, and characterization of the overall three-dimensional structure.

Molecular modeling of nucleic acid structure

This unit is the first in a series of four units covering the analysis of nucleic acid structure by molecular modeling. This unit provides an overview of computer simulation of nucleic acids. Topics include the static structure model, computational graphics and energy models, generation of an initial model, and characterization of the overall three-dimensional structure.

Molecular modeling of nucleic acid structure: energy and sampling

An overview of computer simulation techniques as applied to nucleic acid systems is presented. This unit expands an accompanying overview unit (UNIT 7.5) by discussing methods used to treat the energy and sample representative configurations. Emphasis is placed on molecular mechanics and empirical force fields.

A computational approach to modeling nucleic acid hairpin structures

Hairpin is a structural motif frequently observed in both RNA and DNA molecules. This motif is involved specifically in various biological functions (e.g., gene expression and regulation). To understand how these hairpin motifs perform their functions, it is important to study their structures. Compared to protein structural motifs, structures of nucleic acid hairpins are less known. Based on a set of reduced coordinates for describing nucleic acid structures and a sampling algorithm that equilibrates structures using Metropolis Monte Carlo simulation, we developed a method to model nucleic acid hairpin structures. This method was used to predict the structure of a DNA hairpin with a single-guanosine loop. The lowest energy structure from the ensemble of 200 sampled structures has a RMSD of < 1.5 A, from the structure determined using NMR. Additional constraints for the loop bases were introduced for modeling an RNA hairpin with two nucleotides in the loop. The modeled structure of this RNA hairpin has extensive base stacking and an extra hydrogen bond (between the CYT in the loop and a phosphate oxygen), as observed in the NMR structure.

Constructing optimal backbone segments for joining fixed DNA base pairs

A method is presented to link a sequence of space-fixed base pairs by the sugar-phosphate segments of single nucleotides and to evaluate the effects in the backbone caused by this positioning of the bases. The entire computational unit comprises several nucleotides that are energy-minimized, subject to constraints imposed by the sugar-phosphate backbone segments being anchored to space-fixed base pairs. The minimization schemes are based on two stages, a conjugate gradient method followed by a Newton-Raphson algorithm. Because our purpose is to examine the response, or relaxation, of an artificially stressed backbone, it is essential to be able to obtain, as closely as possible, a lowest minimum energy conformation of the backbone segment in conformational space. For this purpose, an algorithm is developed that leads to the generation of an assembly of many local energy minima. From these sets of local minima, one conformation corresponding to the one with the lowest minimum is then selected and designated to represent the backbone segment at its minimum. The effective electrostatic potential of mean force is expressed in terms of adjustable parameters that incorporate solvent screening action in the Coulombic interactions between charged backbone atoms; these parameters are adjusted to obtain the best fit of the nearest-neighbor phosphorous atoms in an x-ray structure.

CICADA interface with AMBER. An application on oligonucleotides and their fragments

The potential energy hypersurfaces (PES) of several nucleotide fragments were analyzed by the conformational search algorithm CICADA interfaced with the molecular mechanics program AMBER, version 4.0. The low energy conformers for dimethylphosphate, dinucleoside monophosphate fragments, and deoxyadenosine are described. Calculated relative and absolute flexibilities of single conformers, molecular fragments as well as entire molecules are introduced. The comparison of the results with the literature data shows good ability of the CICADA-AMBER combination to describe conformational space. It is revealed that the number of low energy conformers as well as flexibility decreases as the size of the molecule increases. The conformational behavior of freely rotatable single bonds, specially those within a sugar ring, is more "sharp" in larger structures.

RNA loop structure prediction via bond scaling and relaxation

We have developed a method for predicting the structure of small RNA loops that can be used to augment already existing RNA modeling techniques. The method requires no input constraints on loop configuration other than end-to-end distance. Initial loop structures are generated by randomizing the torsion angles, beginning at one end of the polynucleotide chain and correlating each successive angle with the previous. The bond lengths of these structures are then scaled to fit within the known end constraints and the equilibrium bond lengths of the potential energy function are scaled accordingly. Through a series of rescaling and minimization steps the structures are allowed to relax to lower energy configurations with standard bond lengths and reduced van der Waals clashes. This algorithm has been tested on the variable loops of yeast tRNA-Asp and yeast tRNA-Phe, as well as the sarcin-ricin tetraloop and the anticodon loop of yeast tRNA-Phe. The results indicate good correlation between potential energy and the loop structure predictions that are closest to the variable loop crystal structures, but poorer correlation for the more isolated stem loops. The number of stacking interactions has proven to be a good objective measure of the best loop predictions. Selecting on the basis of energy and stacking, we obtain two structures with 0.65 and 0.75 A all-atom rms deviations (RMSD) from the crystal structure for the tRNA-Asp variable loop. The best structure prediction for the tRNA-Phe variable loop has an all-atom RMSD of 2.2 A and a backbone RMSD of 1.6 A, with a single base responsible for most of the deviation. For the sarcin-ricin loop from 28S ribosomal RNA, the predicted structure's all-atom RMSD from the nmr structure is 1.0 A. We obtain a 1.8 A RMSD structure for the tRNA-Phe anticodon loop.